From 3ed4bd3aae92d3f16593b911fd131e41c7768e30 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 9 Nov 2023 17:08:11 +0100 Subject: [PATCH 001/110] Updated first couple of datasets in deltares_data.yml datacatalog --- data/catalogs/deltares_data.yml | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index c59d8fe5a..ca374a925 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -139,7 +139,7 @@ copdem30_v2021.1: meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem.vrt @@ -158,7 +158,7 @@ copdem30_mask_v2021.1: meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem_mask.vrt @@ -177,7 +177,7 @@ copdem30_masked_v2021.1: meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' path: topography/copdem/copdem_masked.vrt rename: @@ -231,6 +231,8 @@ dtu10mdt_egm96: paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography source_version: 2010 + processing_notes: /topography/dtu10mdt/READ_ME.txt + processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb unit: m+EGM96 path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif From d93f9a5b0457291d062b26df7d1bed0a0855ac57 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 10 Nov 2023 14:21:57 +0100 Subject: [PATCH 002/110] Added processing scripts/notes tags where necessary #356 --- data/catalogs/deltares_data.yml | 41 ++++++++++++++++++++++++++++++++- 1 file changed, 40 insertions(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index ca374a925..3c5127b96 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -313,6 +313,7 @@ eobs_v24.0e: source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_version: 24.0e + processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc rename: pp: press_msl @@ -341,6 +342,7 @@ eobs_v25.0e: source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_version: 25.0e + processing_script: v25.0e_fix_qq_dims_and_match_extent.py path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc rename: pp: press_msl @@ -469,6 +471,7 @@ era5_daily: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 source_version: ERA5 daily data on pressure levels + processing_script: meteo/era5_daily/src/ path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc rename: d2m: temp_dew @@ -499,6 +502,15 @@ era5_daily_zarr: driver: zarr kwargs: chunks: auto + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + processing_script: meteo/era5_zarr/scripts/ path: meteo/era5_daily.zarr era5_hourly: @@ -521,6 +533,7 @@ era5_hourly: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 source_version: ERA5 hourly data on single levels from 1940 to present + processing_script: meteo/era5/src/ path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc rename: d2m: temp_dew @@ -548,6 +561,15 @@ era5_hourly_zarr: driver: zarr kwargs: chunks: auto + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.adbb2d47 + source_version: ERA5 hourly data on single levels from 1940 to present + processing_script: meteo/era5_zarr/scripts/ path: meteo/era5.zarr era5_ocean: @@ -735,9 +757,10 @@ gebco_v2020: paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 - source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_url: https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data/ source_version: 2020 unit: m+MSL + processing_script: bathymetry/gebco/gebco_tiles.ipynb path: bathymetry/gebco/gebco.vrt rename: gebco: elevtn @@ -854,6 +877,7 @@ glofas_era5_v31: source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 source_version: v31 + processing_script: hydro/glofas_era5/glofas_cds_get.py path: hydro/glofas_era5/glofas_v31_{year}.nc rename: dis24: discharge @@ -1059,6 +1083,7 @@ grip_roads_v4: paper_doi: 10.1088/1748-9326/aabd42 source_license: CC0-1.0 source_version: v4 + processing_script: infrastructure/grip/merge.ipynb path: infrastructure/grip/GRIP4_world.fgb rename: GP_RTP: road_type @@ -1243,6 +1268,7 @@ mdt_cnes_cls18: source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html source_version: 18 unit: m+GOCO05S + processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif merit: @@ -1313,6 +1339,7 @@ merit_hydro_ihu_30sec_v1.0: source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk source_doi: 10.5281/zenodo.5166932 source_version: 1.0 + processing_notes: topography/merit_hydro_ihu/README path: topography/merit_hydro_ihu/30sec/*.tif rename: 30sec_basids: basins @@ -1333,6 +1360,7 @@ merit_hydro_ihu_index: paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + processing_notes: topography/merit_hydro_ihu/README path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: @@ -1365,6 +1393,7 @@ merit_hydro_patch_v1.0: source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro source_version: 1.0 Deltares patch + processing_script: topography/merit_hydro/patches/scripts path: topography/merit_hydro/patches/*.vrt rename: bas: basins @@ -1395,6 +1424,9 @@ modis_mcd15a3h_v006: source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ source_version: MCD15A3H V006 + processing_script: + GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js + merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: LAI: 0.1 @@ -1464,6 +1496,7 @@ rivers_lin2019_v1: source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk source_version: 1 + processing_notes: hydrography/rivers_lin2019/README path: hydrography/rivers_lin2019/rivers_ge30m.fgb rename: width_m: rivwth @@ -1502,6 +1535,7 @@ SM2RAIN_ASCAT_monthly_025_v1.4: paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: rainfall: precip @@ -1636,6 +1670,8 @@ soilgrids_v2.0: source_license: CC BY 4.0 source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids source_version: 2020 + processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb + processing_notes: soil/soilgrids_v2.0/src/readme.txt path: soil/soilgrids_v2.0/*/*_mean.vrt rename: bdod_0-5cm_mean: bd_sl1 @@ -1856,6 +1892,7 @@ worldpop_2020_constrained: paper_ref: Stevens et al. (2015) source_license: CC BY 4.0 source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 + processing_script: socio_economic/worldpop/src/ nodata: -99999 path: socio_economic/worldpop/ppp_2020_constrained.vrt rename: @@ -1863,6 +1900,8 @@ worldpop_2020_constrained: worldpop_2020_UNadj_constrained: alias: worldpop_2020_constrained + meta: + processing_script: socio_economic/worldpop/src/ path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt rename: ppp_2020_UNadj_constrained: population From 4a9d7910c153040e63c03bc2e365609082fad0ca Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 30 Nov 2023 11:25:15 +0100 Subject: [PATCH 003/110] Updated kwargs to driver_kwargs --- data/catalogs/deltares_data.yml | 146 ++++++++++++++++---------------- 1 file changed, 73 insertions(+), 73 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 3c5127b96..0ae6528e2 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -8,7 +8,7 @@ basin_atlas_level12_v10: crs: 4326 data_type: GeoDataFrame driver: vector - kwargs: + driver_kwargs: layer: BasinATLAS_v10_lev12 meta: category: hydrography @@ -40,7 +40,7 @@ lake_atlas_pol_v10: crs: 4326 data_type: GeoDataFrame driver: vector - kwargs: + driver_driver_kwargs: layer: LakeATLAS_v10_pol meta: category: hydrography @@ -60,7 +60,7 @@ chelsa_v1.2: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_driver_kwargs: chunks: x: 3600 y: 3600 @@ -79,7 +79,7 @@ chirps_africa_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_driver_kwargs: chunks: lat: 160 lon: 150 @@ -106,7 +106,7 @@ chirps_global_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_driver_kwargs: chunks: latitude: 112 longitude: 400 @@ -132,7 +132,7 @@ copdem30: copdem30_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_driver_kwargs: chunks: x: 3600 y: 3600 @@ -151,7 +151,7 @@ copdem30_mask: copdem30_mask_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_driver_kwargs: chunks: x: 3600 y: 3600 @@ -170,7 +170,7 @@ copdem30_masked: copdem30_masked_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_driver_kwargs: chunks: x: 3600 y: 3600 @@ -188,7 +188,7 @@ corine: corine_2018_v2020_u1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -204,7 +204,7 @@ dtu10mdt: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -221,7 +221,7 @@ dtu10mdt_egm96: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -242,7 +242,7 @@ eobs_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -270,7 +270,7 @@ eobs_v23.1e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -298,7 +298,7 @@ eobs_v24.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -327,7 +327,7 @@ eobs_v25.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -356,7 +356,7 @@ eobs_orography_v20.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -377,7 +377,7 @@ eobs_orography_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -396,7 +396,7 @@ eobs_orography_v23.1e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -415,7 +415,7 @@ eobs_orography_v24.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -434,7 +434,7 @@ eobs_orography_v25.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -455,7 +455,7 @@ era5_daily: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 250 longitude: 240 @@ -500,7 +500,7 @@ era5_daily_zarr: crs: 4326 data_type: RasterDataset driver: zarr - kwargs: + driver_kwargs: chunks: auto meta: category: meteo @@ -517,7 +517,7 @@ era5_hourly: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 125 longitude: 120 @@ -559,7 +559,7 @@ era5_hourly_zarr: crs: 4326 data_type: RasterDataset driver: zarr - kwargs: + driver_kwargs: chunks: auto meta: category: meteo @@ -576,7 +576,7 @@ era5_ocean: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 60 longitude: 60 @@ -597,7 +597,7 @@ era5_orography: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 120 longitude: 125 @@ -620,7 +620,7 @@ esa_worldcover_2020_v100: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 36000 y: 36000 @@ -635,7 +635,7 @@ fabdem: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -671,7 +671,7 @@ gadm_level2_v3.6: crs: 4326 data_type: GeoDataFrame driver: vector - kwargs: + driver_kwargs: layer: level2 meta: category: geography @@ -688,7 +688,7 @@ gadm_level3_v3.6: crs: 4326 data_type: GeoDataFrame driver: vector - kwargs: + driver_kwargs: layer: level3 meta: category: geography @@ -706,7 +706,7 @@ gcn250: gcn250_v1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -748,7 +748,7 @@ gebco_v2020: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -771,7 +771,7 @@ ghs_pop_2015_4326_v2019a: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -789,7 +789,7 @@ ghs_pop_2015_54009_v2019a: crs: 54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -807,7 +807,7 @@ ghs_smod_2015_54009_v2016a: crs: 54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -824,7 +824,7 @@ ghs_smod_2015_54009_v2019a: crs: 54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -844,7 +844,7 @@ globcover_2009_v2.3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -861,7 +861,7 @@ glofas_era5_v31: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: time: 180 latitude: 150 @@ -885,7 +885,7 @@ glofas_era5_v31: glofas_uparea: alias: glofas_era5_v31 driver: raster - kwargs: + driver_kwargs: chunks: x: 150 y: 360 @@ -901,7 +901,7 @@ glw_buffaloes_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -921,7 +921,7 @@ glw_cattle_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -941,7 +941,7 @@ glw_chicken_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -961,7 +961,7 @@ glw_ducks_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -981,7 +981,7 @@ glw_goats_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1001,7 +1001,7 @@ glw_horses_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1021,7 +1021,7 @@ glw_pigs_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1041,7 +1041,7 @@ glw_sheeps_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1059,7 +1059,7 @@ grdc: crs: 4326 data_type: GeoDataFrame driver: xlsx - kwargs: + driver_kwargs: index_col: grdc_no meta: category: observed data @@ -1108,11 +1108,11 @@ grwl_mask: grwl_mask_v1.01: data_type: RasterDataset driver: raster_tindex - kwargs: + driver_kwargs: chunks: x: 3000 y: 3000 - mosaic_kwargs: + mosaic_driver_kwargs: method: nearest tileindex: location meta: @@ -1130,7 +1130,7 @@ gswo: gswo_v2019: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 4000 y: 4000 @@ -1147,7 +1147,7 @@ gtsm_codec_reanalysis_{freq}_v1: crs: 4326 data_type: GeoDataset driver: netcdf - kwargs: + driver_kwargs: chunks: stations: 10 time: -1 @@ -1172,7 +1172,7 @@ guf_bld_2012_v02: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -1240,7 +1240,7 @@ koppen_geiger: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1257,7 +1257,7 @@ mdt_cnes_cls18: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 720 y: 720 @@ -1277,7 +1277,7 @@ merit_v1.0.3: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: drop_variables: projection chunks: lat: 6000 @@ -1299,7 +1299,7 @@ merit_hydro_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1327,7 +1327,7 @@ merit_hydro_ihu_30sec_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1382,7 +1382,7 @@ merit_hydro_patch_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1411,7 +1411,7 @@ modis_mcd15a3h_v006: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1508,7 +1508,7 @@ simard_v2011: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1523,7 +1523,7 @@ SM2RAIN_ASCAT_monthly_025_v1.4: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 360 longitude: 720 @@ -1544,7 +1544,7 @@ SM2RAIN_ASCAT_monthly_05_v1.4: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 180 longitude: 360 @@ -1566,7 +1566,7 @@ soilgrids_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 2400 y: 2400 @@ -1655,7 +1655,7 @@ soilgrids_2020: soilgrids_v2.0: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 2400 y: 2400 @@ -1762,7 +1762,7 @@ vito_2015_v2.0.2: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1778,7 +1778,7 @@ vito_2016_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1794,7 +1794,7 @@ vito_2017_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1810,7 +1810,7 @@ vito_2018_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1826,7 +1826,7 @@ vito_2019_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1866,7 +1866,7 @@ worldclim_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: lat: 3600 lon: 3600 @@ -1884,7 +1884,7 @@ worldclim_v2.0: worldpop_2020_constrained: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: auto meta: category: socio-economic @@ -1912,7 +1912,7 @@ wsf_bld_2015_v1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 From 4c215db75a0f84aed199852cacd575f2e3b4d87d Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 30 Nov 2023 14:47:31 +0100 Subject: [PATCH 004/110] Updated deltares datacatalog with data version and added variants where possible --- data/catalogs/deltares_data.yml | 814 +++++++++++++------------------- 1 file changed, 328 insertions(+), 486 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 0ae6528e2..cf79aa610 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -18,6 +18,7 @@ basin_atlas_level12_v10: source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas source_version: 10 + version: 10 path: hydrography/hydro_atlas/basin_atlas_v10.gpkg river_atlas_v10: @@ -33,6 +34,7 @@ river_atlas_v10: source_url: https://www.hydrosheds.org/hydroatlas source_version: 10 path: hydrography/hydro_atlas/river_atlas_v10.gpkg + version: 10 rename: dis_m3_pyr: Dis_avg @@ -40,7 +42,7 @@ lake_atlas_pol_v10: crs: 4326 data_type: GeoDataFrame driver: vector - driver_driver_kwargs: + driver_kwargs: layer: LakeATLAS_v10_pol meta: category: hydrography @@ -51,16 +53,15 @@ lake_atlas_pol_v10: source_url: https://www.hydrosheds.org/hydroatlas source_version: 10 path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + version: 10 rename: dis_m3_pyr: Dis_avg chelsa: - alias: chelsa_v1.2 -chelsa_v1.2: crs: 4326 data_type: RasterDataset driver: raster - driver_driver_kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -71,15 +72,14 @@ chelsa_v1.2: source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ source_version: 1.2 + version: 1.2 path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif chirps: - alias: chirps_africa_daily_v2.0 -chirps_africa_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - driver_driver_kwargs: + driver_kwargs: chunks: lat: 160 lon: 150 @@ -94,6 +94,7 @@ chirps_africa_daily_v2.0: source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps source_version: v2.0 + version: 2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: precipitation: precip @@ -101,12 +102,10 @@ chirps_africa_daily_v2.0: time: 86400 chirps_global: - alias: chirps_global_daily_v2.0 -chirps_global_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - driver_driver_kwargs: + driver_kwargs: chunks: latitude: 112 longitude: 400 @@ -121,6 +120,7 @@ chirps_global_daily_v2.0: source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps source_version: v2.0 + version: 2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: precipitation: precip @@ -128,11 +128,9 @@ chirps_global_daily_v2.0: time: 86400 copdem30: - alias: copdem30_v2021.1 -copdem30_v2021.1: data_type: RasterDataset driver: raster - driver_driver_kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -141,17 +139,16 @@ copdem30_v2021.1: source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' - nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning + version: 2021.1 path: topography/copdem/copdem.vrt + nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning rename: copdem: elevtn copdem30_mask: - alias: copdem30_mask_v2021.1 -copdem30_mask_v2021.1: data_type: RasterDataset driver: raster - driver_driver_kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -160,17 +157,16 @@ copdem30_mask_v2021.1: source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' - nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning + version: 2021.1 path: topography/copdem/copdem_mask.vrt + nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning rename: copdem_mask: mask copdem30_masked: - alias: copdem30_masked_v2021.1 -copdem30_masked_v2021.1: data_type: RasterDataset driver: raster - driver_driver_kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -179,13 +175,12 @@ copdem30_masked_v2021.1: source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 source_version: '2021_1' + version: 2021.1 path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn corine: - alias: corine_2018_v2020_u1 -corine_2018_v2020_u1: data_type: RasterDataset driver: raster driver_kwargs: @@ -198,8 +193,11 @@ corine_2018_v2020_u1: source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 source_version: v.2020_20u1 + provider: local + version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif + dtu10mdt: crs: 4326 data_type: RasterDataset @@ -215,6 +213,7 @@ dtu10mdt: source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography source_version: 2010 unit: m+EGM2008 + version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_float32.tif dtu10mdt_egm96: @@ -234,39 +233,10 @@ dtu10mdt_egm96: processing_notes: /topography/dtu10mdt/READ_ME.txt processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb unit: m+EGM96 + version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif eobs: - alias: eobs_v22.0e -eobs_v22.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v23.1e: crs: 4326 data_type: RasterDataset driver: netcdf @@ -284,8 +254,25 @@ eobs_v23.1e: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + variants: + - version: 22.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + meta: + source_version: 22.0e + - version: 23.1e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + meta: + source_version: 23.1e + - version: 24.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + meta: + source_version: 24.0e + processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py + - version: 25.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + meta: + source_version: 25.0e + processing_script: v25.0e_fix_qq_dims_and_match_extent.py rename: pp: press_msl qq: kin @@ -294,86 +281,7 @@ eobs_v23.1e: unit_add: time: 86400 -eobs_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - processing_script: v25.0e_fix_qq_dims_and_match_extent.py - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_orography_v20.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 20.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - rename: - elevation: elevtn - eobs_orography: - alias: eobs_orography_v22.0e -eobs_orography_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf @@ -387,71 +295,34 @@ eobs_orography_v22.0e: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - rename: - elevation: elevtn + source_version: 20.0e + variants: + - version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + meta: + source_version: 20.0e + - version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + meta: + source_version: 22.0e + - version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + meta: + source_version: 23.1e + - version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + meta: + source_version: 24.0e + - version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + meta: + source_version: 25.0e -eobs_orography_v23.1e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc rename: elevation: elevtn -eobs_orography_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - rename: - elevation: elevtn - -eobs_orography_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - driver_kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - rename: - elevation: elevtn era5: - alias: era5_daily -era5_daily: crs: 4326 data_type: RasterDataset driver: netcdf @@ -496,7 +367,6 @@ era5_daily: press_msl: 0.01 era5_daily_zarr: - alias: era5_daily crs: 4326 data_type: RasterDataset driver: zarr @@ -555,7 +425,6 @@ era5_hourly: press_msl: 0.01 era5_hourly_zarr: - alias: era5_hourly crs: 4326 data_type: RasterDataset driver: zarr @@ -615,8 +484,6 @@ era5_orography: elevtn: 0.10197162129779283 esa_worldcover: - alias: esa_worldcover_2020_v100 -esa_worldcover_2020_v100: crs: 4326 data_type: RasterDataset driver: raster @@ -628,7 +495,8 @@ esa_worldcover_2020_v100: category: landuse source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 - source_version: v100 + source_version: 100 + version: 100 path: landuse/esa_worldcover/esa-worldcover.vrt fabdem: @@ -646,13 +514,12 @@ fabdem: source_license: CC BY-NC-SA 4.0 source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 source_version: 1.0 + version: 1.0 path: topography/fabdem/fabdem.vrt rename: fabdem: elevtn gadm: - alias: gadm_level1_v3.6 -gadm_level1_v3.6: crs: 4326 data_type: GeoDataFrame driver: vector @@ -663,6 +530,7 @@ gadm_level1_v3.6: source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html source_version: 3.6 + version: 3.6 path: geography/gadm/gadm36_levels.gpkg rename: ID: gadm_level1 @@ -680,6 +548,7 @@ gadm_level2_v3.6: source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html source_version: 3.6 + version: 3.6 path: geography/gadm/gadm36_levels.gpkg rename: fid: gadm_level2 @@ -702,8 +571,6 @@ gadm_level3_v3.6: fid: gadm_level3 gcn250: - alias: gcn250_v1 -gcn250_v1: data_type: RasterDataset driver: raster driver_kwargs: @@ -716,8 +583,9 @@ gcn250_v1: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 + source_version: 1 nodata: 255 + version: 1 path: landuse/gcn250/GCN250_*.tif rename: GCN250_ARCI: cn_dry @@ -725,8 +593,6 @@ gcn250_v1: GCN250_ARCIII: cn_wet gdp_world: - alias: gdp_world_v1 -gdp_world_v1: crs: 4326 data_type: GeoDataFrame driver: vector @@ -736,6 +602,7 @@ gdp_world_v1: source_author: Wilfred Altena source_license: CC BY-4.0 source_version: 1.0 + version: 1.0 path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb rename: GDP: gdp @@ -743,8 +610,6 @@ gdp_world_v1: gdp: 0.001 gebco: - alias: gebco_v2020 -gebco_v2020: crs: 4326 data_type: RasterDataset driver: raster @@ -761,17 +626,16 @@ gebco_v2020: source_version: 2020 unit: m+MSL processing_script: bathymetry/gebco/gebco_tiles.ipynb + version: 2020 path: bathymetry/gebco/gebco.vrt rename: gebco: elevtn ghs_pop: - alias: ghs_pop_2015_54009_v2019a -ghs_pop_2015_4326_v2019a: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -783,13 +647,14 @@ ghs_pop_2015_4326_v2019a: source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f source_version: R2019A_v1.0 + version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif ghs_pop_2015_54009_v2019a: crs: 54009 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 1000 y: 1000 @@ -799,11 +664,11 @@ ghs_pop_2015_54009_v2019a: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + source_version: R2019A_54009_250_v1.0 + version: R2019A_54009_250_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif ghs_smod: - alias: ghs_smod_2015_54009_v2019a -ghs_smod_2015_54009_v2016a: crs: 54009 data_type: RasterDataset driver: raster @@ -813,34 +678,24 @@ ghs_smod_2015_54009_v2016a: y: 3600 meta: category: socio-economic - paper_ref: Pesaresi and Freire (2016) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - -ghs_smod_2015_54009_v2019a: - crs: 54009 - data_type: RasterDataset - driver: raster - driver_kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + variants: + - version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + - version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 globcover: - alias: globcover_2009_v2.3 -globcover_2009_v2.3: crs: 4326 data_type: RasterDataset driver: raster @@ -855,6 +710,7 @@ globcover_2009_v2.3: source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php source_version: v2.3 + version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif glofas_era5_v31: @@ -878,17 +734,26 @@ glofas_era5_v31: source_url: https://doi.org/10.24381/cds.a4fdd6b9 source_version: v31 processing_script: hydro/glofas_era5/glofas_cds_get.py + version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc rename: dis24: discharge glofas_uparea: - alias: glofas_era5_v31 driver: raster driver_kwargs: chunks: x: 150 y: 360 + meta: + category: hydro + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.5194/essd-12-2043-2020 + paper_ref: Harrigan et al. (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf + source_url: https://doi.org/10.24381/cds.a4fdd6b9 + source_version: 31 + version: 31 path: hydro/glofas_era5/glofas_v31_uparea.tif rename: glofas_v31_uparea: uparea @@ -896,8 +761,6 @@ glofas_uparea: uparea: 0.000001 glw_buffaloes: - alias: glw_buffaloes_v3 -glw_buffaloes_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -912,12 +775,11 @@ glw_buffaloes_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Bf_2010_Da.tif glw_cattle: - alias: glw_cattle_v3 -glw_cattle_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -932,12 +794,11 @@ glw_cattle_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Ct_2010_Da.tif glw_chicken: - alias: glw_chicken_v3 -glw_chicken_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -952,12 +813,11 @@ glw_chicken_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Ch_2010_Da.tif glw_ducks: - alias: glw_ducks_v3 -glw_ducks_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -972,12 +832,11 @@ glw_ducks_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Dk_2010_Da.tif glw_goats: - alias: glw_goats_v3 -glw_goats_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -992,12 +851,11 @@ glw_goats_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Gt_2010_Da.tif glw_horses: - alias: glw_horses_v3 -glw_horses_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -1012,12 +870,11 @@ glw_horses_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Ho_2010_Da.tif glw_pigs: - alias: glw_pigs_v3 -glw_pigs_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -1032,12 +889,11 @@ glw_pigs_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Pg_2010_Da.tif glw_sheeps: - alias: glw_sheeps_v3 -glw_sheeps_v3: crs: 4326 data_type: RasterDataset driver: raster @@ -1052,7 +908,8 @@ glw_sheeps_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_version: v3 + version: 3 path: socio_economic/glw/5_Sh_2010_Da.tif grdc: @@ -1071,8 +928,6 @@ grdc: area: uparea grip_roads: - alias: grip_roads_v4 -grip_roads_v4: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1084,14 +939,13 @@ grip_roads_v4: source_license: CC0-1.0 source_version: v4 processing_script: infrastructure/grip/merge.ipynb + version: 4 path: infrastructure/grip/GRIP4_world.fgb rename: GP_RTP: road_type GP_RCY: country_code grwl: - alias: grwl_v1.01 -grwl_v1.01: data_type: GeoDataFrame driver: vector meta: @@ -1101,11 +955,10 @@ grwl_v1.01: source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 source_version: 1.01 + version: 1.01 path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb grwl_mask: - alias: grwl_mask_v1.01 -grwl_mask_v1.01: data_type: RasterDataset driver: raster_tindex driver_kwargs: @@ -1123,11 +976,10 @@ grwl_mask_v1.01: source_url: https://doi.org/10.5281/zenodo.1297434 source_version: 1.01 nodata: 0 + version: 1.01 path: hydrography/grwl/tindex.gpkg gswo: - alias: gswo_v2019 -gswo_v2019: data_type: RasterDataset driver: raster driver_kwargs: @@ -1141,6 +993,7 @@ gswo_v2019: source_url: https://global-surface-water.appspot.com/download source_version: v1_1_2019 nodata: 255 + version: v1_1_2019 path: hydrography/gswo/occur.vrt gtsm_codec_reanalysis_{freq}_v1: @@ -1157,7 +1010,8 @@ gtsm_codec_reanalysis_{freq}_v1: paper_ref: Muis at al (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf source_url: https://doi.org/10.24381/cds.8c59054f - source_version: v1 + source_version: 1 + version: 1 path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc placeholders: freq: [10min, hourly, dailymax] @@ -1167,8 +1021,6 @@ gtsm_codec_reanalysis_{freq}_v1: stations: index guf_bld_2012: - alias: guf_bld_2012_v02 -guf_bld_2012_v02: crs: 4326 data_type: RasterDataset driver: raster @@ -1193,6 +1045,7 @@ hydro_lakes: notes: HydroLAKES.v10_extract source_author: Arjen Haag source_version: 1.0 + version: 1.0 path: hydrography/lakes/lake-db.fgb rename: Depth_avg: Depth_avg @@ -1215,6 +1068,7 @@ hydro_reservoirs: source_author: Alessia Matano source_version: 1.0 nodata: -99 + version: 1.0 path: hydrography/reservoirs/reservoir-db.fgb rename: Depth_avg: Depth_avg @@ -1251,6 +1105,7 @@ koppen_geiger: source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm source_version: 2017 nodata: 0 + version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif mdt_cnes_cls18: @@ -1269,11 +1124,10 @@ mdt_cnes_cls18: source_version: 18 unit: m+GOCO05S processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb + version: 18 path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif merit: - alias: merit_v1.0.3 -merit_v1.0.3: crs: 4326 data_type: RasterDataset driver: netcdf @@ -1289,13 +1143,12 @@ merit_v1.0.3: source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ source_version: 1.0.3 + version: 1.0.3 path: topography/merit/merit.nc rename: elevation: elevtn merit_hydro: - alias: merit_hydro_v1.0 -merit_hydro_v1.0: crs: 4326 data_type: RasterDataset driver: raster @@ -1310,6 +1163,7 @@ merit_hydro_v1.0: source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro source_version: 1.0 + version: 1.0 path: topography/merit_hydro/*.vrt rename: bas: basins @@ -1322,8 +1176,6 @@ merit_hydro_v1.0: wth: rivwth merit_hydro_ihu: - alias: merit_hydro_ihu_30sec_v1.0 -merit_hydro_ihu_30sec_v1.0: crs: 4326 data_type: RasterDataset driver: raster @@ -1341,6 +1193,7 @@ merit_hydro_ihu_30sec_v1.0: source_version: 1.0 processing_notes: topography/merit_hydro_ihu/README path: topography/merit_hydro_ihu/30sec/*.tif + version: 1.0 rename: 30sec_basids: basins 30sec_flwdir: flwdir @@ -1364,8 +1217,6 @@ merit_hydro_ihu_index: path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: - alias: merit_hydro_index_v1.0 -merit_hydro_index_v1.0: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1374,11 +1225,11 @@ merit_hydro_index_v1.0: paper_doi: 10.5194/hess-25-5287-2021 paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 + source_version: 1.0 + version: 1.0 path: topography/merit_hydro/basin_index.fgb merit_hydro_patch: - alias: merit_hydro_patch_v1.0 -merit_hydro_patch_v1.0: crs: 4326 data_type: RasterDataset driver: raster @@ -1394,6 +1245,7 @@ merit_hydro_patch_v1.0: source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro source_version: 1.0 Deltares patch processing_script: topography/merit_hydro/patches/scripts + version: 1.0 path: topography/merit_hydro/patches/*.vrt rename: bas: basins @@ -1406,8 +1258,6 @@ merit_hydro_patch_v1.0: wth: rivwth modis_lai: - alias: modis_mcd15a3h_v006 -modis_mcd15a3h_v006: crs: 4326 data_type: RasterDataset driver: raster @@ -1427,13 +1277,12 @@ modis_mcd15a3h_v006: processing_script: GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py + version: MCD15A3H V006 path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: LAI: 0.1 osm_coastlines: - alias: osm_coastlines_v20200109 -osm_coastlines_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1444,13 +1293,12 @@ osm_coastlines_v20200109: source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html source_version: 1.0 + version: 1.0 path: geography/osm/osm_coastlines-db.fgb rename: fid: coastline_id osm_landareas: - alias: osm_landareas_v20200109 -osm_landareas_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1461,13 +1309,12 @@ osm_landareas_v20200109: source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html source_version: 1.0 + version: 1.0 path: geography/osm/osm_landareas-db.fgb rename: fid: land_id rgi: - alias: rgi_v0.6 -rgi_v0.6: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1479,6 +1326,7 @@ rgi_v0.6: source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview source_version: 6.0 + version: 6.0 path: hydrography/rgi/rgi.fgb rename: C3S_ID: C3S_id @@ -1497,14 +1345,13 @@ rivers_lin2019_v1: source_url: https://zenodo.org/record/3552776#.YVbOrppByUk source_version: 1 processing_notes: hydrography/rivers_lin2019/README + version: 1 path: hydrography/rivers_lin2019/rivers_ge30m.fgb rename: width_m: rivwth Q2: qbankfull simard: - alias: simard_v2011 -simard_v2011: crs: 4326 data_type: RasterDataset driver: raster @@ -1517,6 +1364,8 @@ simard_v2011: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + source_version: 2011 + version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif SM2RAIN_ASCAT_monthly_025_v1.4: @@ -1536,6 +1385,7 @@ SM2RAIN_ASCAT_monthly_025_v1.4: source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl source_version: 1.4 + version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: rainfall: precip @@ -1556,13 +1406,13 @@ SM2RAIN_ASCAT_monthly_05_v1.4: paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_version: 1.4 + version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: rainfall: precip soilgrids: - alias: soilgrids_v1.0 -soilgrids_v1.0: crs: 4326 data_type: RasterDataset driver: raster @@ -1572,193 +1422,181 @@ soilgrids_v1.0: y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. (2017) - source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 - path: soil/soilgrids_v1.0/*_250m_ll.tif - rename: - BLDFIE_M_sl1_250m_ll: bd_sl1 - BLDFIE_M_sl2_250m_ll: bd_sl2 - BLDFIE_M_sl3_250m_ll: bd_sl3 - BLDFIE_M_sl4_250m_ll: bd_sl4 - BLDFIE_M_sl5_250m_ll: bd_sl5 - BLDFIE_M_sl6_250m_ll: bd_sl6 - BLDFIE_M_sl7_250m_ll: bd_sl7 - CLYPPT_M_sl1_250m_ll: clyppt_sl1 - CLYPPT_M_sl2_250m_ll: clyppt_sl2 - CLYPPT_M_sl3_250m_ll: clyppt_sl3 - CLYPPT_M_sl4_250m_ll: clyppt_sl4 - CLYPPT_M_sl5_250m_ll: clyppt_sl5 - CLYPPT_M_sl6_250m_ll: clyppt_sl6 - CLYPPT_M_sl7_250m_ll: clyppt_sl7 - ORCDRC_M_sl1_250m_ll: oc_sl1 - ORCDRC_M_sl2_250m_ll: oc_sl2 - ORCDRC_M_sl3_250m_ll: oc_sl3 - ORCDRC_M_sl4_250m_ll: oc_sl4 - ORCDRC_M_sl5_250m_ll: oc_sl5 - ORCDRC_M_sl6_250m_ll: oc_sl6 - ORCDRC_M_sl7_250m_ll: oc_sl7 - PHIHOX_M_sl1_250m_ll: ph_sl1 - PHIHOX_M_sl2_250m_ll: ph_sl2 - PHIHOX_M_sl3_250m_ll: ph_sl3 - PHIHOX_M_sl4_250m_ll: ph_sl4 - PHIHOX_M_sl5_250m_ll: ph_sl5 - PHIHOX_M_sl6_250m_ll: ph_sl6 - PHIHOX_M_sl7_250m_ll: ph_sl7 - SLTPPT_M_sl1_250m_ll: sltppt_sl1 - SLTPPT_M_sl2_250m_ll: sltppt_sl2 - SLTPPT_M_sl3_250m_ll: sltppt_sl3 - SLTPPT_M_sl4_250m_ll: sltppt_sl4 - SLTPPT_M_sl5_250m_ll: sltppt_sl5 - SLTPPT_M_sl6_250m_ll: sltppt_sl6 - SLTPPT_M_sl7_250m_ll: sltppt_sl7 - SNDPPT_M_sl1_250m_ll: sndppt_sl1 - SNDPPT_M_sl2_250m_ll: sndppt_sl2 - SNDPPT_M_sl3_250m_ll: sndppt_sl3 - SNDPPT_M_sl4_250m_ll: sndppt_sl4 - SNDPPT_M_sl5_250m_ll: sndppt_sl5 - SNDPPT_M_sl6_250m_ll: sndppt_sl6 - SNDPPT_M_sl7_250m_ll: sndppt_sl7 - SoilThickness_250m_ll: soilthickness - TAXOUSDA_250m_ll: tax_usda - unit_mult: - bd_sl1: 0.001 - bd_sl2: 0.001 - bd_sl3: 0.001 - bd_sl4: 0.001 - bd_sl5: 0.001 - bd_sl6: 0.001 - bd_sl7: 0.001 - oc_sl1: 0.1 - oc_sl2: 0.1 - oc_sl3: 0.1 - oc_sl4: 0.1 - oc_sl5: 0.1 - oc_sl6: 0.1 - oc_sl7: 0.1 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - -soilgrids_2020: - alias: soilgrids_v2.0 -soilgrids_v2.0: - data_type: RasterDataset - driver: raster - driver_kwargs: - chunks: - x: 2400 - y: 2400 - meta: - category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - source_version: 2020 - processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb - processing_notes: soil/soilgrids_v2.0/src/readme.txt - path: soil/soilgrids_v2.0/*/*_mean.vrt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 + variants: + - version: 2017 + path: soil/soilgrids_v1.0/*_250m_ll.tif + meta: + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + rename: + BLDFIE_M_sl1_250m_ll: bd_sl1 + BLDFIE_M_sl2_250m_ll: bd_sl2 + BLDFIE_M_sl3_250m_ll: bd_sl3 + BLDFIE_M_sl4_250m_ll: bd_sl4 + BLDFIE_M_sl5_250m_ll: bd_sl5 + BLDFIE_M_sl6_250m_ll: bd_sl6 + BLDFIE_M_sl7_250m_ll: bd_sl7 + CLYPPT_M_sl1_250m_ll: clyppt_sl1 + CLYPPT_M_sl2_250m_ll: clyppt_sl2 + CLYPPT_M_sl3_250m_ll: clyppt_sl3 + CLYPPT_M_sl4_250m_ll: clyppt_sl4 + CLYPPT_M_sl5_250m_ll: clyppt_sl5 + CLYPPT_M_sl6_250m_ll: clyppt_sl6 + CLYPPT_M_sl7_250m_ll: clyppt_sl7 + ORCDRC_M_sl1_250m_ll: oc_sl1 + ORCDRC_M_sl2_250m_ll: oc_sl2 + ORCDRC_M_sl3_250m_ll: oc_sl3 + ORCDRC_M_sl4_250m_ll: oc_sl4 + ORCDRC_M_sl5_250m_ll: oc_sl5 + ORCDRC_M_sl6_250m_ll: oc_sl6 + ORCDRC_M_sl7_250m_ll: oc_sl7 + PHIHOX_M_sl1_250m_ll: ph_sl1 + PHIHOX_M_sl2_250m_ll: ph_sl2 + PHIHOX_M_sl3_250m_ll: ph_sl3 + PHIHOX_M_sl4_250m_ll: ph_sl4 + PHIHOX_M_sl5_250m_ll: ph_sl5 + PHIHOX_M_sl6_250m_ll: ph_sl6 + PHIHOX_M_sl7_250m_ll: ph_sl7 + SLTPPT_M_sl1_250m_ll: sltppt_sl1 + SLTPPT_M_sl2_250m_ll: sltppt_sl2 + SLTPPT_M_sl3_250m_ll: sltppt_sl3 + SLTPPT_M_sl4_250m_ll: sltppt_sl4 + SLTPPT_M_sl5_250m_ll: sltppt_sl5 + SLTPPT_M_sl6_250m_ll: sltppt_sl6 + SLTPPT_M_sl7_250m_ll: sltppt_sl7 + SNDPPT_M_sl1_250m_ll: sndppt_sl1 + SNDPPT_M_sl2_250m_ll: sndppt_sl2 + SNDPPT_M_sl3_250m_ll: sndppt_sl3 + SNDPPT_M_sl4_250m_ll: sndppt_sl4 + SNDPPT_M_sl5_250m_ll: sndppt_sl5 + SNDPPT_M_sl6_250m_ll: sndppt_sl6 + SNDPPT_M_sl7_250m_ll: sndppt_sl7 + SoilThickness_250m_ll: soilthickness + TAXOUSDA_250m_ll: tax_usda + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + - version: 2020 + path: soil/soilgrids_v2.0/*/*_mean.vrt + meta: + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + source_version: 2020 + processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb + processing_notes: soil/soilgrids_v2.0/src/readme.txt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 + vito: - alias: vito_2015_v2.0.2 -vito_2015_v2.0.2: crs: 4326 data_type: RasterDataset driver: raster @@ -1839,8 +1677,6 @@ vito_2019_v3.0.1: path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: - alias: wb_countries_v20200319 -wb_countries_v20200319: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1849,7 +1685,9 @@ wb_countries_v20200319: source_author: World Bank source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries source_license: CC-BY 4.0 + source_version: 20200319 timestamp: February 2020 + version: 20200319 path: geography/wb/WB_countries_Admin0.fgb rename: ISO_A3: country_iso @@ -1861,8 +1699,6 @@ wb_countries_v20200319: gdp_pc: 1000 worldclim: - alias: worldclim_v2.0 -worldclim_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf @@ -1875,8 +1711,9 @@ worldclim_v2.0: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 + source_version: 2.0 nodata: -999.0 + version: 2.0 path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc rename: prec: precip @@ -1899,7 +1736,10 @@ worldpop_2020_constrained: ppp_2020_constrained: population worldpop_2020_UNadj_constrained: - alias: worldpop_2020_constrained + data_type: RasterDataset + driver: raster + driver_kwargs: + chunks: auto meta: processing_script: socio_economic/worldpop/src/ path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt @@ -1922,4 +1762,6 @@ wsf_bld_2015_v1: paper_ref: Marconcini at al (2020) source_license: CC0 1.0 source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc + source_version: 1 + version: 1 path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt From 94ba8150166f9413d0ba4acdf3503b386981ac09 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 30 Nov 2023 17:07:30 +0100 Subject: [PATCH 005/110] updated data catalog sources with version and where applicable variants --- data/catalogs/deltares_data.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index cf79aa610..39ff8c3fc 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -635,7 +635,7 @@ ghs_pop: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -654,7 +654,7 @@ ghs_pop_2015_54009_v2019a: crs: 54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -709,7 +709,7 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php - source_version: v2.3 + source_version: 2.3 version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif @@ -732,7 +732,7 @@ glofas_era5_v31: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 - source_version: v31 + source_version: 31 processing_script: hydro/glofas_era5/glofas_cds_get.py version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc From 818002c7346314f58fb3e8fd1df010044c0295a8 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 30 Nov 2023 17:08:28 +0100 Subject: [PATCH 006/110] Added code for updating meta from variants --- hydromt/data_catalog.py | 3 +++ tests/data/merged_esa_worldcover.yml | 2 ++ tests/test_data_catalog.py | 5 +++++ 3 files changed, 10 insertions(+) diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 63eaecde2..f3040527d 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -1859,6 +1859,9 @@ def _denormalise_data_dict(data_dict) -> List[Tuple[str, Dict]]: variants = source.pop("variants") for diff in variants: source_copy = copy.deepcopy(source) + if "meta" in source_copy: + # Update meta if variant has variant specific meta data + source_copy["meta"].update(diff.pop("meta", {})) source_copy.update(**diff) data_dicts.append({name: source_copy}) elif "placeholders" in source: diff --git a/tests/data/merged_esa_worldcover.yml b/tests/data/merged_esa_worldcover.yml index 7f7778587..88143b1b1 100644 --- a/tests/data/merged_esa_worldcover.yml +++ b/tests/data/merged_esa_worldcover.yml @@ -18,6 +18,8 @@ esa_worldcover: - provider: local version: 2020 path: landuse/esa_worldcover/esa-worldcover.vrt + meta: + source_author: Test Dummy - provider: aws version: 2020 path: s3://esa-worldcover/v100/2020/ESA_WorldCover_10m_2020_v100_Map_AWS.vrt diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index cad15b302..7d7215b44 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -194,6 +194,11 @@ def test_versioned_catalog_entries(tmpdir): # test round trip to and from dict merged_catalog2 = DataCatalog().from_dict(merged_catalog.to_dict()) assert merged_catalog2 == merged_catalog + # test updating source meta data from version meta data + source_2020_local = merged_catalog.get_source( + "esa_worldcover", version="2020", provider="local" + ) + assert source_2020_local.meta["source_author"] == "Test Dummy" # Make sure we can query for the version we want aws_and_legacy_catalog = DataCatalog(data_libs=[legacy_yml_fn, aws_yml_fn]) From 66259fe688b180846dc98d0d130453c38bca437b Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Dec 2023 09:16:06 +0100 Subject: [PATCH 007/110] updated tests for checking if meta is preserved for variants that have their own meta --- tests/test_data_catalog.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 7d7215b44..c033fb896 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -199,6 +199,7 @@ def test_versioned_catalog_entries(tmpdir): "esa_worldcover", version="2020", provider="local" ) assert source_2020_local.meta["source_author"] == "Test Dummy" + assert source_2020_local.meta["source_license"] == "CC BY 4.0" # Make sure we can query for the version we want aws_and_legacy_catalog = DataCatalog(data_libs=[legacy_yml_fn, aws_yml_fn]) From 9d6b3466276a2d3e3f2a4333c920245aeae6dc62 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Dec 2023 09:40:23 +0100 Subject: [PATCH 008/110] removed source_version --- data/catalogs/deltares_data.yml | 91 +-------------------------------- 1 file changed, 2 insertions(+), 89 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 39ff8c3fc..0f0c9ab29 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -17,7 +17,6 @@ basin_atlas_level12_v10: paper_ref: Linke et al. (2019) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 version: 10 path: hydrography/hydro_atlas/basin_atlas_v10.gpkg @@ -32,7 +31,6 @@ river_atlas_v10: paper_ref: Linke et al. (2019) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 path: hydrography/hydro_atlas/river_atlas_v10.gpkg version: 10 rename: @@ -51,7 +49,6 @@ lake_atlas_pol_v10: paper_ref: Lehner et al. (2022) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 path: hydrography/hydro_atlas/lake_atlas_v10.gpkg version: 10 rename: @@ -71,7 +68,6 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 version: 1.2 path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif @@ -93,7 +89,6 @@ chirps: paper_ref: Funk et al (2015) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 version: 2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: @@ -119,7 +114,6 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 version: 2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: @@ -138,7 +132,6 @@ copdem30: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' version: 2021.1 path: topography/copdem/copdem.vrt nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning @@ -156,7 +149,6 @@ copdem30_mask: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' version: 2021.1 path: topography/copdem/copdem_mask.vrt nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning @@ -174,7 +166,6 @@ copdem30_masked: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' version: 2021.1 path: topography/copdem/copdem_masked.vrt rename: @@ -192,7 +183,6 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 provider: local version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif @@ -211,7 +201,6 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM2008 version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_float32.tif @@ -229,7 +218,6 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 processing_notes: /topography/dtu10mdt/READ_ME.txt processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb unit: m+EGM96 @@ -257,21 +245,15 @@ eobs: variants: - version: 22.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - meta: - source_version: 22.0e - version: 23.1e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - meta: - source_version: 23.1e - version: 24.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc meta: - source_version: 24.0e processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py - version: 25.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc meta: - source_version: 25.0e processing_script: v25.0e_fix_qq_dims_and_match_extent.py rename: pp: press_msl @@ -295,28 +277,17 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 20.0e variants: - version: 20.0e path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - meta: - source_version: 20.0e - version: 22.0e path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - meta: - source_version: 22.0e - version: 23.1e path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - meta: - source_version: 23.1e - version: 24.0e path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - meta: - source_version: 24.0e - version: 25.0e path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - meta: - source_version: 25.0e rename: elevation: elevtn @@ -341,7 +312,6 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels processing_script: meteo/era5_daily/src/ path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc rename: @@ -379,7 +349,6 @@ era5_daily_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels processing_script: meteo/era5_zarr/scripts/ path: meteo/era5_daily.zarr @@ -402,7 +371,6 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 - source_version: ERA5 hourly data on single levels from 1940 to present processing_script: meteo/era5/src/ path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc rename: @@ -437,7 +405,6 @@ era5_hourly_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 - source_version: ERA5 hourly data on single levels from 1940 to present processing_script: meteo/era5_zarr/scripts/ path: meteo/era5.zarr @@ -495,7 +462,6 @@ esa_worldcover: category: landuse source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 - source_version: 100 version: 100 path: landuse/esa_worldcover/esa-worldcover.vrt @@ -513,7 +479,6 @@ fabdem: paper_ref: Hawker et al. (2022) source_license: CC BY-NC-SA 4.0 source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 - source_version: 1.0 version: 1.0 path: topography/fabdem/fabdem.vrt rename: @@ -529,7 +494,6 @@ gadm: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 3.6 version: 3.6 path: geography/gadm/gadm36_levels.gpkg rename: @@ -547,7 +511,6 @@ gadm_level2_v3.6: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 3.6 version: 3.6 path: geography/gadm/gadm36_levels.gpkg rename: @@ -565,7 +528,6 @@ gadm_level3_v3.6: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 3.6 path: geography/gadm/gadm36_levels.gpkg rename: fid: gadm_level3 @@ -583,7 +545,6 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: 1 nodata: 255 version: 1 path: landuse/gcn250/GCN250_*.tif @@ -601,7 +562,6 @@ gdp_world: notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 - source_version: 1.0 version: 1.0 path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb rename: @@ -623,7 +583,6 @@ gebco: paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 source_url: https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data/ - source_version: 2020 unit: m+MSL processing_script: bathymetry/gebco/gebco_tiles.ipynb version: 2020 @@ -646,7 +605,6 @@ ghs_pop: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif @@ -664,7 +622,6 @@ ghs_pop_2015_54009_v2019a: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop - source_version: R2019A_54009_250_v1.0 version: R2019A_54009_250_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif @@ -686,14 +643,13 @@ ghs_smod: meta: paper_ref: Pesaresi and Freire (2016) source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - version: R2019A_v2.0 path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif meta: paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 paper_ref: Pesaresi et al (2019) source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 + globcover: crs: 4326 @@ -709,7 +665,6 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php - source_version: 2.3 version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif @@ -732,7 +687,6 @@ glofas_era5_v31: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 - source_version: 31 processing_script: hydro/glofas_era5/glofas_cds_get.py version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc @@ -752,7 +706,6 @@ glofas_uparea: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 - source_version: 31 version: 31 path: hydro/glofas_era5/glofas_v31_uparea.tif rename: @@ -775,7 +728,6 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Bf_2010_Da.tif @@ -794,7 +746,6 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Ct_2010_Da.tif @@ -813,7 +764,6 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Ch_2010_Da.tif @@ -832,7 +782,6 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Dk_2010_Da.tif @@ -851,7 +800,6 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Gt_2010_Da.tif @@ -870,7 +818,6 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Ho_2010_Da.tif @@ -889,7 +836,6 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Pg_2010_Da.tif @@ -908,7 +854,6 @@ glw_sheeps: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: v3 version: 3 path: socio_economic/glw/5_Sh_2010_Da.tif @@ -937,7 +882,6 @@ grip_roads: paper_ref: Meijer et al, 2018 paper_doi: 10.1088/1748-9326/aabd42 source_license: CC0-1.0 - source_version: v4 processing_script: infrastructure/grip/merge.ipynb version: 4 path: infrastructure/grip/GRIP4_world.fgb @@ -954,7 +898,6 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 version: 1.01 path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb @@ -974,7 +917,6 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 nodata: 0 version: 1.01 path: hydrography/grwl/tindex.gpkg @@ -991,7 +933,6 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 nodata: 255 version: v1_1_2019 path: hydrography/gswo/occur.vrt @@ -1010,7 +951,6 @@ gtsm_codec_reanalysis_{freq}_v1: paper_ref: Muis at al (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf source_url: https://doi.org/10.24381/cds.8c59054f - source_version: 1 version: 1 path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc placeholders: @@ -1044,7 +984,6 @@ hydro_lakes: category: surface water notes: HydroLAKES.v10_extract source_author: Arjen Haag - source_version: 1.0 version: 1.0 path: hydrography/lakes/lake-db.fgb rename: @@ -1066,7 +1005,6 @@ hydro_reservoirs: category: surface water notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 source_author: Alessia Matano - source_version: 1.0 nodata: -99 version: 1.0 path: hydrography/reservoirs/reservoir-db.fgb @@ -1103,7 +1041,6 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 nodata: 0 version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif @@ -1121,7 +1058,6 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 unit: m+GOCO05S processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb version: 18 @@ -1142,7 +1078,6 @@ merit: paper_ref: Yamazaki et al. (2018) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ - source_version: 1.0.3 version: 1.0.3 path: topography/merit/merit.nc rename: @@ -1162,7 +1097,6 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 version: 1.0 path: topography/merit_hydro/*.vrt rename: @@ -1190,7 +1124,6 @@ merit_hydro_ihu: source_license: ODC-By 1.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk source_doi: 10.5281/zenodo.5166932 - source_version: 1.0 processing_notes: topography/merit_hydro_ihu/README path: topography/merit_hydro_ihu/30sec/*.tif version: 1.0 @@ -1225,7 +1158,6 @@ merit_hydro_index: paper_doi: 10.5194/hess-25-5287-2021 paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 - source_version: 1.0 version: 1.0 path: topography/merit_hydro/basin_index.fgb @@ -1243,7 +1175,6 @@ merit_hydro_patch: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 Deltares patch processing_script: topography/merit_hydro/patches/scripts version: 1.0 path: topography/merit_hydro/patches/*.vrt @@ -1273,7 +1204,6 @@ modis_lai: paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 processing_script: GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py @@ -1292,7 +1222,6 @@ osm_coastlines: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 version: 1.0 path: geography/osm/osm_coastlines-db.fgb rename: @@ -1308,7 +1237,6 @@ osm_landareas: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 version: 1.0 path: geography/osm/osm_landareas-db.fgb rename: @@ -1325,7 +1253,6 @@ rgi: paper_ref: Pfeffer et al. (2014) source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 version: 6.0 path: hydrography/rgi/rgi.fgb rename: @@ -1343,7 +1270,6 @@ rivers_lin2019_v1: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 processing_notes: hydrography/rivers_lin2019/README version: 1 path: hydrography/rivers_lin2019/rivers_ge30m.fgb @@ -1364,7 +1290,6 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - source_version: 2011 version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif @@ -1384,7 +1309,6 @@ SM2RAIN_ASCAT_monthly_025_v1.4: paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - source_version: 1.4 version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: @@ -1406,7 +1330,6 @@ SM2RAIN_ASCAT_monthly_05_v1.4: paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - source_version: 1.4 version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: @@ -1433,8 +1356,7 @@ soilgrids: paper_doi: 10.1371/journal.pone.0169748 paper_ref: Hengl et al. (2017) source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 rename: BLDFIE_M_sl1_250m_ll: bd_sl1 BLDFIE_M_sl2_250m_ll: bd_sl2 @@ -1509,7 +1431,6 @@ soilgrids: paper_ref: de Sousa et al. (2020) source_license: CC BY 4.0 source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - source_version: 2020 processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb processing_notes: soil/soilgrids_v2.0/src/readme.txt rename: @@ -1609,7 +1530,6 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif vito_2016_v3.0.1: @@ -1625,7 +1545,6 @@ vito_2016_v3.0.1: paper_doi: 10.5281/zenodo.3518026 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif vito_2017_v3.0.1: @@ -1641,7 +1560,6 @@ vito_2017_v3.0.1: paper_doi: 10.5281/zenodo.3518036 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif vito_2018_v3.0.1: @@ -1657,7 +1575,6 @@ vito_2018_v3.0.1: paper_doi: 10.5281/zenodo.3518038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif vito_2019_v3.0.1: @@ -1673,7 +1590,6 @@ vito_2019_v3.0.1: paper_doi: 10.5281/zenodo.3939050 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: @@ -1685,7 +1601,6 @@ wb_countries: source_author: World Bank source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries source_license: CC-BY 4.0 - source_version: 20200319 timestamp: February 2020 version: 20200319 path: geography/wb/WB_countries_Admin0.fgb @@ -1711,7 +1626,6 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2.0 nodata: -999.0 version: 2.0 path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc @@ -1762,6 +1676,5 @@ wsf_bld_2015_v1: paper_ref: Marconcini at al (2020) source_license: CC0 1.0 source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc - source_version: 1 version: 1 path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt From 77c3055e462f27b521b1b42cf082b50c63500cfe Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Dec 2023 10:28:00 +0100 Subject: [PATCH 009/110] Updated predefined data catalog changelog --- data/catalogs/changelog.rst | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index e01e9c5db..dc7dd63a9 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -2,6 +2,26 @@ Change log predefined datasets ============================== +deltares_data +============= + +version: 2023.3 +--------------- + +changed +^^^^^^^ +- removed source_version from data source meta +- kwargs to driver_kwargs +- updated source_url if url was not working anymore + + +added +^^^^^ +- version argument to data source where applicable +- variants argument for data sources that are of the same dataset but different versions +- processing_script / processing_notes arguments to data sources that have been (pre-) processed + + deltares_data ============= From 8d37459f162ab6fbfa51aee97c64f24578e766ee Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Dec 2023 10:32:55 +0100 Subject: [PATCH 010/110] updated changelog --- docs/changelog.rst | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/changelog.rst b/docs/changelog.rst index 3ecaecb5a..07f592256 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -15,9 +15,11 @@ Added ----- - Export CLI now also accepts time tuples (#660) + Changed ------- - Export CLI now uses '-s' for source, '-t' for time and '-i' for config. (#660) +- Updated deltares_data data catalog to incorporate the newest data catalog features (#667) Fixed ----- From efe622a7d09fee0422ab9c6d7cef431ee8fd809e Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 7 Dec 2023 14:50:38 +0100 Subject: [PATCH 011/110] removed '*' era5 path in deltares data catalog and added check in data adapter --- data/catalogs/deltares_data.yml | 4 ++-- hydromt/data_adapter/data_adapter.py | 8 ++++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index c59d8fe5a..43812dd84 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -467,7 +467,7 @@ era5_daily: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 source_version: ERA5 daily data on pressure levels - path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc rename: d2m: temp_dew msl: press_msl @@ -519,7 +519,7 @@ era5_hourly: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 source_version: ERA5 hourly data on single levels from 1940 to present - path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc rename: d2m: temp_dew msl: press_msl diff --git a/hydromt/data_adapter/data_adapter.py b/hydromt/data_adapter/data_adapter.py index 9aaa49131..24ac8a05d 100644 --- a/hydromt/data_adapter/data_adapter.py +++ b/hydromt/data_adapter/data_adapter.py @@ -325,9 +325,13 @@ def _resolve_paths( continue key_str = "{" + f"{key}:{fmt}" + "}" if fmt else "{" + key + "}" # remove unused fields - if key in ["year", "month"] and time_tuple is None: + if ( + key in ["year", "month"] + and time_tuple is None + and not path.endswith("*") + ): path += "*" - elif key == "variable" and variables is None: + elif key == "variable" and variables is None and not path.endswith("*"): path += "*" # escape unknown fields elif key is not None and key not in known_keys: From fe8ea5a3a7f9535d82c9d5f7dceaa05ec2cdc134 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 8 Dec 2023 11:43:47 +0100 Subject: [PATCH 012/110] Added data_type to glofas_uparea --- data/catalogs/deltares_data.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 0f0c9ab29..77a2efc58 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -694,6 +694,7 @@ glofas_era5_v31: dis24: discharge glofas_uparea: + data_type: RasterDataset driver: raster driver_kwargs: chunks: From 47f7fdccdbb79498569d10ff32644b3930550379 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 15 Dec 2023 10:05:44 +0100 Subject: [PATCH 013/110] Set mollweide crs to ESRI:54009 otherwise will error --- data/catalogs/deltares_data.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 40d9bb603..1dfdc5d5f 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -609,7 +609,7 @@ ghs_pop: path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif ghs_pop_2015_54009_v2019a: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster driver_kwargs: @@ -626,7 +626,7 @@ ghs_pop_2015_54009_v2019a: path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif ghs_smod: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster driver_kwargs: From 252dab38977460affa9f9a1b334ea21c52108d74 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 21 Dec 2023 13:26:42 +0100 Subject: [PATCH 014/110] fixed failing datacatalog validation tests --- hydromt/validators/data_catalog.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/hydromt/validators/data_catalog.py b/hydromt/validators/data_catalog.py index a5592d314..9e6391146 100644 --- a/hydromt/validators/data_catalog.py +++ b/hydromt/validators/data_catalog.py @@ -111,7 +111,9 @@ class DataCatalogItem(BaseModel): path: Optional[Path] = None crs: Optional[Union[int, str]] = None filesystem: Optional[str] = None - kwargs: Dict[str, Any] = Field(default_factory=dict) + provider: Optional[str] = None + driver_kwargs: Dict[str, Any] = Field(default_factory=dict) + kwargs: Dict[str, Any] = Field(default_factory=dict) # deprecated storage_options: Dict[str, Any] = Field(default_factory=dict) placeholders: Optional[Dict[str, Any]] = None rename: Dict[str, str] = Field(default_factory=dict) From 1817fbc37d8fba88dd3dcdfb1529be9ee4614459 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 21 Dec 2023 14:49:19 +0100 Subject: [PATCH 015/110] added temporal extent to deltares data --- data/catalogs/deltares_data.yml | 460 +++++++++++++++++--------------- 1 file changed, 250 insertions(+), 210 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 418959cc4..bac7bb7de 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -89,6 +89,9 @@ chirps: paper_ref: Funk et al (2015) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps + source_temporal_extent: + start: '1981-01-02' + end: '2022-04-01' version: 2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: @@ -114,6 +117,9 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps + source_temporal_extent: + start: '1981-01-02' + end: '2023-02-01' version: 2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: @@ -134,7 +140,7 @@ copdem30: source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 version: 2021.1 path: topography/copdem/copdem.vrt - nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning + nodata: -9999 rename: copdem: elevtn @@ -151,7 +157,7 @@ copdem30_mask: source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 version: 2021.1 path: topography/copdem/copdem_mask.vrt - nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning + nodata: -1 rename: copdem_mask: mask @@ -184,10 +190,9 @@ corine: source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 provider: local - version: 2020_20u1 + version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif - dtu10mdt: crs: 4326 data_type: RasterDataset @@ -242,6 +247,9 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_temporal_extent: + start: '1950-01-02' + end: '2022-01-01' variants: - version: 22.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc @@ -278,21 +286,19 @@ eobs_orography: source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles variants: - - version: 20.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - - version: 22.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - - version: 23.1e - path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - - version: 24.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - - version: 25.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - + - version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + - version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + - version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + - version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + - version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc rename: elevation: elevtn - era5: crs: 4326 data_type: RasterDataset @@ -307,12 +313,16 @@ era5: parallel: true meta: category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 source_version: ERA5 daily data on pressure levels + source_temporal_extent: + start: '1950-01-02' + end: '2023-11-30' path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc rename: d2m: temp_dew @@ -344,12 +354,16 @@ era5_daily_zarr: chunks: auto meta: category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 processing_script: meteo/era5_zarr/scripts/ + source_temporal_extent: + start: '1950-01-02' + end: '2023-02-01' path: meteo/era5_daily.zarr era5_hourly: @@ -372,6 +386,9 @@ era5_hourly: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 source_version: ERA5 hourly data on single levels from 1940 to present + source_temporal_extent: + start: '1950-01-01' + end: '2023-03-01' path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc rename: d2m: temp_dew @@ -406,6 +423,9 @@ era5_hourly_zarr: source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 processing_script: meteo/era5_zarr/scripts/ + source_temporal_extent: + start: '1950-01-01' + end: '2023-02-01' path: meteo/era5.zarr era5_ocean: @@ -427,6 +447,9 @@ era5_ocean: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_temporal_extent: + start: '1979-01-01' + end: '2022-04-08' path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc era5_orography: @@ -444,6 +467,9 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 + source_temporal_extent: + start: '2018-01-01' + end: '2018-01-01' path: meteo/era5/meta/era5_orography_2018.nc rename: z: elevtn @@ -484,7 +510,6 @@ fabdem: rename: fabdem: elevtn - gadm_level0: crs: 4326 data_type: GeoDataFrame @@ -568,7 +593,8 @@ gdp_world: driver: vector meta: category: socio-economic - notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 version: 1.0 @@ -618,7 +644,7 @@ ghs_pop: path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif ghs_pop_2015_54009_v2019a: - crs: "ESRI:54009" + crs: ESRI:54009 data_type: RasterDataset driver: raster driver_kwargs: @@ -647,18 +673,17 @@ ghs_smod: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse variants: - - version: R2016A_v1.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - meta: - paper_ref: Pesaresi and Freire (2016) - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - - version: R2019A_v2.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif - meta: - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - + - version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 globcover: crs: 4326 @@ -697,6 +722,9 @@ glofas_era5_v31: source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 processing_script: hydro/glofas_era5/glofas_cds_get.py + source_temporal_extent: + start: '1980-01-01' + end: '2021-05-31' version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc rename: @@ -721,7 +749,7 @@ glofas_uparea: rename: glofas_v31_uparea: uparea unit_mult: - uparea: 0.000001 + uparea: 1.0e-06 glw_buffaloes: crs: 4326 @@ -964,7 +992,10 @@ gtsm_codec_reanalysis_{freq}_v1: version: 1 path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc placeholders: - freq: [10min, hourly, dailymax] + freq: + - 10min + - hourly + - dailymax rename: station_x_coordinate: lon station_y_coordinate: lat @@ -1209,7 +1240,8 @@ modis_lai: concat: true meta: category: landuse - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' + notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ @@ -1314,11 +1346,15 @@ SM2RAIN_ASCAT_monthly_025_v1.4: time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, + 0.25-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_temporal_extent: + start: '2007-01-01' + end: '2020-12-01' version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: @@ -1335,11 +1371,15 @@ SM2RAIN_ASCAT_monthly_05_v1.4: time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, + 0.5-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_temporal_extent: + start: '2007-01-01' + end: '2020-12-01' version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: @@ -1356,176 +1396,178 @@ soilgrids: meta: category: soil variants: - - version: 2017 - path: soil/soilgrids_v1.0/*_250m_ll.tif - meta: - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. (2017) - source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 - rename: - BLDFIE_M_sl1_250m_ll: bd_sl1 - BLDFIE_M_sl2_250m_ll: bd_sl2 - BLDFIE_M_sl3_250m_ll: bd_sl3 - BLDFIE_M_sl4_250m_ll: bd_sl4 - BLDFIE_M_sl5_250m_ll: bd_sl5 - BLDFIE_M_sl6_250m_ll: bd_sl6 - BLDFIE_M_sl7_250m_ll: bd_sl7 - CLYPPT_M_sl1_250m_ll: clyppt_sl1 - CLYPPT_M_sl2_250m_ll: clyppt_sl2 - CLYPPT_M_sl3_250m_ll: clyppt_sl3 - CLYPPT_M_sl4_250m_ll: clyppt_sl4 - CLYPPT_M_sl5_250m_ll: clyppt_sl5 - CLYPPT_M_sl6_250m_ll: clyppt_sl6 - CLYPPT_M_sl7_250m_ll: clyppt_sl7 - ORCDRC_M_sl1_250m_ll: oc_sl1 - ORCDRC_M_sl2_250m_ll: oc_sl2 - ORCDRC_M_sl3_250m_ll: oc_sl3 - ORCDRC_M_sl4_250m_ll: oc_sl4 - ORCDRC_M_sl5_250m_ll: oc_sl5 - ORCDRC_M_sl6_250m_ll: oc_sl6 - ORCDRC_M_sl7_250m_ll: oc_sl7 - PHIHOX_M_sl1_250m_ll: ph_sl1 - PHIHOX_M_sl2_250m_ll: ph_sl2 - PHIHOX_M_sl3_250m_ll: ph_sl3 - PHIHOX_M_sl4_250m_ll: ph_sl4 - PHIHOX_M_sl5_250m_ll: ph_sl5 - PHIHOX_M_sl6_250m_ll: ph_sl6 - PHIHOX_M_sl7_250m_ll: ph_sl7 - SLTPPT_M_sl1_250m_ll: sltppt_sl1 - SLTPPT_M_sl2_250m_ll: sltppt_sl2 - SLTPPT_M_sl3_250m_ll: sltppt_sl3 - SLTPPT_M_sl4_250m_ll: sltppt_sl4 - SLTPPT_M_sl5_250m_ll: sltppt_sl5 - SLTPPT_M_sl6_250m_ll: sltppt_sl6 - SLTPPT_M_sl7_250m_ll: sltppt_sl7 - SNDPPT_M_sl1_250m_ll: sndppt_sl1 - SNDPPT_M_sl2_250m_ll: sndppt_sl2 - SNDPPT_M_sl3_250m_ll: sndppt_sl3 - SNDPPT_M_sl4_250m_ll: sndppt_sl4 - SNDPPT_M_sl5_250m_ll: sndppt_sl5 - SNDPPT_M_sl6_250m_ll: sndppt_sl6 - SNDPPT_M_sl7_250m_ll: sndppt_sl7 - SoilThickness_250m_ll: soilthickness - TAXOUSDA_250m_ll: tax_usda - unit_mult: - bd_sl1: 0.001 - bd_sl2: 0.001 - bd_sl3: 0.001 - bd_sl4: 0.001 - bd_sl5: 0.001 - bd_sl6: 0.001 - bd_sl7: 0.001 - oc_sl1: 0.1 - oc_sl2: 0.1 - oc_sl3: 0.1 - oc_sl4: 0.1 - oc_sl5: 0.1 - oc_sl6: 0.1 - oc_sl7: 0.1 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - - version: 2020 - path: soil/soilgrids_v2.0/*/*_mean.vrt - meta: - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb - processing_notes: soil/soilgrids_v2.0/src/readme.txt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 - + - version: 2017 + path: soil/soilgrids_v1.0/*_250m_ll.tif + meta: + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\n\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land\ + \ Use Policy 29 (2), 329\xC3\xA2\xE2\u201A\xAC\xE2\u20AC\u0153338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 + rename: + BLDFIE_M_sl1_250m_ll: bd_sl1 + BLDFIE_M_sl2_250m_ll: bd_sl2 + BLDFIE_M_sl3_250m_ll: bd_sl3 + BLDFIE_M_sl4_250m_ll: bd_sl4 + BLDFIE_M_sl5_250m_ll: bd_sl5 + BLDFIE_M_sl6_250m_ll: bd_sl6 + BLDFIE_M_sl7_250m_ll: bd_sl7 + CLYPPT_M_sl1_250m_ll: clyppt_sl1 + CLYPPT_M_sl2_250m_ll: clyppt_sl2 + CLYPPT_M_sl3_250m_ll: clyppt_sl3 + CLYPPT_M_sl4_250m_ll: clyppt_sl4 + CLYPPT_M_sl5_250m_ll: clyppt_sl5 + CLYPPT_M_sl6_250m_ll: clyppt_sl6 + CLYPPT_M_sl7_250m_ll: clyppt_sl7 + ORCDRC_M_sl1_250m_ll: oc_sl1 + ORCDRC_M_sl2_250m_ll: oc_sl2 + ORCDRC_M_sl3_250m_ll: oc_sl3 + ORCDRC_M_sl4_250m_ll: oc_sl4 + ORCDRC_M_sl5_250m_ll: oc_sl5 + ORCDRC_M_sl6_250m_ll: oc_sl6 + ORCDRC_M_sl7_250m_ll: oc_sl7 + PHIHOX_M_sl1_250m_ll: ph_sl1 + PHIHOX_M_sl2_250m_ll: ph_sl2 + PHIHOX_M_sl3_250m_ll: ph_sl3 + PHIHOX_M_sl4_250m_ll: ph_sl4 + PHIHOX_M_sl5_250m_ll: ph_sl5 + PHIHOX_M_sl6_250m_ll: ph_sl6 + PHIHOX_M_sl7_250m_ll: ph_sl7 + SLTPPT_M_sl1_250m_ll: sltppt_sl1 + SLTPPT_M_sl2_250m_ll: sltppt_sl2 + SLTPPT_M_sl3_250m_ll: sltppt_sl3 + SLTPPT_M_sl4_250m_ll: sltppt_sl4 + SLTPPT_M_sl5_250m_ll: sltppt_sl5 + SLTPPT_M_sl6_250m_ll: sltppt_sl6 + SLTPPT_M_sl7_250m_ll: sltppt_sl7 + SNDPPT_M_sl1_250m_ll: sndppt_sl1 + SNDPPT_M_sl2_250m_ll: sndppt_sl2 + SNDPPT_M_sl3_250m_ll: sndppt_sl3 + SNDPPT_M_sl4_250m_ll: sndppt_sl4 + SNDPPT_M_sl5_250m_ll: sndppt_sl5 + SNDPPT_M_sl6_250m_ll: sndppt_sl6 + SNDPPT_M_sl7_250m_ll: sndppt_sl7 + SoilThickness_250m_ll: soilthickness + TAXOUSDA_250m_ll: tax_usda + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + - version: 2020 + path: soil/soilgrids_v2.0/*/*_mean.vrt + meta: + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb + processing_notes: soil/soilgrids_v2.0/src/readme.txt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 vito: crs: 4326 @@ -1671,8 +1713,6 @@ worldpop_2020_UNadj_constrained: ppp_2020_UNadj_constrained: population wsf_bld_2015: - alias: wsf_bld_2015_v1 -wsf_bld_2015_v1: crs: 4326 data_type: RasterDataset driver: raster From 2bab26bfc06a047de62d28effe70804694c890bc Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 21 Dec 2023 15:01:36 +0100 Subject: [PATCH 016/110] updated changelog --- data/catalogs/changelog.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 03b33ff74..3da8ca5a8 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -20,6 +20,7 @@ added - version argument to data source where applicable - variants argument for data sources that are of the same dataset but different versions - processing_script / processing_notes arguments to data sources that have been (pre-) processed +- temporal extent of datasets that have a temporal dimension. From 9a85eb32136f5fc4104d8baa172e5f9a46db5882 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 10 Jan 2024 13:42:51 +0100 Subject: [PATCH 017/110] added hydromt version to deltares_data --- data/catalogs/deltares_data.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index e6a4b8631..af963a505 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -2,6 +2,7 @@ meta: root: p:/wflow_global/hydromt version: 2023.12 + hydromt_version: '>=0.9' basin_atlas_level12_v10: From 2dc66f1205b6e92d864115bed98297a8fbd439a8 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 10 Jan 2024 13:48:59 +0100 Subject: [PATCH 018/110] added hydromt versions to aws_data and gcs_cmip6_data data catalogs --- data/catalogs/aws_data.yml | 2 ++ data/catalogs/gcs_cmip6_data.yml | 2 ++ 2 files changed, 4 insertions(+) diff --git a/data/catalogs/aws_data.yml b/data/catalogs/aws_data.yml index ae6891376..1251c9096 100644 --- a/data/catalogs/aws_data.yml +++ b/data/catalogs/aws_data.yml @@ -1,6 +1,8 @@ --- meta: version: 2023.2 + hydromt_version: '>=0.9' + esa_worldcover_2020_v100: crs: 4326 data_type: RasterDataset diff --git a/data/catalogs/gcs_cmip6_data.yml b/data/catalogs/gcs_cmip6_data.yml index 54bca2f6e..6258d2835 100644 --- a/data/catalogs/gcs_cmip6_data.yml +++ b/data/catalogs/gcs_cmip6_data.yml @@ -1,6 +1,8 @@ --- meta: version: 2023.2 + hydromt_version: '>=0.8.1' + cmip6_{model}_historical_{member}_{timestep}: crs: 4326 data_type: RasterDataset From 237579ff52bc6307b2fc1de5463dfb1d04bc68e1 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 10 Jan 2024 14:52:53 +0100 Subject: [PATCH 019/110] Updated data catalog version --- data/catalogs/aws_data.yml | 2 +- data/catalogs/deltares_data.yml | 2 +- data/catalogs/gcs_cmip6_data.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/data/catalogs/aws_data.yml b/data/catalogs/aws_data.yml index 1251c9096..7bdd7bf60 100644 --- a/data/catalogs/aws_data.yml +++ b/data/catalogs/aws_data.yml @@ -1,6 +1,6 @@ --- meta: - version: 2023.2 + version: 2024.1 hydromt_version: '>=0.9' esa_worldcover_2020_v100: diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index af963a505..0c685cd84 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1,7 +1,7 @@ --- meta: root: p:/wflow_global/hydromt - version: 2023.12 + version: 2024.1 hydromt_version: '>=0.9' diff --git a/data/catalogs/gcs_cmip6_data.yml b/data/catalogs/gcs_cmip6_data.yml index 6258d2835..6732c82bd 100644 --- a/data/catalogs/gcs_cmip6_data.yml +++ b/data/catalogs/gcs_cmip6_data.yml @@ -1,6 +1,6 @@ --- meta: - version: 2023.2 + version: 2024.1 hydromt_version: '>=0.8.1' cmip6_{model}_historical_{member}_{timestep}: From dd8068355334ab2f2d9489047e6f2d31dc450023 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 10 Jan 2024 14:53:47 +0100 Subject: [PATCH 020/110] updated changelog --- data/catalogs/changelog.rst | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 298810f23..3d5669e56 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -5,6 +5,13 @@ Change log predefined datasets deltares_data ============= +version: 2024.1 +---------------- + +added +^^^^^ +- hydromt_version to data catalog meta + version: 2023.12 ----------------- @@ -77,6 +84,13 @@ fixed cmip6_data ========== +version: 2024.1 +---------------- + +added +^^^^^ +- hydromt_version to data catalog meta + version: 2023.2 --------------- @@ -87,6 +101,13 @@ added aws_data ======== +version: 2024.1 +---------------- + +added +^^^^^ +- hydromt_version to data catalog meta + version: 2023.2 --------------- From cac2cf3b1c10896ba252e650a684c243b1443466 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Mon, 15 Jan 2024 15:54:25 +0100 Subject: [PATCH 021/110] Added spatial extent for raster datasets --- data/catalogs/deltares_data.yml | 295 ++++++++++++++++++++++++++++++++ 1 file changed, 295 insertions(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 0c685cd84..73af27df5 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -69,6 +69,11 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 84.0 version: 1.2 path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif @@ -93,6 +98,11 @@ chirps: source_temporal_extent: start: '1981-01-02' end: '2022-04-01' + source_spatial_extent: + West: -20.0 + South: -40.0 + East: 55.0 + North: 40.0 version: 2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: @@ -121,6 +131,11 @@ chirps_global: source_temporal_extent: start: '1981-01-02' end: '2023-02-01' + source_spatial_extent: + West: -180.0 + South: -50.0 + East: 180.0 + North: 50.0 version: 2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: @@ -139,6 +154,11 @@ copdem30: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 version: 2021.1 path: topography/copdem/copdem.vrt nodata: -9999 @@ -156,6 +176,11 @@ copdem30_mask: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 version: 2021.1 path: topography/copdem/copdem_mask.vrt nodata: -1 @@ -173,6 +198,11 @@ copdem30_masked: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 version: 2021.1 path: topography/copdem/copdem_masked.vrt rename: @@ -190,6 +220,11 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_spatial_extent: + West: 900000.0 + South: 900000.0 + East: 7400000.0 + North: 5500000.0 provider: local version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif @@ -208,6 +243,11 @@ dtu10mdt: paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography unit: m+EGM2008 + source_spatial_extent: + West: -179.992 + South: -89.992 + East: 179.992 + North: 89.992 version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_float32.tif @@ -227,6 +267,11 @@ dtu10mdt_egm96: processing_notes: /topography/dtu10mdt/READ_ME.txt processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb unit: m+EGM96 + source_spatial_extent: + West: -179.992 + South: -89.985 + East: 179.995 + North: 89.992 version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif @@ -251,6 +296,11 @@ eobs: source_temporal_extent: start: '1950-01-02' end: '2022-01-01' + source_spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 variants: - version: 22.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc @@ -286,6 +336,11 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 variants: - version: 20.0e path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc @@ -324,6 +379,11 @@ era5: source_temporal_extent: start: '1950-01-02' end: '2023-11-30' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc rename: d2m: temp_dew @@ -365,6 +425,11 @@ era5_daily_zarr: source_temporal_extent: start: '1950-01-02' end: '2023-02-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5_daily.zarr era5_hourly: @@ -390,6 +455,11 @@ era5_hourly: source_temporal_extent: start: '1950-01-01' end: '2023-03-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc rename: d2m: temp_dew @@ -427,6 +497,11 @@ era5_hourly_zarr: source_temporal_extent: start: '1950-01-01' end: '2023-02-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5.zarr era5_ocean: @@ -451,6 +526,11 @@ era5_ocean: source_temporal_extent: start: '1979-01-01' end: '2022-04-08' + source_spatial_extent: + West: -0.25 + South: -90.25 + East: 359.75 + North: 90.25 path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc era5_orography: @@ -471,6 +551,11 @@ era5_orography: source_temporal_extent: start: '2018-01-01' end: '2018-01-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5/meta/era5_orography_2018.nc rename: z: elevtn @@ -489,6 +574,11 @@ esa_worldcover: category: landuse source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 84.0 version: 100 path: landuse/esa_worldcover/esa-worldcover.vrt @@ -506,6 +596,11 @@ fabdem: paper_ref: Hawker et al. (2022) source_license: CC BY-NC-SA 4.0 source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 version: 1.0 path: topography/fabdem/fabdem.vrt rename: @@ -580,6 +675,11 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_spatial_extent: + West: -180.0 + South: -56.0 + East: 180.0 + North: 84.0 nodata: 255 version: 1 path: landuse/gcn250/GCN250_*.tif @@ -621,6 +721,11 @@ gebco: source_url: https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data/ unit: m+MSL processing_script: bathymetry/gebco/gebco_tiles.ipynb + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 2020 path: bathymetry/gebco/gebco.vrt rename: @@ -641,6 +746,11 @@ ghs_pop: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_spatial_extent: + West: -180.0 + South: -59.485 + East: 180.0 + North: 83.628 version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif @@ -658,6 +768,11 @@ ghs_pop_2015_54009_v2019a: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + source_spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 version: R2019A_54009_250_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif @@ -673,6 +788,11 @@ ghs_smod: category: socio-economic source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 variants: - version: R2016A_v1.0 path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif @@ -700,6 +820,11 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php + source_spatial_extent: + West: -180.001 + South: -64.999 + East: 179.999 + North: 90.001 version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif @@ -726,6 +851,11 @@ glofas_era5_v31: source_temporal_extent: start: '1980-01-01' end: '2021-05-31' + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 90.0 version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc rename: @@ -745,6 +875,11 @@ glofas_uparea: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 90.0 version: 31 path: hydro/glofas_era5/glofas_v31_uparea.tif rename: @@ -767,6 +902,11 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Bf_2010_Da.tif @@ -785,6 +925,11 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Ct_2010_Da.tif @@ -803,6 +948,11 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Ch_2010_Da.tif @@ -821,6 +971,11 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Dk_2010_Da.tif @@ -839,6 +994,11 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Gt_2010_Da.tif @@ -857,6 +1017,11 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Ho_2010_Da.tif @@ -875,6 +1040,11 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Pg_2010_Da.tif @@ -893,6 +1063,11 @@ glw_sheeps: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 3 path: socio_economic/glw/5_Sh_2010_Da.tif @@ -907,6 +1082,11 @@ grdc: notes: GRDC-Station Catalogue, last downloaded 2020-07-16 source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + source_spatial_extent: + West: -179.25 + South: -90.0 + East: 180.0 + North: 80.6 path: hydro/grdc/GRDC_Stations.xlsx rename: area: uparea @@ -972,6 +1152,11 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 nodata: 255 version: v1_1_2019 path: hydrography/gswo/occur.vrt @@ -1016,6 +1201,11 @@ guf_bld_2012: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf + source_spatial_extent: + West: -180.0 + South: -65.0 + East: 180.0 + North: 85.0 path: infrastructure/guf/GUF04_DLR_v02.vrt hydro_lakes: @@ -1083,6 +1273,11 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 nodata: 0 version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif @@ -1102,6 +1297,11 @@ mdt_cnes_cls18: source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html unit: m+GOCO05S processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 18 path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif @@ -1120,6 +1320,11 @@ merit: paper_ref: Yamazaki et al. (2018) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 1.0.3 path: topography/merit/merit.nc rename: @@ -1139,6 +1344,11 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 version: 1.0 path: topography/merit_hydro/*.vrt rename: @@ -1167,6 +1377,11 @@ merit_hydro_ihu: source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk source_doi: 10.5281/zenodo.5166932 processing_notes: topography/merit_hydro_ihu/README + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 path: topography/merit_hydro_ihu/30sec/*.tif version: 1.0 rename: @@ -1218,6 +1433,11 @@ merit_hydro_patch: source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro processing_script: topography/merit_hydro/patches/scripts + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 version: 1.0 path: topography/merit_hydro/patches/*.vrt rename: @@ -1250,6 +1470,11 @@ modis_lai: processing_script: GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py + source_spatial_extent: + West: -180.004 + South: -90.002 + East: 180.004 + North: 90.002 version: MCD15A3H V006 path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: @@ -1299,6 +1524,11 @@ pcr_globwb: source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 variants: - version: 1990 path: hydro/pcr_globwb/glob_1990.zarr @@ -1372,6 +1602,11 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif @@ -1395,6 +1630,11 @@ SM2RAIN_ASCAT_monthly_025_v1.4: source_temporal_extent: start: '2007-01-01' end: '2020-12-01' + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: @@ -1420,6 +1660,11 @@ SM2RAIN_ASCAT_monthly_05_v1.4: source_temporal_extent: start: '2007-01-01' end: '2020-12-01' + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: @@ -1435,6 +1680,11 @@ soilgrids: y: 2400 meta: category: soil + source_spatial_extent: + West: -19949000.0 + South: -6147500.0 + East: 19861750.0 + North: 8361000.0 variants: - version: 2017 path: soil/soilgrids_v1.0/*_250m_ll.tif @@ -1622,6 +1872,11 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif vito_2016_v3.0.1: @@ -1637,6 +1892,11 @@ vito_2016_v3.0.1: paper_doi: 10.5281/zenodo.3518026 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif vito_2017_v3.0.1: @@ -1652,6 +1912,11 @@ vito_2017_v3.0.1: paper_doi: 10.5281/zenodo.3518036 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif vito_2018_v3.0.1: @@ -1667,6 +1932,11 @@ vito_2018_v3.0.1: paper_doi: 10.5281/zenodo.3518038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif vito_2019_v3.0.1: @@ -1682,6 +1952,11 @@ vito_2019_v3.0.1: paper_doi: 10.5281/zenodo.3939050 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: @@ -1719,6 +1994,11 @@ worldclim: paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html nodata: -999.0 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 2.0 path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc rename: @@ -1736,6 +2016,11 @@ worldpop_2020_constrained: source_license: CC BY 4.0 source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 processing_script: socio_economic/worldpop/src/ + source_spatial_extent: + West: -180.0 + South: -55.985 + East: 180.0 + North: 83.628 nodata: -99999 path: socio_economic/worldpop/ppp_2020_constrained.vrt rename: @@ -1748,6 +2033,11 @@ worldpop_2020_UNadj_constrained: chunks: auto meta: processing_script: socio_economic/worldpop/src/ + source_spatial_extent: + West: -180.0 + South: -55.985 + East: 180.0 + North: 83.628 path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt rename: ppp_2020_UNadj_constrained: population @@ -1766,5 +2056,10 @@ wsf_bld_2015: paper_ref: Marconcini at al (2020) source_license: CC0 1.0 source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 version: 1 path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt From c53b5c9bd0e933e2fa2bbbc6d0304d5ce4d1139c Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Tue, 16 Jan 2024 14:18:33 +0100 Subject: [PATCH 022/110] Added spatial extents to geodataframe --- data/catalogs/deltares_data.yml | 164 +++++++++++++++++++++++++------- 1 file changed, 129 insertions(+), 35 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 73af27df5..2e4fb8de5 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -4,7 +4,6 @@ meta: version: 2024.1 hydromt_version: '>=0.9' - basin_atlas_level12_v10: crs: 4326 data_type: GeoDataFrame @@ -18,43 +17,14 @@ basin_atlas_level12_v10: paper_ref: Linke et al. (2019) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas + source_spatial_extent: + West: -180.0 + South: -55.988 + East: 180.001 + North: 83.626 version: 10 path: hydrography/hydro_atlas/basin_atlas_v10.gpkg -river_atlas_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - path: hydrography/hydro_atlas/river_atlas_v10.gpkg - version: 10 - rename: - dis_m3_pyr: Dis_avg - -lake_atlas_pol_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - driver_kwargs: - layer: LakeATLAS_v10_pol - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-022-01425-z - paper_ref: Lehner et al. (2022) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - path: hydrography/hydro_atlas/lake_atlas_v10.gpkg - version: 10 - rename: - dis_m3_pyr: Dis_avg - chelsa: crs: 4326 data_type: RasterDataset @@ -618,6 +588,11 @@ gadm_level0: source_url: https://gadm.org/download_world.html source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 path: geography/gadm/version4_1/gadm_level0.fgb gadm_level1: @@ -632,6 +607,11 @@ gadm_level1: source_url: https://gadm.org/download_world.html source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 path: geography/gadm/version4_1/gadm_level1.fgb gadm_level2: @@ -646,6 +626,11 @@ gadm_level2: source_url: https://gadm.org/download_world.html source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 path: geography/gadm/version4_1/gadm_level2.fgb gadm_level3: @@ -660,6 +645,11 @@ gadm_level3: source_url: https://gadm.org/download_world.html source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 path: geography/gadm/version4_1/gadm_level3.fgb gcn250: @@ -698,6 +688,11 @@ gdp_world: and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.665 version: 1.0 path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb rename: @@ -1102,6 +1097,11 @@ grip_roads: paper_doi: 10.1088/1748-9326/aabd42 source_license: CC0-1.0 processing_script: infrastructure/grip/merge.ipynb + source_spatial_extent: + West: -179.999 + South: -55.055 + East: 180.0 + North: 73.836 version: 4 path: infrastructure/grip/GRIP4_world.fgb rename: @@ -1117,6 +1117,11 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 + source_spatial_extent: + West: -180.0 + South: -54.31 + East: 180.0 + North: 82.311 version: 1.01 path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb @@ -1216,6 +1221,11 @@ hydro_lakes: category: surface water notes: HydroLAKES.v10_extract source_author: Arjen Haag + source_spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 version: 1.0 path: hydrography/lakes/lake-db.fgb rename: @@ -1237,6 +1247,11 @@ hydro_reservoirs: category: surface water notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 source_author: Alessia Matano + source_spatial_extent: + West: -153.059 + South: -45.881 + East: 176.825 + North: 70.396 nodata: -99 version: 1.0 path: hydrography/reservoirs/reservoir-db.fgb @@ -1282,6 +1297,29 @@ koppen_geiger: version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif +lake_atlas_pol_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + driver_kwargs: + layer: LakeATLAS_v10_pol + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 + path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + version: 10 + rename: + dis_m3_pyr: Dis_avg + mdt_cnes_cls18: crs: 4326 data_type: RasterDataset @@ -1404,6 +1442,11 @@ merit_hydro_ihu_index: source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk processing_notes: topography/merit_hydro_ihu/README + source_spatial_extent: + West: -180.025 + South: -59.467 + East: 190.35 + North: 83.683 path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: @@ -1415,6 +1458,11 @@ merit_hydro_index: paper_doi: 10.5194/hess-25-5287-2021 paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 + source_spatial_extent: + West: -180.028 + South: -59.46 + East: 190.338 + North: 83.661 version: 1.0 path: topography/merit_hydro/basin_index.fgb @@ -1490,6 +1538,11 @@ osm_coastlines: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_spatial_extent: + West: -180.0 + South: -78.733 + East: 180.0 + North: 90.0 version: 1.0 path: geography/osm/osm_coastlines-db.fgb rename: @@ -1505,6 +1558,11 @@ osm_landareas: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.666 version: 1.0 path: geography/osm/osm_landareas-db.fgb rename: @@ -1565,6 +1623,11 @@ rgi: paper_ref: Pfeffer et al. (2014) source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_spatial_extent: + West: -179.921 + South: -78.309 + East: 179.751 + North: 83.608 version: 6.0 path: hydrography/rgi/rgi.fgb rename: @@ -1573,6 +1636,27 @@ rgi: ID: simple_id RGIID: RGI_id +river_atlas_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_spatial_extent: + West: -179.998 + South: -55.877 + East: 179.998 + North: 83.59 + path: hydrography/hydro_atlas/river_atlas_v10.gpkg + version: 10 + rename: + dis_m3_pyr: Dis_avg + rivers_lin2019_v1: data_type: GeoDataFrame driver: vector @@ -1583,6 +1667,11 @@ rivers_lin2019_v1: source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk processing_notes: hydrography/rivers_lin2019/README + source_spatial_extent: + West: -177.204 + South: -55.414 + East: 180.237 + North: 82.112 version: 1 path: hydrography/rivers_lin2019/rivers_ge30m.fgb rename: @@ -1969,6 +2058,11 @@ wb_countries: source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries source_license: CC-BY 4.0 timestamp: February 2020 + source_spatial_extent: + West: -180.0 + South: -59.473 + East: 180.0 + North: 83.634 version: 20200319 path: geography/wb/WB_countries_Admin0.fgb rename: From 9a9b6a9808a177c813f94dfe5a649f9fac0a247d Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Tue, 16 Jan 2024 14:22:25 +0100 Subject: [PATCH 023/110] updated data catalog changelog --- data/catalogs/changelog.rst | 17 +++++------------ 1 file changed, 5 insertions(+), 12 deletions(-) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 3d5669e56..816ccbe33 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -8,19 +8,13 @@ deltares_data version: 2024.1 ---------------- -added -^^^^^ -- hydromt_version to data catalog meta - -version: 2023.12 ------------------ - changed ^^^^^^^ -- Updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files +- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files - removed source_version from data source meta - kwargs to driver_kwargs - updated source_url if url was not working anymore +- sorted datasets by alphabetical order added ^^^^^ @@ -28,10 +22,9 @@ added - variants argument for data sources that are of the same dataset but different versions - processing_script / processing_notes arguments to data sources that have been (pre-) processed - temporal extent of datasets that have a temporal dimension. - -added -^^^^^ -- Added waterdemand pcr_globwb dataset +- hydromt_version to data catalog meta +- waterdemand pcr_globwb dataset +- spatial extents to datasets version: 2023.2 From 9ad2aad5072664d1ff350095957416149af61a9f Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Tue, 16 Jan 2024 15:02:04 +0100 Subject: [PATCH 024/110] removed gtsm_codec_reanalysis dataset from deltares data catalog and created a separate gtsm data catalog --- data/catalogs/deltares_data.yml | 26 --------------------- data/catalogs/gtsm_codec_reanalysis.yml | 30 +++++++++++++++++++++++++ 2 files changed, 30 insertions(+), 26 deletions(-) create mode 100644 data/catalogs/gtsm_codec_reanalysis.yml diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 2e4fb8de5..e29e5a48c 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1166,32 +1166,6 @@ gswo: version: v1_1_2019 path: hydrography/gswo/occur.vrt -gtsm_codec_reanalysis_{freq}_v1: - crs: 4326 - data_type: GeoDataset - driver: netcdf - driver_kwargs: - chunks: - stations: 10 - time: -1 - meta: - category: ocean - paper_doi: 10.3389/fmars.2020.00263 - paper_ref: Muis at al (2020) - source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf - source_url: https://doi.org/10.24381/cds.8c59054f - version: 1 - path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc - placeholders: - freq: - - 10min - - hourly - - dailymax - rename: - station_x_coordinate: lon - station_y_coordinate: lat - stations: index - guf_bld_2012: crs: 4326 data_type: RasterDataset diff --git a/data/catalogs/gtsm_codec_reanalysis.yml b/data/catalogs/gtsm_codec_reanalysis.yml new file mode 100644 index 000000000..88bc6efa4 --- /dev/null +++ b/data/catalogs/gtsm_codec_reanalysis.yml @@ -0,0 +1,30 @@ +--- +meta: + version: 2024.1 + + +gtsm_codec_reanalysis_{freq}_v1: + crs: 4326 + data_type: GeoDataset + driver: netcdf + driver_kwargs: + chunks: + stations: 10 + time: -1 + meta: + category: ocean + paper_doi: 10.3389/fmars.2020.00263 + paper_ref: Muis at al (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf + source_url: https://doi.org/10.24381/cds.8c59054f + version: 1 + path: p:/archivedprojects/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc + placeholders: + freq: + - 10min + - hourly + - dailymax + rename: + station_x_coordinate: lon + station_y_coordinate: lat + stations: index From cb16e3ce037feecfbe61a1da7a4475cccb8d0a6b Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Tue, 16 Jan 2024 15:03:21 +0100 Subject: [PATCH 025/110] updated data catalog change log --- data/catalogs/changelog.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 897b36ec9..0cea2be9a 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -15,6 +15,7 @@ changed - kwargs to driver_kwargs - updated source_url if url was not working anymore - sorted datasets by alphabetical order +- removed gtsm_codec_reanalysis dataset added ^^^^^ From 552c1428c0fcae45cda4cd9c7fb9dc0aad5a764a Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Tue, 23 Jan 2024 16:58:43 +0100 Subject: [PATCH 026/110] updated changelog --- docs/changelog.rst | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/changelog.rst b/docs/changelog.rst index d2ee12b1a..fe2e09a01 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -16,12 +16,15 @@ Added Changed ------- +- Datacatalog preserves variant specific meta data (#521) +- Updated DataCatalogValidator to deal with provider and driver_kwargs (#521) Fixed ----- - Reading Vector formats that consist of more than one file via geopandas. (#691) - Handle NoDataStrategy consistently when reading data in adapters (#738) + v0.9.2 (2024-01-09) =================== This release adds additional bug fixes for the meridian offset functinality, and improvements to the new CLI commands. From e4acd671f4715ac6550332051d238892502030c8 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Mon, 29 Jan 2024 14:03:04 +0100 Subject: [PATCH 027/110] update data catalog readme --- data/catalogs/README.rst | 25 +++++++++++++++---------- 1 file changed, 15 insertions(+), 10 deletions(-) diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 58007af48..af7677718 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -80,21 +80,26 @@ structure per data set: - order the components of each data set alphabetically - for adding meta data use the following optional keys: -category: -notes: -paper_doi: -paper_ref: -source_author: (if different from paper_ref) -source_license: -source_url: -source_version: -unit: +meta: + category: + notes: + paper_doi: + paper_ref: + source_author: (if different from paper_ref) + source_license: + source_url: + source_version: + source_spatial_extent: + source_temporal_extent: + unit: + processing_script: + processing_notes: updates ------- - create new branch on github - make changes and bump the version in the global meta section using `calendar versioning ` -- test your yml file (Can the added/changed data sources be read through HydroMT?) +- test your yml file (Can the added/changed data sources be read through HydroMT?), this can be done by running the test_data_catalog.py file located in this folder. Read the docstring for more information. - create pull request - add new version to hydromt\data\predefined_catalogs.yml From 7d468306c93727bf13afc1548a035999d0509630 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 14:04:53 +0100 Subject: [PATCH 028/110] removed merge conflict statements --- data/catalogs/changelog.rst | 19 +------------------ 1 file changed, 1 insertion(+), 18 deletions(-) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 0e8aa2f8b..996f030b2 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -97,21 +97,13 @@ fixed cmip6_data ========== -<<<<<<< HEAD -version: 2024.1 +version: 2024.1.30 ---------------- added ^^^^^ - hydromt_version to data catalog meta -======= -version: 2024.1.30 ---------------- -added -^^^^^ -- HydroMT version to catalog ->>>>>>> main version: 2023.2 --------------- @@ -123,21 +115,12 @@ added aws_data ======== -<<<<<<< HEAD -version: 2024.1 ----------------- - -added -^^^^^ -- hydromt_version to data catalog meta -======= version: 2024.1.30 --------------- added ^^^^^ - HydroMT version to catalog ->>>>>>> main version: 2023.2 --------------- From a3569744cdfd0f16e8721037fd6dedda80ece0c2 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 16:55:28 +0100 Subject: [PATCH 029/110] Added mapping table for old to new names of datasets in datacatalog --- data/catalogs/changelog.rst | 40 +++++++++++++++++++++++++++++++++++++ 1 file changed, 40 insertions(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 996f030b2..8b8d967e1 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -22,6 +22,46 @@ changed - kwargs to driver_kwargs - updated source_url if url was not working anymore - sorted datasets by alphabetical order +- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. + +.. list-table:: Dataset name changes: + :widths: 25 25 50 + :header-rows: 1 + * - Old name + - New name + * - basin_atlas_level12_v10 + - hydro_basin_atlas_level12 + * - eobs_v* + - eobs + * - eobs_orography_v* + - eobs_orography + * - lake_atlas_pol_v10 + - hydro_lake_atlas + * - river_atlas_v10 + - hydro_river_atlas + * - ghs_pop_2015_54009_v2019a + - ghs_pop_2015_54009 + * - glofas_era5_v31 + - glofas_era5 + * - guf_bld_2012 + - guf + * - rivers_lin2019_v1 + - hydro_rivers_lin2019 + * - SM2RAIN_ASCAT_monthly_025_v1.4 + - SM2RAIN_ASCAT_monthly_025 + * - SM2RAIN_ASCAT_monthly_05_v1.4 + - SM2RAIN_ASCAT_monthly_05 + * - soilgrids_2020 + - soilgrids + * - vito_2016_v3.0.1 + - vito_2016 + * - vito_2017_v3.0.1 + - vito_2017 + * - vito_2018_v3.0.1 + - vito_2018 + * - vito_2019_v3.0.1 + - vito_2019 + version: 2024.1.30 From b4ee49132b226f19fdfb899cc7fc9dad2bb99d90 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 16:56:14 +0100 Subject: [PATCH 030/110] removed versions from dataset names and added hydro prefix where necessary --- data/catalogs/deltares_data.yml | 35 +++++++++++++++++++-------------- 1 file changed, 20 insertions(+), 15 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index aafebd11f..b6ee6837c 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -5,7 +5,7 @@ meta: hydromt_version: '>=0.9, <1.0' -basin_atlas_level12_v10: +hydro_basin_atlas_level12: crs: 4326 data_type: GeoDataFrame driver: vector @@ -750,7 +750,7 @@ ghs_pop: version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif -ghs_pop_2015_54009_v2019a: +ghs_pop_2015_54009: crs: ESRI:54009 data_type: RasterDataset driver: raster @@ -769,7 +769,7 @@ ghs_pop_2015_54009_v2019a: South: -9000000.0 East: 18041000.0 North: 9000000.0 - version: R2019A_54009_250_v1.0 + version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif ghs_smod: @@ -824,7 +824,7 @@ globcover: version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif -glofas_era5_v31: +glofas_era5: crs: 4326 data_type: RasterDataset driver: netcdf @@ -1160,10 +1160,10 @@ gswo: East: 180.0 North: 80.0 nodata: 255 - version: v1_1_2019 + version: v1_1 path: hydrography/gswo/occur.vrt -guf_bld_2012: +guf: crs: 4326 data_type: RasterDataset driver: raster @@ -1182,6 +1182,7 @@ guf_bld_2012: South: -65.0 East: 180.0 North: 85.0 + version: 2 path: infrastructure/guf/GUF04_DLR_v02.vrt hydro_lakes: @@ -1268,7 +1269,7 @@ koppen_geiger: version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif -lake_atlas_pol_v10: +hydro_lake_atlas_pol: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1607,7 +1608,7 @@ rgi: ID: simple_id RGIID: RGI_id -river_atlas_v10: +hydro_river_atlas: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1628,7 +1629,7 @@ river_atlas_v10: rename: dis_m3_pyr: Dis_avg -rivers_lin2019_v1: +hydro_rivers_lin2019: data_type: GeoDataFrame driver: vector meta: @@ -1670,7 +1671,7 @@ simard: version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif -SM2RAIN_ASCAT_monthly_025_v1.4: +SM2RAIN_ASCAT_monthly_025: crs: 4326 data_type: RasterDataset driver: netcdf @@ -1700,7 +1701,7 @@ SM2RAIN_ASCAT_monthly_025_v1.4: rename: rainfall: precip -SM2RAIN_ASCAT_monthly_05_v1.4: +SM2RAIN_ASCAT_monthly_05: crs: 4326 data_type: RasterDataset driver: netcdf @@ -1937,9 +1938,10 @@ vito: South: -60.0 East: 180.0 North: 80.0 + version: 2.0.2 path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif -vito_2016_v3.0.1: +vito_2016: crs: 4326 data_type: RasterDataset driver: raster @@ -1957,9 +1959,10 @@ vito_2016_v3.0.1: South: -60.0 East: 180.0 North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2017_v3.0.1: +vito_2017: crs: 4326 data_type: RasterDataset driver: raster @@ -1977,9 +1980,10 @@ vito_2017_v3.0.1: South: -60.0 East: 180.0 North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2018_v3.0.1: +vito_2018: crs: 4326 data_type: RasterDataset driver: raster @@ -1999,7 +2003,7 @@ vito_2018_v3.0.1: North: 80.0 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2019_v3.0.1: +vito_2019: crs: 4326 data_type: RasterDataset driver: raster @@ -2017,6 +2021,7 @@ vito_2019_v3.0.1: South: -60.0 East: 180.0 North: 80.0 + version: 3.0.1 path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: From 5944ecf788bd800f8c73d9437cac363c91943e3f Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 16:57:19 +0100 Subject: [PATCH 031/110] removed source version and unit from meta --- data/catalogs/README.rst | 2 -- 1 file changed, 2 deletions(-) diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index af7677718..5b97a8b5f 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -88,10 +88,8 @@ meta: source_author: (if different from paper_ref) source_license: source_url: - source_version: source_spatial_extent: source_temporal_extent: - unit: processing_script: processing_notes: From 4397c358095ba5b9899c0e7ccd4a5480c20d13b8 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 16:57:43 +0100 Subject: [PATCH 032/110] removed archived gtsm dataset data catalog --- data/catalogs/gtsm_codec_reanalysis.yml | 30 ------------------------- 1 file changed, 30 deletions(-) delete mode 100644 data/catalogs/gtsm_codec_reanalysis.yml diff --git a/data/catalogs/gtsm_codec_reanalysis.yml b/data/catalogs/gtsm_codec_reanalysis.yml deleted file mode 100644 index 88bc6efa4..000000000 --- a/data/catalogs/gtsm_codec_reanalysis.yml +++ /dev/null @@ -1,30 +0,0 @@ ---- -meta: - version: 2024.1 - - -gtsm_codec_reanalysis_{freq}_v1: - crs: 4326 - data_type: GeoDataset - driver: netcdf - driver_kwargs: - chunks: - stations: 10 - time: -1 - meta: - category: ocean - paper_doi: 10.3389/fmars.2020.00263 - paper_ref: Muis at al (2020) - source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf - source_url: https://doi.org/10.24381/cds.8c59054f - version: 1 - path: p:/archivedprojects/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc - placeholders: - freq: - - 10min - - hourly - - dailymax - rename: - station_x_coordinate: lon - station_y_coordinate: lat - stations: index From 0174234001b2410e5e311c25ac1bedc9661b1c99 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 17:06:48 +0100 Subject: [PATCH 033/110] trying to add table to rst --- data/catalogs/changelog.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 8b8d967e1..e76c9df95 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -27,6 +27,7 @@ changed .. list-table:: Dataset name changes: :widths: 25 25 50 :header-rows: 1 + * - Old name - New name * - basin_atlas_level12_v10 From 86f1a254ea82ecbf102bf93b25c175662c05d0fd Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 17:11:20 +0100 Subject: [PATCH 034/110] trying to add table to rst --- data/catalogs/changelog.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index e76c9df95..881859015 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -25,7 +25,7 @@ changed - Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. .. list-table:: Dataset name changes: - :widths: 25 25 50 + :widths: 25 25 :header-rows: 1 * - Old name From 13d2f31d8336fb195ba22a78337c90dd0b39b76d Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 7 Feb 2024 17:12:33 +0100 Subject: [PATCH 035/110] trying to add table to rst --- data/catalogs/changelog.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 881859015..4843d3612 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -32,9 +32,9 @@ changed - New name * - basin_atlas_level12_v10 - hydro_basin_atlas_level12 - * - eobs_v* + * - eobs_v.. - eobs - * - eobs_orography_v* + * - eobs_orography_v.. - eobs_orography * - lake_atlas_pol_v10 - hydro_lake_atlas From 0c8e3061e80f73c66f6ed8691a203c134e99e6a6 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 09:33:57 +0100 Subject: [PATCH 036/110] test changelog in markdown --- data/catalogs/changelog.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) create mode 100644 data/catalogs/changelog.md diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md new file mode 100644 index 000000000..08bcab546 --- /dev/null +++ b/data/catalogs/changelog.md @@ -0,0 +1,12 @@ +# Change log predefined datasets + +## deltares_data + +### version 2024.2 + +#### added +- version argument to data source where applicable +- variants argument for data sources that are of the same dataset but different versions +- processing_script / processing_notes arguments to data sources that have been (pre-) processed +- temporal extent of datasets that have a temporal dimension. +- spatial extents to datasets From 8b2c0efff26eabbd13d0406b65d55c3ee06d585b Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 09:45:03 +0100 Subject: [PATCH 037/110] added table to changelog --- data/catalogs/changelog.md | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index 08bcab546..4ef8d4b00 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -10,3 +10,29 @@ - processing_script / processing_notes arguments to data sources that have been (pre-) processed - temporal extent of datasets that have a temporal dimension. - spatial extents to datasets + +#### changed +- removed source_version from data source meta +- kwargs to driver_kwargs +- updated source_url if url was not working anymore +- sorted datasets by alphabetical order +- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. + +| Old name | New name | +|--------------------------------|---------------------------| +| basin_atlas_level12_v10 | hydro_basin_atlas_level12 | +| eobs_v.. | eobs | +| eobs_orography_v.. | eobs_orography | +| lake_atlas_pol_v10 | hydro_lake_atlas | +| river_atlas_v10 | hydro_river_atlas | +| ghs_pop_2015_54009_v2019a | ghs_pop_2015_54009 | +| glofas_era5_v31 | glofas_era5 | +| guf_bld_2012 | guf | +| rivers_lin2019_v1 | hydro_rivers_lin2019 | +| SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | +| SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | +| soilgrids_2020 | soilgrids | +| vito_2016_v3.0.1 | vito_2016 | +| vito_2017_v3.0.1 | vito_2017 | +| vito_2018_v3.0.1 | vito_2018 | +| vito_2019_v3.0.1 | vito_2019 | From 5d928ebfd3e34c54b38cf37a0fa25d399fd91996 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 09:55:00 +0100 Subject: [PATCH 038/110] transefered rst changelog to md changelog --- data/catalogs/changelog.md | 87 +++++++++++++++++++++++++++++++++++++- 1 file changed, 86 insertions(+), 1 deletion(-) diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index 4ef8d4b00..fe7f1de22 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -23,7 +23,7 @@ | basin_atlas_level12_v10 | hydro_basin_atlas_level12 | | eobs_v.. | eobs | | eobs_orography_v.. | eobs_orography | -| lake_atlas_pol_v10 | hydro_lake_atlas | +| lake_atlas_pol_v10 | hydro_lake_atlas_pol | | river_atlas_v10 | hydro_river_atlas | | ghs_pop_2015_54009_v2019a | ghs_pop_2015_54009 | | glofas_era5_v31 | glofas_era5 | @@ -36,3 +36,88 @@ | vito_2017_v3.0.1 | vito_2017 | | vito_2018_v3.0.1 | vito_2018 | | vito_2019_v3.0.1 | vito_2019 | + + +### version 2024.1.30 + +#### added +- HydroMT version to catalog +- GRDC dataset + + +### version: 2023.12 + +#### changed +- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files +- removed gtsm_codec_reanalysis dataset + +#### added +- Added waterdemand pcr_globwb dataset +- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) + + +### version: 2023.2 + +#### changed +- convert GeoPackage files to FlatGeoBuf for cloud compatibility +- fix ERA5 nc files to read from archive of combined yearly and monthly files + +#### added +- Additional variables to era5 daily and hourly with name and unit conventions + - temp_dew: dewpoint temperature (degree C) + - wind10_u: 10m wind U-component (m s-1) + - wind10_v: 10m wind V-component (m s-1) + - ssr: surface net solar radiation (W m-2) + - tcc: total cloud cover (-) + + +### version: 2022.7 + +#### added + +- README with conventions regarding data (download, storage, .yml) +- change log file of deltares_data.yml +- new data sets + - basin_atlas_level12_v10 + - river_atlas_v10 + - lake_atlas_pol_v10 + - eobs_v24.0e + - eobs_v25.0e + - eobs_orography_v24.0e + - eobs_orography_v25.0e + - SM2RAIN_ASCAT_monthly_025_v1.4 + - SM2RAIN_ASCAT_monthly_05_v1.4 + +#### changed +- Apply convention specified in the README + - check reasonable alphabetical order in data sets and components + - implement right versioning convention _v where possible + - apply consistent meta information + +#### fixed +- enable versioning of yml.files + +## cmip6_data + +### version: 2024.1.30 + +#### added +- hydromt_version to data catalog meta + + +### version: 2023.2 + +#### added +- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed + +## aws_data + +### version: 2024.1.30 + +#### added +- HydroMT version to catalog + +### version: 2023.2 + +#### added +- ESA Worldcover v100 2020. From 93b360bf4a68555f604274e7f56aa26b7c039730 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 11:23:17 +0100 Subject: [PATCH 039/110] added versions to datasets where possible --- data/catalogs/deltares_data.yml | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index b6ee6837c..57b8a8d49 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -594,6 +594,7 @@ gadm_level0: South: -90.0 East: 180.0 North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level0.fgb gadm_level1: @@ -613,6 +614,7 @@ gadm_level1: South: -90.0 East: 180.0 North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level1.fgb gadm_level2: @@ -632,6 +634,7 @@ gadm_level2: South: -90.0 East: 180.0 North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level2.fgb gadm_level3: @@ -651,6 +654,7 @@ gadm_level3: South: -90.0 East: 180.0 North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level3.fgb gcn250: @@ -1419,6 +1423,7 @@ merit_hydro_ihu_index: South: -59.467 East: 190.35 North: 83.683 + version: 1.0 path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: @@ -1747,7 +1752,7 @@ soilgrids: East: 19861750.0 North: 8361000.0 variants: - - version: 2017 + - version: 1.0 path: soil/soilgrids_v1.0/*_250m_ll.tif meta: notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ @@ -1828,7 +1833,7 @@ soilgrids: ph_sl5: 0.1 ph_sl6: 0.1 ph_sl7: 0.1 - - version: 2020 + - version: 2.0 path: soil/soilgrids_v2.0/*/*_mean.vrt meta: paper_doi: https://doi.org/10.5194/soil-2020-65 @@ -2001,6 +2006,7 @@ vito_2018: South: -60.0 East: 180.0 North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif vito_2019: From b93ca087876b0d905b21adad91b66f124eef2416 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 11:41:39 +0100 Subject: [PATCH 040/110] removed source version --- data/catalogs/deltares_data.yml | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 57b8a8d49..ea8ff0182 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -346,7 +346,6 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels source_temporal_extent: start: '1950-01-02' end: '2023-11-30' @@ -422,7 +421,6 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 - source_version: ERA5 hourly data on single levels from 1940 to present source_temporal_extent: start: '1950-01-01' end: '2023-03-01' @@ -587,7 +585,6 @@ gadm_level0: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh source_spatial_extent: West: -180.0 @@ -607,7 +604,6 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh source_spatial_extent: West: -180.0 @@ -627,7 +623,6 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh source_spatial_extent: West: -180.0 @@ -647,7 +642,6 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh source_spatial_extent: West: -180.0 @@ -1164,7 +1158,7 @@ gswo: East: 180.0 North: 80.0 nodata: 255 - version: v1_1 + version: 1.1 path: hydrography/gswo/occur.vrt guf: @@ -1557,7 +1551,6 @@ pcr_globwb: paper_doi: 10.5281/zenodo.1045339 paper_ref: Sutanudjaja, E. H., et al (2017) source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR - source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py source_spatial_extent: West: -180.0 From 1c4c20488e814419cfa41b2ebeff9446d5a2bc4b Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 8 Feb 2024 11:42:25 +0100 Subject: [PATCH 041/110] added table with default versions for datasets with variants --- data/catalogs/changelog.md | 11 +++ data/catalogs/changelog.rst | 171 ------------------------------------ 2 files changed, 11 insertions(+), 171 deletions(-) delete mode 100644 data/catalogs/changelog.rst diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index fe7f1de22..88448cd2d 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -37,6 +37,17 @@ | vito_2018_v3.0.1 | vito_2018 | | vito_2019_v3.0.1 | vito_2019 | +- Some datasets have multiple versions, for these datasets the default can be changed if you do not supply a version in your config file. See the table below for which dataset the default version has changed. + +| Dataset name | Default version | +|----------------|-----------------| +| eobs | 25.0e | +| eobs_orography | 25.0e | +| ghs_mod | R2019A_v2.0 | +| pcr_globwb | 2005 | +| soilgrids | 2.0 | + + ### version 2024.1.30 diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst deleted file mode 100644 index 4843d3612..000000000 --- a/data/catalogs/changelog.rst +++ /dev/null @@ -1,171 +0,0 @@ -============================== -Change log predefined datasets -============================== - -deltares_data -============= - -version: 2024.2 ---------------- - -added -^^^^^ -- version argument to data source where applicable -- variants argument for data sources that are of the same dataset but different versions -- processing_script / processing_notes arguments to data sources that have been (pre-) processed -- temporal extent of datasets that have a temporal dimension. -- spatial extents to datasets - -changed -^^^^^^^ -- removed source_version from data source meta -- kwargs to driver_kwargs -- updated source_url if url was not working anymore -- sorted datasets by alphabetical order -- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. - -.. list-table:: Dataset name changes: - :widths: 25 25 - :header-rows: 1 - - * - Old name - - New name - * - basin_atlas_level12_v10 - - hydro_basin_atlas_level12 - * - eobs_v.. - - eobs - * - eobs_orography_v.. - - eobs_orography - * - lake_atlas_pol_v10 - - hydro_lake_atlas - * - river_atlas_v10 - - hydro_river_atlas - * - ghs_pop_2015_54009_v2019a - - ghs_pop_2015_54009 - * - glofas_era5_v31 - - glofas_era5 - * - guf_bld_2012 - - guf - * - rivers_lin2019_v1 - - hydro_rivers_lin2019 - * - SM2RAIN_ASCAT_monthly_025_v1.4 - - SM2RAIN_ASCAT_monthly_025 - * - SM2RAIN_ASCAT_monthly_05_v1.4 - - SM2RAIN_ASCAT_monthly_05 - * - soilgrids_2020 - - soilgrids - * - vito_2016_v3.0.1 - - vito_2016 - * - vito_2017_v3.0.1 - - vito_2017 - * - vito_2018_v3.0.1 - - vito_2018 - * - vito_2019_v3.0.1 - - vito_2019 - - - -version: 2024.1.30 ---------------- - -added -^^^^^ -- HydroMT version to catalog -- GRDC dataset - - -version: 2023.12 ------------------ - -changed -^^^^^^^ -- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files -- removed gtsm_codec_reanalysis dataset - -added -^^^^^ -- Added waterdemand pcr_globwb dataset -- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) - - -version: 2023.2 ----------------- - -changed -^^^^^^^ -- convert GeoPackage files to FlatGeoBuf for cloud compatibility -- fix ERA5 nc files to read from archive of combined yearly and monthly files - -added -^^^^^ -- Additional variables to era5 daily and hourly with name and unit conventions - - temp_dew: dewpoint temperature (degree C) - - wind10_u: 10m wind U-component (m s-1) - - wind10_v: 10m wind V-component (m s-1) - - ssr: surface net solar radiation (W m-2) - - tcc: total cloud cover (-) - - -version: 2022.7 ---------------- - -added -^^^^^ -- README with conventions regarding data (download, storage, .yml) -- change log file of deltares_data.yml -- new data sets - - basin_atlas_level12_v10 - - river_atlas_v10 - - lake_atlas_pol_v10 - - eobs_v24.0e - - eobs_v25.0e - - eobs_orography_v24.0e - - eobs_orography_v25.0e - - SM2RAIN_ASCAT_monthly_025_v1.4 - - SM2RAIN_ASCAT_monthly_05_v1.4 - -changed -^^^^^^^ -- Apply convention specified in the README - - check reasonable alphabetical order in data sets and components - - implement right versioning convention _v where possible - - apply consistent meta information - -fixed -^^^^^ -- enable versioning of yml.files - -cmip6_data -========== - -version: 2024.1.30 ----------------- - -added -^^^^^ -- hydromt_version to data catalog meta - - -version: 2023.2 ---------------- - -added -^^^^^ -- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed - -aws_data -======== - -version: 2024.1.30 ---------------- - -added -^^^^^ -- HydroMT version to catalog - -version: 2023.2 ---------------- - -added -^^^^^ -- ESA Worldcover v100 2020. From 710e37850cb994aa8eb593921562f71319b1e757 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 13:50:24 +0100 Subject: [PATCH 042/110] moved soilgrids_v2 from deltares_data catalog to its own data catalog --- data/catalogs/deltares_data.yml | 254 ++++++++++---------------------- data/catalogs/soilgrids_v2.yml | 111 ++++++++++++++ 2 files changed, 191 insertions(+), 174 deletions(-) create mode 100644 data/catalogs/soilgrids_v2.yml diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index ea8ff0182..9716987ba 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1065,12 +1065,11 @@ glw_sheeps: version: 3 path: socio_economic/glw/5_Sh_2010_Da.tif - grdc: crs: 4326 data_type: GeoDataFrame driver: csv - kwargs: + driver_kwargs: index_col: grdc_no meta: category: observed data @@ -1739,184 +1738,91 @@ soilgrids: y: 2400 meta: category: soil - source_spatial_extent: - West: -19949000.0 - South: -6147500.0 - East: 19861750.0 - North: 8361000.0 - variants: - - version: 1.0 - path: soil/soilgrids_v1.0/*_250m_ll.tif - meta: - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ \ distribution version 2.0, european commission and the European soil bureau\n\ \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ \ Response to european policy support and public data requirements. Land\ \ Use Policy 29 (2), 329\xC3\xA2\xE2\u201A\xAC\xE2\u20AC\u0153338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. (2017) - source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 - rename: - BLDFIE_M_sl1_250m_ll: bd_sl1 - BLDFIE_M_sl2_250m_ll: bd_sl2 - BLDFIE_M_sl3_250m_ll: bd_sl3 - BLDFIE_M_sl4_250m_ll: bd_sl4 - BLDFIE_M_sl5_250m_ll: bd_sl5 - BLDFIE_M_sl6_250m_ll: bd_sl6 - BLDFIE_M_sl7_250m_ll: bd_sl7 - CLYPPT_M_sl1_250m_ll: clyppt_sl1 - CLYPPT_M_sl2_250m_ll: clyppt_sl2 - CLYPPT_M_sl3_250m_ll: clyppt_sl3 - CLYPPT_M_sl4_250m_ll: clyppt_sl4 - CLYPPT_M_sl5_250m_ll: clyppt_sl5 - CLYPPT_M_sl6_250m_ll: clyppt_sl6 - CLYPPT_M_sl7_250m_ll: clyppt_sl7 - ORCDRC_M_sl1_250m_ll: oc_sl1 - ORCDRC_M_sl2_250m_ll: oc_sl2 - ORCDRC_M_sl3_250m_ll: oc_sl3 - ORCDRC_M_sl4_250m_ll: oc_sl4 - ORCDRC_M_sl5_250m_ll: oc_sl5 - ORCDRC_M_sl6_250m_ll: oc_sl6 - ORCDRC_M_sl7_250m_ll: oc_sl7 - PHIHOX_M_sl1_250m_ll: ph_sl1 - PHIHOX_M_sl2_250m_ll: ph_sl2 - PHIHOX_M_sl3_250m_ll: ph_sl3 - PHIHOX_M_sl4_250m_ll: ph_sl4 - PHIHOX_M_sl5_250m_ll: ph_sl5 - PHIHOX_M_sl6_250m_ll: ph_sl6 - PHIHOX_M_sl7_250m_ll: ph_sl7 - SLTPPT_M_sl1_250m_ll: sltppt_sl1 - SLTPPT_M_sl2_250m_ll: sltppt_sl2 - SLTPPT_M_sl3_250m_ll: sltppt_sl3 - SLTPPT_M_sl4_250m_ll: sltppt_sl4 - SLTPPT_M_sl5_250m_ll: sltppt_sl5 - SLTPPT_M_sl6_250m_ll: sltppt_sl6 - SLTPPT_M_sl7_250m_ll: sltppt_sl7 - SNDPPT_M_sl1_250m_ll: sndppt_sl1 - SNDPPT_M_sl2_250m_ll: sndppt_sl2 - SNDPPT_M_sl3_250m_ll: sndppt_sl3 - SNDPPT_M_sl4_250m_ll: sndppt_sl4 - SNDPPT_M_sl5_250m_ll: sndppt_sl5 - SNDPPT_M_sl6_250m_ll: sndppt_sl6 - SNDPPT_M_sl7_250m_ll: sndppt_sl7 - SoilThickness_250m_ll: soilthickness - TAXOUSDA_250m_ll: tax_usda - unit_mult: - bd_sl1: 0.001 - bd_sl2: 0.001 - bd_sl3: 0.001 - bd_sl4: 0.001 - bd_sl5: 0.001 - bd_sl6: 0.001 - bd_sl7: 0.001 - oc_sl1: 0.1 - oc_sl2: 0.1 - oc_sl3: 0.1 - oc_sl4: 0.1 - oc_sl5: 0.1 - oc_sl6: 0.1 - oc_sl7: 0.1 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - - version: 2.0 - path: soil/soilgrids_v2.0/*/*_mean.vrt - meta: - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb - processing_notes: soil/soilgrids_v2.0/src/readme.txt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 + source_spatial_extent: + West: -19949000.0 + South: -6147500.0 + East: 19861750.0 + North: 8361000.0 + version: 1.0 + path: soil/soilgrids_v1.0/*_250m_ll.tif + rename: + BLDFIE_M_sl1_250m_ll: bd_sl1 + BLDFIE_M_sl2_250m_ll: bd_sl2 + BLDFIE_M_sl3_250m_ll: bd_sl3 + BLDFIE_M_sl4_250m_ll: bd_sl4 + BLDFIE_M_sl5_250m_ll: bd_sl5 + BLDFIE_M_sl6_250m_ll: bd_sl6 + BLDFIE_M_sl7_250m_ll: bd_sl7 + CLYPPT_M_sl1_250m_ll: clyppt_sl1 + CLYPPT_M_sl2_250m_ll: clyppt_sl2 + CLYPPT_M_sl3_250m_ll: clyppt_sl3 + CLYPPT_M_sl4_250m_ll: clyppt_sl4 + CLYPPT_M_sl5_250m_ll: clyppt_sl5 + CLYPPT_M_sl6_250m_ll: clyppt_sl6 + CLYPPT_M_sl7_250m_ll: clyppt_sl7 + ORCDRC_M_sl1_250m_ll: oc_sl1 + ORCDRC_M_sl2_250m_ll: oc_sl2 + ORCDRC_M_sl3_250m_ll: oc_sl3 + ORCDRC_M_sl4_250m_ll: oc_sl4 + ORCDRC_M_sl5_250m_ll: oc_sl5 + ORCDRC_M_sl6_250m_ll: oc_sl6 + ORCDRC_M_sl7_250m_ll: oc_sl7 + PHIHOX_M_sl1_250m_ll: ph_sl1 + PHIHOX_M_sl2_250m_ll: ph_sl2 + PHIHOX_M_sl3_250m_ll: ph_sl3 + PHIHOX_M_sl4_250m_ll: ph_sl4 + PHIHOX_M_sl5_250m_ll: ph_sl5 + PHIHOX_M_sl6_250m_ll: ph_sl6 + PHIHOX_M_sl7_250m_ll: ph_sl7 + SLTPPT_M_sl1_250m_ll: sltppt_sl1 + SLTPPT_M_sl2_250m_ll: sltppt_sl2 + SLTPPT_M_sl3_250m_ll: sltppt_sl3 + SLTPPT_M_sl4_250m_ll: sltppt_sl4 + SLTPPT_M_sl5_250m_ll: sltppt_sl5 + SLTPPT_M_sl6_250m_ll: sltppt_sl6 + SLTPPT_M_sl7_250m_ll: sltppt_sl7 + SNDPPT_M_sl1_250m_ll: sndppt_sl1 + SNDPPT_M_sl2_250m_ll: sndppt_sl2 + SNDPPT_M_sl3_250m_ll: sndppt_sl3 + SNDPPT_M_sl4_250m_ll: sndppt_sl4 + SNDPPT_M_sl5_250m_ll: sndppt_sl5 + SNDPPT_M_sl6_250m_ll: sndppt_sl6 + SNDPPT_M_sl7_250m_ll: sndppt_sl7 + SoilThickness_250m_ll: soilthickness + TAXOUSDA_250m_ll: tax_usda + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 vito: crs: 4326 diff --git a/data/catalogs/soilgrids_v2.yml b/data/catalogs/soilgrids_v2.yml new file mode 100644 index 000000000..7079828a1 --- /dev/null +++ b/data/catalogs/soilgrids_v2.yml @@ -0,0 +1,111 @@ +--- +meta: + root: p:/wflow_global/hydromt + version: 2024.3 + hydromt_version: '>=0.9, <1.0' + +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + driver_kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb + processing_notes: soil/soilgrids_v2.0/src/readme.txt + source_spatial_extent: + West: -19949000.0 + South: -6147500.0 + East: 19861750.0 + North: 8361000.0 + version: 2.0 + path: soil/soilgrids_v2.0/*/*_mean.vrt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 From cef7a6916eff316c5490e3bb370212163eb9b288 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 13:58:58 +0100 Subject: [PATCH 043/110] updated artifact_data catalog --- data/catalogs/artifact_data.yml | 189 ++++++++++++++++++++------------ 1 file changed, 119 insertions(+), 70 deletions(-) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index c83438f6c..36c8ee67a 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,5 +1,5 @@ meta: - version: v0.0.8 + version: v0.0.9 hydromt_version: '>=0.9, <1.0' root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/0.0.8/data.tar.gz @@ -13,8 +13,9 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 + version: 1.2 path: chelsa.tif + chirps_global: crs: 4326 data_type: RasterDataset @@ -25,10 +26,11 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 + version: 2.0 path: chirps_global.nc unit_add: time: 86400 + corine: data_type: RasterDataset driver: raster @@ -37,8 +39,9 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 + version: 2020_20u1 path: corine.tif + dtu10mdt: crs: 4326 data_type: RasterDataset @@ -48,9 +51,10 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM2008 + version: 2010 path: dtu10mdt.tif + dtu10mdt_egm96: crs: 4326 data_type: RasterDataset @@ -60,9 +64,10 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM96 + version: 2010 path: dtu10mdt_egm96.tif + eobs: crs: 4326 data_type: RasterDataset @@ -73,10 +78,11 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs.nc unit_add: time: 86400 + eobs_orography: crs: 4326 data_type: RasterDataset @@ -87,8 +93,9 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs_orography.nc + era5: crs: 4326 data_type: RasterDataset @@ -101,7 +108,6 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels path: era5.nc unit_add: temp: -273.15 @@ -113,6 +119,7 @@ era5: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_hourly: crs: 4326 data_type: RasterDataset @@ -124,7 +131,6 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly.nc unit_add: temp: -273.15 @@ -133,6 +139,7 @@ era5_hourly: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_daily_zarr: crs: 4326 data_type: RasterDataset @@ -145,7 +152,6 @@ era5_daily_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels path: era5_daily_zarr.zarr rename: d2m: temp_dew @@ -155,6 +161,7 @@ era5_daily_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 + era5_hourly_zarr: crs: 4326 data_type: RasterDataset @@ -166,7 +173,6 @@ era5_hourly_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly_zarr.zarr rename: d2m: temp_dew @@ -176,6 +182,7 @@ era5_hourly_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 + era5_orography: crs: 4326 data_type: RasterDataset @@ -187,10 +194,10 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_orography.nc unit_mult: elevtn: 0.10197162129779283 + gadm_level1: crs: 4326 data_type: GeoDataFrame @@ -201,8 +208,9 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level1.gpkg + gadm_level2: crs: 4326 data_type: GeoDataFrame @@ -213,8 +221,9 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level2.gpkg + gadm_level3: crs: 4326 data_type: GeoDataFrame @@ -225,8 +234,9 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level3.gpkg + gcn250: data_type: RasterDataset driver: raster @@ -236,9 +246,10 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 + version: 1 nodata: 255 path: gcn250/{variable}.tif + gdp_world: crs: 4326 data_type: GeoDataFrame @@ -249,8 +260,9 @@ gdp_world: source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 - source_version: 1.0 + version: 1.0 path: gdp_world.gpkg + gebco: crs: 4326 data_type: RasterDataset @@ -261,22 +273,31 @@ gebco: paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ - source_version: 2020 unit: m+MSL + version: 2020 path: gebco.tif -ghs-smod_2015_v2: - crs: 54009 + +ghs_smod_2015: + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: category: socio economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 - path: ghs-smod_2015_v2.tif + variants: + - version: R2016A_v1.0 + path: ghs_smod_2015.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + ghs_pop_2015: crs: 4326 data_type: RasterDataset @@ -288,10 +309,11 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 + version: R2019A_v1.0 path: ghs_pop_2015.tif + ghs_pop_2015_54009: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: @@ -300,19 +322,9 @@ ghs_pop_2015_54009: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + version: R2019A_v1.0 path: ghs_pop_2015_54009.tif -ghs_smod_2015: - crs: 54009 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_ref: Pesaresi and Freire (2016) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - path: ghs_smod_2015.tif + globcover: crs: 4326 data_type: RasterDataset @@ -323,7 +335,9 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php + version: 2.3 path: globcover.tif + glw_buffaloes: crs: 4326 data_type: RasterDataset @@ -335,8 +349,9 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_buffaloes.tif + glw_cattle: crs: 4326 data_type: RasterDataset @@ -348,8 +363,9 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_cattle.tif + glw_chicken: crs: 4326 data_type: RasterDataset @@ -361,8 +377,9 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_chicken.tif + glw_ducks: crs: 4326 data_type: RasterDataset @@ -374,8 +391,9 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_ducks.tif + glw_goats: crs: 4326 data_type: RasterDataset @@ -387,8 +405,9 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_goats.tif + glw_horses: crs: 4326 data_type: RasterDataset @@ -400,8 +419,9 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_horses.tif + glw_pigs: crs: 4326 data_type: RasterDataset @@ -413,8 +433,9 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_pigs.tif + glw_sheep: crs: 4326 data_type: RasterDataset @@ -426,8 +447,9 @@ glw_sheep: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_sheep.tif + grdc: crs: 4326 data_type: GeoDataFrame @@ -438,6 +460,7 @@ grdc: source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue path: grdc.csv + grip_roads: crs: 4326 data_type: GeoDataFrame @@ -448,8 +471,9 @@ grip_roads: paper_ref: Meijer et al, 2018 source_license: CC0-1.0 source_url: https://www.globio.info/download-grip-dataset - source_version: v4 + version: 4 path: grip_roads.gpkg + grwl: data_type: GeoDataFrame driver: vector @@ -459,12 +483,13 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 path: grwl.gpkg + grwl_mask: data_type: RasterDataset driver: raster_tindex - kwargs: + driver_kwargs: chunks: x: 3000 y: 3000 @@ -476,9 +501,10 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 nodata: 0 path: grwl_tindex.gpkg + gswo: data_type: RasterDataset driver: raster @@ -487,9 +513,10 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 + version: 1.1 nodata: 255 path: gswo.tif + gtsmv3_eu_era5: crs: 4326 data_type: GeoDataset @@ -500,9 +527,10 @@ gtsmv3_eu_era5: paper_ref: Copernicus Climate Change Service 2019 source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 + version: 3.0 path: gtsmv3_eu_era5.nc -guf_bld_2012: + +guf: crs: 4326 data_type: RasterDataset driver: raster @@ -512,7 +540,9 @@ guf_bld_2012: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf + version: 2 path: guf_bld_2012.tif + hydro_lakes: crs: 4326 data_type: GeoDataFrame @@ -521,10 +551,11 @@ hydro_lakes: category: surface water source_author: Arjen Haag source_info: HydroLAKES.v10_extract - source_version: 1.0 + version: 1.0 path: hydro_lakes.gpkg unit_mult: Area_avg: 1000000.0 + hydro_reservoirs: crs: 4326 data_type: GeoDataFrame @@ -533,7 +564,7 @@ hydro_reservoirs: category: surface water source_author: Alessia Matano source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 + version: 1.0 nodata: -99 path: hydro_reservoirs.gpkg unit_mult: @@ -542,6 +573,7 @@ hydro_reservoirs: Capacity_min: 1000000.0 Capacity_norm: 1000000.0 Vol_avg: 1000000.0 + koppen_geiger: crs: 4326 data_type: RasterDataset @@ -551,9 +583,10 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 + version: 2017 nodata: 0 path: koppen_geiger.tif + mdt_cnes_cls18: crs: 4326 data_type: RasterDataset @@ -563,9 +596,10 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 unit: m+GOCO05S + version: 18 path: mdt_cnes_cls18.tif + merit_hydro: crs: 4326 data_type: RasterDataset @@ -576,8 +610,9 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 + version: 1.0 path: merit_hydro/{variable}.tif + merit_hydro_1k: crs: 4326 data_type: RasterDataset @@ -588,8 +623,9 @@ merit_hydro_1k: paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 source_url: https://doi.org/10.5281/zenodo.4138776 - source_version: 0.1 + version: 0.1 path: merit_hydro_1k/{variable}.tif + merit_hydro_index: crs: 4326 data_type: GeoDataFrame @@ -599,7 +635,9 @@ merit_hydro_index: paper_doi: 10.5194/hess-2020-582 paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 + version: 1.0 path: merit_hydro_index.gpkg + modis_lai: crs: 4326 data_type: RasterDataset @@ -612,10 +650,11 @@ modis_lai: paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 + version: MCD15A3H V006 path: modis_lai.nc unit_mult: LAI: 0.1 + osm_coastlines: crs: 4326 data_type: GeoDataFrame @@ -626,8 +665,9 @@ osm_coastlines: source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_coastlines.gpkg + osm_landareas: crs: 4326 data_type: GeoDataFrame @@ -638,8 +678,9 @@ osm_landareas: source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_landareas.gpkg + rgi: crs: 4326 data_type: GeoDataFrame @@ -651,9 +692,10 @@ rgi: source_info: Randolph Glacier Inventory source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 + version: 6.0 path: rgi.gpkg -rivers_lin2019_v1: + +hydro_rivers_lin2019: data_type: GeoDataFrame driver: vector meta: @@ -662,8 +704,9 @@ rivers_lin2019_v1: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 + version: 1 path: rivers_lin2019_v1.gpkg + simard: crs: 4326 data_type: RasterDataset @@ -673,7 +716,9 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + version: 2011 path: simard.tif + soilgrids: crs: 4326 data_type: RasterDataset @@ -691,7 +736,7 @@ soilgrids: paper_ref: Hengl et al. (2017) source_license: ODbL source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 + version: 2017 path: soilgrids/{variable}.tif unit_mult: bd_sl1: 0.001 @@ -715,6 +760,7 @@ soilgrids: ph_sl5: 0.1 ph_sl6: 0.1 ph_sl7: 0.1 + vito: crs: 4326 data_type: RasterDataset @@ -724,8 +770,9 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 + version: 2.0.2 path: vito.tif + wb_countries: crs: 4326 data_type: GeoDataFrame @@ -736,7 +783,9 @@ wb_countries: source_license: CC-BY 4.0 source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries timestamp: February 2020 + version: 2020319 path: wb_countries.gpkg + worldclim: crs: 4326 data_type: RasterDataset @@ -746,5 +795,5 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 + version: 2 path: worldclim.nc From f3849556cd163f38b1682cab2a9fdec62f98af79 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 14:01:08 +0100 Subject: [PATCH 044/110] updated artifact_data in predefined_data_catalog.yml --- data/predefined_catalogs.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index 1a31bde93..e3a9decda 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -37,8 +37,9 @@ aws_data: v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: - urlpath: https://github.com/DirkEilander/hydromt-artifacts/releases/download/{version}/data.tar.gz + urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml versions: + v0.0.9: v0.0.9 v0.0.8: v0.0.8 v0.0.7: v0.0.7 v0.0.6: v0.0.6 From 166af6ec88ec1172f132c587f93e444d334f82b5 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Fri, 1 Mar 2024 14:03:17 +0100 Subject: [PATCH 045/110] Update data/catalogs/deltares_data.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 9716987ba..f8d85ac70 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -281,6 +281,7 @@ eobs: path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc meta: processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables - version: 25.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc meta: From 8622059c03b90df404f826b0b9a5dac6d3e70794 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Fri, 1 Mar 2024 14:47:38 +0100 Subject: [PATCH 046/110] Update data/catalogs/deltares_data.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index f8d85ac70..23c46e141 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -342,7 +342,7 @@ era5: meta: category: meteo notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to - daily frequency + daily frequency using right label for time. paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products From 58d0c41b1519a433fa1b452c1b6290dd72160440 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 14:48:27 +0100 Subject: [PATCH 047/110] renamed vito --- data/catalogs/deltares_data.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 9716987ba..6f4d14258 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1749,6 +1749,8 @@ soilgrids: paper_ref: Hengl et al. (2017) source_license: ODbL source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 + processing_notes: "soilthickness is based on 1) soilgrids (global, depth to bedrock - BDRICM variable) and 2) dataset for Eurasia" + processing_script: p:/wflow_global/static_data/wflow_sbm_parameters/ source_spatial_extent: West: -19949000.0 South: -6147500.0 @@ -1824,7 +1826,7 @@ soilgrids: ph_sl6: 0.1 ph_sl7: 0.1 -vito: +vito_2015: crs: 4326 data_type: RasterDataset driver: raster From 67c0a448e5d5a671eb30eadcf3c4895e97ab1935 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Fri, 1 Mar 2024 14:53:06 +0100 Subject: [PATCH 048/110] Update data/catalogs/deltares_data.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 23c46e141..cbe8cea1a 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -286,6 +286,7 @@ eobs: path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc meta: processing_script: v25.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables rename: pp: press_msl qq: kin From fe6a942dcb84a329b63035a0650e597df23e443a Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 15:23:56 +0100 Subject: [PATCH 049/110] added temporal extents for each eobs version --- data/catalogs/deltares_data.yml | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 9994a87d2..d2e61ea10 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -275,18 +275,32 @@ eobs: variants: - version: 22.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + meta: + source_temporal_extent: + start: '1950-01-02' + end: '2020-07-01' - version: 23.1e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + meta: + source_temporal_extent: + start: '1950-01-02' + end: '2021-01-01' - version: 24.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc meta: processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + source_temporal_extent: + start: '1950-01-02' + end: '2021-07-01' - version: 25.0e path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc meta: processing_script: v25.0e_fix_qq_dims_and_match_extent.py processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + source_temporal_extent: + start: '1950-01-02' + end: '2022-01-01' rename: pp: press_msl qq: kin From e630cb9a3d4bda4c434d7808764700501df47a59 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 15:51:09 +0100 Subject: [PATCH 050/110] added nodata to worldclim --- data/catalogs/artifact_data.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index 36c8ee67a..f174b41ec 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -796,4 +796,5 @@ worldclim: paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html version: 2 + nodata: -999.0 path: worldclim.nc From 94632b3652fe0c9a46cd1d933ed1a763db1a15b4 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 1 Mar 2024 15:54:54 +0100 Subject: [PATCH 051/110] updated artifact versions --- data/catalogs/artifact_data.yml | 2 +- data/predefined_catalogs.yml | 6 ++---- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index f174b41ec..d95868480 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: version: v0.0.9 hydromt_version: '>=0.9, <1.0' - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/0.0.8/data.tar.gz + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/0.0.9/data.tar.gz chelsa: crs: 4326 diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index e3a9decda..a6fb1ceef 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -39,8 +39,6 @@ aws_data: artifact_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml versions: - v0.0.9: v0.0.9 - v0.0.8: v0.0.8 - v0.0.7: v0.0.7 - v0.0.6: v0.0.6 + v0.0.9: main + v0.0.8: 0ec2411c2548785d6ee4c8925b75287ca8fad0b0 notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. From b4914e80e6fb1c2518c4950e94d218d339e4dedc Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Fri, 1 Mar 2024 17:23:12 +0100 Subject: [PATCH 052/110] review changes and add consistency with epoch in naming --- data/catalogs/aws_data.yml | 2 +- data/catalogs/changelog.md | 20 +++--- data/catalogs/deltares_data.yml | 22 ++++--- data/catalogs/soilgrids_v2.yml | 111 -------------------------------- 4 files changed, 24 insertions(+), 131 deletions(-) delete mode 100644 data/catalogs/soilgrids_v2.yml diff --git a/data/catalogs/aws_data.yml b/data/catalogs/aws_data.yml index 9dfb98997..0e2378c2c 100644 --- a/data/catalogs/aws_data.yml +++ b/data/catalogs/aws_data.yml @@ -1,6 +1,6 @@ --- meta: - version: 2024.2 + version: 2024.1.30 hydromt_version: '>=0.9, <1.0' diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index 88448cd2d..69255acef 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -25,13 +25,15 @@ | eobs_orography_v.. | eobs_orography | | lake_atlas_pol_v10 | hydro_lake_atlas_pol | | river_atlas_v10 | hydro_river_atlas | -| ghs_pop_2015_54009_v2019a | ghs_pop_2015_54009 | +| ghs_pop_2015_54009_v2019a | ghs_pop_2015 | +| ghs_smod_2015_54009_v2019a | ghs_smod_2015 | | glofas_era5_v31 | glofas_era5 | -| guf_bld_2012 | guf | +| guf_bld_2012 | guf_bld_2012 | | rivers_lin2019_v1 | hydro_rivers_lin2019 | | SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | | SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | -| soilgrids_2020 | soilgrids | +| vito | vito_2015 | +| vito_2015_v2.0.2 | vito_2015 | | vito_2016_v3.0.1 | vito_2016 | | vito_2017_v3.0.1 | vito_2017 | | vito_2018_v3.0.1 | vito_2018 | @@ -39,14 +41,10 @@ - Some datasets have multiple versions, for these datasets the default can be changed if you do not supply a version in your config file. See the table below for which dataset the default version has changed. -| Dataset name | Default version | -|----------------|-----------------| -| eobs | 25.0e | -| eobs_orography | 25.0e | -| ghs_mod | R2019A_v2.0 | -| pcr_globwb | 2005 | -| soilgrids | 2.0 | - +| Dataset name | Default version | Previous default version | +|----------------|-----------------|--------------------------| +| eobs | 25.0e | 22.0e | +| eobs_orography | 25.0e | 22.0e | ### version 2024.1.30 diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index d2e61ea10..a2d7826ff 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -360,6 +360,7 @@ era5: daily frequency using right label for time. paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) + processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 source_temporal_extent: @@ -405,9 +406,9 @@ era5_daily_zarr: daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) + processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - processing_script: meteo/era5_zarr/scripts/ source_temporal_extent: start: '1950-01-02' end: '2023-02-01' @@ -557,6 +558,7 @@ esa_worldcover: y: 36000 meta: category: landuse + processing_notes: prepare vrt file with gdalbuildvrt source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 source_spatial_extent: @@ -741,7 +743,7 @@ gebco: rename: gebco: elevtn -ghs_pop: +ghs_pop_2015: crs: 4326 data_type: RasterDataset driver: raster @@ -786,7 +788,7 @@ ghs_pop_2015_54009: version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif -ghs_smod: +ghs_smod_2015: crs: ESRI:54009 data_type: RasterDataset driver: raster @@ -907,6 +909,7 @@ glw_buffaloes: y: 3600 meta: category: socio-economic + notes: last downloaded 2020-06-11 paper_doi: 10.7910/DVN/5U8MWI paper_ref: Gilbert at al (2018) source_author: glw (Gridded Livestock of World 3 Dataverse) @@ -1176,7 +1179,7 @@ gswo: version: 1.1 path: hydrography/gswo/occur.vrt -guf: +guf_bld_2012: crs: 4326 data_type: RasterDataset driver: raster @@ -1204,8 +1207,8 @@ hydro_lakes: driver: vector meta: category: surface water - notes: HydroLAKES.v10_extract - source_author: Arjen Haag + processing_notes: extract of hydrolakes to only include natural lakes and exclude reservoirs and control lakes (ie filter on Lake_type = 1) + source_author: HydroSHEDS source_spatial_extent: West: -180.0 South: -55.865 @@ -1365,6 +1368,8 @@ merit_hydro: category: topography paper_doi: 10.1029/2019WR024873 paper_ref: Yamazaki et al. (2019) + processing_notes: create vrt file with gdalbuildvrt; + additional variables for stream-order, basin index (basins), and slope (lndslp) derived with pyflwdir source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro source_spatial_extent: @@ -1467,6 +1472,7 @@ merit_hydro_patch: source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro processing_script: topography/merit_hydro/patches/scripts + processing_notes: local corrections of flow direction raster and re-derive the related maps (basins, uparea, strord) source_spatial_extent: West: -180.0 South: -60.0 @@ -1495,12 +1501,12 @@ modis_lai: concat: true meta: category: landuse - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the - period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + processing_notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') + for the period '2003-01-01', '2017-12-31' processing_script: GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py diff --git a/data/catalogs/soilgrids_v2.yml b/data/catalogs/soilgrids_v2.yml deleted file mode 100644 index 7079828a1..000000000 --- a/data/catalogs/soilgrids_v2.yml +++ /dev/null @@ -1,111 +0,0 @@ ---- -meta: - root: p:/wflow_global/hydromt - version: 2024.3 - hydromt_version: '>=0.9, <1.0' - -soilgrids: - crs: 4326 - data_type: RasterDataset - driver: raster - driver_kwargs: - chunks: - x: 2400 - y: 2400 - meta: - category: soil - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - processing_script: soil/soilgrids_v2.0/src/preprocess_soilgrids_v2020.ipynb - processing_notes: soil/soilgrids_v2.0/src/readme.txt - source_spatial_extent: - West: -19949000.0 - South: -6147500.0 - East: 19861750.0 - North: 8361000.0 - version: 2.0 - path: soil/soilgrids_v2.0/*/*_mean.vrt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 From d138d4cd44e78298ab3684d3a8afffd86f3da344 Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Fri, 1 Mar 2024 17:37:25 +0100 Subject: [PATCH 053/110] revert move artifact_data catalog to core --- data/predefined_catalogs.yml | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index a6fb1ceef..828a99bef 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -37,8 +37,10 @@ aws_data: v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: - urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml + urlpath: https://github.com/DirkEilander/hydromt-artifacts/releases/download/{version}/data.tar.gz versions: - v0.0.9: main - v0.0.8: 0ec2411c2548785d6ee4c8925b75287ca8fad0b0 + v0.0.9: v0.0.9 + v0.0.8: v0.0.8 + v0.0.7: v0.0.7 + v0.0.6: v0.0.6 notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. From 76ea69659b4084f08680fc1f77658e0582a96962 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Mon, 4 Mar 2024 11:03:06 +0100 Subject: [PATCH 054/110] Update data/catalogs/deltares_data.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index a2d7826ff..f017217dd 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -701,7 +701,7 @@ gdp_world: driver: vector meta: category: socio-economic - notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + processing_notes: data combined by Deltares (Wilfred Altena) from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 From 6a582a753dc7726863e94ce4acff906419f818b3 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Mon, 4 Mar 2024 11:55:13 +0100 Subject: [PATCH 055/110] fixed typo --- data/catalogs/artifact_data.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index d95868480..3628c828a 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: version: v0.0.9 hydromt_version: '>=0.9, <1.0' - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/0.0.9/data.tar.gz + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.9/data.tar.gz chelsa: crs: 4326 From 9fa671350dc62cfdc7d041d83cd462bbe8c022ee Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Mon, 4 Mar 2024 19:01:47 +0100 Subject: [PATCH 056/110] re-revert move artifact data cataloc to core --- data/predefined_catalogs.yml | 8 +++----- examples/prep_data_catalog.ipynb | 2 +- tests/test_data_catalog.py | 4 ++-- 3 files changed, 6 insertions(+), 8 deletions(-) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index 828a99bef..a6fb1ceef 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -37,10 +37,8 @@ aws_data: v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: - urlpath: https://github.com/DirkEilander/hydromt-artifacts/releases/download/{version}/data.tar.gz + urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml versions: - v0.0.9: v0.0.9 - v0.0.8: v0.0.8 - v0.0.7: v0.0.7 - v0.0.6: v0.0.6 + v0.0.9: main + v0.0.8: 0ec2411c2548785d6ee4c8925b75287ca8fad0b0 notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. diff --git a/examples/prep_data_catalog.ipynb b/examples/prep_data_catalog.ipynb index c74066a24..26e3952e8 100644 --- a/examples/prep_data_catalog.ipynb +++ b/examples/prep_data_catalog.ipynb @@ -64,7 +64,7 @@ "outputs": [], "source": [ "# this download the artifact_data archive v0.0.6\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.6\"])\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.9\"])\n", "pprint(data_catalog.predefined_catalogs)" ] }, diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index fa358b58e..0a7564975 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -594,8 +594,8 @@ def test_get_dataframe(df, tmpdir): def test_deprecation_warnings(artifact_data): with pytest.deprecated_call(): - # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) - DataCatalog(artifact_data="v0.0.6") + # should be DataCatalog(data_libs=['v0.0.6']) + DataCatalog(artifact_data="v0.0.9") with pytest.deprecated_call(): cat = DataCatalog() # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') From 555ccb886baa7c5d986fe39168c401c1b9562d69 Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Mon, 4 Mar 2024 19:07:45 +0100 Subject: [PATCH 057/110] fix artifact version in example and test; add artifact data changelog --- data/catalogs/changelog.md | 7 +++++++ examples/prep_data_catalog.ipynb | 4 ++-- tests/test_data_catalog.py | 8 ++++---- 3 files changed, 13 insertions(+), 6 deletions(-) diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index 69255acef..c294edcd6 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -106,6 +106,13 @@ #### fixed - enable versioning of yml.files +## aws_data + +### version 0.0.9 + +#### changed +- updated source naming to match deltares_data version 2024.2 + ## cmip6_data ### version: 2024.1.30 diff --git a/examples/prep_data_catalog.ipynb b/examples/prep_data_catalog.ipynb index 26e3952e8..9f1d16fdd 100644 --- a/examples/prep_data_catalog.ipynb +++ b/examples/prep_data_catalog.ipynb @@ -64,7 +64,7 @@ "outputs": [], "source": [ "# this download the artifact_data archive v0.0.6\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.9\"])\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"])\n", "pprint(data_catalog.predefined_catalogs)" ] }, @@ -85,7 +85,7 @@ "outputs": [], "source": [ "# the artifact data is stored in the following location\n", - "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.6\")\n", + "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.8\")\n", "# let's print some of the file that are there\n", "for item in os.listdir(root)[-10:]:\n", " print(item)" diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 0a7564975..8682982ae 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -594,12 +594,12 @@ def test_get_dataframe(df, tmpdir): def test_deprecation_warnings(artifact_data): with pytest.deprecated_call(): - # should be DataCatalog(data_libs=['v0.0.6']) - DataCatalog(artifact_data="v0.0.9") + # should be DataCatalog(data_libs=['v0.0.8']) + DataCatalog(artifact_data="v0.0.8") with pytest.deprecated_call(): cat = DataCatalog() - # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') - cat.from_artifacts("artifact_data", version="v0.0.6") + # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.8') + cat.from_artifacts("artifact_data", version="v0.0.8") with pytest.deprecated_call(): fn = artifact_data["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) From 202874eb4fe3415d0608ea81cd61620af6f5816a Mon Sep 17 00:00:00 2001 From: DirkEilander <15379728+DirkEilander@users.noreply.github.com> Date: Wed, 6 Mar 2024 10:55:06 +0100 Subject: [PATCH 058/110] fix typo in artifacts root (#828) --- data/catalogs/artifact_data.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index c83438f6c..e09b16148 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: version: v0.0.8 hydromt_version: '>=0.9, <1.0' - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/0.0.8/data.tar.gz + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz chelsa: crs: 4326 From 64c1c16a295309cc9cb9fb7b470e3ede1c0d8000 Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Wed, 6 Mar 2024 10:59:14 +0100 Subject: [PATCH 059/110] update artifact data v0.0.8 git hash --- data/predefined_catalogs.yml | 2 +- examples/delineate_basin.ipynb | 5 ++--- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index a6fb1ceef..c96d9eadd 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -40,5 +40,5 @@ artifact_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml versions: v0.0.9: main - v0.0.8: 0ec2411c2548785d6ee4c8925b75287ca8fad0b0 + v0.0.8: 202874eb4fe3415d0608ea81cd61620af6f5816a notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index e674c76dc..17b245fdc 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -33,8 +33,7 @@ "source": [ "import numpy as np\n", "import geopandas as gpd\n", - "from shapely.geometry import box\n", - "from pprint import pprint" + "from shapely.geometry import box" ] }, { @@ -378,7 +377,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.8" + "version": "3.11.7" }, "vscode": { "interpreter": { From 9f4d3f2a8762fbc1b71a85ad734910b170884e20 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 6 Mar 2024 16:07:15 +0100 Subject: [PATCH 060/110] Update data catalog (#718) Co-authored-by: Sam Vente Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> Co-authored-by: Dirk Eilander Co-authored-by: DirkEilander <15379728+DirkEilander@users.noreply.github.com> --- data/catalogs/README.rst | 23 +- data/catalogs/artifact_data.yml | 192 ++-- data/catalogs/changelog.md | 139 +++ data/catalogs/changelog.rst | 109 --- data/catalogs/deltares_data.yml | 1329 ++++++++++++++------------ data/predefined_catalogs.yml | 10 +- docs/changelog.rst | 8 + examples/delineate_basin.ipynb | 5 +- examples/prep_data_catalog.ipynb | 4 +- hydromt/data_adapter/data_adapter.py | 8 +- hydromt/data_catalog.py | 3 + hydromt/validators/data_catalog.py | 4 +- tests/data/merged_esa_worldcover.yml | 2 + tests/test_data_catalog.py | 14 +- 14 files changed, 1044 insertions(+), 806 deletions(-) create mode 100644 data/catalogs/changelog.md delete mode 100644 data/catalogs/changelog.rst diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 58007af48..5b97a8b5f 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -80,21 +80,24 @@ structure per data set: - order the components of each data set alphabetically - for adding meta data use the following optional keys: -category: -notes: -paper_doi: -paper_ref: -source_author: (if different from paper_ref) -source_license: -source_url: -source_version: -unit: +meta: + category: + notes: + paper_doi: + paper_ref: + source_author: (if different from paper_ref) + source_license: + source_url: + source_spatial_extent: + source_temporal_extent: + processing_script: + processing_notes: updates ------- - create new branch on github - make changes and bump the version in the global meta section using `calendar versioning ` -- test your yml file (Can the added/changed data sources be read through HydroMT?) +- test your yml file (Can the added/changed data sources be read through HydroMT?), this can be done by running the test_data_catalog.py file located in this folder. Read the docstring for more information. - create pull request - add new version to hydromt\data\predefined_catalogs.yml diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index e09b16148..3628c828a 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: - version: v0.0.8 + version: v0.0.9 hydromt_version: '>=0.9, <1.0' - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.9/data.tar.gz chelsa: crs: 4326 @@ -13,8 +13,9 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 + version: 1.2 path: chelsa.tif + chirps_global: crs: 4326 data_type: RasterDataset @@ -25,10 +26,11 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 + version: 2.0 path: chirps_global.nc unit_add: time: 86400 + corine: data_type: RasterDataset driver: raster @@ -37,8 +39,9 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 + version: 2020_20u1 path: corine.tif + dtu10mdt: crs: 4326 data_type: RasterDataset @@ -48,9 +51,10 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM2008 + version: 2010 path: dtu10mdt.tif + dtu10mdt_egm96: crs: 4326 data_type: RasterDataset @@ -60,9 +64,10 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM96 + version: 2010 path: dtu10mdt_egm96.tif + eobs: crs: 4326 data_type: RasterDataset @@ -73,10 +78,11 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs.nc unit_add: time: 86400 + eobs_orography: crs: 4326 data_type: RasterDataset @@ -87,8 +93,9 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs_orography.nc + era5: crs: 4326 data_type: RasterDataset @@ -101,7 +108,6 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels path: era5.nc unit_add: temp: -273.15 @@ -113,6 +119,7 @@ era5: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_hourly: crs: 4326 data_type: RasterDataset @@ -124,7 +131,6 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly.nc unit_add: temp: -273.15 @@ -133,6 +139,7 @@ era5_hourly: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_daily_zarr: crs: 4326 data_type: RasterDataset @@ -145,7 +152,6 @@ era5_daily_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels path: era5_daily_zarr.zarr rename: d2m: temp_dew @@ -155,6 +161,7 @@ era5_daily_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 + era5_hourly_zarr: crs: 4326 data_type: RasterDataset @@ -166,7 +173,6 @@ era5_hourly_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly_zarr.zarr rename: d2m: temp_dew @@ -176,6 +182,7 @@ era5_hourly_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 + era5_orography: crs: 4326 data_type: RasterDataset @@ -187,10 +194,10 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_orography.nc unit_mult: elevtn: 0.10197162129779283 + gadm_level1: crs: 4326 data_type: GeoDataFrame @@ -201,8 +208,9 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level1.gpkg + gadm_level2: crs: 4326 data_type: GeoDataFrame @@ -213,8 +221,9 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level2.gpkg + gadm_level3: crs: 4326 data_type: GeoDataFrame @@ -225,8 +234,9 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level3.gpkg + gcn250: data_type: RasterDataset driver: raster @@ -236,9 +246,10 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 + version: 1 nodata: 255 path: gcn250/{variable}.tif + gdp_world: crs: 4326 data_type: GeoDataFrame @@ -249,8 +260,9 @@ gdp_world: source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 - source_version: 1.0 + version: 1.0 path: gdp_world.gpkg + gebco: crs: 4326 data_type: RasterDataset @@ -261,22 +273,31 @@ gebco: paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ - source_version: 2020 unit: m+MSL + version: 2020 path: gebco.tif -ghs-smod_2015_v2: - crs: 54009 + +ghs_smod_2015: + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: category: socio economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 - path: ghs-smod_2015_v2.tif + variants: + - version: R2016A_v1.0 + path: ghs_smod_2015.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + ghs_pop_2015: crs: 4326 data_type: RasterDataset @@ -288,10 +309,11 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 + version: R2019A_v1.0 path: ghs_pop_2015.tif + ghs_pop_2015_54009: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: @@ -300,19 +322,9 @@ ghs_pop_2015_54009: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + version: R2019A_v1.0 path: ghs_pop_2015_54009.tif -ghs_smod_2015: - crs: 54009 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_ref: Pesaresi and Freire (2016) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - path: ghs_smod_2015.tif + globcover: crs: 4326 data_type: RasterDataset @@ -323,7 +335,9 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php + version: 2.3 path: globcover.tif + glw_buffaloes: crs: 4326 data_type: RasterDataset @@ -335,8 +349,9 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_buffaloes.tif + glw_cattle: crs: 4326 data_type: RasterDataset @@ -348,8 +363,9 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_cattle.tif + glw_chicken: crs: 4326 data_type: RasterDataset @@ -361,8 +377,9 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_chicken.tif + glw_ducks: crs: 4326 data_type: RasterDataset @@ -374,8 +391,9 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_ducks.tif + glw_goats: crs: 4326 data_type: RasterDataset @@ -387,8 +405,9 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_goats.tif + glw_horses: crs: 4326 data_type: RasterDataset @@ -400,8 +419,9 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_horses.tif + glw_pigs: crs: 4326 data_type: RasterDataset @@ -413,8 +433,9 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_pigs.tif + glw_sheep: crs: 4326 data_type: RasterDataset @@ -426,8 +447,9 @@ glw_sheep: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_sheep.tif + grdc: crs: 4326 data_type: GeoDataFrame @@ -438,6 +460,7 @@ grdc: source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue path: grdc.csv + grip_roads: crs: 4326 data_type: GeoDataFrame @@ -448,8 +471,9 @@ grip_roads: paper_ref: Meijer et al, 2018 source_license: CC0-1.0 source_url: https://www.globio.info/download-grip-dataset - source_version: v4 + version: 4 path: grip_roads.gpkg + grwl: data_type: GeoDataFrame driver: vector @@ -459,12 +483,13 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 path: grwl.gpkg + grwl_mask: data_type: RasterDataset driver: raster_tindex - kwargs: + driver_kwargs: chunks: x: 3000 y: 3000 @@ -476,9 +501,10 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 nodata: 0 path: grwl_tindex.gpkg + gswo: data_type: RasterDataset driver: raster @@ -487,9 +513,10 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 + version: 1.1 nodata: 255 path: gswo.tif + gtsmv3_eu_era5: crs: 4326 data_type: GeoDataset @@ -500,9 +527,10 @@ gtsmv3_eu_era5: paper_ref: Copernicus Climate Change Service 2019 source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 + version: 3.0 path: gtsmv3_eu_era5.nc -guf_bld_2012: + +guf: crs: 4326 data_type: RasterDataset driver: raster @@ -512,7 +540,9 @@ guf_bld_2012: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf + version: 2 path: guf_bld_2012.tif + hydro_lakes: crs: 4326 data_type: GeoDataFrame @@ -521,10 +551,11 @@ hydro_lakes: category: surface water source_author: Arjen Haag source_info: HydroLAKES.v10_extract - source_version: 1.0 + version: 1.0 path: hydro_lakes.gpkg unit_mult: Area_avg: 1000000.0 + hydro_reservoirs: crs: 4326 data_type: GeoDataFrame @@ -533,7 +564,7 @@ hydro_reservoirs: category: surface water source_author: Alessia Matano source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 + version: 1.0 nodata: -99 path: hydro_reservoirs.gpkg unit_mult: @@ -542,6 +573,7 @@ hydro_reservoirs: Capacity_min: 1000000.0 Capacity_norm: 1000000.0 Vol_avg: 1000000.0 + koppen_geiger: crs: 4326 data_type: RasterDataset @@ -551,9 +583,10 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 + version: 2017 nodata: 0 path: koppen_geiger.tif + mdt_cnes_cls18: crs: 4326 data_type: RasterDataset @@ -563,9 +596,10 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 unit: m+GOCO05S + version: 18 path: mdt_cnes_cls18.tif + merit_hydro: crs: 4326 data_type: RasterDataset @@ -576,8 +610,9 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 + version: 1.0 path: merit_hydro/{variable}.tif + merit_hydro_1k: crs: 4326 data_type: RasterDataset @@ -588,8 +623,9 @@ merit_hydro_1k: paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 source_url: https://doi.org/10.5281/zenodo.4138776 - source_version: 0.1 + version: 0.1 path: merit_hydro_1k/{variable}.tif + merit_hydro_index: crs: 4326 data_type: GeoDataFrame @@ -599,7 +635,9 @@ merit_hydro_index: paper_doi: 10.5194/hess-2020-582 paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 + version: 1.0 path: merit_hydro_index.gpkg + modis_lai: crs: 4326 data_type: RasterDataset @@ -612,10 +650,11 @@ modis_lai: paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 + version: MCD15A3H V006 path: modis_lai.nc unit_mult: LAI: 0.1 + osm_coastlines: crs: 4326 data_type: GeoDataFrame @@ -626,8 +665,9 @@ osm_coastlines: source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_coastlines.gpkg + osm_landareas: crs: 4326 data_type: GeoDataFrame @@ -638,8 +678,9 @@ osm_landareas: source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_landareas.gpkg + rgi: crs: 4326 data_type: GeoDataFrame @@ -651,9 +692,10 @@ rgi: source_info: Randolph Glacier Inventory source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 + version: 6.0 path: rgi.gpkg -rivers_lin2019_v1: + +hydro_rivers_lin2019: data_type: GeoDataFrame driver: vector meta: @@ -662,8 +704,9 @@ rivers_lin2019_v1: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 + version: 1 path: rivers_lin2019_v1.gpkg + simard: crs: 4326 data_type: RasterDataset @@ -673,7 +716,9 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + version: 2011 path: simard.tif + soilgrids: crs: 4326 data_type: RasterDataset @@ -691,7 +736,7 @@ soilgrids: paper_ref: Hengl et al. (2017) source_license: ODbL source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 + version: 2017 path: soilgrids/{variable}.tif unit_mult: bd_sl1: 0.001 @@ -715,6 +760,7 @@ soilgrids: ph_sl5: 0.1 ph_sl6: 0.1 ph_sl7: 0.1 + vito: crs: 4326 data_type: RasterDataset @@ -724,8 +770,9 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 + version: 2.0.2 path: vito.tif + wb_countries: crs: 4326 data_type: GeoDataFrame @@ -736,7 +783,9 @@ wb_countries: source_license: CC-BY 4.0 source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries timestamp: February 2020 + version: 2020319 path: wb_countries.gpkg + worldclim: crs: 4326 data_type: RasterDataset @@ -746,5 +795,6 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 + version: 2 + nodata: -999.0 path: worldclim.nc diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md new file mode 100644 index 000000000..c294edcd6 --- /dev/null +++ b/data/catalogs/changelog.md @@ -0,0 +1,139 @@ +# Change log predefined datasets + +## deltares_data + +### version 2024.2 + +#### added +- version argument to data source where applicable +- variants argument for data sources that are of the same dataset but different versions +- processing_script / processing_notes arguments to data sources that have been (pre-) processed +- temporal extent of datasets that have a temporal dimension. +- spatial extents to datasets + +#### changed +- removed source_version from data source meta +- kwargs to driver_kwargs +- updated source_url if url was not working anymore +- sorted datasets by alphabetical order +- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. + +| Old name | New name | +|--------------------------------|---------------------------| +| basin_atlas_level12_v10 | hydro_basin_atlas_level12 | +| eobs_v.. | eobs | +| eobs_orography_v.. | eobs_orography | +| lake_atlas_pol_v10 | hydro_lake_atlas_pol | +| river_atlas_v10 | hydro_river_atlas | +| ghs_pop_2015_54009_v2019a | ghs_pop_2015 | +| ghs_smod_2015_54009_v2019a | ghs_smod_2015 | +| glofas_era5_v31 | glofas_era5 | +| guf_bld_2012 | guf_bld_2012 | +| rivers_lin2019_v1 | hydro_rivers_lin2019 | +| SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | +| SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | +| vito | vito_2015 | +| vito_2015_v2.0.2 | vito_2015 | +| vito_2016_v3.0.1 | vito_2016 | +| vito_2017_v3.0.1 | vito_2017 | +| vito_2018_v3.0.1 | vito_2018 | +| vito_2019_v3.0.1 | vito_2019 | + +- Some datasets have multiple versions, for these datasets the default can be changed if you do not supply a version in your config file. See the table below for which dataset the default version has changed. + +| Dataset name | Default version | Previous default version | +|----------------|-----------------|--------------------------| +| eobs | 25.0e | 22.0e | +| eobs_orography | 25.0e | 22.0e | + + +### version 2024.1.30 + +#### added +- HydroMT version to catalog +- GRDC dataset + + +### version: 2023.12 + +#### changed +- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files +- removed gtsm_codec_reanalysis dataset + +#### added +- Added waterdemand pcr_globwb dataset +- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) + + +### version: 2023.2 + +#### changed +- convert GeoPackage files to FlatGeoBuf for cloud compatibility +- fix ERA5 nc files to read from archive of combined yearly and monthly files + +#### added +- Additional variables to era5 daily and hourly with name and unit conventions + - temp_dew: dewpoint temperature (degree C) + - wind10_u: 10m wind U-component (m s-1) + - wind10_v: 10m wind V-component (m s-1) + - ssr: surface net solar radiation (W m-2) + - tcc: total cloud cover (-) + + +### version: 2022.7 + +#### added + +- README with conventions regarding data (download, storage, .yml) +- change log file of deltares_data.yml +- new data sets + - basin_atlas_level12_v10 + - river_atlas_v10 + - lake_atlas_pol_v10 + - eobs_v24.0e + - eobs_v25.0e + - eobs_orography_v24.0e + - eobs_orography_v25.0e + - SM2RAIN_ASCAT_monthly_025_v1.4 + - SM2RAIN_ASCAT_monthly_05_v1.4 + +#### changed +- Apply convention specified in the README + - check reasonable alphabetical order in data sets and components + - implement right versioning convention _v where possible + - apply consistent meta information + +#### fixed +- enable versioning of yml.files + +## aws_data + +### version 0.0.9 + +#### changed +- updated source naming to match deltares_data version 2024.2 + +## cmip6_data + +### version: 2024.1.30 + +#### added +- hydromt_version to data catalog meta + + +### version: 2023.2 + +#### added +- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed + +## aws_data + +### version: 2024.1.30 + +#### added +- HydroMT version to catalog + +### version: 2023.2 + +#### added +- ESA Worldcover v100 2020. diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst deleted file mode 100644 index 0748c3a89..000000000 --- a/data/catalogs/changelog.rst +++ /dev/null @@ -1,109 +0,0 @@ -============================== -Change log predefined datasets -============================== - -deltares_data -============= - -version: 2024.1.30 ---------------- - -added -^^^^^ -- HydroMT version to catalog -- GRDC dataset - - -version: 2023.12 ------------------ - -changed -^^^^^^^ -- Updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files - -added -^^^^^ -- Added waterdemand pcr_globwb dataset -- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) - - -version: 2023.2 ----------------- - -changed -^^^^^^^ -- convert GeoPackage files to FlatGeoBuf for cloud compatibility -- fix ERA5 nc files to read from archive of combined yearly and monthly files - -added -^^^^^ -- Additional variables to era5 daily and hourly with name and unit conventions - - temp_dew: dewpoint temperature (degree C) - - wind10_u: 10m wind U-component (m s-1) - - wind10_v: 10m wind V-component (m s-1) - - ssr: surface net solar radiation (W m-2) - - tcc: total cloud cover (-) - - -version: 2022.7 ---------------- - -added -^^^^^ -- README with conventions regarding data (download, storage, .yml) -- change log file of deltares_data.yml -- new data sets - - basin_atlas_level12_v10 - - river_atlas_v10 - - lake_atlas_pol_v10 - - eobs_v24.0e - - eobs_v25.0e - - eobs_orography_v24.0e - - eobs_orography_v25.0e - - SM2RAIN_ASCAT_monthly_025_v1.4 - - SM2RAIN_ASCAT_monthly_05_v1.4 - -changed -^^^^^^^ -- Apply convention specified in the README - - check reasonable alphabetical order in data sets and components - - implement right versioning convention _v where possible - - apply consistent meta information - -fixed -^^^^^ -- enable versioning of yml.files - -cmip6_data -========== - -version: 2024.1.30 ---------------- - -added -^^^^^ -- HydroMT version to catalog - -version: 2023.2 ---------------- - -added -^^^^^ -- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed - -aws_data -======== - -version: 2024.1.30 ---------------- - -added -^^^^^ -- HydroMT version to catalog - -version: 2023.2 ---------------- - -added -^^^^^ -- ESA Worldcover v100 2020. diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 5dbeb7c49..f017217dd 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1,15 +1,15 @@ --- meta: root: p:/wflow_global/hydromt - version: 2024.1.30 + version: 2024.2 hydromt_version: '>=0.9, <1.0' -basin_atlas_level12_v10: +hydro_basin_atlas_level12: crs: 4326 data_type: GeoDataFrame driver: vector - kwargs: + driver_kwargs: layer: BasinATLAS_v10_lev12 meta: category: hydrography @@ -18,50 +18,19 @@ basin_atlas_level12_v10: paper_ref: Linke et al. (2019) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 + source_spatial_extent: + West: -180.0 + South: -55.988 + East: 180.001 + North: 83.626 + version: 10 path: hydrography/hydro_atlas/basin_atlas_v10.gpkg -river_atlas_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 - path: hydrography/hydro_atlas/river_atlas_v10.gpkg - rename: - dis_m3_pyr: Dis_avg - -lake_atlas_pol_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - kwargs: - layer: LakeATLAS_v10_pol - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-022-01425-z - paper_ref: Lehner et al. (2022) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 - path: hydrography/hydro_atlas/lake_atlas_v10.gpkg - rename: - dis_m3_pyr: Dis_avg - chelsa: - alias: chelsa_v1.2 -chelsa_v1.2: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -71,16 +40,19 @@ chelsa_v1.2: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 84.0 + version: 1.2 path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif chirps: - alias: chirps_africa_daily_v2.0 -chirps_africa_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: lat: 160 lon: 150 @@ -94,7 +66,15 @@ chirps_africa_daily_v2.0: paper_ref: Funk et al (2015) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 + source_temporal_extent: + start: '1981-01-02' + end: '2022-04-01' + source_spatial_extent: + West: -20.0 + South: -40.0 + East: 55.0 + North: 40.0 + version: 2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: precipitation: precip @@ -102,12 +82,10 @@ chirps_africa_daily_v2.0: time: 86400 chirps_global: - alias: chirps_global_daily_v2.0 -chirps_global_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 112 longitude: 400 @@ -121,7 +99,15 @@ chirps_global_daily_v2.0: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 + source_temporal_extent: + start: '1981-01-02' + end: '2023-02-01' + source_spatial_extent: + West: -180.0 + South: -50.0 + East: 180.0 + North: 50.0 + version: 2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: precipitation: precip @@ -129,67 +115,74 @@ chirps_global_daily_v2.0: time: 86400 copdem30: - alias: copdem30_v2021.1 -copdem30_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' - nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 + version: 2021.1 path: topography/copdem/copdem.vrt + nodata: -9999 rename: copdem: elevtn copdem30_mask: - alias: copdem30_mask_v2021.1 -copdem30_mask_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' - nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 + version: 2021.1 path: topography/copdem/copdem_mask.vrt + nodata: -1 rename: copdem_mask: mask copdem30_masked: - alias: copdem30_masked_v2021.1 -copdem30_masked_v2021.1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 + version: 2021.1 path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn corine: - alias: corine_2018_v2020_u1 -corine_2018_v2020_u1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -198,14 +191,20 @@ corine_2018_v2020_u1: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 + source_spatial_extent: + West: 900000.0 + South: 900000.0 + East: 7400000.0 + North: 5500000.0 + provider: local + version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif dtu10mdt: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -214,15 +213,20 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM2008 + source_spatial_extent: + West: -179.992 + South: -89.992 + East: 179.992 + North: 89.992 + version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_float32.tif dtu10mdt_egm96: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -231,17 +235,22 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 + processing_notes: /topography/dtu10mdt/READ_ME.txt + processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb unit: m+EGM96 + source_spatial_extent: + West: -179.992 + South: -89.985 + East: 179.995 + North: 89.992 + version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif eobs: - alias: eobs_v22.0e -eobs_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -255,92 +264,43 @@ eobs_v22.0e: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v23.1e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + source_temporal_extent: + start: '1950-01-02' + end: '2022-01-01' + source_spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 + variants: + - version: 22.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + meta: + source_temporal_extent: + start: '1950-01-02' + end: '2020-07-01' + - version: 23.1e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + meta: + source_temporal_extent: + start: '1950-01-02' + end: '2021-01-01' + - version: 24.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + meta: + processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + source_temporal_extent: + start: '1950-01-02' + end: '2021-07-01' + - version: 25.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + meta: + processing_script: v25.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + source_temporal_extent: + start: '1950-01-02' + end: '2022-01-01' rename: pp: press_msl qq: kin @@ -349,51 +309,11 @@ eobs_v25.0e: unit_add: time: 86400 -eobs_orography_v20.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 20.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - rename: - elevation: elevtn - eobs_orography: - alias: eobs_orography_v22.0e -eobs_orography_v22.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - rename: - elevation: elevtn - -eobs_orography_v23.1e: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 100 longitude: 100 @@ -403,56 +323,30 @@ eobs_orography_v23.1e: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - rename: - elevation: elevtn - -eobs_orography_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - rename: - elevation: elevtn - -eobs_orography_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + source_spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 + variants: + - version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + - version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + - version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + - version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + - version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc rename: elevation: elevtn era5: - alias: era5_daily -era5_daily: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 250 longitude: 240 @@ -462,13 +356,22 @@ era5_daily: parallel: true meta: category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency using right label for time. paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) + processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels - path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + source_temporal_extent: + start: '1950-01-02' + end: '2023-11-30' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 + path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc rename: d2m: temp_dew msl: press_msl @@ -492,19 +395,35 @@ era5_daily: press_msl: 0.01 era5_daily_zarr: - alias: era5_daily crs: 4326 data_type: RasterDataset driver: zarr - kwargs: + driver_kwargs: chunks: auto + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_temporal_extent: + start: '1950-01-02' + end: '2023-02-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5_daily.zarr era5_hourly: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 125 longitude: 120 @@ -519,8 +438,15 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 - source_version: ERA5 hourly data on single levels from 1940 to present - path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + source_temporal_extent: + start: '1950-01-01' + end: '2023-03-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 + path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc rename: d2m: temp_dew msl: press_msl @@ -541,19 +467,34 @@ era5_hourly: press_msl: 0.01 era5_hourly_zarr: - alias: era5_hourly crs: 4326 data_type: RasterDataset driver: zarr - kwargs: + driver_kwargs: chunks: auto + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.adbb2d47 + processing_script: meteo/era5_zarr/scripts/ + source_temporal_extent: + start: '1950-01-01' + end: '2023-02-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5.zarr era5_ocean: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 60 longitude: 60 @@ -568,13 +509,21 @@ era5_ocean: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_temporal_extent: + start: '1979-01-01' + end: '2022-04-08' + source_spatial_extent: + West: -0.25 + South: -90.25 + East: 359.75 + North: 90.25 path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc era5_orography: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 120 longitude: 125 @@ -585,6 +534,14 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 + source_temporal_extent: + start: '2018-01-01' + end: '2018-01-01' + source_spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 path: meteo/era5/meta/era5_orography_2018.nc rename: z: elevtn @@ -592,27 +549,31 @@ era5_orography: elevtn: 0.10197162129779283 esa_worldcover: - alias: esa_worldcover_2020_v100 -esa_worldcover_2020_v100: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 36000 y: 36000 meta: category: landuse + processing_notes: prepare vrt file with gdalbuildvrt source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 - source_version: v100 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 84.0 + version: 100 path: landuse/esa_worldcover/esa-worldcover.vrt fabdem: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -622,14 +583,16 @@ fabdem: paper_ref: Hawker et al. (2022) source_license: CC BY-NC-SA 4.0 source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 - source_version: 1.0 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 1.0 path: topography/fabdem/fabdem.vrt rename: fabdem: elevtn -gadm: - alias: gadm_level0 - gadm_level0: crs: 4326 data_type: GeoDataFrame @@ -640,8 +603,13 @@ gadm_level0: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level0.fgb gadm_level1: @@ -654,8 +622,13 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level1.fgb gadm_level2: @@ -668,8 +641,13 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level2.fgb gadm_level3: @@ -682,16 +660,19 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + version: 4.1 path: geography/gadm/version4_1/gadm_level3.fgb gcn250: - alias: gcn250_v1 -gcn250_v1: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -701,8 +682,13 @@ gcn250_v1: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 + source_spatial_extent: + West: -180.0 + South: -56.0 + East: 180.0 + North: 84.0 nodata: 255 + version: 1 path: landuse/gcn250/GCN250_*.tif rename: GCN250_ARCI: cn_dry @@ -710,17 +696,21 @@ gcn250_v1: GCN250_ARCIII: cn_wet gdp_world: - alias: gdp_world_v1 -gdp_world_v1: crs: 4326 data_type: GeoDataFrame driver: vector meta: category: socio-economic - notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + processing_notes: data combined by Deltares (Wilfred Altena) from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 - source_version: 1.0 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.665 + version: 1.0 path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb rename: GDP: gdp @@ -728,12 +718,10 @@ gdp_world_v1: gdp: 0.001 gebco: - alias: gebco_v2020 -gebco_v2020: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -742,20 +730,24 @@ gebco_v2020: paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 - source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ - source_version: 2020 + source_url: https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data/ unit: m+MSL + processing_script: bathymetry/gebco/gebco_tiles.ipynb + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 2020 path: bathymetry/gebco/gebco.vrt rename: gebco: elevtn -ghs_pop: - alias: ghs_pop_2015_54009_v2019a -ghs_pop_2015_4326_v2019a: +ghs_pop_2015: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -766,14 +758,19 @@ ghs_pop_2015_4326_v2019a: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 + source_spatial_extent: + West: -180.0 + South: -59.485 + East: 180.0 + North: 83.628 + version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif -ghs_pop_2015_54009_v2019a: - crs: "ESRI:54009" +ghs_pop_2015_54009: + crs: ESRI:54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -783,52 +780,49 @@ ghs_pop_2015_54009_v2019a: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + source_spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 + version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif -ghs_smod: - alias: ghs_smod_2015_54009_v2019a -ghs_smod_2015_54009_v2016a: - crs: "ESRI:54009" - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_ref: Pesaresi and Freire (2016) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - -ghs_smod_2015_54009_v2019a: - crs: "ESRI:54009" +ghs_smod_2015: + crs: ESRI:54009 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 meta: category: socio-economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + source_spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 + variants: + - version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 globcover: - alias: globcover_2009_v2.3 -globcover_2009_v2.3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -838,14 +832,19 @@ globcover_2009_v2.3: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php - source_version: v2.3 + source_spatial_extent: + West: -180.001 + South: -64.999 + East: 179.999 + North: 90.001 + version: 2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif -glofas_era5_v31: +glofas_era5: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: time: 180 latitude: 150 @@ -860,51 +859,75 @@ glofas_era5_v31: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 - source_version: v31 + processing_script: hydro/glofas_era5/glofas_cds_get.py + source_temporal_extent: + start: '1980-01-01' + end: '2021-05-31' + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 90.0 + version: 31 path: hydro/glofas_era5/glofas_v31_{year}.nc rename: dis24: discharge glofas_uparea: - alias: glofas_era5_v31 + data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 150 y: 360 + meta: + category: hydro + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.5194/essd-12-2043-2020 + paper_ref: Harrigan et al. (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf + source_url: https://doi.org/10.24381/cds.a4fdd6b9 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 90.0 + version: 31 path: hydro/glofas_era5/glofas_v31_uparea.tif rename: glofas_v31_uparea: uparea unit_mult: - uparea: 0.000001 + uparea: 1.0e-06 glw_buffaloes: - alias: glw_buffaloes_v3 -glw_buffaloes_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 meta: category: socio-economic + notes: last downloaded 2020-06-11 paper_doi: 10.7910/DVN/5U8MWI paper_ref: Gilbert at al (2018) source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Bf_2010_Da.tif glw_cattle: - alias: glw_cattle_v3 -glw_cattle_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -915,16 +938,19 @@ glw_cattle_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Ct_2010_Da.tif glw_chicken: - alias: glw_chicken_v3 -glw_chicken_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -935,16 +961,19 @@ glw_chicken_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Ch_2010_Da.tif glw_ducks: - alias: glw_ducks_v3 -glw_ducks_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -955,16 +984,19 @@ glw_ducks_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Dk_2010_Da.tif glw_goats: - alias: glw_goats_v3 -glw_goats_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -975,16 +1007,19 @@ glw_goats_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Gt_2010_Da.tif glw_horses: - alias: glw_horses_v3 -glw_horses_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -995,16 +1030,19 @@ glw_horses_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Ho_2010_Da.tif glw_pigs: - alias: glw_pigs_v3 -glw_pigs_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1015,16 +1053,19 @@ glw_pigs_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Pg_2010_Da.tif glw_sheeps: - alias: glw_sheeps_v3 -glw_sheeps_v3: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1035,15 +1076,19 @@ glw_sheeps_v3: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 3 path: socio_economic/glw/5_Sh_2010_Da.tif - grdc: crs: 4326 data_type: GeoDataFrame driver: csv - kwargs: + driver_kwargs: index_col: grdc_no meta: category: observed data @@ -1055,8 +1100,6 @@ grdc: area: uparea grip_roads: - alias: grip_roads_v4 -grip_roads_v4: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1066,15 +1109,19 @@ grip_roads_v4: paper_ref: Meijer et al, 2018 paper_doi: 10.1088/1748-9326/aabd42 source_license: CC0-1.0 - source_version: v4 + processing_script: infrastructure/grip/merge.ipynb + source_spatial_extent: + West: -179.999 + South: -55.055 + East: 180.0 + North: 73.836 + version: 4 path: infrastructure/grip/GRIP4_world.fgb rename: GP_RTP: road_type GP_RCY: country_code grwl: - alias: grwl_v1.01 -grwl_v1.01: data_type: GeoDataFrame driver: vector meta: @@ -1083,19 +1130,22 @@ grwl_v1.01: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + source_spatial_extent: + West: -180.0 + South: -54.31 + East: 180.0 + North: 82.311 + version: 1.01 path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb grwl_mask: - alias: grwl_mask_v1.01 -grwl_mask_v1.01: data_type: RasterDataset driver: raster_tindex - kwargs: + driver_kwargs: chunks: x: 3000 y: 3000 - mosaic_kwargs: + mosaic_driver_kwargs: method: nearest tileindex: location meta: @@ -1104,16 +1154,14 @@ grwl_mask_v1.01: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 nodata: 0 + version: 1.01 path: hydrography/grwl/tindex.gpkg gswo: - alias: gswo_v2019 -gswo_v2019: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 4000 y: 4000 @@ -1122,40 +1170,20 @@ gswo_v2019: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 nodata: 255 + version: 1.1 path: hydrography/gswo/occur.vrt -gtsm_codec_reanalysis_{freq}_v1: - crs: 4326 - data_type: GeoDataset - driver: netcdf - kwargs: - chunks: - stations: 10 - time: -1 - meta: - category: ocean - paper_doi: 10.3389/fmars.2020.00263 - paper_ref: Muis at al (2020) - source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf - source_url: https://doi.org/10.24381/cds.8c59054f - source_version: v1 - path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc - placeholders: - freq: [10min, hourly, dailymax] - rename: - station_x_coordinate: lon - station_y_coordinate: lat - stations: index - guf_bld_2012: - alias: guf_bld_2012_v02 -guf_bld_2012_v02: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -1165,6 +1193,12 @@ guf_bld_2012_v02: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf + source_spatial_extent: + West: -180.0 + South: -65.0 + East: 180.0 + North: 85.0 + version: 2 path: infrastructure/guf/GUF04_DLR_v02.vrt hydro_lakes: @@ -1173,9 +1207,14 @@ hydro_lakes: driver: vector meta: category: surface water - notes: HydroLAKES.v10_extract - source_author: Arjen Haag - source_version: 1.0 + processing_notes: extract of hydrolakes to only include natural lakes and exclude reservoirs and control lakes (ie filter on Lake_type = 1) + source_author: HydroSHEDS + source_spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 + version: 1.0 path: hydrography/lakes/lake-db.fgb rename: Depth_avg: Depth_avg @@ -1196,8 +1235,13 @@ hydro_reservoirs: category: surface water notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 source_author: Alessia Matano - source_version: 1.0 + source_spatial_extent: + West: -153.059 + South: -45.881 + East: 176.825 + North: 70.396 nodata: -99 + version: 1.0 path: hydrography/reservoirs/reservoir-db.fgb rename: Depth_avg: Depth_avg @@ -1223,7 +1267,7 @@ koppen_geiger: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1232,15 +1276,43 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 nodata: 0 + version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif +hydro_lake_atlas_pol: + crs: 4326 + data_type: GeoDataFrame + driver: vector + driver_kwargs: + layer: LakeATLAS_v10_pol + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 + path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + version: 10 + rename: + dis_m3_pyr: Dis_avg + mdt_cnes_cls18: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 720 y: 720 @@ -1249,17 +1321,21 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 unit: m+GOCO05S + processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 18 path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif merit: - alias: merit_v1.0.3 -merit_v1.0.3: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: drop_variables: projection chunks: lat: 6000 @@ -1270,18 +1346,21 @@ merit_v1.0.3: paper_ref: Yamazaki et al. (2018) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ - source_version: 1.0.3 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 1.0.3 path: topography/merit/merit.nc rename: elevation: elevtn merit_hydro: - alias: merit_hydro_v1.0 -merit_hydro_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1289,9 +1368,16 @@ merit_hydro_v1.0: category: topography paper_doi: 10.1029/2019WR024873 paper_ref: Yamazaki et al. (2019) + processing_notes: create vrt file with gdalbuildvrt; + additional variables for stream-order, basin index (basins), and slope (lndslp) derived with pyflwdir source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 + version: 1.0 path: topography/merit_hydro/*.vrt rename: bas: basins @@ -1304,12 +1390,10 @@ merit_hydro_v1.0: wth: rivwth merit_hydro_ihu: - alias: merit_hydro_ihu_30sec_v1.0 -merit_hydro_ihu_30sec_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1320,8 +1404,14 @@ merit_hydro_ihu_30sec_v1.0: source_license: ODC-By 1.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk source_doi: 10.5281/zenodo.5166932 - source_version: 1.0 + processing_notes: topography/merit_hydro_ihu/README + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 path: topography/merit_hydro_ihu/30sec/*.tif + version: 1.0 rename: 30sec_basids: basins 30sec_flwdir: flwdir @@ -1341,11 +1431,16 @@ merit_hydro_ihu_index: paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + processing_notes: topography/merit_hydro_ihu/README + source_spatial_extent: + West: -180.025 + South: -59.467 + East: 190.35 + North: 83.683 + version: 1.0 path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: - alias: merit_hydro_index_v1.0 -merit_hydro_index_v1.0: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1354,15 +1449,19 @@ merit_hydro_index_v1.0: paper_doi: 10.5194/hess-25-5287-2021 paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 + source_spatial_extent: + West: -180.028 + South: -59.46 + East: 190.338 + North: 83.661 + version: 1.0 path: topography/merit_hydro/basin_index.fgb merit_hydro_patch: - alias: merit_hydro_patch_v1.0 -merit_hydro_patch_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 6000 y: 6000 @@ -1372,7 +1471,14 @@ merit_hydro_patch_v1.0: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 Deltares patch + processing_script: topography/merit_hydro/patches/scripts + processing_notes: local corrections of flow direction raster and re-derive the related maps (basins, uparea, strord) + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 + version: 1.0 path: topography/merit_hydro/patches/*.vrt rename: bas: basins @@ -1385,31 +1491,36 @@ merit_hydro_patch_v1.0: wth: rivwth modis_lai: - alias: modis_mcd15a3h_v006 -modis_mcd15a3h_v006: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 concat: true meta: category: landuse - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 + processing_notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') + for the period '2003-01-01', '2017-12-31' + processing_script: + GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js + merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py + source_spatial_extent: + West: -180.004 + South: -90.002 + East: 180.004 + North: 90.002 + version: MCD15A3H V006 path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: LAI: 0.1 osm_coastlines: - alias: osm_coastlines_v20200109 -osm_coastlines_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1419,14 +1530,17 @@ osm_coastlines_v20200109: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + source_spatial_extent: + West: -180.0 + South: -78.733 + East: 180.0 + North: 90.0 + version: 1.0 path: geography/osm/osm_coastlines-db.fgb rename: fid: coastline_id osm_landareas: - alias: osm_landareas_v20200109 -osm_landareas_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1436,7 +1550,12 @@ osm_landareas_v20200109: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.666 + version: 1.0 path: geography/osm/osm_landareas-db.fgb rename: fid: land_id @@ -1453,8 +1572,12 @@ pcr_globwb: paper_doi: 10.5281/zenodo.1045339 paper_ref: Sutanudjaja, E. H., et al (2017) source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR - source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 variants: - version: 1990 path: hydro/pcr_globwb/glob_1990.zarr @@ -1481,8 +1604,6 @@ pcr_globwb: lsk_gross: 1000 rgi: - alias: rgi_v0.6 -rgi_v0.6: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1493,7 +1614,12 @@ rgi_v0.6: paper_ref: Pfeffer et al. (2014) source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 + source_spatial_extent: + West: -179.921 + South: -78.309 + East: 179.751 + North: 83.608 + version: 6.0 path: hydrography/rgi/rgi.fgb rename: C3S_ID: C3S_id @@ -1501,7 +1627,28 @@ rgi_v0.6: ID: simple_id RGIID: RGI_id -rivers_lin2019_v1: +hydro_river_atlas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_spatial_extent: + West: -179.998 + South: -55.877 + East: 179.998 + North: 83.59 + path: hydrography/hydro_atlas/river_atlas_v10.gpkg + version: 10 + rename: + dis_m3_pyr: Dis_avg + +hydro_rivers_lin2019: data_type: GeoDataFrame driver: vector meta: @@ -1510,19 +1657,23 @@ rivers_lin2019_v1: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 + processing_notes: hydrography/rivers_lin2019/README + source_spatial_extent: + West: -177.204 + South: -55.414 + East: 180.237 + North: 82.112 + version: 1 path: hydrography/rivers_lin2019/rivers_ge30m.fgb rename: width_m: rivwth Q2: qbankfull simard: - alias: simard_v2011 -simard_v2011: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1531,69 +1682,103 @@ simard_v2011: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif -SM2RAIN_ASCAT_monthly_025_v1.4: +SM2RAIN_ASCAT_monthly_025: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 360 longitude: 720 time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, + 0.25-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_temporal_extent: + start: '2007-01-01' + end: '2020-12-01' + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: rainfall: precip -SM2RAIN_ASCAT_monthly_05_v1.4: +SM2RAIN_ASCAT_monthly_05: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: latitude: 180 longitude: 360 time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, + 0.5-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + source_temporal_extent: + start: '2007-01-01' + end: '2020-12-01' + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: rainfall: precip soilgrids: - alias: soilgrids_v1.0 -soilgrids_v1.0: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 2400 y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\n\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land\ + \ Use Policy 29 (2), 329\xC3\xA2\xE2\u201A\xAC\xE2\u20AC\u0153338. \n" paper_doi: 10.1371/journal.pone.0169748 paper_ref: Hengl et al. (2017) source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 + processing_notes: "soilthickness is based on 1) soilgrids (global, depth to bedrock - BDRICM variable) and 2) dataset for Eurasia" + processing_script: p:/wflow_global/static_data/wflow_sbm_parameters/ + source_spatial_extent: + West: -19949000.0 + South: -6147500.0 + East: 19861750.0 + North: 8361000.0 + version: 1.0 path: soil/soilgrids_v1.0/*_250m_ll.tif rename: BLDFIE_M_sl1_250m_ll: bd_sl1 @@ -1663,117 +1848,11 @@ soilgrids_v1.0: ph_sl6: 0.1 ph_sl7: 0.1 -soilgrids_2020: - alias: soilgrids_v2.0 -soilgrids_v2.0: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 2400 - y: 2400 - meta: - category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - source_version: 2020 - path: soil/soilgrids_v2.0/*/*_mean.vrt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 - -vito: - alias: vito_2015_v2.0.2 -vito_2015_v2.0.2: +vito_2015: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1782,14 +1861,19 @@ vito_2015_v2.0.2: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 2.0.2 path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif -vito_2016_v3.0.1: +vito_2016: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1798,14 +1882,19 @@ vito_2016_v3.0.1: paper_doi: 10.5281/zenodo.3518026 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2017_v3.0.1: +vito_2017: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1814,14 +1903,19 @@ vito_2017_v3.0.1: paper_doi: 10.5281/zenodo.3518036 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2018_v3.0.1: +vito_2018: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1830,14 +1924,19 @@ vito_2018_v3.0.1: paper_doi: 10.5281/zenodo.3518038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2019_v3.0.1: +vito_2019: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 3600 y: 3600 @@ -1846,12 +1945,15 @@ vito_2019_v3.0.1: paper_doi: 10.5281/zenodo.3939050 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 3.0.1 path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: - alias: wb_countries_v20200319 -wb_countries_v20200319: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1861,6 +1963,12 @@ wb_countries_v20200319: source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries source_license: CC-BY 4.0 timestamp: February 2020 + source_spatial_extent: + West: -180.0 + South: -59.473 + East: 180.0 + North: 83.634 + version: 20200319 path: geography/wb/WB_countries_Admin0.fgb rename: ISO_A3: country_iso @@ -1872,12 +1980,10 @@ wb_countries_v20200319: gdp_pc: 1000 worldclim: - alias: worldclim_v2.0 -worldclim_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - kwargs: + driver_kwargs: chunks: lat: 3600 lon: 3600 @@ -1886,8 +1992,13 @@ worldclim_v2.0: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 nodata: -999.0 + source_spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + version: 2.0 path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc rename: prec: precip @@ -1895,7 +2006,7 @@ worldclim_v2.0: worldpop_2020_constrained: data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: auto meta: category: socio-economic @@ -1903,24 +2014,38 @@ worldpop_2020_constrained: paper_ref: Stevens et al. (2015) source_license: CC BY 4.0 source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 + processing_script: socio_economic/worldpop/src/ + source_spatial_extent: + West: -180.0 + South: -55.985 + East: 180.0 + North: 83.628 nodata: -99999 path: socio_economic/worldpop/ppp_2020_constrained.vrt rename: ppp_2020_constrained: population worldpop_2020_UNadj_constrained: - alias: worldpop_2020_constrained + data_type: RasterDataset + driver: raster + driver_kwargs: + chunks: auto + meta: + processing_script: socio_economic/worldpop/src/ + source_spatial_extent: + West: -180.0 + South: -55.985 + East: 180.0 + North: 83.628 path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt rename: ppp_2020_UNadj_constrained: population wsf_bld_2015: - alias: wsf_bld_2015_v1 -wsf_bld_2015_v1: crs: 4326 data_type: RasterDataset driver: raster - kwargs: + driver_kwargs: chunks: x: 1000 y: 1000 @@ -1930,4 +2055,10 @@ wsf_bld_2015_v1: paper_ref: Marconcini at al (2020) source_license: CC0 1.0 source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc + source_spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + version: 1 path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index f7cae9857..c96d9eadd 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -16,7 +16,8 @@ deltares_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/deltares_data.yml versions: - v2024.1.30: main + v2024.2: main + v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 v2023.12.21: 392206b21b26e62e00ae76db7ffc61a3b95e2175 v2023.12.19: bf25e79dcbda67612a75588cd782d57abe3881de v2023.2: 0bf8e2a1e716095dc6df54a5e9114ce88da0701b @@ -36,9 +37,8 @@ aws_data: v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: - urlpath: https://github.com/DirkEilander/hydromt-artifacts/releases/download/{version}/data.tar.gz + urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml versions: - v0.0.8: v0.0.8 - v0.0.7: v0.0.7 - v0.0.6: v0.0.6 + v0.0.9: main + v0.0.8: 202874eb4fe3415d0608ea81cd61620af6f5816a notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. diff --git a/docs/changelog.rst b/docs/changelog.rst index db57a3c72..645b1320b 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -37,6 +37,11 @@ Added - Test script for testing predefined catalogs locally. (#735) - Option to write a data catalog to a csv file (#425) +Changed +------- +- Datacatalog preserves variant specific meta data (#521) +- Updated DataCatalogValidator to deal with provider and driver_kwargs (#521) + Fixed ----- - Reading Vector formats that consist of more than one file via geopandas. (#691) @@ -45,6 +50,7 @@ Fixed - Fix bug in `raster._check_dimensions` for datasets with multiple variables with varying dimension size (#761) - Fix bug when reading COGs at requested zoom level (#758) + v0.9.2 (2024-01-09) =================== This release adds additional bug fixes for the meridian offset functinality, and improvements to the new CLI commands. @@ -55,9 +61,11 @@ Added - New stats.skills VE and RSR (#666) - Check CLI command can now validate bbox and geom regions (#664) + Changed ------- - Export CLI now uses '-s' for source, '-t' for time and '-i' for config. (#660) +- Updated deltares_data data catalog to incorporate the newest data catalog features (#667) Fixed ----- diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index e674c76dc..17b245fdc 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -33,8 +33,7 @@ "source": [ "import numpy as np\n", "import geopandas as gpd\n", - "from shapely.geometry import box\n", - "from pprint import pprint" + "from shapely.geometry import box" ] }, { @@ -378,7 +377,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.8" + "version": "3.11.7" }, "vscode": { "interpreter": { diff --git a/examples/prep_data_catalog.ipynb b/examples/prep_data_catalog.ipynb index c74066a24..9f1d16fdd 100644 --- a/examples/prep_data_catalog.ipynb +++ b/examples/prep_data_catalog.ipynb @@ -64,7 +64,7 @@ "outputs": [], "source": [ "# this download the artifact_data archive v0.0.6\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.6\"])\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"])\n", "pprint(data_catalog.predefined_catalogs)" ] }, @@ -85,7 +85,7 @@ "outputs": [], "source": [ "# the artifact data is stored in the following location\n", - "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.6\")\n", + "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.8\")\n", "# let's print some of the file that are there\n", "for item in os.listdir(root)[-10:]:\n", " print(item)" diff --git a/hydromt/data_adapter/data_adapter.py b/hydromt/data_adapter/data_adapter.py index 9c9314974..2ea21731e 100644 --- a/hydromt/data_adapter/data_adapter.py +++ b/hydromt/data_adapter/data_adapter.py @@ -334,9 +334,13 @@ def _resolve_paths( continue key_str = "{" + f"{key}:{fmt}" + "}" if fmt else "{" + key + "}" # remove unused fields - if key in ["year", "month"] and time_tuple is None: + if ( + key in ["year", "month"] + and time_tuple is None + and not path.endswith("*") + ): path += "*" - elif key == "variable" and variables is None: + elif key == "variable" and variables is None and not path.endswith("*"): path += "*" # escape unknown fields elif key is not None and key not in known_keys: diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 9402c31d3..d306daf23 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -1913,6 +1913,9 @@ def _denormalise_data_dict(data_dict) -> List[Tuple[str, Dict]]: variants = source.pop("variants") for diff in variants: source_copy = copy.deepcopy(source) + if "meta" in source_copy: + # Update meta if variant has variant specific meta data + source_copy["meta"].update(diff.pop("meta", {})) source_copy.update(**diff) data_dicts.append({name: source_copy}) elif "placeholders" in source: diff --git a/hydromt/validators/data_catalog.py b/hydromt/validators/data_catalog.py index a5592d314..9e6391146 100644 --- a/hydromt/validators/data_catalog.py +++ b/hydromt/validators/data_catalog.py @@ -111,7 +111,9 @@ class DataCatalogItem(BaseModel): path: Optional[Path] = None crs: Optional[Union[int, str]] = None filesystem: Optional[str] = None - kwargs: Dict[str, Any] = Field(default_factory=dict) + provider: Optional[str] = None + driver_kwargs: Dict[str, Any] = Field(default_factory=dict) + kwargs: Dict[str, Any] = Field(default_factory=dict) # deprecated storage_options: Dict[str, Any] = Field(default_factory=dict) placeholders: Optional[Dict[str, Any]] = None rename: Dict[str, str] = Field(default_factory=dict) diff --git a/tests/data/merged_esa_worldcover.yml b/tests/data/merged_esa_worldcover.yml index 7f7778587..88143b1b1 100644 --- a/tests/data/merged_esa_worldcover.yml +++ b/tests/data/merged_esa_worldcover.yml @@ -18,6 +18,8 @@ esa_worldcover: - provider: local version: 2020 path: landuse/esa_worldcover/esa-worldcover.vrt + meta: + source_author: Test Dummy - provider: aws version: 2020 path: s3://esa-worldcover/v100/2020/ESA_WorldCover_10m_2020_v100_Map_AWS.vrt diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 958ffb97a..8682982ae 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -195,6 +195,12 @@ def test_versioned_catalog_entries(tmpdir): # test round trip to and from dict merged_catalog2 = DataCatalog().from_dict(merged_catalog.to_dict()) assert merged_catalog2 == merged_catalog + # test updating source meta data from version meta data + source_2020_local = merged_catalog.get_source( + "esa_worldcover", version="2020", provider="local" + ) + assert source_2020_local.meta["source_author"] == "Test Dummy" + assert source_2020_local.meta["source_license"] == "CC BY 4.0" # Make sure we can query for the version we want aws_and_legacy_catalog = DataCatalog(data_libs=[legacy_yml_fn, aws_yml_fn]) @@ -588,12 +594,12 @@ def test_get_dataframe(df, tmpdir): def test_deprecation_warnings(artifact_data): with pytest.deprecated_call(): - # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) - DataCatalog(artifact_data="v0.0.6") + # should be DataCatalog(data_libs=['v0.0.8']) + DataCatalog(artifact_data="v0.0.8") with pytest.deprecated_call(): cat = DataCatalog() - # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') - cat.from_artifacts("artifact_data", version="v0.0.6") + # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.8') + cat.from_artifacts("artifact_data", version="v0.0.8") with pytest.deprecated_call(): fn = artifact_data["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) From 69ad608b374cc28e9266bb9f5d7551a1fd882f4a Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 6 Mar 2024 16:34:26 +0100 Subject: [PATCH 061/110] Revert "Update data catalog" (#831) --- data/catalogs/README.rst | 23 +- data/catalogs/artifact_data.yml | 192 ++-- data/catalogs/changelog.md | 139 --- data/catalogs/changelog.rst | 109 +++ data/catalogs/deltares_data.yml | 1329 ++++++++++++-------------- data/predefined_catalogs.yml | 10 +- docs/changelog.rst | 8 - examples/delineate_basin.ipynb | 5 +- examples/prep_data_catalog.ipynb | 4 +- hydromt/data_adapter/data_adapter.py | 8 +- hydromt/data_catalog.py | 3 - hydromt/validators/data_catalog.py | 4 +- tests/data/merged_esa_worldcover.yml | 2 - tests/test_data_catalog.py | 14 +- 14 files changed, 806 insertions(+), 1044 deletions(-) delete mode 100644 data/catalogs/changelog.md create mode 100644 data/catalogs/changelog.rst diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 5b97a8b5f..58007af48 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -80,24 +80,21 @@ structure per data set: - order the components of each data set alphabetically - for adding meta data use the following optional keys: -meta: - category: - notes: - paper_doi: - paper_ref: - source_author: (if different from paper_ref) - source_license: - source_url: - source_spatial_extent: - source_temporal_extent: - processing_script: - processing_notes: +category: +notes: +paper_doi: +paper_ref: +source_author: (if different from paper_ref) +source_license: +source_url: +source_version: +unit: updates ------- - create new branch on github - make changes and bump the version in the global meta section using `calendar versioning ` -- test your yml file (Can the added/changed data sources be read through HydroMT?), this can be done by running the test_data_catalog.py file located in this folder. Read the docstring for more information. +- test your yml file (Can the added/changed data sources be read through HydroMT?) - create pull request - add new version to hydromt\data\predefined_catalogs.yml diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index 3628c828a..e09b16148 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: - version: v0.0.9 + version: v0.0.8 hydromt_version: '>=0.9, <1.0' - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.9/data.tar.gz + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz chelsa: crs: 4326 @@ -13,9 +13,8 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - version: 1.2 + source_version: 1.2 path: chelsa.tif - chirps_global: crs: 4326 data_type: RasterDataset @@ -26,11 +25,10 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - version: 2.0 + source_version: v2.0 path: chirps_global.nc unit_add: time: 86400 - corine: data_type: RasterDataset driver: raster @@ -39,9 +37,8 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - version: 2020_20u1 + source_version: v.2020_20u1 path: corine.tif - dtu10mdt: crs: 4326 data_type: RasterDataset @@ -51,10 +48,9 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 unit: m+EGM2008 - version: 2010 path: dtu10mdt.tif - dtu10mdt_egm96: crs: 4326 data_type: RasterDataset @@ -64,10 +60,9 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 unit: m+EGM96 - version: 2010 path: dtu10mdt_egm96.tif - eobs: crs: 4326 data_type: RasterDataset @@ -78,11 +73,10 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 22.0e + source_version: 22.0e path: eobs.nc unit_add: time: 86400 - eobs_orography: crs: 4326 data_type: RasterDataset @@ -93,9 +87,8 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 22.0e + source_version: 22.0e path: eobs_orography.nc - era5: crs: 4326 data_type: RasterDataset @@ -108,6 +101,7 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels path: era5.nc unit_add: temp: -273.15 @@ -119,7 +113,6 @@ era5: kout: 0.000277778 precip: 1000 press_msl: 0.01 - era5_hourly: crs: 4326 data_type: RasterDataset @@ -131,6 +124,7 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels path: era5_hourly.nc unit_add: temp: -273.15 @@ -139,7 +133,6 @@ era5_hourly: kout: 0.000277778 precip: 1000 press_msl: 0.01 - era5_daily_zarr: crs: 4326 data_type: RasterDataset @@ -152,6 +145,7 @@ era5_daily_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels path: era5_daily_zarr.zarr rename: d2m: temp_dew @@ -161,7 +155,6 @@ era5_daily_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 - era5_hourly_zarr: crs: 4326 data_type: RasterDataset @@ -173,6 +166,7 @@ era5_hourly_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels path: era5_hourly_zarr.zarr rename: d2m: temp_dew @@ -182,7 +176,6 @@ era5_hourly_zarr: temp_dew: -273.15 unit_mult: ssr: 0.000277778 - era5_orography: crs: 4326 data_type: RasterDataset @@ -194,10 +187,10 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels path: era5_orography.nc unit_mult: elevtn: 0.10197162129779283 - gadm_level1: crs: 4326 data_type: GeoDataFrame @@ -208,9 +201,8 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - version: 1.0 + source_version: 1.0 path: gadm_level1.gpkg - gadm_level2: crs: 4326 data_type: GeoDataFrame @@ -221,9 +213,8 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - version: 1.0 + source_version: 1.0 path: gadm_level2.gpkg - gadm_level3: crs: 4326 data_type: GeoDataFrame @@ -234,9 +225,8 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - version: 1.0 + source_version: 1.0 path: gadm_level3.gpkg - gcn250: data_type: RasterDataset driver: raster @@ -246,10 +236,9 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - version: 1 + source_version: v1 nodata: 255 path: gcn250/{variable}.tif - gdp_world: crs: 4326 data_type: GeoDataFrame @@ -260,9 +249,8 @@ gdp_world: source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 - version: 1.0 + source_version: 1.0 path: gdp_world.gpkg - gebco: crs: 4326 data_type: RasterDataset @@ -273,31 +261,22 @@ gebco: paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 unit: m+MSL - version: 2020 path: gebco.tif - -ghs_smod_2015: - crs: ESRI:54009 +ghs-smod_2015_v2: + crs: 54009 data_type: RasterDataset driver: raster meta: category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - variants: - - version: R2016A_v1.0 - path: ghs_smod_2015.tif - meta: - paper_ref: Pesaresi and Freire (2016) - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - - version: R2019A_v2.0 - path: ghs-smod_2015_v2.tif - meta: - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif ghs_pop_2015: crs: 4326 data_type: RasterDataset @@ -309,11 +288,10 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - version: R2019A_v1.0 + source_version: R2019A_v1.0 path: ghs_pop_2015.tif - ghs_pop_2015_54009: - crs: ESRI:54009 + crs: 54009 data_type: RasterDataset driver: raster meta: @@ -322,9 +300,19 @@ ghs_pop_2015_54009: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop - version: R2019A_v1.0 path: ghs_pop_2015_54009.tif - +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif globcover: crs: 4326 data_type: RasterDataset @@ -335,9 +323,7 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php - version: 2.3 path: globcover.tif - glw_buffaloes: crs: 4326 data_type: RasterDataset @@ -349,9 +335,8 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_buffaloes.tif - glw_cattle: crs: 4326 data_type: RasterDataset @@ -363,9 +348,8 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_cattle.tif - glw_chicken: crs: 4326 data_type: RasterDataset @@ -377,9 +361,8 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_chicken.tif - glw_ducks: crs: 4326 data_type: RasterDataset @@ -391,9 +374,8 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_ducks.tif - glw_goats: crs: 4326 data_type: RasterDataset @@ -405,9 +387,8 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_goats.tif - glw_horses: crs: 4326 data_type: RasterDataset @@ -419,9 +400,8 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_horses.tif - glw_pigs: crs: 4326 data_type: RasterDataset @@ -433,9 +413,8 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_pigs.tif - glw_sheep: crs: 4326 data_type: RasterDataset @@ -447,9 +426,8 @@ glw_sheep: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: glw_sheep.tif - grdc: crs: 4326 data_type: GeoDataFrame @@ -460,7 +438,6 @@ grdc: source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue path: grdc.csv - grip_roads: crs: 4326 data_type: GeoDataFrame @@ -471,9 +448,8 @@ grip_roads: paper_ref: Meijer et al, 2018 source_license: CC0-1.0 source_url: https://www.globio.info/download-grip-dataset - version: 4 + source_version: v4 path: grip_roads.gpkg - grwl: data_type: GeoDataFrame driver: vector @@ -483,13 +459,12 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - version: 1.01 + source_version: 1.01 path: grwl.gpkg - grwl_mask: data_type: RasterDataset driver: raster_tindex - driver_kwargs: + kwargs: chunks: x: 3000 y: 3000 @@ -501,10 +476,9 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - version: 1.01 + source_version: 1.01 nodata: 0 path: grwl_tindex.gpkg - gswo: data_type: RasterDataset driver: raster @@ -513,10 +487,9 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - version: 1.1 + source_version: v1_1_2019 nodata: 255 path: gswo.tif - gtsmv3_eu_era5: crs: 4326 data_type: GeoDataset @@ -527,10 +500,9 @@ gtsmv3_eu_era5: paper_ref: Copernicus Climate Change Service 2019 source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - version: 3.0 + source_version: GTSM v3.0 path: gtsmv3_eu_era5.nc - -guf: +guf_bld_2012: crs: 4326 data_type: RasterDataset driver: raster @@ -540,9 +512,7 @@ guf: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf - version: 2 path: guf_bld_2012.tif - hydro_lakes: crs: 4326 data_type: GeoDataFrame @@ -551,11 +521,10 @@ hydro_lakes: category: surface water source_author: Arjen Haag source_info: HydroLAKES.v10_extract - version: 1.0 + source_version: 1.0 path: hydro_lakes.gpkg unit_mult: Area_avg: 1000000.0 - hydro_reservoirs: crs: 4326 data_type: GeoDataFrame @@ -564,7 +533,7 @@ hydro_reservoirs: category: surface water source_author: Alessia Matano source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - version: 1.0 + source_version: 1.0 nodata: -99 path: hydro_reservoirs.gpkg unit_mult: @@ -573,7 +542,6 @@ hydro_reservoirs: Capacity_min: 1000000.0 Capacity_norm: 1000000.0 Vol_avg: 1000000.0 - koppen_geiger: crs: 4326 data_type: RasterDataset @@ -583,10 +551,9 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - version: 2017 + source_version: 2017 nodata: 0 path: koppen_geiger.tif - mdt_cnes_cls18: crs: 4326 data_type: RasterDataset @@ -596,10 +563,9 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 unit: m+GOCO05S - version: 18 path: mdt_cnes_cls18.tif - merit_hydro: crs: 4326 data_type: RasterDataset @@ -610,9 +576,8 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - version: 1.0 + source_version: 1.0 path: merit_hydro/{variable}.tif - merit_hydro_1k: crs: 4326 data_type: RasterDataset @@ -623,9 +588,8 @@ merit_hydro_1k: paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 source_url: https://doi.org/10.5281/zenodo.4138776 - version: 0.1 + source_version: 0.1 path: merit_hydro_1k/{variable}.tif - merit_hydro_index: crs: 4326 data_type: GeoDataFrame @@ -635,9 +599,7 @@ merit_hydro_index: paper_doi: 10.5194/hess-2020-582 paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 - version: 1.0 path: merit_hydro_index.gpkg - modis_lai: crs: 4326 data_type: RasterDataset @@ -650,11 +612,10 @@ modis_lai: paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - version: MCD15A3H V006 + source_version: MCD15A3H V006 path: modis_lai.nc unit_mult: LAI: 0.1 - osm_coastlines: crs: 4326 data_type: GeoDataFrame @@ -665,9 +626,8 @@ osm_coastlines: source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - version: 1.0 + source_version: 1.0 path: osm_coastlines.gpkg - osm_landareas: crs: 4326 data_type: GeoDataFrame @@ -678,9 +638,8 @@ osm_landareas: source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - version: 1.0 + source_version: 1.0 path: osm_landareas.gpkg - rgi: crs: 4326 data_type: GeoDataFrame @@ -692,10 +651,9 @@ rgi: source_info: Randolph Glacier Inventory source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - version: 6.0 + source_version: 6.0 path: rgi.gpkg - -hydro_rivers_lin2019: +rivers_lin2019_v1: data_type: GeoDataFrame driver: vector meta: @@ -704,9 +662,8 @@ hydro_rivers_lin2019: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - version: 1 + source_version: 1 path: rivers_lin2019_v1.gpkg - simard: crs: 4326 data_type: RasterDataset @@ -716,9 +673,7 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - version: 2011 path: simard.tif - soilgrids: crs: 4326 data_type: RasterDataset @@ -736,7 +691,7 @@ soilgrids: paper_ref: Hengl et al. (2017) source_license: ODbL source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - version: 2017 + source_version: 2017 path: soilgrids/{variable}.tif unit_mult: bd_sl1: 0.001 @@ -760,7 +715,6 @@ soilgrids: ph_sl5: 0.1 ph_sl6: 0.1 ph_sl7: 0.1 - vito: crs: 4326 data_type: RasterDataset @@ -770,9 +724,8 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - version: 2.0.2 + source_version: v2.0.2 path: vito.tif - wb_countries: crs: 4326 data_type: GeoDataFrame @@ -783,9 +736,7 @@ wb_countries: source_license: CC-BY 4.0 source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries timestamp: February 2020 - version: 2020319 path: wb_countries.gpkg - worldclim: crs: 4326 data_type: RasterDataset @@ -795,6 +746,5 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - version: 2 - nodata: -999.0 + source_version: 2 path: worldclim.nc diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md deleted file mode 100644 index c294edcd6..000000000 --- a/data/catalogs/changelog.md +++ /dev/null @@ -1,139 +0,0 @@ -# Change log predefined datasets - -## deltares_data - -### version 2024.2 - -#### added -- version argument to data source where applicable -- variants argument for data sources that are of the same dataset but different versions -- processing_script / processing_notes arguments to data sources that have been (pre-) processed -- temporal extent of datasets that have a temporal dimension. -- spatial extents to datasets - -#### changed -- removed source_version from data source meta -- kwargs to driver_kwargs -- updated source_url if url was not working anymore -- sorted datasets by alphabetical order -- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. - -| Old name | New name | -|--------------------------------|---------------------------| -| basin_atlas_level12_v10 | hydro_basin_atlas_level12 | -| eobs_v.. | eobs | -| eobs_orography_v.. | eobs_orography | -| lake_atlas_pol_v10 | hydro_lake_atlas_pol | -| river_atlas_v10 | hydro_river_atlas | -| ghs_pop_2015_54009_v2019a | ghs_pop_2015 | -| ghs_smod_2015_54009_v2019a | ghs_smod_2015 | -| glofas_era5_v31 | glofas_era5 | -| guf_bld_2012 | guf_bld_2012 | -| rivers_lin2019_v1 | hydro_rivers_lin2019 | -| SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | -| SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | -| vito | vito_2015 | -| vito_2015_v2.0.2 | vito_2015 | -| vito_2016_v3.0.1 | vito_2016 | -| vito_2017_v3.0.1 | vito_2017 | -| vito_2018_v3.0.1 | vito_2018 | -| vito_2019_v3.0.1 | vito_2019 | - -- Some datasets have multiple versions, for these datasets the default can be changed if you do not supply a version in your config file. See the table below for which dataset the default version has changed. - -| Dataset name | Default version | Previous default version | -|----------------|-----------------|--------------------------| -| eobs | 25.0e | 22.0e | -| eobs_orography | 25.0e | 22.0e | - - -### version 2024.1.30 - -#### added -- HydroMT version to catalog -- GRDC dataset - - -### version: 2023.12 - -#### changed -- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files -- removed gtsm_codec_reanalysis dataset - -#### added -- Added waterdemand pcr_globwb dataset -- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) - - -### version: 2023.2 - -#### changed -- convert GeoPackage files to FlatGeoBuf for cloud compatibility -- fix ERA5 nc files to read from archive of combined yearly and monthly files - -#### added -- Additional variables to era5 daily and hourly with name and unit conventions - - temp_dew: dewpoint temperature (degree C) - - wind10_u: 10m wind U-component (m s-1) - - wind10_v: 10m wind V-component (m s-1) - - ssr: surface net solar radiation (W m-2) - - tcc: total cloud cover (-) - - -### version: 2022.7 - -#### added - -- README with conventions regarding data (download, storage, .yml) -- change log file of deltares_data.yml -- new data sets - - basin_atlas_level12_v10 - - river_atlas_v10 - - lake_atlas_pol_v10 - - eobs_v24.0e - - eobs_v25.0e - - eobs_orography_v24.0e - - eobs_orography_v25.0e - - SM2RAIN_ASCAT_monthly_025_v1.4 - - SM2RAIN_ASCAT_monthly_05_v1.4 - -#### changed -- Apply convention specified in the README - - check reasonable alphabetical order in data sets and components - - implement right versioning convention _v where possible - - apply consistent meta information - -#### fixed -- enable versioning of yml.files - -## aws_data - -### version 0.0.9 - -#### changed -- updated source naming to match deltares_data version 2024.2 - -## cmip6_data - -### version: 2024.1.30 - -#### added -- hydromt_version to data catalog meta - - -### version: 2023.2 - -#### added -- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed - -## aws_data - -### version: 2024.1.30 - -#### added -- HydroMT version to catalog - -### version: 2023.2 - -#### added -- ESA Worldcover v100 2020. diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst new file mode 100644 index 000000000..0748c3a89 --- /dev/null +++ b/data/catalogs/changelog.rst @@ -0,0 +1,109 @@ +============================== +Change log predefined datasets +============================== + +deltares_data +============= + +version: 2024.1.30 +--------------- + +added +^^^^^ +- HydroMT version to catalog +- GRDC dataset + + +version: 2023.12 +----------------- + +changed +^^^^^^^ +- Updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files + +added +^^^^^ +- Added waterdemand pcr_globwb dataset +- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) + + +version: 2023.2 +---------------- + +changed +^^^^^^^ +- convert GeoPackage files to FlatGeoBuf for cloud compatibility +- fix ERA5 nc files to read from archive of combined yearly and monthly files + +added +^^^^^ +- Additional variables to era5 daily and hourly with name and unit conventions + - temp_dew: dewpoint temperature (degree C) + - wind10_u: 10m wind U-component (m s-1) + - wind10_v: 10m wind V-component (m s-1) + - ssr: surface net solar radiation (W m-2) + - tcc: total cloud cover (-) + + +version: 2022.7 +--------------- + +added +^^^^^ +- README with conventions regarding data (download, storage, .yml) +- change log file of deltares_data.yml +- new data sets + - basin_atlas_level12_v10 + - river_atlas_v10 + - lake_atlas_pol_v10 + - eobs_v24.0e + - eobs_v25.0e + - eobs_orography_v24.0e + - eobs_orography_v25.0e + - SM2RAIN_ASCAT_monthly_025_v1.4 + - SM2RAIN_ASCAT_monthly_05_v1.4 + +changed +^^^^^^^ +- Apply convention specified in the README + - check reasonable alphabetical order in data sets and components + - implement right versioning convention _v where possible + - apply consistent meta information + +fixed +^^^^^ +- enable versioning of yml.files + +cmip6_data +========== + +version: 2024.1.30 +--------------- + +added +^^^^^ +- HydroMT version to catalog + +version: 2023.2 +--------------- + +added +^^^^^ +- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed + +aws_data +======== + +version: 2024.1.30 +--------------- + +added +^^^^^ +- HydroMT version to catalog + +version: 2023.2 +--------------- + +added +^^^^^ +- ESA Worldcover v100 2020. diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index f017217dd..5dbeb7c49 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -1,15 +1,15 @@ --- meta: root: p:/wflow_global/hydromt - version: 2024.2 + version: 2024.1.30 hydromt_version: '>=0.9, <1.0' -hydro_basin_atlas_level12: +basin_atlas_level12_v10: crs: 4326 data_type: GeoDataFrame driver: vector - driver_kwargs: + kwargs: layer: BasinATLAS_v10_lev12 meta: category: hydrography @@ -18,19 +18,50 @@ hydro_basin_atlas_level12: paper_ref: Linke et al. (2019) source_license: CC BY 4.0 source_url: https://www.hydrosheds.org/hydroatlas - source_spatial_extent: - West: -180.0 - South: -55.988 - East: 180.001 - North: 83.626 - version: 10 + source_version: 10 path: hydrography/hydro_atlas/basin_atlas_v10.gpkg +river_atlas_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/river_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + +lake_atlas_pol_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + kwargs: + layer: LakeATLAS_v10_pol + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + chelsa: + alias: chelsa_v1.2 +chelsa_v1.2: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -40,19 +71,16 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 84.0 - version: 1.2 + source_version: 1.2 path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif chirps: + alias: chirps_africa_daily_v2.0 +chirps_africa_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: lat: 160 lon: 150 @@ -66,15 +94,7 @@ chirps: paper_ref: Funk et al (2015) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_temporal_extent: - start: '1981-01-02' - end: '2022-04-01' - source_spatial_extent: - West: -20.0 - South: -40.0 - East: 55.0 - North: 40.0 - version: 2.0 + source_version: v2.0 path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc rename: precipitation: precip @@ -82,10 +102,12 @@ chirps: time: 86400 chirps_global: + alias: chirps_global_daily_v2.0 +chirps_global_daily_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 112 longitude: 400 @@ -99,15 +121,7 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_temporal_extent: - start: '1981-01-02' - end: '2023-02-01' - source_spatial_extent: - West: -180.0 - South: -50.0 - East: 180.0 - North: 50.0 - version: 2.0 + source_version: v2.0 path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc rename: precipitation: precip @@ -115,74 +129,67 @@ chirps_global: time: 86400 copdem30: + alias: copdem30_v2021.1 +copdem30_v2021.1: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_spatial_extent: - West: -180.001 - South: -90.0 - East: 180.0 - North: 84.0 - version: 2021.1 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: '2021_1' + nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem.vrt - nodata: -9999 rename: copdem: elevtn copdem30_mask: + alias: copdem30_mask_v2021.1 +copdem30_mask_v2021.1: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_spatial_extent: - West: -180.001 - South: -90.0 - East: 180.0 - North: 84.0 - version: 2021.1 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: '2021_1' + nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem_mask.vrt - nodata: -1 rename: copdem_mask: mask copdem30_masked: + alias: copdem30_masked_v2021.1 +copdem30_masked_v2021.1: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 meta: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/guest/collections/copernicus-digital-elevation-model?p_l_back_url=%2Fweb%2Fguest%2Fsearch%3Fq%3Ddemhttps://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_spatial_extent: - West: -180.001 - South: -90.0 - East: 180.0 - North: 84.0 - version: 2021.1 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: '2021_1' path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn corine: + alias: corine_2018_v2020_u1 +corine_2018_v2020_u1: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 6000 y: 6000 @@ -191,20 +198,14 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_spatial_extent: - West: 900000.0 - South: 900000.0 - East: 7400000.0 - North: 5500000.0 - provider: local - version: 2020_20u1 + source_version: v.2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif dtu10mdt: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -213,20 +214,15 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 unit: m+EGM2008 - source_spatial_extent: - West: -179.992 - South: -89.992 - East: 179.992 - North: 89.992 - version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_float32.tif dtu10mdt_egm96: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -235,22 +231,17 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - processing_notes: /topography/dtu10mdt/READ_ME.txt - processing_script: /topography/dtu10mdt/DTU10MDT_egm96_1min.ipynb + source_version: 2010 unit: m+EGM96 - source_spatial_extent: - West: -179.992 - South: -89.985 - East: 179.995 - North: 89.992 - version: 2010 path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif eobs: + alias: eobs_v22.0e +eobs_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 100 longitude: 100 @@ -264,43 +255,8 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_temporal_extent: - start: '1950-01-02' - end: '2022-01-01' - source_spatial_extent: - West: -25.0 - South: 25.0 - East: 45.5 - North: 71.5 - variants: - - version: 22.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - meta: - source_temporal_extent: - start: '1950-01-02' - end: '2020-07-01' - - version: 23.1e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - meta: - source_temporal_extent: - start: '1950-01-02' - end: '2021-01-01' - - version: 24.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - meta: - processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py - processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables - source_temporal_extent: - start: '1950-01-02' - end: '2021-07-01' - - version: 25.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc - meta: - processing_script: v25.0e_fix_qq_dims_and_match_extent.py - processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables - source_temporal_extent: - start: '1950-01-02' - end: '2022-01-01' + source_version: 22.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc rename: pp: press_msl qq: kin @@ -309,11 +265,116 @@ eobs: unit_add: time: 86400 +eobs_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_orography_v20.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + rename: + elevation: elevtn + eobs_orography: + alias: eobs_orography_v22.0e +eobs_orography_v22.0e: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 100 longitude: 100 @@ -323,30 +384,75 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_spatial_extent: - West: -25.0 - South: 25.0 - East: 45.5 - North: 71.5 - variants: - - version: 20.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - - version: 22.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - - version: 23.1e - path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - - version: 24.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - - version: 25.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + source_version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + rename: + elevation: elevtn + +eobs_orography_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + rename: + elevation: elevtn + +eobs_orography_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + rename: + elevation: elevtn + +eobs_orography_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc rename: elevation: elevtn era5: + alias: era5_daily +era5_daily: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 250 longitude: 240 @@ -356,22 +462,13 @@ era5: parallel: true meta: category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to - daily frequency using right label for time. + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) - processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_temporal_extent: - start: '1950-01-02' - end: '2023-11-30' - source_spatial_extent: - West: -0.125 - South: -90.125 - East: 359.875 - North: 90.125 - path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc + source_version: ERA5 daily data on pressure levels + path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc rename: d2m: temp_dew msl: press_msl @@ -395,35 +492,19 @@ era5: press_msl: 0.01 era5_daily_zarr: + alias: era5_daily crs: 4326 data_type: RasterDataset driver: zarr - driver_kwargs: + kwargs: chunks: auto - meta: - category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to - daily frequency - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. (2019) - processing_script: https://github.com/Deltares/hydromt/blob/main/data/src/era5_download_resample_convert.py - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://doi.org/10.24381/cds.bd0915c6 - source_temporal_extent: - start: '1950-01-02' - end: '2023-02-01' - source_spatial_extent: - West: -0.125 - South: -90.125 - East: 359.875 - North: 90.125 path: meteo/era5_daily.zarr era5_hourly: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 125 longitude: 120 @@ -438,15 +519,8 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.adbb2d47 - source_temporal_extent: - start: '1950-01-01' - end: '2023-03-01' - source_spatial_extent: - West: -0.125 - South: -90.125 - East: 359.875 - North: 90.125 - path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc + source_version: ERA5 hourly data on single levels from 1940 to present + path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc rename: d2m: temp_dew msl: press_msl @@ -467,34 +541,19 @@ era5_hourly: press_msl: 0.01 era5_hourly_zarr: + alias: era5_hourly crs: 4326 data_type: RasterDataset driver: zarr - driver_kwargs: + kwargs: chunks: auto - meta: - category: meteo - notes: Extracted from Copernicus Climate Data Store - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. (2019) - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://doi.org/10.24381/cds.adbb2d47 - processing_script: meteo/era5_zarr/scripts/ - source_temporal_extent: - start: '1950-01-01' - end: '2023-02-01' - source_spatial_extent: - West: -0.125 - South: -90.125 - East: 359.875 - North: 90.125 path: meteo/era5.zarr era5_ocean: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 60 longitude: 60 @@ -509,21 +568,13 @@ era5_ocean: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_temporal_extent: - start: '1979-01-01' - end: '2022-04-08' - source_spatial_extent: - West: -0.25 - South: -90.25 - East: 359.75 - North: 90.25 path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc era5_orography: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 120 longitude: 125 @@ -534,14 +585,6 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 - source_temporal_extent: - start: '2018-01-01' - end: '2018-01-01' - source_spatial_extent: - West: -0.125 - South: -90.125 - East: 359.875 - North: 90.125 path: meteo/era5/meta/era5_orography_2018.nc rename: z: elevtn @@ -549,31 +592,27 @@ era5_orography: elevtn: 0.10197162129779283 esa_worldcover: + alias: esa_worldcover_2020_v100 +esa_worldcover_2020_v100: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 36000 y: 36000 meta: category: landuse - processing_notes: prepare vrt file with gdalbuildvrt source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.5571936 - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 84.0 - version: 100 + source_version: v100 path: landuse/esa_worldcover/esa-worldcover.vrt fabdem: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -583,16 +622,14 @@ fabdem: paper_ref: Hawker et al. (2022) source_license: CC BY-NC-SA 4.0 source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 1.0 + source_version: 1.0 path: topography/fabdem/fabdem.vrt rename: fabdem: elevtn +gadm: + alias: gadm_level0 + gadm_level0: crs: 4326 data_type: GeoDataFrame @@ -603,13 +640,8 @@ gadm_level0: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html + source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.658 - version: 4.1 path: geography/gadm/version4_1/gadm_level0.fgb gadm_level1: @@ -622,13 +654,8 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html + source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.658 - version: 4.1 path: geography/gadm/version4_1/gadm_level1.fgb gadm_level2: @@ -641,13 +668,8 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html + source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.658 - version: 4.1 path: geography/gadm/version4_1/gadm_level2.fgb gadm_level3: @@ -660,19 +682,16 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html + source_version: 4.1 processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.658 - version: 4.1 path: geography/gadm/version4_1/gadm_level3.fgb gcn250: + alias: gcn250_v1 +gcn250_v1: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -682,13 +701,8 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_spatial_extent: - West: -180.0 - South: -56.0 - East: 180.0 - North: 84.0 + source_version: v1 nodata: 255 - version: 1 path: landuse/gcn250/GCN250_*.tif rename: GCN250_ARCI: cn_dry @@ -696,21 +710,17 @@ gcn250: GCN250_ARCIII: cn_wet gdp_world: + alias: gdp_world_v1 +gdp_world_v1: crs: 4326 data_type: GeoDataFrame driver: vector meta: category: socio-economic - processing_notes: data combined by Deltares (Wilfred Altena) from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) - and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_author: Wilfred Altena source_license: CC BY-4.0 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.665 - version: 1.0 + source_version: 1.0 path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb rename: GDP: gdp @@ -718,10 +728,12 @@ gdp_world: gdp: 0.001 gebco: + alias: gebco_v2020 +gebco_v2020: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -730,24 +742,20 @@ gebco: paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 - source_url: https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data/ + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 unit: m+MSL - processing_script: bathymetry/gebco/gebco_tiles.ipynb - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 2020 path: bathymetry/gebco/gebco.vrt rename: gebco: elevtn -ghs_pop_2015: +ghs_pop: + alias: ghs_pop_2015_54009_v2019a +ghs_pop_2015_4326_v2019a: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -758,19 +766,14 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_spatial_extent: - West: -180.0 - South: -59.485 - East: 180.0 - North: 83.628 - version: R2019A_v1.0 + source_version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif -ghs_pop_2015_54009: - crs: ESRI:54009 +ghs_pop_2015_54009_v2019a: + crs: "ESRI:54009" data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 1000 y: 1000 @@ -780,49 +783,52 @@ ghs_pop_2015_54009: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop - source_spatial_extent: - West: -18041000.0 - South: -9000000.0 - East: 18041000.0 - North: 9000000.0 - version: R2019A_v1.0 path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif -ghs_smod_2015: - crs: ESRI:54009 +ghs_smod: + alias: ghs_smod_2015_54009_v2019a +ghs_smod_2015_54009_v2016a: + crs: "ESRI:54009" data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 meta: category: socio-economic + paper_ref: Pesaresi and Freire (2016) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_spatial_extent: - West: -18041000.0 - South: -9000000.0 - East: 18041000.0 - North: 9000000.0 - variants: - - version: R2016A_v1.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - meta: - paper_ref: Pesaresi and Freire (2016) - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - - version: R2019A_v2.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif - meta: - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + +ghs_smod_2015_54009_v2019a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif globcover: + alias: globcover_2009_v2.3 +globcover_2009_v2.3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -832,19 +838,14 @@ globcover: paper_ref: Arino et al (2012) source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php - source_spatial_extent: - West: -180.001 - South: -64.999 - East: 179.999 - North: 90.001 - version: 2.3 + source_version: v2.3 path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif -glofas_era5: +glofas_era5_v31: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: time: 180 latitude: 150 @@ -859,75 +860,51 @@ glofas_era5: paper_ref: Harrigan et al. (2020) source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf source_url: https://doi.org/10.24381/cds.a4fdd6b9 - processing_script: hydro/glofas_era5/glofas_cds_get.py - source_temporal_extent: - start: '1980-01-01' - end: '2021-05-31' - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 90.0 - version: 31 + source_version: v31 path: hydro/glofas_era5/glofas_v31_{year}.nc rename: dis24: discharge glofas_uparea: - data_type: RasterDataset + alias: glofas_era5_v31 driver: raster - driver_kwargs: + kwargs: chunks: x: 150 y: 360 - meta: - category: hydro - notes: Extracted from Copernicus Climate Data Store - paper_doi: 10.5194/essd-12-2043-2020 - paper_ref: Harrigan et al. (2020) - source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf - source_url: https://doi.org/10.24381/cds.a4fdd6b9 - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 90.0 - version: 31 path: hydro/glofas_era5/glofas_v31_uparea.tif rename: glofas_v31_uparea: uparea unit_mult: - uparea: 1.0e-06 + uparea: 0.000001 glw_buffaloes: + alias: glw_buffaloes_v3 +glw_buffaloes_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 meta: category: socio-economic - notes: last downloaded 2020-06-11 paper_doi: 10.7910/DVN/5U8MWI paper_ref: Gilbert at al (2018) source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Bf_2010_Da.tif glw_cattle: + alias: glw_cattle_v3 +glw_cattle_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -938,19 +915,16 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Ct_2010_Da.tif glw_chicken: + alias: glw_chicken_v3 +glw_chicken_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -961,19 +935,16 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Ch_2010_Da.tif glw_ducks: + alias: glw_ducks_v3 +glw_ducks_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -984,19 +955,16 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Dk_2010_Da.tif glw_goats: + alias: glw_goats_v3 +glw_goats_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1007,19 +975,16 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Gt_2010_Da.tif glw_horses: + alias: glw_horses_v3 +glw_horses_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1030,19 +995,16 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Ho_2010_Da.tif glw_pigs: + alias: glw_pigs_v3 +glw_pigs_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1053,19 +1015,16 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Pg_2010_Da.tif glw_sheeps: + alias: glw_sheeps_v3 +glw_sheeps_v3: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1076,19 +1035,15 @@ glw_sheeps: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 3 + source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Sh_2010_Da.tif + grdc: crs: 4326 data_type: GeoDataFrame driver: csv - driver_kwargs: + kwargs: index_col: grdc_no meta: category: observed data @@ -1100,6 +1055,8 @@ grdc: area: uparea grip_roads: + alias: grip_roads_v4 +grip_roads_v4: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1109,19 +1066,15 @@ grip_roads: paper_ref: Meijer et al, 2018 paper_doi: 10.1088/1748-9326/aabd42 source_license: CC0-1.0 - processing_script: infrastructure/grip/merge.ipynb - source_spatial_extent: - West: -179.999 - South: -55.055 - East: 180.0 - North: 73.836 - version: 4 + source_version: v4 path: infrastructure/grip/GRIP4_world.fgb rename: GP_RTP: road_type GP_RCY: country_code grwl: + alias: grwl_v1.01 +grwl_v1.01: data_type: GeoDataFrame driver: vector meta: @@ -1130,22 +1083,19 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_spatial_extent: - West: -180.0 - South: -54.31 - East: 180.0 - North: 82.311 - version: 1.01 + source_version: 1.01 path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb grwl_mask: + alias: grwl_mask_v1.01 +grwl_mask_v1.01: data_type: RasterDataset driver: raster_tindex - driver_kwargs: + kwargs: chunks: x: 3000 y: 3000 - mosaic_driver_kwargs: + mosaic_kwargs: method: nearest tileindex: location meta: @@ -1154,14 +1104,16 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 nodata: 0 - version: 1.01 path: hydrography/grwl/tindex.gpkg gswo: + alias: gswo_v2019 +gswo_v2019: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 4000 y: 4000 @@ -1170,20 +1122,40 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 + source_version: v1_1_2019 nodata: 255 - version: 1.1 path: hydrography/gswo/occur.vrt +gtsm_codec_reanalysis_{freq}_v1: + crs: 4326 + data_type: GeoDataset + driver: netcdf + kwargs: + chunks: + stations: 10 + time: -1 + meta: + category: ocean + paper_doi: 10.3389/fmars.2020.00263 + paper_ref: Muis at al (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf + source_url: https://doi.org/10.24381/cds.8c59054f + source_version: v1 + path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc + placeholders: + freq: [10min, hourly, dailymax] + rename: + station_x_coordinate: lon + station_y_coordinate: lat + stations: index + guf_bld_2012: + alias: guf_bld_2012_v02 +guf_bld_2012_v02: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 1000 y: 1000 @@ -1193,12 +1165,6 @@ guf_bld_2012: paper_ref: Esch et al (2017) source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf - source_spatial_extent: - West: -180.0 - South: -65.0 - East: 180.0 - North: 85.0 - version: 2 path: infrastructure/guf/GUF04_DLR_v02.vrt hydro_lakes: @@ -1207,14 +1173,9 @@ hydro_lakes: driver: vector meta: category: surface water - processing_notes: extract of hydrolakes to only include natural lakes and exclude reservoirs and control lakes (ie filter on Lake_type = 1) - source_author: HydroSHEDS - source_spatial_extent: - West: -180.0 - South: -55.865 - East: 180.0 - North: 83.576 - version: 1.0 + notes: HydroLAKES.v10_extract + source_author: Arjen Haag + source_version: 1.0 path: hydrography/lakes/lake-db.fgb rename: Depth_avg: Depth_avg @@ -1235,13 +1196,8 @@ hydro_reservoirs: category: surface water notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 source_author: Alessia Matano - source_spatial_extent: - West: -153.059 - South: -45.881 - East: 176.825 - North: 70.396 + source_version: 1.0 nodata: -99 - version: 1.0 path: hydrography/reservoirs/reservoir-db.fgb rename: Depth_avg: Depth_avg @@ -1267,7 +1223,7 @@ koppen_geiger: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1276,43 +1232,15 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 + source_version: 2017 nodata: 0 - version: 2017 path: meteo/climate_classification_v2017/Map_KG-Global.tif -hydro_lake_atlas_pol: - crs: 4326 - data_type: GeoDataFrame - driver: vector - driver_kwargs: - layer: LakeATLAS_v10_pol - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-022-01425-z - paper_ref: Lehner et al. (2022) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_spatial_extent: - West: -180.0 - South: -55.865 - East: 180.0 - North: 83.576 - path: hydrography/hydro_atlas/lake_atlas_v10.gpkg - version: 10 - rename: - dis_m3_pyr: Dis_avg - mdt_cnes_cls18: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 720 y: 720 @@ -1321,21 +1249,17 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 unit: m+GOCO05S - processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 18 path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif merit: + alias: merit_v1.0.3 +merit_v1.0.3: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: drop_variables: projection chunks: lat: 6000 @@ -1346,21 +1270,18 @@ merit: paper_ref: Yamazaki et al. (2018) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 1.0.3 + source_version: 1.0.3 path: topography/merit/merit.nc rename: elevation: elevtn merit_hydro: + alias: merit_hydro_v1.0 +merit_hydro_v1.0: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 6000 y: 6000 @@ -1368,16 +1289,9 @@ merit_hydro: category: topography paper_doi: 10.1029/2019WR024873 paper_ref: Yamazaki et al. (2019) - processing_notes: create vrt file with gdalbuildvrt; - additional variables for stream-order, basin index (basins), and slope (lndslp) derived with pyflwdir source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 85.0 - version: 1.0 + source_version: 1.0 path: topography/merit_hydro/*.vrt rename: bas: basins @@ -1390,10 +1304,12 @@ merit_hydro: wth: rivwth merit_hydro_ihu: + alias: merit_hydro_ihu_30sec_v1.0 +merit_hydro_ihu_30sec_v1.0: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 6000 y: 6000 @@ -1404,14 +1320,8 @@ merit_hydro_ihu: source_license: ODC-By 1.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk source_doi: 10.5281/zenodo.5166932 - processing_notes: topography/merit_hydro_ihu/README - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 85.0 + source_version: 1.0 path: topography/merit_hydro_ihu/30sec/*.tif - version: 1.0 rename: 30sec_basids: basins 30sec_flwdir: flwdir @@ -1431,16 +1341,11 @@ merit_hydro_ihu_index: paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk - processing_notes: topography/merit_hydro_ihu/README - source_spatial_extent: - West: -180.025 - South: -59.467 - East: 190.35 - North: 83.683 - version: 1.0 path: topography/merit_hydro_ihu/30sec/basins.gpkg merit_hydro_index: + alias: merit_hydro_index_v1.0 +merit_hydro_index_v1.0: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1449,19 +1354,15 @@ merit_hydro_index: paper_doi: 10.5194/hess-25-5287-2021 paper_ref: Eilander et al. (2021) source_license: CC-BY-NC 4.0 - source_spatial_extent: - West: -180.028 - South: -59.46 - East: 190.338 - North: 83.661 - version: 1.0 path: topography/merit_hydro/basin_index.fgb merit_hydro_patch: + alias: merit_hydro_patch_v1.0 +merit_hydro_patch_v1.0: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 6000 y: 6000 @@ -1471,14 +1372,7 @@ merit_hydro_patch: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - processing_script: topography/merit_hydro/patches/scripts - processing_notes: local corrections of flow direction raster and re-derive the related maps (basins, uparea, strord) - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 85.0 - version: 1.0 + source_version: 1.0 Deltares patch path: topography/merit_hydro/patches/*.vrt rename: bas: basins @@ -1491,36 +1385,31 @@ merit_hydro_patch: wth: rivwth modis_lai: + alias: modis_mcd15a3h_v006 +modis_mcd15a3h_v006: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 concat: true meta: category: landuse + notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - processing_notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') - for the period '2003-01-01', '2017-12-31' - processing_script: - GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js - merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py - source_spatial_extent: - West: -180.004 - South: -90.002 - East: 180.004 - North: 90.002 - version: MCD15A3H V006 + source_version: MCD15A3H V006 path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: LAI: 0.1 osm_coastlines: + alias: osm_coastlines_v20200109 +osm_coastlines_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1530,17 +1419,14 @@ osm_coastlines: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_spatial_extent: - West: -180.0 - South: -78.733 - East: 180.0 - North: 90.0 - version: 1.0 + source_version: 1.0 path: geography/osm/osm_coastlines-db.fgb rename: fid: coastline_id osm_landareas: + alias: osm_landareas_v20200109 +osm_landareas_v20200109: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1550,12 +1436,7 @@ osm_landareas: source_author: OpenStreetMap source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 83.666 - version: 1.0 + source_version: 1.0 path: geography/osm/osm_landareas-db.fgb rename: fid: land_id @@ -1572,12 +1453,8 @@ pcr_globwb: paper_doi: 10.5281/zenodo.1045339 paper_ref: Sutanudjaja, E. H., et al (2017) source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR + source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 variants: - version: 1990 path: hydro/pcr_globwb/glob_1990.zarr @@ -1604,6 +1481,8 @@ pcr_globwb: lsk_gross: 1000 rgi: + alias: rgi_v0.6 +rgi_v0.6: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1614,12 +1493,7 @@ rgi: paper_ref: Pfeffer et al. (2014) source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_spatial_extent: - West: -179.921 - South: -78.309 - East: 179.751 - North: 83.608 - version: 6.0 + source_version: 6.0 path: hydrography/rgi/rgi.fgb rename: C3S_ID: C3S_id @@ -1627,28 +1501,7 @@ rgi: ID: simple_id RGIID: RGI_id -hydro_river_atlas: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_spatial_extent: - West: -179.998 - South: -55.877 - East: 179.998 - North: 83.59 - path: hydrography/hydro_atlas/river_atlas_v10.gpkg - version: 10 - rename: - dis_m3_pyr: Dis_avg - -hydro_rivers_lin2019: +rivers_lin2019_v1: data_type: GeoDataFrame driver: vector meta: @@ -1657,23 +1510,19 @@ hydro_rivers_lin2019: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - processing_notes: hydrography/rivers_lin2019/README - source_spatial_extent: - West: -177.204 - South: -55.414 - East: 180.237 - North: 82.112 - version: 1 + source_version: 1 path: hydrography/rivers_lin2019/rivers_ge30m.fgb rename: width_m: rivwth Q2: qbankfull simard: + alias: simard_v2011 +simard_v2011: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1682,103 +1531,69 @@ simard: paper_doi: 10.1029/2011JG001708 paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 2011 path: landuse/simard/sdat_10023_canopy_height_simard.tif -SM2RAIN_ASCAT_monthly_025: +SM2RAIN_ASCAT_monthly_025_v1.4: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 360 longitude: 720 time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, - 0.25-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - source_temporal_extent: - start: '2007-01-01' - end: '2020-12-01' - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc rename: rainfall: precip -SM2RAIN_ASCAT_monthly_05: +SM2RAIN_ASCAT_monthly_05_v1.4: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: latitude: 180 longitude: 360 time: 84 meta: category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, - 0.5-degree resolution + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution paper_doi: 10.5194/essd-11-1583-2019 paper_ref: Brocca et al. (2019) source_license: https://creativecommons.org/licenses/by/4.0/legalcode source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - source_temporal_extent: - start: '2007-01-01' - end: '2020-12-01' - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 1.4 path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc rename: rainfall: precip soilgrids: + alias: soilgrids_v1.0 +soilgrids_v1.0: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 2400 y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ - \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ - \ distribution version 2.0, european commission and the European soil bureau\n\ - \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ - \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ - \ Response to european policy support and public data requirements. Land\ - \ Use Policy 29 (2), 329\xC3\xA2\xE2\u201A\xAC\xE2\u20AC\u0153338. \n" + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" paper_doi: 10.1371/journal.pone.0169748 paper_ref: Hengl et al. (2017) source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-201 - processing_notes: "soilthickness is based on 1) soilgrids (global, depth to bedrock - BDRICM variable) and 2) dataset for Eurasia" - processing_script: p:/wflow_global/static_data/wflow_sbm_parameters/ - source_spatial_extent: - West: -19949000.0 - South: -6147500.0 - East: 19861750.0 - North: 8361000.0 - version: 1.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 path: soil/soilgrids_v1.0/*_250m_ll.tif rename: BLDFIE_M_sl1_250m_ll: bd_sl1 @@ -1848,11 +1663,117 @@ soilgrids: ph_sl6: 0.1 ph_sl7: 0.1 -vito_2015: +soilgrids_2020: + alias: soilgrids_v2.0 +soilgrids_v2.0: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + source_version: 2020 + path: soil/soilgrids_v2.0/*/*_mean.vrt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 + +vito: + alias: vito_2015_v2.0.2 +vito_2015_v2.0.2: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1861,19 +1782,14 @@ vito_2015: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 2.0.2 + source_version: v2.0.2 path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif -vito_2016: +vito_2016_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1882,19 +1798,14 @@ vito_2016: paper_doi: 10.5281/zenodo.3518026 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 3.0.1 + source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2017: +vito_2017_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1903,19 +1814,14 @@ vito_2017: paper_doi: 10.5281/zenodo.3518036 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 3.0.1 + source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2018: +vito_2018_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1924,19 +1830,14 @@ vito_2018: paper_doi: 10.5281/zenodo.3518038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 3.0.1 + source_version: v3.0.1 path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif -vito_2019: +vito_2019_v3.0.1: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 3600 y: 3600 @@ -1945,15 +1846,12 @@ vito_2019: paper_doi: 10.5281/zenodo.3939050 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 3.0.1 + source_version: v3.0.1 path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif wb_countries: + alias: wb_countries_v20200319 +wb_countries_v20200319: crs: 4326 data_type: GeoDataFrame driver: vector @@ -1963,12 +1861,6 @@ wb_countries: source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries source_license: CC-BY 4.0 timestamp: February 2020 - source_spatial_extent: - West: -180.0 - South: -59.473 - East: 180.0 - North: 83.634 - version: 20200319 path: geography/wb/WB_countries_Admin0.fgb rename: ISO_A3: country_iso @@ -1980,10 +1872,12 @@ wb_countries: gdp_pc: 1000 worldclim: + alias: worldclim_v2.0 +worldclim_v2.0: crs: 4326 data_type: RasterDataset driver: netcdf - driver_kwargs: + kwargs: chunks: lat: 3600 lon: 3600 @@ -1992,13 +1886,8 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 nodata: -999.0 - source_spatial_extent: - West: -180.0 - South: -90.0 - East: 180.0 - North: 90.0 - version: 2.0 path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc rename: prec: precip @@ -2006,7 +1895,7 @@ worldclim: worldpop_2020_constrained: data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: auto meta: category: socio-economic @@ -2014,38 +1903,24 @@ worldpop_2020_constrained: paper_ref: Stevens et al. (2015) source_license: CC BY 4.0 source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 - processing_script: socio_economic/worldpop/src/ - source_spatial_extent: - West: -180.0 - South: -55.985 - East: 180.0 - North: 83.628 nodata: -99999 path: socio_economic/worldpop/ppp_2020_constrained.vrt rename: ppp_2020_constrained: population worldpop_2020_UNadj_constrained: - data_type: RasterDataset - driver: raster - driver_kwargs: - chunks: auto - meta: - processing_script: socio_economic/worldpop/src/ - source_spatial_extent: - West: -180.0 - South: -55.985 - East: 180.0 - North: 83.628 + alias: worldpop_2020_constrained path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt rename: ppp_2020_UNadj_constrained: population wsf_bld_2015: + alias: wsf_bld_2015_v1 +wsf_bld_2015_v1: crs: 4326 data_type: RasterDataset driver: raster - driver_kwargs: + kwargs: chunks: x: 1000 y: 1000 @@ -2055,10 +1930,4 @@ wsf_bld_2015: paper_ref: Marconcini at al (2020) source_license: CC0 1.0 source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc - source_spatial_extent: - West: -180.0 - South: -60.0 - East: 180.0 - North: 80.0 - version: 1 path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index c96d9eadd..f7cae9857 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -16,8 +16,7 @@ deltares_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/deltares_data.yml versions: - v2024.2: main - v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 + v2024.1.30: main v2023.12.21: 392206b21b26e62e00ae76db7ffc61a3b95e2175 v2023.12.19: bf25e79dcbda67612a75588cd782d57abe3881de v2023.2: 0bf8e2a1e716095dc6df54a5e9114ce88da0701b @@ -37,8 +36,9 @@ aws_data: v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: - urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/artifact_data.yml + urlpath: https://github.com/DirkEilander/hydromt-artifacts/releases/download/{version}/data.tar.gz versions: - v0.0.9: main - v0.0.8: 202874eb4fe3415d0608ea81cd61620af6f5816a + v0.0.8: v0.0.8 + v0.0.7: v0.0.7 + v0.0.6: v0.0.6 notes: This data archive contains a sample dataset for the Piave basin (North Italy) to be used for tests and docs/demo purposes. diff --git a/docs/changelog.rst b/docs/changelog.rst index 645b1320b..db57a3c72 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -37,11 +37,6 @@ Added - Test script for testing predefined catalogs locally. (#735) - Option to write a data catalog to a csv file (#425) -Changed -------- -- Datacatalog preserves variant specific meta data (#521) -- Updated DataCatalogValidator to deal with provider and driver_kwargs (#521) - Fixed ----- - Reading Vector formats that consist of more than one file via geopandas. (#691) @@ -50,7 +45,6 @@ Fixed - Fix bug in `raster._check_dimensions` for datasets with multiple variables with varying dimension size (#761) - Fix bug when reading COGs at requested zoom level (#758) - v0.9.2 (2024-01-09) =================== This release adds additional bug fixes for the meridian offset functinality, and improvements to the new CLI commands. @@ -61,11 +55,9 @@ Added - New stats.skills VE and RSR (#666) - Check CLI command can now validate bbox and geom regions (#664) - Changed ------- - Export CLI now uses '-s' for source, '-t' for time and '-i' for config. (#660) -- Updated deltares_data data catalog to incorporate the newest data catalog features (#667) Fixed ----- diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index 17b245fdc..e674c76dc 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -33,7 +33,8 @@ "source": [ "import numpy as np\n", "import geopandas as gpd\n", - "from shapely.geometry import box" + "from shapely.geometry import box\n", + "from pprint import pprint" ] }, { @@ -377,7 +378,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.10.8" }, "vscode": { "interpreter": { diff --git a/examples/prep_data_catalog.ipynb b/examples/prep_data_catalog.ipynb index 9f1d16fdd..c74066a24 100644 --- a/examples/prep_data_catalog.ipynb +++ b/examples/prep_data_catalog.ipynb @@ -64,7 +64,7 @@ "outputs": [], "source": [ "# this download the artifact_data archive v0.0.6\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"])\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.6\"])\n", "pprint(data_catalog.predefined_catalogs)" ] }, @@ -85,7 +85,7 @@ "outputs": [], "source": [ "# the artifact data is stored in the following location\n", - "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.8\")\n", + "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.6\")\n", "# let's print some of the file that are there\n", "for item in os.listdir(root)[-10:]:\n", " print(item)" diff --git a/hydromt/data_adapter/data_adapter.py b/hydromt/data_adapter/data_adapter.py index 2ea21731e..9c9314974 100644 --- a/hydromt/data_adapter/data_adapter.py +++ b/hydromt/data_adapter/data_adapter.py @@ -334,13 +334,9 @@ def _resolve_paths( continue key_str = "{" + f"{key}:{fmt}" + "}" if fmt else "{" + key + "}" # remove unused fields - if ( - key in ["year", "month"] - and time_tuple is None - and not path.endswith("*") - ): + if key in ["year", "month"] and time_tuple is None: path += "*" - elif key == "variable" and variables is None and not path.endswith("*"): + elif key == "variable" and variables is None: path += "*" # escape unknown fields elif key is not None and key not in known_keys: diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index d306daf23..9402c31d3 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -1913,9 +1913,6 @@ def _denormalise_data_dict(data_dict) -> List[Tuple[str, Dict]]: variants = source.pop("variants") for diff in variants: source_copy = copy.deepcopy(source) - if "meta" in source_copy: - # Update meta if variant has variant specific meta data - source_copy["meta"].update(diff.pop("meta", {})) source_copy.update(**diff) data_dicts.append({name: source_copy}) elif "placeholders" in source: diff --git a/hydromt/validators/data_catalog.py b/hydromt/validators/data_catalog.py index 9e6391146..a5592d314 100644 --- a/hydromt/validators/data_catalog.py +++ b/hydromt/validators/data_catalog.py @@ -111,9 +111,7 @@ class DataCatalogItem(BaseModel): path: Optional[Path] = None crs: Optional[Union[int, str]] = None filesystem: Optional[str] = None - provider: Optional[str] = None - driver_kwargs: Dict[str, Any] = Field(default_factory=dict) - kwargs: Dict[str, Any] = Field(default_factory=dict) # deprecated + kwargs: Dict[str, Any] = Field(default_factory=dict) storage_options: Dict[str, Any] = Field(default_factory=dict) placeholders: Optional[Dict[str, Any]] = None rename: Dict[str, str] = Field(default_factory=dict) diff --git a/tests/data/merged_esa_worldcover.yml b/tests/data/merged_esa_worldcover.yml index 88143b1b1..7f7778587 100644 --- a/tests/data/merged_esa_worldcover.yml +++ b/tests/data/merged_esa_worldcover.yml @@ -18,8 +18,6 @@ esa_worldcover: - provider: local version: 2020 path: landuse/esa_worldcover/esa-worldcover.vrt - meta: - source_author: Test Dummy - provider: aws version: 2020 path: s3://esa-worldcover/v100/2020/ESA_WorldCover_10m_2020_v100_Map_AWS.vrt diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 8682982ae..958ffb97a 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -195,12 +195,6 @@ def test_versioned_catalog_entries(tmpdir): # test round trip to and from dict merged_catalog2 = DataCatalog().from_dict(merged_catalog.to_dict()) assert merged_catalog2 == merged_catalog - # test updating source meta data from version meta data - source_2020_local = merged_catalog.get_source( - "esa_worldcover", version="2020", provider="local" - ) - assert source_2020_local.meta["source_author"] == "Test Dummy" - assert source_2020_local.meta["source_license"] == "CC BY 4.0" # Make sure we can query for the version we want aws_and_legacy_catalog = DataCatalog(data_libs=[legacy_yml_fn, aws_yml_fn]) @@ -594,12 +588,12 @@ def test_get_dataframe(df, tmpdir): def test_deprecation_warnings(artifact_data): with pytest.deprecated_call(): - # should be DataCatalog(data_libs=['v0.0.8']) - DataCatalog(artifact_data="v0.0.8") + # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) + DataCatalog(artifact_data="v0.0.6") with pytest.deprecated_call(): cat = DataCatalog() - # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.8') - cat.from_artifacts("artifact_data", version="v0.0.8") + # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') + cat.from_artifacts("artifact_data", version="v0.0.6") with pytest.deprecated_call(): fn = artifact_data["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) From 3f1445f4d366faaac73cea74a54081364d2e5e69 Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Wed, 6 Mar 2024 19:21:32 +0100 Subject: [PATCH 062/110] add data catalog versions and data variants to docs --- docs/conf.py | 90 ++------------ docs/parse_predefined_catalogs.py | 162 ++++++++++++++++++++++++++ docs/user_guide/data_existing_cat.rst | 82 ++++++++++++- docs/user_guide/hydromt_cli.rst | 2 +- pixi.toml | 80 +++++++++++-- 5 files changed, 323 insertions(+), 93 deletions(-) create mode 100644 docs/parse_predefined_catalogs.py diff --git a/docs/conf.py b/docs/conf.py index 7a5d551b4..2dd6193b0 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -20,13 +20,14 @@ import shutil from distutils.dir_util import copy_tree -import numpy as np import sphinx_autosummary_accessors from click.testing import CliRunner import hydromt from hydromt.cli.main import main as hydromt_cli +from docs.parse_predefined_catalogs import write_predefined_catalogs_to_rst_panels + os.environ["PYDEVD_DISABLE_FILE_VALIDATION"] = "1" @@ -46,58 +47,6 @@ def remove_dir_content(path: str) -> None: if os.path.isdir(path): shutil.rmtree(path) - -def write_panel(f, name, content="", level=0, item="dropdown"): - pad = "".ljust(level * 3) - f.write(f"{pad}.. {item}:: {name}\n") - f.write("\n") - if content: - pad = "".ljust((level + 1) * 3) - for line in content.split("\n"): - line_clean = line.replace("*", "\\*") - f.write(f"{pad}{line_clean}\n") - f.write("\n") - - -def write_nested_dropdown(name, data_cat, note="", categories=[]): - df = data_cat.to_dataframe().sort_index().drop_duplicates("path") - with open(f"_generated/{name}.rst", mode="w") as f: - write_panel(f, name, note, level=0) - write_panel(f, "", level=1, item="tab-set") - for category in categories: - if category == "other": - sources = df.index[~np.isin(df["category"], categories)] - else: - sources = df.index[df["category"] == category] - if len(sources) > 0: - write_panel(f, category, level=2, item="tab-item") - for source in sources: - items = data_cat[source].summary().items() - summary = "\n".join( - [f":{k}: {clean_str(v)}" for k, v in items if k != "category"] - ) - write_panel(f, source, summary, level=3) - - write_panel(f, "all", level=2, item="tab-item") - for source in df.index.values: - items = data_cat[source].summary() - items = {k: clean_str(v) for (k, v) in items.items()}.items() - summary = "\n".join([f":{k}: {v}" for k, v in items]) - write_panel(f, source, summary, level=3) - - -def clean_str(s): - if not isinstance(s, str): - return s - clean = s.replace("*", "\\*") - clean = clean.replace("_", "\\_") - idx = clean.find("p:/") - if idx > -1: - clean = clean[idx:] - - return clean - - # NOTE: the examples/ folder in the root should be copied to docs/examples/examples/ before running sphinx # -- Project information ----------------------------------------------------- @@ -112,41 +61,16 @@ def clean_str(s): # # -- Copy notebooks to include in docs ------- if os.path.isdir("_examples"): remove_dir_content("_examples") -os.makedirs("_examples") -copy_tree("../examples", "_examples") +if not bool(os.getenv("SPHINX_SKIP_EXAMPLES", False)): + os.makedirs("_examples") + copy_tree("../examples", "_examples") if not os.path.isdir("_generated"): os.makedirs("_generated") # # -- Generate panels rst files from data catalogs to include in docs ------- -categories = [ - "geography", - "hydrography", - "landuse", - "hydro", - "meteo", - "ocean", - "socio-economic", - "topography", - "climate", - "other", -] -data_cat = hydromt.DataCatalog() -data_cat.set_predefined_catalogs(r"../data/predefined_catalogs.yml") -predefined_catalogs = data_cat.predefined_catalogs -for name in predefined_catalogs: - try: - data_cat.from_predefined_catalogs(name) - except OSError as e: - print(e) - continue - note = predefined_catalogs[name].get("notes", "") - write_nested_dropdown(name, data_cat, note=note, categories=categories) - data_cat._sources = {} # reset -with open("_generated/predefined_catalogs.rst", "w") as f: - f.writelines( - [f".. include:: ../_generated/{name}.rst\n" for name in predefined_catalogs] - ) +write_predefined_catalogs_to_rst_panels() + # -- Generate cli help docs ---------------------------------------------- diff --git a/docs/parse_predefined_catalogs.py b/docs/parse_predefined_catalogs.py new file mode 100644 index 000000000..90ce21174 --- /dev/null +++ b/docs/parse_predefined_catalogs.py @@ -0,0 +1,162 @@ +import os +import numpy as np +import pandas as pd +from hydromt import DataCatalog +from pathlib import Path + +FILE_ROOT = Path(__file__).parent + +N_VERSIONS = 5 # number of versions to include in the dropdown + +CATEGORIES = [ + "geography", + "hydrography", + "landuse", + "hydro", + "meteo", + "ocean", + "socio-economic", + "topography", + "climate", + "other", +] + +ATTRS = [ + "data_type", + "driver", + "version", + "provider", + "paper_ref", + "paper_doi", + "source_license", + "source_url", + "source_spatial_extent", + "source_temporal_extent", +] + + +def write_panel(f, name: str, content: str="", level: int=0, item: str="dropdown") -> None: + pad = "".ljust(level * 3) + f.write(f"{pad}.. {item}:: {name}\n") + f.write("\n") + if content: + pad = "".ljust((level + 1) * 3) + for line in content.split("\n"): + f.write(f"{pad}{line}\n") + f.write("\n") + + +def write_nested_dropdown(name, df_dict: dict, note: str=""): + path = Path(FILE_ROOT, f"_generated/{name.replace(' ', '_')}.rst") + with open(path, mode="w") as f: + write_panel(f, name, note, level=0) + for i, version in enumerate(df_dict): + df = df_dict[version]#.reset_index().set_index(["name", "provider", "version"]) + df = df.sort_index() + name_str = f"{version}" + if i == 0: + name_str += " (latest)" + write_panel(f, name_str, level=1) + write_panel(f, "", level=2, item="tab-set") + for category in CATEGORIES: + if category == "other": + sources = df.index[~np.isin(df["category"], CATEGORIES)] + else: + sources = df.index[df["category"] == category] + if len(sources) > 0: + write_panel(f, category, level=3, item="tab-item") + write_sources_panel(f, df, level=4, sources=sources) + + + write_panel(f, "all", level=3, item="tab-item") + write_sources_panel(f, df, level=4) + + # return relative path + return path.relative_to(FILE_ROOT) + +def write_sources_panel(f, df, level, sources=None): + attrs = [a for a in ATTRS if a in df.columns] # accomodate older versions + if sources is None: + sources = df.index + sources = sorted(set(sources)) + for source in sources: + df0 = df.loc[source, attrs] + if isinstance(df0, pd.Series): + df0 = df.loc[[source], attrs] + # combine all variants + var_cols = [c for c in ['version', 'provider'] if df0[c].notna().any()] + df_variants = df0[var_cols].sort_values(var_cols).reset_index(drop=True) + variants: list[dict] = list(reversed(df_variants.to_dict(orient='index').values())) + items = list(df0.iloc[0].drop(var_cols).items()) + if len(variants) > 0 and len(variants[0]) > 0: # list of dicts + items += [('variants', variants)] + # parse items to rst table + summary = "\n".join( + [parse_item(k, v) for k, v in items if not (v is np.nan or v is None)] + ) + write_panel(f, source, summary, level=level) + +def parse_item(k: str, v: str | list | dict) -> str: + def _parse_dict(d: dict) -> str: + return " ".join([f"**{k}:** {_parse(v)}" for k, v in d.items()]) + def _parse_list(l: list) -> str: + return "\n".join([f" - {_parse(d)}" for d in l]) + def _parse_str(s: str) -> str: + if s.startswith("http"): # make hyperlink + return f"`link <{s}>`__" + else: # escape special characters + return s.replace("*", "\\*").replace("_", "\\_") + def _parse(v): + if isinstance(v, dict): + return _parse_dict(v) + elif isinstance(v, list): + return _parse_list(v) + else: + return _parse_str(str(v)) + k = k.replace("source_", "").replace("paper_", "") + if k == "doi": + v = f"`{v} `__" + else: + v = _parse(v) + return f":{k}: {v}" + +def write_predefined_catalogs_to_rst_panels( + predefined_catalog_uri: Path = Path(FILE_ROOT, r"../data/predefined_catalogs.yml"), + git_raw_uri: str = r"https://raw.githubusercontent.com/Deltares/hydromt", +) -> None: + """Generate panels rst files from data catalogs to include in docs""" + os.makedirs(Path(FILE_ROOT, "_generated"), exist_ok=True) + data_cat = DataCatalog() + data_cat.set_predefined_catalogs(predefined_catalog_uri) + predefined_catalogs = data_cat.predefined_catalogs + paths = [] + for name in predefined_catalogs: + urlpath = predefined_catalogs[name].get("urlpath", "") + note = predefined_catalogs[name].get("notes", "") + df_dict = {} + for iversion, version in enumerate(predefined_catalogs[name].get("versions", [])): + if iversion >= N_VERSIONS: + break + githash = predefined_catalogs[name]['versions'][version] + if urlpath.startswith(git_raw_uri) and githash == "main": + # make sure to load the latest version from current branch + local_path = Path(FILE_ROOT, urlpath.replace(f'{git_raw_uri}/{{version}}', '../')) + data_cat.from_yml(local_path, catalog_name=name) + else: + try: + data_cat.from_predefined_catalogs(name, version=version) + except OSError as e: + print(e) + continue + df = data_cat.to_dataframe().sort_index().drop_duplicates("path") + df_dict[version] = df.copy() + data_cat._sources = {} # reset + path = write_nested_dropdown(name, df_dict, note=note) + paths.append(path) + with open(Path(FILE_ROOT, "_generated/predefined_catalogs.rst"), "w") as f: + f.writelines( + [f".. include:: ../{path}\n" for path in paths] + ) + +if __name__ == "__main__": + write_predefined_catalogs_to_rst_panels() diff --git a/docs/user_guide/data_existing_cat.rst b/docs/user_guide/data_existing_cat.rst index ea861532a..73e6ac4f5 100644 --- a/docs/user_guide/data_existing_cat.rst +++ b/docs/user_guide/data_existing_cat.rst @@ -12,7 +12,87 @@ The summary per dataset contains links to the online source and available litera The ``deltares_data`` catalog is only available within the Deltares network. However a selection of this data for a the Piave basin (Northern Italy) is available online in the ``artifact_data`` archive and will be used if no data catalog is provided. Local or other datasets can also be included by extending the data catalog with new yaml :ref:`data catalog files `. -We plan to provide more data catalogs with open data sources in the (near) future. See the data catalog `changelog `_ for recent updates on the pre-defined catalogs. +We plan to provide more data catalogs with open data sources in the (near) future. +See the data catalog `changelog `_ for recent updates on the pre-defined catalogs. +Using a predefined catalog +-------------------------- + +From CLI +~~~~~~~~ + +To use a predefined catalog, you can specify the catalog name with the ``--dd`` or ``--data_catalog`` option when running a HydroMT command. +For example, to use the ``deltares_data`` catalog with the `hydromt build` command, you can run the following: + +.. code-block:: bash + + hydromt build MODEL --dd deltares_data ... + +You can specify a version of the catalog by adding the version number after the catalog name, e.g. ``deltares_data=2024.2``. + +.. code-block:: bash + + hydromt build MODEL --dd deltares_data=2024.2 ... + +Once you have set the data catalog you can specify the datat source(s) for each method in the HydroMT +:ref:`model configuration file ` as shown in the example below with the `setup_precip_forcing` method. + +.. code-block:: yaml + + setup_region: + region: + bbox: [4.5, 51.5, 6.5, 53.5] + + setup_maps_from_rasterdataset: + raster_fn: + source: 'eobs' + version: 'v22.0e' + + + +From Python +~~~~~~~~~~~ + +To use a predefined catalog in Python, you can specify the catalog name with the +``data_libs`` argument when initializing a :py:class:`DataCatalog` class. +You can specify a data catalog version by adding the version number after the +catalog name. You can then get data from the catalog using the +:py:meth:`DataCatalog.get_rasterdataset` or other :ref:`DataCatalog methods `. + +.. code-block:: python + + from hydromt import DataCatalog + data_catalog = DataCatalog(data_libs=["deltares_data"]) + # specify a data catalog version + data_catalog = DataCatalog(data_libs=["deltares_data=v2024.2"]) + # get data from the catalog + ds = data_catalog.get_rasterdataset("eobs") # get the latest + ds = data_catalog.get_rasterdataset("eobs", version="22.0e") # get a specific version + + +Similar when building a model using the :py:class:`Model` class you can specify the +data catalog and version. Subsequently you can use specific data sources for each +model :ref:`setup method ` + +.. code-block:: python + + from hydromt import Model + # initialize a model with a specific data catalog version + mod = Model(data_libs=["deltares_data=v2024.2"]) + # setup a region and create a map based on eobs orography + mod.setup_region(region = {'bbox': [4.5, 51.5, 6.5, 53.5]}) + # create a map using the latest version + mod.setup_maps_from_rasterdataset( + raster_fn='eobs_orography', + name="orography_latest", + ) + # create a map using a specific version + mod.setup_maps_from_rasterdataset( + raster_fn={'source': 'eobs_orography', "version": "22.0e"}, + name="orography_v22.0e", + ) + +Available pre-defined data catalogs +----------------------------------- .. include:: ../_generated/predefined_catalogs.rst diff --git a/docs/user_guide/hydromt_cli.rst b/docs/user_guide/hydromt_cli.rst index 9c309443a..77b081732 100644 --- a/docs/user_guide/hydromt_cli.rst +++ b/docs/user_guide/hydromt_cli.rst @@ -40,7 +40,7 @@ where HydroMT is installed): Commands: build Build models check Validate config / data catalog / region - clip Clip models. + clip Clip models export Export data update Update models diff --git a/pixi.toml b/pixi.toml index 423a67677..cdcd7378b 100644 --- a/pixi.toml +++ b/pixi.toml @@ -92,6 +92,17 @@ docker-publish = { depends_on = [ docker-clean = { cmd = ["docker", "system", "prune", "-f"] } html = { cmd = ["sphinx-build", "-M", "html", "docs", "docs/_build", "-W"] } +html-test = { cmd = ["sphinx-build", "-M", "html", "docs", "docs/_build"] } +html-test-skip-examples = { cmd = [ + "export", + "SPHINX_SKIP_EXAMPLES=1;", + "sphinx-build", + "-M", + "html", + "docs", + "docs/_build", +] } +html-clean = { cmd = ["rm", "-rf", "docs/_build", "docs/_generated"] } docs = { depends_on = ["html"] } doc = { depends_on = ["html"] } serve = { cmd = ["python", "-m", "http.server", "-d", "docs/_build/html"] } @@ -124,7 +135,13 @@ clean-docs-exmaples = { cmd = ["rm", "-rf", "docs/examples"] } test = { cmd = ["pytest"] } test-lf = { cmd = ["pytest", "--lf", "--tb=short"] } -test-cov = { cmd = ["pytest", "--verbose", "--cov=hydromt", "--cov-report", "xml"] } +test-cov = { cmd = [ + "pytest", + "--verbose", + "--cov=hydromt", + "--cov-report", + "xml", +] } [dependencies] affine = "*" @@ -212,13 +229,60 @@ jupyterlab = "*" notebook = "*" [environments] -default = { features = ["py311", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py311" } -full-py311 = { features = ["py311", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py311" } -slim-py311 = { features = ["py311", "io", "extra", "examples"], solve-group = "py311" } +default = { features = [ + "py311", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py311" } +full-py311 = { features = [ + "py311", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py311" } +slim-py311 = { features = [ + "py311", + "io", + "extra", + "examples", +], solve-group = "py311" } min-py311 = { features = ["py311"], solve-group = "py311" } -full-py310 = { features = ["py310", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py310" } -slim-py310 = { features = ["py310", "io", "extra", "examples"], solve-group = "py310" } +full-py310 = { features = [ + "py310", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py310" } +slim-py310 = { features = [ + "py310", + "io", + "extra", + "examples", +], solve-group = "py310" } min-py310 = { features = ["py310"], solve-group = "py310" } -full-py39 = { features = ["py39", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py39" } -slim-py39 = { features = ["py39", "io", "extra", "examples"], solve-group = "py39" } +full-py39 = { features = [ + "py39", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py39" } +slim-py39 = { features = [ + "py39", + "io", + "extra", + "examples", +], solve-group = "py39" } min-py39 = { features = ["py39"], solve-group = "py39" } From 3a407966124325b8b870da84fb1416982f3560e9 Mon Sep 17 00:00:00 2001 From: Dirk Eilander Date: Wed, 6 Mar 2024 20:53:02 +0100 Subject: [PATCH 063/110] version fixes; unit era5 zarr fix --- data/catalogs/artifact_data.yml | 4 +-- data/catalogs/changelog.md | 13 +++++++-- data/catalogs/deltares_data.yml | 51 +++++++++++++++++++++++++++++---- 3 files changed, 59 insertions(+), 9 deletions(-) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data.yml index 3628c828a..1c8c84dd8 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data.yml @@ -31,7 +31,7 @@ chirps_global: unit_add: time: 86400 -corine: +corine_2018: data_type: RasterDataset driver: raster meta: @@ -325,7 +325,7 @@ ghs_pop_2015_54009: version: R2019A_v1.0 path: ghs_pop_2015_54009.tif -globcover: +globcover_2009: crs: 4326 data_type: RasterDataset driver: raster diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md index c294edcd6..4d8a39aea 100644 --- a/data/catalogs/changelog.md +++ b/data/catalogs/changelog.md @@ -16,7 +16,11 @@ - kwargs to driver_kwargs - updated source_url if url was not working anymore - sorted datasets by alphabetical order -- Removed version from dataset names and prefixed 'hydro' where necessary, see table below for mapping of old and new names. +- Removed version from dataset names +- prefixed 'hydro' where for all HydroSHEDS datasets +- added the epoch of the dataset to the name of the dataset + +See table below for mapping of old and new names: | Old name | New name | |--------------------------------|---------------------------| @@ -38,8 +42,13 @@ | vito_2017_v3.0.1 | vito_2017 | | vito_2018_v3.0.1 | vito_2018 | | vito_2019_v3.0.1 | vito_2019 | +| esa_worldcover | esa_worldcover_2020 | +| corine | corine_2018 | +| globcover | globcover_2009 | -- Some datasets have multiple versions, for these datasets the default can be changed if you do not supply a version in your config file. See the table below for which dataset the default version has changed. +- Some datasets have multiple versions, for these datasets the default can be changed if +you do not supply a version in your config file. See the table below for which dataset +the default version has changed. | Dataset name | Default version | Previous default version | |----------------|-----------------|--------------------------| diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index f017217dd..e00fa7df7 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -179,7 +179,7 @@ copdem30_masked: rename: copdem_masked: elevtn -corine: +corine_2018: data_type: RasterDataset driver: raster driver_kwargs: @@ -196,7 +196,6 @@ corine: South: 900000.0 East: 7400000.0 North: 5500000.0 - provider: local version: 2020_20u1 path: landuse/corine/CLC2018_CLC2018_V2018_20.tif @@ -418,6 +417,27 @@ era5_daily_zarr: East: 359.875 North: 90.125 path: meteo/era5_daily.zarr + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tmax: temp_max + tmin: temp_min + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + temp_max: -273.15 + temp_min: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + press_msl: 0.01 era5_hourly: crs: 4326 @@ -489,6 +509,24 @@ era5_hourly_zarr: East: 359.875 North: 90.125 path: meteo/era5.zarr + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + precip: 1000 + press_msl: 0.01 era5_ocean: crs: 4326 @@ -548,7 +586,7 @@ era5_orography: unit_mult: elevtn: 0.10197162129779283 -esa_worldcover: +esa_worldcover_2020: crs: 4326 data_type: RasterDataset driver: raster @@ -566,6 +604,9 @@ esa_worldcover: South: -60.0 East: 180.0 North: 84.0 + source_temporal_extent: + start: '2020-01-01' + end: '2020-12-31' version: 100 path: landuse/esa_worldcover/esa-worldcover.vrt @@ -818,7 +859,7 @@ ghs_smod_2015: paper_ref: Pesaresi et al (2019) source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 -globcover: +globcover_2009: crs: 4326 data_type: RasterDataset driver: raster @@ -1515,7 +1556,7 @@ modis_lai: South: -90.002 East: 180.004 North: 90.002 - version: MCD15A3H V006 + version: 6 path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif unit_mult: LAI: 0.1 From f59f7a59fbd28d3e54567d8e12b061dc36e0f3e0 Mon Sep 17 00:00:00 2001 From: deltamarnix <150045289+deltamarnix@users.noreply.github.com> Date: Mon, 11 Mar 2024 13:35:18 +0100 Subject: [PATCH 064/110] Main pin pixi 0.15.2 (#839) Co-authored-by: Sam Vente --- .github/workflows/check-data-catalogs.yml | 2 +- .github/workflows/docs.yml | 2 +- .github/workflows/pixi_auto_update.yml | 2 +- .github/workflows/tests.yml | 6 +- pixi.lock | 404 +++++++++++----------- pixi.toml | 69 +++- 6 files changed, 273 insertions(+), 212 deletions(-) diff --git a/.github/workflows/check-data-catalogs.yml b/.github/workflows/check-data-catalogs.yml index b36279ac2..c9840d305 100644 --- a/.github/workflows/check-data-catalogs.yml +++ b/.github/workflows/check-data-catalogs.yml @@ -31,7 +31,7 @@ jobs: - uses: actions/checkout@v3 - uses: prefix-dev/setup-pixi@v0.5.1 with: - pixi-version: "latest" + pixi-version: "v0.15.2" environments: min-py311 - name: Prepare pixi run: | diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 81ce663bb..99e6b19e2 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -35,7 +35,7 @@ jobs: uses: actions/checkout@v3 - uses: prefix-dev/setup-pixi@v0.5.1 with: - pixi-version: "latest" + pixi-version: "v0.15.2" environments: full-py311 - name: Prepare pixi run: | diff --git a/.github/workflows/pixi_auto_update.yml b/.github/workflows/pixi_auto_update.yml index 0b9096599..84523f6fd 100644 --- a/.github/workflows/pixi_auto_update.yml +++ b/.github/workflows/pixi_auto_update.yml @@ -16,7 +16,7 @@ jobs: ssh-key: ${{ secrets.SSH_PRIVATE_KEY }} - uses: prefix-dev/setup-pixi@v0.5.1 with: - pixi-version: "latest" + pixi-version: "v0.15.2" cache: false - name: Update pixi lock file run: | diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 59ff7a833..b6dfcc7e5 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -12,6 +12,8 @@ on: - data/* - pyproject.toml - pixi.lock + - pixi.toml + - .github/workflows/tests.yml pull_request: branches: - main @@ -22,6 +24,8 @@ on: - data/* - pyproject.toml - pixi.lock + - pixi.toml + - .github/workflows/tests.yml jobs: @@ -46,7 +50,7 @@ jobs: - uses: actions/checkout@v4 - uses: prefix-dev/setup-pixi@v0.5.1 with: - pixi-version: "latest" + pixi-version: "v0.15.2" environments: full-py${{ matrix.python-version }} - name: Prepare pixi run: | diff --git a/pixi.lock b/pixi.lock index 6d21f1892..99169e9c8 100644 --- a/pixi.lock +++ b/pixi.lock @@ -7,9 +7,9 @@ environments: linux-64: - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2 - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2 - - conda: https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.9.3-py311h459d7ec_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.9.3-py39hd1e30aa_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.11-hd590300_1.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/argon2-cffi-bindings-21.2.0-py311h459d7ec_4.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/argon2-cffi-bindings-21.2.0-py39hd1e30aa_4.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.1-h166bdaf_1.tar.bz2 - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.7.16-h79b3bcb_6.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.6.10-hb29e0c7_1.conda @@ -27,38 +27,38 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-core-cpp-1.11.1-h91d86a7_1.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-blobs-cpp-12.10.0-h00ab1b0_1.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-common-cpp-12.5.0-h94269e2_4.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/black-24.2.0-py311h38be061_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/black-24.2.0-py39hf3d152e_0.conda - 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kind: conda name: fiona - version: 1.9.5 - build: py39h3ed1388_3 - build_number: 3 + version: 1.9.6 + build: py39h3ed1388_0 subdir: win-64 - url: https://conda.anaconda.org/conda-forge/win-64/fiona-1.9.5-py39h3ed1388_3.conda - sha256: c1abba5eb38795f09de75c3f1b18da5062de7cfdeb0ea2230a850d09e19c5a1a - md5: 9b0b4f2e68e4f36cc602b0e2971be658 + url: https://conda.anaconda.org/conda-forge/win-64/fiona-1.9.6-py39h3ed1388_0.conda + sha256: e70c8421e7f5cd7a43cdcf3913a7d49cea1ce8943a1089d523f82dfbc3bf85a0 + md5: 3a457ffeefeaa8e050505751f6e24341 depends: - attrs >=19.2.0 + - certifi - click >=8.0,<9.dev0 - click-plugins >=1.0 - cligj >=0.5 - gdal - importlib-metadata - - libgdal >=3.8.2,<3.9.0a0 + - libgdal >=3.8.4,<3.9.0a0 - numpy >=1.22.4,<2.0a0 - python >=3.9,<3.10.0a0 - python_abi 3.9.* *_cp39 - - setuptools - shapely - six - ucrt >=10.0.20348.0 @@ -11969,39 +11974,38 @@ packages: license_family: BSD purls: - pkg:pypi/fiona - size: 805018 - timestamp: 1704132898605 + size: 812403 + timestamp: 1709931722272 - kind: conda name: fiona - version: 1.9.5 - build: py39hcfcd403_3 - build_number: 3 + version: 1.9.6 + build: py39hcfcd403_0 subdir: linux-64 - url: https://conda.anaconda.org/conda-forge/linux-64/fiona-1.9.5-py39hcfcd403_3.conda - sha256: fa3e5ff7c316a94bc8b3f6ebf61c28421a0c339a4318af1b754bfe5b05144508 - md5: 4cbedb0d1f0add97a71a9482c15a8122 + url: https://conda.anaconda.org/conda-forge/linux-64/fiona-1.9.6-py39hcfcd403_0.conda + sha256: 89e29d589bd8f749471a7286cfd275f6b27c37bdf7b87a2f81bac24c025018d3 + md5: 37555ce3fc10c4edc5b5a063bc6449aa depends: - attrs >=19.2.0 + - certifi - click >=8.0,<9.dev0 - click-plugins >=1.0 - cligj >=0.5 - gdal - importlib-metadata - libgcc-ng >=12 - - libgdal >=3.8.2,<3.9.0a0 + - libgdal >=3.8.4,<3.9.0a0 - libstdcxx-ng >=12 - numpy >=1.22.4,<2.0a0 - python >=3.9,<3.10.0a0 - python_abi 3.9.* *_cp39 - - setuptools - shapely - six license: BSD-3-Clause license_family: BSD purls: - pkg:pypi/fiona - size: 957007 - timestamp: 1704131536028 + size: 957698 + timestamp: 1709930922592 - kind: conda name: flit version: 3.9.0 @@ -24334,12 +24338,12 @@ packages: timestamp: 1709230225444 - kind: conda name: ruff - version: 0.3.0 + version: 0.3.2 build: py39h756cfbc_0 subdir: win-64 - url: https://conda.anaconda.org/conda-forge/win-64/ruff-0.3.0-py39h756cfbc_0.conda - sha256: 4452d4d11adc8191641d3259a7ab749438079012d175de15b19da9b7bd5df909 - md5: 47fcf191d092403e5cb122ebaf9d31c0 + url: https://conda.anaconda.org/conda-forge/win-64/ruff-0.3.2-py39h756cfbc_0.conda + sha256: c4a10ee2a752d28590551c788062022392898741aa342658e1e4073399441d9e + md5: 9674eda462b7d2fecb8b92b84b1f86ec depends: - python >=3.9,<3.10.0a0 - python_abi 3.9.* *_cp39 @@ -24350,16 +24354,16 @@ packages: license_family: MIT purls: - pkg:pypi/ruff - size: 5675944 - timestamp: 1709230384089 + size: 5666648 + timestamp: 1709957905252 - kind: conda name: ruff - version: 0.3.0 + version: 0.3.2 build: py39h7efa1f9_0 subdir: linux-64 - url: https://conda.anaconda.org/conda-forge/linux-64/ruff-0.3.0-py39h7efa1f9_0.conda - sha256: fb30f7e4ee44109a50ed702192fa20c498db1b6ba7a45e150cd31af8ab47469b - md5: cb3dfd14bb45827d3570c014d5d9f22b + url: https://conda.anaconda.org/conda-forge/linux-64/ruff-0.3.2-py39h7efa1f9_0.conda + sha256: b84fa822f73eb228fbdb2220eb69024476569712a62fe3d80add743562439ac5 + md5: 827084aab29b6d864e909dfd9f404499 depends: - libgcc-ng >=12 - libstdcxx-ng >=12 @@ -24369,8 +24373,8 @@ packages: license_family: MIT purls: - pkg:pypi/ruff - size: 5737993 - timestamp: 1709229153031 + size: 5755175 + timestamp: 1709956479247 - kind: conda name: s2n version: 1.4.5 diff --git a/pixi.toml b/pixi.toml index 423a67677..572b1eb40 100644 --- a/pixi.toml +++ b/pixi.toml @@ -124,7 +124,13 @@ clean-docs-exmaples = { cmd = ["rm", "-rf", "docs/examples"] } test = { cmd = ["pytest"] } test-lf = { cmd = ["pytest", "--lf", "--tb=short"] } -test-cov = { cmd = ["pytest", "--verbose", "--cov=hydromt", "--cov-report", "xml"] } +test-cov = { cmd = [ + "pytest", + "--verbose", + "--cov=hydromt", + "--cov-report", + "xml", +] } [dependencies] affine = "*" @@ -212,13 +218,60 @@ jupyterlab = "*" notebook = "*" [environments] -default = { features = ["py311", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py311" } -full-py311 = { features = ["py311", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py311" } -slim-py311 = { features = ["py311", "io", "extra", "examples"], solve-group = "py311" } +default = { features = [ + "py39", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py39" } +full-py311 = { features = [ + "py311", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py311" } +slim-py311 = { features = [ + "py311", + "io", + "extra", + "examples", +], solve-group = "py311" } min-py311 = { features = ["py311"], solve-group = "py311" } -full-py310 = { features = ["py310", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py310" } -slim-py310 = { features = ["py310", "io", "extra", "examples"], solve-group = "py310" } +full-py310 = { features = [ + "py310", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py310" } +slim-py310 = { features = [ + "py310", + "io", + "extra", + "examples", +], solve-group = "py310" } min-py310 = { features = ["py310"], solve-group = "py310" } -full-py39 = { features = ["py39", "io", "extra", "dev", "test", "doc", "examples"], solve-group = "py39" } -slim-py39 = { features = ["py39", "io", "extra", "examples"], solve-group = "py39" } +full-py39 = { features = [ + "py39", + "io", + "extra", + "dev", + "test", + "doc", + "examples", +], solve-group = "py39" } +slim-py39 = { features = [ + "py39", + "io", + "extra", + "examples", +], solve-group = "py39" } min-py39 = { features = ["py39"], solve-group = "py39" } From 9b7f394d45fe95d2d173c883860c6fed7079a0c7 Mon Sep 17 00:00:00 2001 From: roeldegoede <83765910+roeldegoede@users.noreply.github.com> Date: Mon, 18 Mar 2024 15:49:11 +0100 Subject: [PATCH 065/110] =?UTF-8?q?fix=20mesh=5F2d=5Ffrom=5Frasterdataset?= =?UTF-8?q?=20for=20rasterdatasets=20with=20multidimension=E2=80=A6=20(#84?= =?UTF-8?q?3)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/changelog.rst | 1 + hydromt/workflows/mesh.py | 3 ++- pixi.toml | 2 +- pyproject.toml | 2 +- 4 files changed, 5 insertions(+), 3 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index db57a3c72..65a332863 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -16,6 +16,7 @@ Changed Fixed ----- - Bug in `raster.transform` with lazy coordinates. (#801) +- Bug in `workflows.mesh.mesh2d_from_rasterdataset` with multi-dimensional coordinates. (#843) v0.9.4 (2024-02-26) diff --git a/hydromt/workflows/mesh.py b/hydromt/workflows/mesh.py index dd67c559f..0b52ee210 100644 --- a/hydromt/workflows/mesh.py +++ b/hydromt/workflows/mesh.py @@ -1,4 +1,5 @@ """Implementation for mesh based workflows.""" + import logging from typing import Dict, List, Optional, Union @@ -261,7 +262,7 @@ def mesh2d_from_rasterdataset( # Get one variable name in ds to simplify to da var = [v for v in ds.data_vars][0] uda = xu.UgridDataArray.from_structured( - ds[var].rename({ds.raster.x_dim: "x", ds.raster.y_dim: "y"}) + ds[var], x=ds.raster.xcoords.name, y=ds.raster.ycoords.name ) uda.ugrid.set_crs(ds.raster.crs) diff --git a/pixi.toml b/pixi.toml index 572b1eb40..1b8292e62 100644 --- a/pixi.toml +++ b/pixi.toml @@ -185,7 +185,7 @@ s3fs = "*" [feature.extra.dependencies] matplotlib = "*" pyet = "*" -xugrid = ">=0.6.5" +xugrid = ">=0.9.0" [feature.dev.dependencies] black = "*" diff --git a/pyproject.toml b/pyproject.toml index b254d315d..ed03f8a87 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -66,7 +66,7 @@ io = [ extra = [ "matplotlib", # plotting; required for slippy tiles "pyet", # calc evapotraspiration, quite well used, used in all wflow models but domain specific - "xugrid>=0.6.5", # xarray wrapper for mesh processing + "xugrid>=0.9.0", # xarray wrapper for mesh processing ] dev = [ "black", # linting From 49f3c071ac9d288336ddb97c583a8fbbd53fda7f Mon Sep 17 00:00:00 2001 From: hboisgon <45457510+hboisgon@users.noreply.github.com> Date: Wed, 27 Mar 2024 09:22:33 +0800 Subject: [PATCH 066/110] fix get_mesh after xugrid update (#848) --- docs/changelog.rst | 1 + hydromt/models/model_mesh.py | 26 ++++++++++++++++++-------- tests/test_model.py | 2 ++ 3 files changed, 21 insertions(+), 8 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index 65a332863..0373c4e99 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -17,6 +17,7 @@ Fixed ----- - Bug in `raster.transform` with lazy coordinates. (#801) - Bug in `workflows.mesh.mesh2d_from_rasterdataset` with multi-dimensional coordinates. (#843) +- Bug in `MeshModel.get_mesh` after xugrid update to 0.9.0. (#848) v0.9.4 (2024-02-26) diff --git a/hydromt/models/model_mesh.py b/hydromt/models/model_mesh.py index e3ad83e2e..3eb4696c1 100644 --- a/hydromt/models/model_mesh.py +++ b/hydromt/models/model_mesh.py @@ -382,19 +382,29 @@ def get_mesh( if grid_name not in self.mesh_names: raise ValueError(f"Grid {grid_name} not found in mesh.") if include_data: - grid = self.mesh_grids[grid_name] - uds = xu.UgridDataset(grid.to_dataset(optional_attributes=True)) - uds.ugrid.grid.set_crs(grid.crs) # Look for data_vars that are defined on grid_name + variables = [] for var in self.mesh.data_vars: if hasattr(self.mesh[var], "ugrid"): - if self.mesh[var].ugrid.grid.name == grid_name: - uds[var] = self.mesh[var] - # additionnal topology properties - elif var.startswith(grid_name): - uds[var] = self.mesh[var] + if self.mesh[var].ugrid.grid.name != grid_name: + variables.append(var) + # additional topology properties + elif not var.startswith(grid_name): + variables.append(var) # else is global property (not grid specific) + if variables and len(variables) < len(self.mesh.data_vars): + uds = self.mesh.drop_vars(variables) + # Drop coords as well + drop_coords = [c for c in uds.coords if not c.startswith(grid_name)] + uds = uds.drop_vars(drop_coords) + elif variables and len(variables) == len(self.mesh.data_vars): + grid = self.mesh_grids[grid_name] + uds = xu.UgridDataset(grid.to_dataset(optional_attributes=True)) + uds.ugrid.grid.set_crs(grid.crs) + else: + uds = self.mesh.copy() + return uds else: diff --git a/tests/test_model.py b/tests/test_model.py index 790b1b3c9..975de27fc 100644 --- a/tests/test_model.py +++ b/tests/test_model.py @@ -840,5 +840,7 @@ def test_meshmodel_setup(griduda, world): resampling_method=["mode", "centroid"], grid_name="mesh2d", ) + ds_mesh2d = mod1.get_mesh("mesh2d", include_data=True) + assert "vito" in ds_mesh2d assert "roughness_manning" in mod1.mesh.data_vars assert np.all(mod1.mesh["landuse"].values == mod1.mesh["vito"].values) From 0a1346c8a8d18008910ae5f7102e8789afb9c72c Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Wed, 3 Apr 2024 09:59:54 +0200 Subject: [PATCH 067/110] Update pixi lock file (#868) Co-authored-by: GitHub --- pixi.lock | 9458 +++++++++++++++++++++++++++-------------------------- 1 file changed, 4784 insertions(+), 4674 deletions(-) diff --git a/pixi.lock b/pixi.lock index 99169e9c8..97443f5ca 100644 --- a/pixi.lock +++ b/pixi.lock @@ -7,80 +7,80 @@ environments: linux-64: - 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Development environment is now set up via pixi instead of mamba / conda. See the documentation for more information on how to install. +- Use the native data CRS when determining zoom levels over the data catalog crs. (#851) Fixed ----- - Bug in `raster.transform` with lazy coordinates. (#801) - Bug in `workflows.mesh.mesh2d_from_rasterdataset` with multi-dimensional coordinates. (#843) - Bug in `MeshModel.get_mesh` after xugrid update to 0.9.0. (#848) +- Allow for string format in zoom_level path, e.g. `{zoom_level:02d}` (#851) v0.9.4 (2024-02-26) diff --git a/hydromt/data_adapter/rasterdataset.py b/hydromt/data_adapter/rasterdataset.py index 37c4240f8..0202d0081 100644 --- a/hydromt/data_adapter/rasterdataset.py +++ b/hydromt/data_adapter/rasterdataset.py @@ -356,7 +356,7 @@ def _resolve_paths( bbox: Optional[Bbox] = None, logger: Logger = logger, ): - if zoom_level is not None and "{zoom_level}" in str(self.path): + if zoom_level is not None and "{zoom_level" in str(self.path): zoom_level = self._parse_zoom_level(zoom_level, geom, bbox, logger=logger) # resolve path based on time, zoom level and/or variables @@ -412,7 +412,8 @@ def _read_data( fns = fns_cached if np.issubdtype(type(self.nodata), np.number): kwargs.update(nodata=self.nodata) - if zoom_level is not None and "{zoom_level}" not in str(self.path): + # check if {zoom_level*} is in path + if zoom_level is not None and "{zoom_level" not in str(self.path): zls_dict, crs = self._get_zoom_levels_and_crs(fns[0], logger=logger) zoom_level = self._parse_zoom_level( zoom_level, geom, bbox, zls_dict, crs, logger=logger @@ -660,7 +661,7 @@ def _set_metadata(self, ds): def _get_zoom_levels_and_crs( self, fn: Optional[StrPath] = None, logger=logger - ) -> Tuple[int, int]: + ) -> Tuple[Optional[dict], Optional[int]]: """Get zoom levels and crs from adapter or detect from tif file if missing.""" if self.zoom_levels is not None and self.crs is not None: return self.zoom_levels, self.crs @@ -682,9 +683,12 @@ def _get_zoom_levels_and_crs( zoom_levels = {i: res * zl for i, zl in enumerate(zls)} except RasterioIOError as e: logger.warning(f"IO error while detecting zoom levels: {e}") + crs = crs if crs is not None else self.crs + if crs is None: + logger.warning("No CRS detected. Hence no zoom levels can be determined.") + return None, None self.zoom_levels = zoom_levels - if self.crs is None: - self.crs = crs + self.crs = crs return zoom_levels, crs def _parse_zoom_level( @@ -763,7 +767,7 @@ def _parse_zoom_level( fdst = conversions.get(dst_crs_unit, 1) dst_res = src_res * fsrc / fdst # find nearest zoom level - res = list(zls_dict.values())[0] / 2 + res = list(zls_dict.values())[0] / 2 # org res is half of first overview zls = list(zls_dict.keys()) smaller = [x < (dst_res + res * 0.01) for x in zls_dict.values()] zl = zls[-1] if all(smaller) else zls[max(smaller.index(False) - 1, 0)] @@ -771,7 +775,7 @@ def _parse_zoom_level( raise ValueError("No CRS defined, hence no zoom level can be determined.") else: raise TypeError(f"zoom_level not understood: {type(zoom_level)}") - logger.debug(f"Using zoom level {zl} ({dst_res:.2f})") + logger.debug(f"Using zoom level {zl} (res: {zls_dict[zl]:.6f})") return zl def get_bbox(self, detect=True) -> TotalBounds: diff --git a/tests/test_data_adapter.py b/tests/test_data_adapter.py index ef045c7ab..afded1754 100644 --- a/tests/test_data_adapter.py +++ b/tests/test_data_adapter.py @@ -158,7 +158,7 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir): "crs": 4326, "data_type": "RasterDataset", "driver": "raster", - "path": f"{str(tmpdir)}/test_zl{{zoom_level}}.tif", + "path": f"{str(tmpdir)}/test_zl{{zoom_level:d}}.tif", # test with str format for zoom level "zoom_levels": {0: 0.1, 1: 0.3}, } } From 8a446b035cbfcf1faa2e981a88f67f29259bfcf1 Mon Sep 17 00:00:00 2001 From: roeldegoede <83765910+roeldegoede@users.noreply.github.com> Date: Thu, 11 Apr 2024 15:18:33 +0200 Subject: [PATCH 069/110] bugfix in clip_bbox for clipping on a bbox outside of rasterdataset (#860) Co-authored-by: Dirk Eilander Co-authored-by: DirkEilander <15379728+DirkEilander@users.noreply.github.com> --- docs/changelog.rst | 2 +- hydromt/raster.py | 24 +++++++++++++++--------- tests/test_raster.py | 16 ++++++++++++++-- 3 files changed, 30 insertions(+), 12 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index 18097a34d..a8beafb06 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -19,9 +19,9 @@ Fixed - Bug in `raster.transform` with lazy coordinates. (#801) - Bug in `workflows.mesh.mesh2d_from_rasterdataset` with multi-dimensional coordinates. (#843) - Bug in `MeshModel.get_mesh` after xugrid update to 0.9.0. (#848) +- Bug in `raster.clip_bbox` when bbox doesn't overlap with raster. (#860) - Allow for string format in zoom_level path, e.g. `{zoom_level:02d}` (#851) - v0.9.4 (2024-02-26) =================== This release fixes a performance regression when reading geometry masks, relaxed warnings for empty raster datasets and updated the documention of the new hydromt commands. diff --git a/hydromt/raster.py b/hydromt/raster.py index 2e17a609a..c02ae9c89 100644 --- a/hydromt/raster.py +++ b/hydromt/raster.py @@ -1239,18 +1239,24 @@ def clip_bbox(self, bbox, align=None, buffer=0, crs=None): e = (e // align + 1) * align n = (n // align + 1) * align xs, ys = [w, e], [s, n] - if self.rotation > 0: # update bbox based on clip to rotated box - gdf_bbox = gpd.GeoDataFrame(geometry=[box(w, s, e, n)], crs=self.crs).clip( - self.box - ) - if not np.all(gdf_bbox.is_empty): - xs, ys = zip(*gdf_bbox.dissolve().boundary[0].coords[:]) + if self.rotation > 0 and w != e and s != n: # if rotated not a point + # make sure bbox touches the rotated raster box + r_w, r_s, r_e, r_n = self.bounds + bbox_geom = box(min(w, r_e), min(s, r_n), max(e, r_w), max(n, r_s)) + # get overlap between bbox and rotated raster box + gdf_bbox = gpd.GeoDataFrame(geometry=[bbox_geom], crs=self.crs) + gdf_bbox_clip = gdf_bbox.clip(self.box).dissolve() + # get the new bounds + if gdf_bbox_clip.type[0] == "Point": # if bbox only touches a corner + xs, ys = gdf_bbox_clip.geometry.x, gdf_bbox_clip.geometry.y + else: # Polygon if bbox overlaps with rotated box + xs, ys = zip(*gdf_bbox_clip.boundary[0].coords[:]) cs, rs = ~self.transform * (np.array(xs), np.array(ys)) - # use round to get integer slices + # use round to get integer slices, max to avoid negative indices c0 = max(int(np.round(cs.min() - buffer)), 0) r0 = max(int(np.round(rs.min() - buffer)), 0) - c1 = int(np.round(cs.max() + buffer)) - r1 = int(np.round(rs.max() + buffer)) + c1 = max(int(np.round(cs.max() + buffer)), 0) + r1 = max(int(np.round(rs.max() + buffer)), 0) return self.clip(slice(c0, c1), slice(r0, r1)) def clip_mask(self, da_mask: xr.DataArray, mask: bool = False): diff --git a/tests/test_raster.py b/tests/test_raster.py index 3e0a61fe2..ac3143608 100644 --- a/tests/test_raster.py +++ b/tests/test_raster.py @@ -299,12 +299,24 @@ def test_clip(transform, shape): assert raster1d.raster._crs is not None assert raster1d.raster.transform is not None # create gdf covering approx half raster - w, s, _, n = da.raster.bounds - e, _ = da.raster.transform * (shape[1] // 2, shape[0] // 2) + w, s, e, n = da.raster.bounds gdf = gpd.GeoDataFrame(geometry=[box(w, s, e, n)], crs=da.raster.crs) # test bbox - buffer da_clip = da.raster.clip_bbox(gdf.total_bounds, buffer=da.raster.width) assert np.all(np.isclose(da.raster.bounds, da_clip.raster.bounds)) + # test bbox - no overlap with raster + # left + da_clip = da.raster.clip_bbox((w - 0.2, s, w - 0.1, n)) + assert len(da_clip[da_clip.raster.x_dim]) == 0 + # right + da_clip = da.raster.clip_bbox((e + 0.1, s, e + 0.2, n)) + assert len(da_clip[da_clip.raster.x_dim]) == 0 + # top + da_clip = da.raster.clip_bbox((w, n + 0.1, e, n + 0.2)) + assert len(da_clip[da_clip.raster.y_dim]) == 0 + # bottom + da_clip = da.raster.clip_bbox((w, s - 0.2, e, s - 0.1)) + assert len(da_clip[da_clip.raster.y_dim]) == 0 # test bbox da_clip0 = da.raster.clip_bbox(gdf.total_bounds) # test geom From d8120b780f3a69c419a512e9d8565867668d300d Mon Sep 17 00:00:00 2001 From: DirkEilander <15379728+DirkEilander@users.noreply.github.com> Date: Fri, 12 Apr 2024 09:14:06 +0200 Subject: [PATCH 070/110] Improved `flw.d8_from_dem` method (#305) Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- docs/changelog.rst | 1 + hydromt/flw.py | 80 ++++++++++++++++++++++++++++++++-------------- tests/test_flw.py | 35 ++++++++++++++++---- 3 files changed, 86 insertions(+), 30 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index a8beafb06..4df4a69fa 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -13,6 +13,7 @@ Changed ------- - Development environment is now set up via pixi instead of mamba / conda. See the documentation for more information on how to install. - Use the native data CRS when determining zoom levels over the data catalog crs. (#851) +- Improved `flw.d8_from_dem` method with different options to use river vector data to aid the flow direction derivation. (#305) Fixed ----- diff --git a/hydromt/flw.py b/hydromt/flw.py index 73efe79a8..5ec639eb9 100644 --- a/hydromt/flw.py +++ b/hydromt/flw.py @@ -2,7 +2,7 @@ import logging import warnings -from typing import Optional, Tuple, Union +from typing import Literal, Optional, Tuple, Union import geopandas as gpd import numpy as np @@ -89,10 +89,13 @@ def flwdir_from_da( def d8_from_dem( da_elv: xr.DataArray, - gdf_stream: Optional[gpd.GeoDataFrame] = None, max_depth: float = -1.0, - outlets: str = "edge", + outlets: Literal["edge", "min", "idxs_pit"] = "edge", idxs_pit: Optional[np.ndarray] = None, + gdf_riv: Optional[gpd.GeoDataFrame] = None, + riv_burn_method: Literal["fixed", "rivdph", "uparea"] = "fixed", + riv_depth: float = 5, + logger=logger, **kwargs, ) -> xr.DataArray: """Derive D8 flow directions grid from an elevation grid. @@ -107,21 +110,29 @@ def d8_from_dem( ---------- da_elv: 2D xarray.DataArray elevation raster - gdf_stream: geopandas.GeoDataArray, optional - stream vector layer with 'uparea' [km2] column which is used to burn - the river in the elevation data. max_depth: float, optional Maximum pour point depth. Depressions with a larger pour point depth are set as pit. A negative value (default) equals an infinitely large pour point depth causing all depressions to be filled. - outlets: {'edge', 'min'} - Position for basin outlet(s) at the all valid elevation edge cell ('edge') - or only the minimum elevation edge cell ('min') + outlets: {'edge', 'min', 'idxs_pit'} + Position of basin outlet(s) + If 'edge' (default) all valid elevation edge cell are considered. + If 'min' only the global minimum elevation edge cell is considered and all flow is directed to this cell. + If 'idxs_pit' the linear indices of the outlet cells are provided in `idxs_pit`. idxs_pit: 1D array of int Linear indices of outlet cells. + gdf_riv: geopandas.GeoDataArray, optional + River vector data. If provided, the river cells are burned into the dem. + Different methods can be used to burn in the river cells, see `riv_burn_method`. + riv_burn_method: {'uparea', 'rivdph', 'fixed'}, optional + Method to burn in river vector to aid the flow direction derivation, requires `gdf_riv`. + If 'fixed' (default) a fixed river depth `rivdph` value is used to burn in the river cells. + If 'rivdph' the rivdph column is used to burn in the river cells directly. + If 'uparea' the uparea column is used to create a synthetic river depth based on `max(1, log10(uparea[m2]))`. + riv_depth: float + fixed depth value used to burn in the dem **kwargs: - Additional keyword arguments that are passed to the `fill_depressions` - function. + Additional keyword arguments that are passed to the :py:func:`pyflwdir.dem.fill_depressions` function. Returns ------- @@ -132,23 +143,42 @@ def d8_from_dem( -------- pyflwdir.dem.fill_depressions """ + if outlets == "idxs_pit" and idxs_pit is None: + raise ValueError("idxs_pit required if outlets='idxs_pit'") + elif idxs_pit is not None and outlets != "idxs_pit": + logger.warning("idxs_pit provided but outlets not set to 'idxs_pit'") + nodata = da_elv.raster.nodata crs = da_elv.raster.crs - assert da_elv.raster.res[1] < 0 - assert nodata is not None - assert ~np.isnan(nodata) - # burn in river if - if gdf_stream is not None and "uparea" in gdf_stream.columns: - gdf_stream = gdf_stream.sort_values(by="uparea") - dst_rivupa = da_elv.raster.rasterize(gdf_stream, col_name="uparea", nodata=0) - # make sure the rivers have a slope and are below all other elevation cells. - # river elevation = min(elv) - log10(uparea[m2]) from rasterized river uparea. - elvmin = da_elv.where(da_elv != nodata).min() - elvriv = elvmin - np.log10(np.maximum(1.0, dst_rivupa * 1e3)) - # synthetic elevation with river burned in - da_elv = elvriv.where(np.logical_and(da_elv != nodata, dst_rivupa > 0), da_elv) + assert da_elv.raster.res[1] < 0, "N->S orientation required" + assert nodata is not None, "Nodata value required" + + nodata_mask = np.isnan(da_elv) if np.isnan(nodata) else da_elv == nodata + if isinstance(gdf_riv, gpd.GeoDataFrame): + # checks and pre-processing gdf_riv + gdf_riv = gdf_riv.copy() + if riv_burn_method == "uparea": + if "uparea" not in gdf_riv.columns: + raise ValueError("uparea column required in gdf_riv") + gdf_riv = gdf_riv.sort_values(by="uparea") + # log10(uparea[m2]) as river depth + gdf_riv["rivdph"] = np.maximum(1, np.log10(gdf_riv["uparea"].values * 1e3)) + elif riv_burn_method == "rivdph": + if "rivdph" not in gdf_riv.columns: + raise ValueError("rivdph column required in gdf_riv") + gdf_riv = gdf_riv.sort_values(by="rivdph") + elif riv_burn_method == "fixed": + gdf_riv = gdf_riv.assign(rivdph=riv_depth) # fixed depth + else: + raise ValueError(f"Unknown riv_burn_method: {riv_burn_method}") + + # burn in river depth + da_rivdph = da_elv.raster.rasterize(gdf_riv, col_name="rivdph", nodata=0) + da_elv = da_elv - np.maximum(0, da_rivdph) + da_elv = da_elv.where(~nodata_mask, nodata) da_elv.raster.set_nodata(nodata) da_elv.raster.set_crs(crs) + # derive new flow directions from (synthetic) elevation d8 = pyflwdir.dem.fill_depressions( da_elv.values.astype(np.float32), @@ -158,6 +188,7 @@ def d8_from_dem( idxs_pit=idxs_pit, **kwargs, )[1] + # return xarray data array da_flw = xr.DataArray( dims=da_elv.raster.dims, @@ -167,6 +198,7 @@ def d8_from_dem( ) da_flw.raster.set_nodata(247) da_flw.raster.set_crs(crs) + return da_flw diff --git a/tests/test_flw.py b/tests/test_flw.py index aac0324ac..853d524c9 100644 --- a/tests/test_flw.py +++ b/tests/test_flw.py @@ -29,17 +29,40 @@ def test_from_da(flwda): def test_from_dem(demda, flwdir): flwda1 = flw.d8_from_dem(demda, outlets="min") - assert np.all( - np.where(flwda1.values.ravel() == 0)[0] == 6 - ) # single outlet position - # with river shape (simplistic example) + # single outlet position + assert np.all(np.where(flwda1.values.ravel() == 0)[0] == 6) + # with river shape; fixed depth upgrid = flwdir.upstream_area("cell") - gdf_stream = gpd.GeoDataFrame.from_features( + gdf_riv = gpd.GeoDataFrame.from_features( flwdir.vectorize(uparea=upgrid, mask=upgrid > 5) ) - flwda2 = flw.d8_from_dem(demda, gdf_stream=gdf_stream, outlets="min") + flwda2 = flw.d8_from_dem( + demda, gdf_riv=gdf_riv, outlets="min", riv_burn_method="fixed", riv_depth=5 + ) upg_max = flw.flwdir_from_da(flwda2).upstream_area("cell").max() assert upg_max == upgrid.max() + # with rivdph column + gdf_riv["rivdph"] = 5 + flwda3 = flw.d8_from_dem( + demda, gdf_riv=gdf_riv, outlets="min", riv_burn_method="rivdph" + ) + xr.testing.assert_equal(flwda2, flwda3) + # with upstream area + flwda4 = flw.d8_from_dem(demda, gdf_riv=gdf_riv, riv_burn_method="uparea") + assert np.sum(flwda4 != flwda2) == 21 # 21 cells are different; regression test + # errors + with pytest.raises(ValueError, match="uparea column required"): + flw.d8_from_dem( + demda, gdf_riv=gdf_riv.drop(columns="uparea"), riv_burn_method="uparea" + ) + with pytest.raises(ValueError, match="rivdph column required"): + flw.d8_from_dem( + demda, gdf_riv=gdf_riv.drop(columns="rivdph"), riv_burn_method="rivdph" + ) + with pytest.raises(ValueError, match="Unknown riv_burn_method"): + flw.d8_from_dem(demda, gdf_riv=gdf_riv, riv_burn_method="unknown") + with pytest.raises(ValueError, match="idxs_pit required"): + flw.d8_from_dem(demda, gdf_riv=gdf_riv, outlets="idxs_pit") def test_upscale(hydds, flwdir): From 9cc9eb49cbd5535993a91b4325006bfa76635d4e Mon Sep 17 00:00:00 2001 From: DirkEilander <15379728+DirkEilander@users.noreply.github.com> Date: Mon, 15 Apr 2024 03:23:36 +0200 Subject: [PATCH 071/110] fix renaming issue (#883) Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> Co-authored-by: Jaap Langemeijer <33715902+Jaapel@users.noreply.github.com> --- docs/changelog.rst | 1 + hydromt/data_adapter/rasterdataset.py | 25 +++++++++++++++---------- tests/test_data_adapter.py | 19 ++++++++++++++++--- 3 files changed, 32 insertions(+), 13 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index 4df4a69fa..8d333d8f1 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -22,6 +22,7 @@ Fixed - Bug in `MeshModel.get_mesh` after xugrid update to 0.9.0. (#848) - Bug in `raster.clip_bbox` when bbox doesn't overlap with raster. (#860) - Allow for string format in zoom_level path, e.g. `{zoom_level:02d}` (#851) +- Fixed incorrect renaming of single variable raster datasets (#883) v0.9.4 (2024-02-26) =================== diff --git a/hydromt/data_adapter/rasterdataset.py b/hydromt/data_adapter/rasterdataset.py index 0202d0081..d82302c19 100644 --- a/hydromt/data_adapter/rasterdataset.py +++ b/hydromt/data_adapter/rasterdataset.py @@ -301,6 +301,7 @@ def get_data( """ try: # load data + variables = list([variables]) if isinstance(variables, str) else variables fns = self._resolve_paths( time_tuple, variables, zoom_level, geom, bbox, logger ) @@ -310,6 +311,7 @@ def get_data( geom, bbox, cache_root, + variables=variables, zoom_level=zoom_level, logger=logger, ) @@ -340,9 +342,10 @@ def get_data( ds = self._set_metadata(ds) # return array if single var and single_var_as_array return self._single_var_as_array(ds, single_var_as_array, variables) - except NoDataException: + except NoDataException as e: + postfix = f"({e.message})" if e.message else "" _exec_nodata_strat( - f"No data was read from source: {self.name}", + f"No data was read from source: {self.name} {postfix}", strategy=handle_nodata, logger=logger, ) @@ -350,7 +353,7 @@ def get_data( def _resolve_paths( self, time_tuple: Optional[TimeRange] = None, - variables: Optional[Variables] = None, + variables: Optional[List] = None, zoom_level: Optional[int] = 0, geom: Optional[Geom] = None, bbox: Optional[Bbox] = None, @@ -374,6 +377,7 @@ def _read_data( bbox: Optional[Bbox], cache_root: Optional[StrPath], zoom_level: Optional[int] = None, + variables: Optional[List] = None, logger: Logger = logger, ): kwargs = self.driver_kwargs.copy() @@ -422,6 +426,9 @@ def _read_data( # NOTE: overview levels start at zoom_level 1, see _get_zoom_levels_and_crs kwargs.update(overview_level=zoom_level - 1) ds = io.open_mfraster(fns, logger=logger, **kwargs) + # rename ds with single band if single variable is requested + if variables is not None and len(variables) == 1 and len(ds.data_vars) == 1: + ds = ds.rename({list(ds.data_vars.keys())[0]: list(variables)[0]}) else: raise ValueError(f"RasterDataset: Driver {self.driver} unknown") @@ -470,7 +477,7 @@ def _set_crs(self, ds: Data, logger: Logger = logger) -> Data: @staticmethod def _slice_data( ds: Data, - variables: Optional[Variables] = None, + variables: Optional[List] = None, geom: Optional[Geom] = None, bbox: Optional[Bbox] = None, buffer: GeomBuffer = 0, @@ -511,12 +518,10 @@ def _slice_data( ds.name = "data" ds = ds.to_dataset() elif variables is not None: - variables = np.atleast_1d(variables).tolist() - if len(variables) > 1 or len(ds.data_vars) > 1: - mvars = [var not in ds.data_vars for var in variables] - if any(mvars): - raise ValueError(f"RasterDataset: variables not found {mvars}") - ds = ds[variables] + mvars = [var for var in variables if var not in ds.data_vars] + if len(mvars) > 0: + raise NoDataException(f"Variables {mvars} not found in data.") + ds = ds[variables] if time_tuple is not None: ds = RasterDatasetAdapter._slice_temporal_dimension( ds, diff --git a/tests/test_data_adapter.py b/tests/test_data_adapter.py index afded1754..f862c60f9 100644 --- a/tests/test_data_adapter.py +++ b/tests/test_data_adapter.py @@ -73,12 +73,21 @@ def test_rasterdataset(rioda, tmpdir): fn_tif = str(tmpdir.join("test.tif")) rioda_utm = rioda.raster.reproject(dst_crs="utm") rioda_utm.raster.to_raster(fn_tif) + fn_nc = str(tmpdir.join("test.nc")) + rioda_utm.to_netcdf(fn_nc) data_catalog = DataCatalog() + da1 = data_catalog.get_rasterdataset(fn_tif, bbox=rioda.raster.bounds) + assert da1.name == "test" # name is taken from file name assert np.all(da1 == rioda_utm) - geom = rioda.raster.box - da1 = data_catalog.get_rasterdataset("test.tif", geom=geom) + assert "test.tif" in data_catalog.sources + + da1 = data_catalog.get_rasterdataset("test.tif", geom=rioda.raster.box) assert np.all(da1 == rioda_utm) + + ds1 = data_catalog.get_rasterdataset(fn_tif, single_var_as_array=False) + assert isinstance(ds1, xr.Dataset) # test single_var_as_array=False + with pytest.raises(FileNotFoundError): data_catalog.get_rasterdataset("no_file.tif") with pytest.raises(NoDataException): @@ -90,9 +99,13 @@ def test_rasterdataset(rioda, tmpdir): bbox=[12.5, 12.6, 12.7, 12.8], handle_nodata=NoDataStrategy.IGNORE, ) - assert da1 is None + da1 = data_catalog.get_rasterdataset(fn_tif, variables=["temp"]) + assert da1.name == "temp" # tif is renamed to variable name + with pytest.raises(NoDataException): # nc variables are not renamed + da1 = data_catalog.get_rasterdataset(fn_nc, variables=["temp"]) + @pytest.mark.skipif(not compat.HAS_GCSFS, reason="GCSFS not installed.") def test_gcs_cmip6(tmpdir): From 5dabbc3196a924273134e7e4d4c162b90c10645e Mon Sep 17 00:00:00 2001 From: DirkEilander <15379728+DirkEilander@users.noreply.github.com> Date: Wed, 17 Apr 2024 10:27:20 +0200 Subject: [PATCH 072/110] fix error message for 0D geometry variable in GeoDataset (#885) --- docs/changelog.rst | 1 + hydromt/vector.py | 87 +++++++++++++++++++++++++------------------- tests/test_vector.py | 16 +++++++- 3 files changed, 65 insertions(+), 39 deletions(-) diff --git a/docs/changelog.rst b/docs/changelog.rst index 8d333d8f1..1069a5304 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -23,6 +23,7 @@ Fixed - Bug in `raster.clip_bbox` when bbox doesn't overlap with raster. (#860) - Allow for string format in zoom_level path, e.g. `{zoom_level:02d}` (#851) - Fixed incorrect renaming of single variable raster datasets (#883) +- Provide better error message for 0D geometry arrays in GeoDataset (#885) v0.9.4 (2024-02-26) =================== diff --git a/hydromt/vector.py b/hydromt/vector.py index d22a7c0a5..c59a19582 100644 --- a/hydromt/vector.py +++ b/hydromt/vector.py @@ -2,7 +2,7 @@ from __future__ import annotations import logging -from typing import Any, Union +from typing import Any, Hashable, Optional, Union import geopandas as gpd import numpy as np @@ -23,13 +23,13 @@ class GeoBase(raster.XGeoBase): """Base accessor class for geo data.""" - def __init__(self, xarray_obj): + def __init__(self, xarray_obj) -> None: """Initialize a new object based on the provided xarray_obj.""" super(GeoBase, self).__init__(xarray_obj) self._geometry = None @property - def _all_names(self): + def _all_names(self) -> list[Hashable]: """Return names of all variables and coordinates in the dataset/array.""" # TODO: move to geobase names = [n for n in self._obj.coords] @@ -42,23 +42,23 @@ def _get_geom_names_types(self, geom_name: str = None) -> tuple[list, list]: names, types = [], [] dvars = self._all_names if geom_name is None else [geom_name] for name in dvars: - if self._obj[name].ndim == 1 and isinstance( - self._obj[name][0].values.item(), BaseGeometry - ): + ndim = self._obj[name].ndim + if ndim != 1: # only single dim geometries + continue + item = self._obj[name][0].values.item() + if isinstance(item, BaseGeometry): names.append(name) types.append("geom") - elif self._obj[name].ndim == 1 and isinstance( - self._obj[name][0].values.item(), str - ): + elif isinstance(item, str): try: - shapely.wkt.loads(self._obj[name][0].values.item()) + shapely.wkt.loads(item) names.append(name) types.append("wkt") except Exception: pass return names, types - def _discover_xy(self, x_name=None, y_name=None, index_dim=None): + def _discover_xy(self, x_name=None, y_name=None, index_dim=None) -> None: """Discover xy type geometries in the dataset/array.""" # infer x dim if x_name is None: @@ -94,7 +94,7 @@ def _discover_xy(self, x_name=None, y_name=None, index_dim=None): self.attrs.pop("geom_format", None) self.attrs.pop("index_dim", None) - def _discover_geom(self, geom_name=None, index_dim=None): + def _discover_geom(self, geom_name=None, index_dim=None) -> None: """Discover geom/wkt type geometries in the dataset/array.""" # check /infer geom dim names, types = self._get_geom_names_types(geom_name=geom_name) @@ -153,7 +153,9 @@ def set_spatial_dims( self._discover_xy(x_name=x_name, y_name=y_name, index_dim=index_dim) self.attrs.pop("geom_name", None) if "geom_format" not in self.attrs: - raise ValueError("No geometry data found.") + raise ValueError( + "No geometry data found. Make sure the data has a 1D geometry variable." + ) @property def geom_format(self) -> str: @@ -185,7 +187,7 @@ def geom_type(self) -> str: return geom_type @property - def x_name(self): + def x_name(self) -> Optional[str]: """Name of x coordinate; only for point geometries in xy format.""" if self.get_attrs("x_name") not in self._obj.dims: self.set_spatial_dims() @@ -193,7 +195,7 @@ def x_name(self): return self.attrs["x_name"] @property - def y_name(self): + def y_name(self) -> Optional[str]: """Name of y coordinate; only for point geometries in xy format.""" if self.get_attrs("y_name") not in self._obj.dims: self.set_spatial_dims() @@ -201,7 +203,7 @@ def y_name(self): return self.attrs["y_name"] @property - def index_dim(self): + def index_dim(self) -> Optional[str]: """Index dimension name.""" if self.get_attrs("index_dim") not in self._obj.dims: self.set_spatial_dims() @@ -209,27 +211,30 @@ def index_dim(self): return self.attrs["index_dim"] @property - def sindex(self): + def sindex(self) -> Any: # type of sindex can be different """Return the spatial index of the geometry.""" return self.geometry.sindex @property - def index(self): + def index(self) -> Optional[xr.DataArray]: """Return the index values.""" - return self._obj[self.index_dim] + if self.index_dim: + return self._obj[self.index_dim] @property - def size(self): + def size(self) -> Optional[int]: """Return the length of the index array.""" - return self._obj[self.index_dim].size + if self.index_dim: + return self._obj[self.index_dim].size @property - def bounds(self): + def bounds(self) -> Optional[np.ndarray]: """Return the bounds (xmin, ymin, xmax, ymax) of the object.""" - return self.geometry.total_bounds + if self.geometry is not None: + return self.geometry.total_bounds @property - def geometry(self) -> GeoSeries: + def geometry(self) -> Optional[GeoSeries]: """Return the geometry of the dataset or array as GeoSeries. Returns @@ -240,7 +245,8 @@ def geometry(self) -> GeoSeries: if self._geometry is not None and self._geometry.index.size == self.size: return self._geometry # if no geometry is present return None self._geometry - # rather than raising an error + # rather than raising an error -> + # FIXME is this the right approach? try: self.set_spatial_dims() except ValueError: @@ -279,7 +285,7 @@ def update_geometry( y_name: str = None, geom_name: str = None, replace: bool = True, - ): + ) -> Union[xr.Dataset, xr.DataArray]: """Update the geometry in the Dataset/Array with a new geometry. if provided or use that, otherwise update the current @@ -316,8 +322,8 @@ def update_geometry( drop_vars = [] if self.geom_format != geom_format: if geom_format != "xy": - drop_vars = [self.x_name, self.y_name] - else: + drop_vars = [name for name in [self.x_name, self.y_name] if name] + elif self.geom_name is not None: drop_vars = [self.geom_name] index_dim = self.index_dim @@ -326,13 +332,13 @@ def update_geometry( geom_name = self.attrs.get("geom_name", "geometry") elif self.geom_name != geom_name: drop_vars.append(self.geom_name) - coords = {geom_name: (self.index_dim, geometry.values)} + coords = {geom_name: (index_dim, geometry.values)} elif geom_format == "wkt": if geom_name is None: geom_name = self.attrs.get("geom_name", "ogc_wkt") elif self.geom_name != geom_name: drop_vars.append(self.geom_name) - coords = {geom_name: (self.index_dim, geometry.to_wkt().values)} + coords = {geom_name: (index_dim, geometry.to_wkt().values)} elif geom_format == "xy": if x_name is None: x_name = self.attrs.get("x_name", "x") @@ -343,8 +349,8 @@ def update_geometry( elif self.y_name != y_name: drop_vars.append(self.y_name) coords = { - x_name: (self.index_dim, geometry.x.values), - y_name: (self.index_dim, geometry.y.values), + x_name: (index_dim, geometry.x.values), + y_name: (index_dim, geometry.y.values), } obj = self._obj.copy() if replace: @@ -364,7 +370,6 @@ def update_geometry( return obj # Internal conversion and selection methods - # i.e. produces xarray.Dataset/ xarray.DataArray def ogr_compliant(self, reducer=None) -> xr.Dataset: """Create a Dataset/Array which is understood by OGR. @@ -495,7 +500,9 @@ def to_wkt( return obj ## clip - def clip_geom(self, geom, predicate="intersects"): + def clip_geom( + self, geom, predicate="intersects" + ) -> Union[xr.DataArray, xr.Dataset]: """Select all geometries that intersect with the input geometry. Arguments @@ -517,7 +524,7 @@ def clip_geom(self, geom, predicate="intersects"): idx = gis_utils.filter_gdf(self.geometry, geom=geom, predicate=predicate) return self._obj.isel({self.index_dim: idx}) - def clip_bbox(self, bbox, crs=None, buffer=None): + def clip_bbox(self, bbox, crs=None, buffer=None) -> Union[xr.DataArray, xr.Dataset]: """Select point locations to bounding box. Arguments @@ -545,7 +552,7 @@ def clip_bbox(self, bbox, crs=None, buffer=None): ## wrap GeoSeries functions # TODO write general wrapper - def to_crs(self, dst_crs): + def to_crs(self, dst_crs) -> Union[xr.DataArray, xr.Dataset]: """Transform spatial coordinates to a new coordinate reference system. The ``crs`` attribute on the current GeoDataArray must be set. @@ -570,7 +577,7 @@ def to_crs(self, dst_crs): ## Output methods ## Either writes to files or other data types - def to_gdf(self, reducer=None): + def to_gdf(self, reducer=None) -> gpd.GeoDataFrame: """Return geopandas GeoDataFrame with Point geometry. Geometry is based on Dataset coordinates. If a reducer is @@ -588,6 +595,10 @@ def to_gdf(self, reducer=None): gdf: geopandas.GeoDataFrame GeoDataFrame """ + if self.geometry is None: + raise ValueError( + "No geometry data found. Make sure the data has a 1D geometry variable." + ) if isinstance(reducer, str): reducer = getattr(np, reducer) obj = self._obj @@ -835,7 +846,7 @@ def __init__(self, xarray_obj): # Properties # Will probably be deleted in the future but now needed for compatibility @property - def vars(self): + def vars(self) -> list[str]: """list: Returns non-coordinate varibles.""" return list(self._obj.data_vars.keys()) diff --git a/tests/test_vector.py b/tests/test_vector.py index dd9fb8147..f48cc7353 100644 --- a/tests/test_vector.py +++ b/tests/test_vector.py @@ -4,7 +4,7 @@ import numpy as np import pytest import xarray as xr -from geopandas import GeoDataFrame +from geopandas import GeoDataFrame, GeoSeries from pyproj import CRS from shapely.geometry import MultiPolygon, Polygon @@ -82,6 +82,20 @@ def test_vector(geoda, geodf): assert da1.vector.crs == gdf1.crs +def test_single_geom_vector(geoda, tmp_dir): + geom = geoda.isel(index=0).vector.geometry + assert geom is None + # write to file + with pytest.raises(ValueError, match="No geometry data found"): + geoda.isel(index=0).vector.to_netcdf(tmp_dir / "test.nc") + + geom1 = geoda.isel(index=[0]).vector.geometry + assert isinstance(geom1, GeoSeries) + fn_nc = tmp_dir / "test.nc" + geoda.isel(index=[0]).vector.to_netcdf(fn_nc) + assert fn_nc.is_file() + + def test_from_gdf(geoda, geodf): geoda0 = geoda.reset_coords(drop=True) # drop geometries dims = list(geoda0.dims) From 7079e9b4aef6c0367a09387416cea81aa3afe6cc Mon Sep 17 00:00:00 2001 From: aweerts Date: Fri, 19 Apr 2024 10:22:49 +0200 Subject: [PATCH 073/110] add EOBS v29.0e deltares_data.yml (#892) --- data/catalogs/deltares_data.yml | 47 +++++++++++++++++++++++++++++++++ 1 file changed, 47 insertions(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 5dbeb7c49..bfaac07ad 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -349,6 +349,34 @@ eobs_v25.0e: unit_add: time: 86400 +eobs_v29.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 29.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + eobs_orography_v20.0e: crs: 4326 data_type: RasterDataset @@ -446,6 +474,25 @@ eobs_orography_v25.0e: rename: elevation: elevtn +eobs_orography_v29.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 29.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v29.0e.nc + rename: + elevation: elevtn + era5: alias: era5_daily era5_daily: From e53b5032cb14377f0dd34d35a39add1203b201f7 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 25 Apr 2024 15:13:41 +0200 Subject: [PATCH 074/110] updated eobs in deltares_data catalog --- data/catalogs/deltares_data.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data.yml index 8892a5ada..c8b3884e4 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data.yml @@ -304,6 +304,9 @@ eobs: path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc meta: processing_script: meteo/eobs/scripts/v29.0e_fix_qq_dims_and_match_extent.py + source_temporal_extent: + start: '1950-01-01' + end: '2024-02-01' rename: pp: press_msl qq: kin From 07537c7a527b2f487e2dea4bb568a889874a76ba Mon Sep 17 00:00:00 2001 From: DirkEilander <15379728+DirkEilander@users.noreply.github.com> Date: Thu, 25 Apr 2024 17:02:21 +0200 Subject: [PATCH 075/110] Catalogs refactor (#849) Co-authored-by: Tjalling-dejong Co-authored-by: Sam Vente Co-authored-by: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Co-authored-by: Sam Vente --- .gitattributes | 2 + .gitignore | 3 + .vscode/extensions.json | 9 - .vscode/launch.json | 13 - .vscode/settings.json | 14 - data/catalogs/README.rst | 7 +- data/catalogs/artifact_data/registry.txt | 4 + .../artifact_data/v0.0.6/data_catalog.yml | 712 ++ .../artifact_data/v0.0.7/data_catalog.yml | 739 ++ .../v0.0.8/data_catalog.yml} | 17 +- .../artifact_data/v0.0.9/data_catalog.yml | 739 ++ data/catalogs/aws_data/registry.txt | 1 + .../v0.1.0/data_catalog.yml} | 5 +- data/catalogs/changelog.rst | 19 + data/catalogs/deltares_data/registry.txt | 2 + .../deltares_data/v0.5.0/data_catalog.yml | 1933 ++++ .../v0.6.0/data_catalog.yml} | 34 +- data/catalogs/gcs_cmip6_data/registry.txt | 1 + .../v0.1.0/data_catalog.yml} | 95 +- data/catalogs/update_versions.py | 11 + data/predefined_catalogs.yml | 8 +- docs/api.rst | 15 +- docs/changelog.rst | 11 + docs/conf.py | 1 - examples/delineate_basin.ipynb | 2 +- examples/export_data.ipynb | 2 +- examples/reading_point_data.ipynb | 2 +- examples/reading_raster_data.ipynb | 2 +- examples/reading_vector_data.ipynb | 2 +- examples/working_with_flow_directions.ipynb | 2 +- examples/working_with_geodatasets.ipynb | 2 +- examples/working_with_meshmodel.ipynb | 2 +- examples/working_with_models.ipynb | 4 +- examples/working_with_raster.ipynb | 2 +- examples/working_with_tiled_raster_data.ipynb | 2 +- hydromt/data_catalog.py | 237 +- hydromt/predefined_catalog.py | 261 + pixi.lock | 9014 +++++++++-------- pixi.toml | 1 + pyproject.toml | 1 + tests/conftest.py | 34 +- tests/test_basin_mask.py | 18 +- tests/test_data_adapter.py | 74 +- tests/test_data_catalog.py | 168 +- tests/test_forcing.py | 15 +- tests/test_predefined_catalogs.py | 106 + .../test_data_catalog_validation.py | 5 +- 47 files changed, 9410 insertions(+), 4943 deletions(-) delete mode 100644 .vscode/extensions.json delete mode 100644 .vscode/launch.json delete mode 100644 .vscode/settings.json create mode 100644 data/catalogs/artifact_data/registry.txt create mode 100644 data/catalogs/artifact_data/v0.0.6/data_catalog.yml create mode 100644 data/catalogs/artifact_data/v0.0.7/data_catalog.yml rename data/catalogs/{artifact_data.yml => artifact_data/v0.0.8/data_catalog.yml} (97%) create mode 100644 data/catalogs/artifact_data/v0.0.9/data_catalog.yml create mode 100644 data/catalogs/aws_data/registry.txt rename data/catalogs/{aws_data.yml => aws_data/v0.1.0/data_catalog.yml} (88%) create mode 100644 data/catalogs/deltares_data/registry.txt create mode 100644 data/catalogs/deltares_data/v0.5.0/data_catalog.yml rename data/catalogs/{deltares_data.yml => deltares_data/v0.6.0/data_catalog.yml} (98%) create mode 100644 data/catalogs/gcs_cmip6_data/registry.txt rename data/catalogs/{gcs_cmip6_data.yml => gcs_cmip6_data/v0.1.0/data_catalog.yml} (84%) create mode 100644 data/catalogs/update_versions.py create mode 100644 hydromt/predefined_catalog.py create mode 100644 tests/test_predefined_catalogs.py diff --git a/.gitattributes b/.gitattributes index d5799bd69..c6702ae45 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,2 +1,4 @@ +* text eol=lf + # GitHub syntax highlighting pixi.lock linguist-language=YAML diff --git a/.gitignore b/.gitignore index ffc641484..a3e74545b 100644 --- a/.gitignore +++ b/.gitignore @@ -107,6 +107,9 @@ venv.bak/ .spyderproject .spyproject +# vscode +.vscode/ + # PyCharm .idea diff --git a/.vscode/extensions.json b/.vscode/extensions.json deleted file mode 100644 index 414b8a341..000000000 --- a/.vscode/extensions.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "recommendations": [ - "ms-python.python", - "ms-python.debugpy", - "ms-python.vscode-pylance", - "charliermarsh.ruff", - "njpwerner.autodocstring" - ] -} diff --git a/.vscode/launch.json b/.vscode/launch.json deleted file mode 100644 index 21ab152d9..000000000 --- a/.vscode/launch.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "version": "0.2.0", - "configurations": [ - { - "name": "Python Debugger: Current File", - "type": "debugpy", - "request": "launch", - "program": "${file}", - "console": "integratedTerminal", - "purpose": ["debug-test"] - } - ] -} diff --git a/.vscode/settings.json b/.vscode/settings.json deleted file mode 100644 index f31a7a366..000000000 --- a/.vscode/settings.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "python.testing.pytestArgs": [ - "tests" - ], - "python.testing.unittestEnabled": false, - "python.testing.pytestEnabled": true, - "[python]": { - "editor.defaultFormatter": "charliermarsh.ruff", - "editor.codeActionsOnSave": { - "source.fixAll": "explicit" - } - }, - "editor.formatOnSave": true -} diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 58007af48..0e86a6871 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -94,7 +94,10 @@ updates ------- - create new branch on github -- make changes and bump the version in the global meta section using `calendar versioning ` +- make a new folder with the name of the version you are going to create +- copy the latest data catalog into the new folder. +- DO NOT modify old catalogs +- bump the version in the global meta section using semantic versioning +- run update_versions.py, this will create a registry file with the versions and hashes of the data catalogs. It is very important that the files have Linux style line endings (LF) as opposed to windows style line endings (CRLF) to keep hashes consistent. If this is not done, pooch will not be able to find the catalogs. This is done automatically for you (CRLF -> LF) if you are updating from windows. - test your yml file (Can the added/changed data sources be read through HydroMT?) - create pull request -- add new version to hydromt\data\predefined_catalogs.yml diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt new file mode 100644 index 000000000..e85a01833 --- /dev/null +++ b/data/catalogs/artifact_data/registry.txt @@ -0,0 +1,4 @@ +v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 +v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee +v0.0.8/data_catalog.yml c1cf2229eeb93607ea881fdbced45ebf43471271f0b7d878db8183734274cd88 +v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 diff --git a/data/catalogs/artifact_data/v0.0.6/data_catalog.yml b/data/catalogs/artifact_data/v0.0.6/data_catalog.yml new file mode 100644 index 000000000..e51554f73 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.6/data_catalog.yml @@ -0,0 +1,712 @@ +meta: + version: v0.0.6 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.6/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + category: null + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/artifact_data/v0.0.7/data_catalog.yml b/data/catalogs/artifact_data/v0.0.7/data_catalog.yml new file mode 100644 index 000000000..4d549a7c3 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.7/data_catalog.yml @@ -0,0 +1,739 @@ +meta: + version: v0.0.7 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.7/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_daily_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5_daily_zarr.zarr +era5_hourly_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly_zarr.zarr +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml similarity index 97% rename from data/catalogs/artifact_data.yml rename to data/catalogs/artifact_data/v0.0.8/data_catalog.yml index e09b16148..e4bcfd3c1 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml @@ -1,7 +1,7 @@ meta: version: v0.0.8 - hydromt_version: '>=0.9, <1.0' root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz + name: artifact_data chelsa: crs: 4326 @@ -95,7 +95,8 @@ era5: driver: netcdf meta: category: meteo - history: Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -139,7 +140,8 @@ era5_daily_zarr: driver: zarr meta: category: meteo - history: Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -246,7 +248,8 @@ gdp_world: meta: category: socio economic source_author: Wilfred Altena - source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 source_version: 1.0 @@ -606,7 +609,8 @@ modis_lai: driver: netcdf meta: category: landuse & landcover - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) @@ -680,7 +684,8 @@ soilgrids: driver: raster meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ \ distribution version 2.0, european commission and the European soil bureau\ \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ diff --git a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml new file mode 100644 index 000000000..518ea84c5 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml @@ -0,0 +1,739 @@ +meta: + version: v0.0.9 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.9/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_daily_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5_daily_zarr.zarr +era5_hourly_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly_zarr.zarr +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/aws_data/registry.txt b/data/catalogs/aws_data/registry.txt new file mode 100644 index 000000000..e1e113d4b --- /dev/null +++ b/data/catalogs/aws_data/registry.txt @@ -0,0 +1 @@ +v0.1.0/data_catalog.yml e0e3c4e10bd6ce51014a04b8ca85de0c987b3cfe7bfa16961f772a953a307038 diff --git a/data/catalogs/aws_data.yml b/data/catalogs/aws_data/v0.1.0/data_catalog.yml similarity index 88% rename from data/catalogs/aws_data.yml rename to data/catalogs/aws_data/v0.1.0/data_catalog.yml index 0e2378c2c..446a8a2fe 100644 --- a/data/catalogs/aws_data.yml +++ b/data/catalogs/aws_data/v0.1.0/data_catalog.yml @@ -1,8 +1,7 @@ --- meta: - version: 2024.1.30 - hydromt_version: '>=0.9, <1.0' - + version: v0.1.0 + name: aws_data esa_worldcover_2020_v100: crs: 4326 diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 0748c3a89..f47ff7746 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -2,6 +2,25 @@ Change log predefined datasets ============================== +Pre-defined catalog refactor +============================ + +Changed +------- +The pre-defined data catalogs have been moved to their own folders together with +a version.yml. This file describes the different versions and relative paths of +the data catalogs present in the folders. + +- predefined_catalogs.yml is deprecated +- data catalog versions are associated with the SHA-256 hash of the files. +- deltares_data versioning is now in semantic style + +Added +----- +- v0.0.6, v0.0.7, v0.0.9 of the artifact_data +- v0.5.0, v0.6.0 of the deltares_data + + deltares_data ============= diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt new file mode 100644 index 000000000..21fbb3c4d --- /dev/null +++ b/data/catalogs/deltares_data/registry.txt @@ -0,0 +1,2 @@ +v0.5.0/data_catalog.yml 73c49e04f63229096ccee10051598a615866ec5c5506b0d28d3c93b14b599436 +v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 diff --git a/data/catalogs/deltares_data/v0.5.0/data_catalog.yml b/data/catalogs/deltares_data/v0.5.0/data_catalog.yml new file mode 100644 index 000000000..1c2a4d100 --- /dev/null +++ b/data/catalogs/deltares_data/v0.5.0/data_catalog.yml @@ -0,0 +1,1933 @@ +--- +meta: + root: p:/wflow_global/hydromt + version: v0.5.0 + name: deltares_data + +basin_atlas_level12_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + kwargs: + layer: BasinATLAS_v10_lev12 + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/basin_atlas_v10.gpkg + +river_atlas_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/river_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + +lake_atlas_pol_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + kwargs: + layer: LakeATLAS_v10_pol + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + +chelsa: + alias: chelsa_v1.2 +chelsa_v1.2: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif + +chirps: + alias: chirps_africa_daily_v2.0 +chirps_africa_daily_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + lat: 160 + lon: 150 + time: 20 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + paper_doi: 10.1038/sdata.2015.66 + paper_ref: Funk et al (2015) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc + rename: + precipitation: precip + unit_add: + time: 86400 + +chirps_global: + alias: chirps_global_daily_v2.0 +chirps_global_daily_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 112 + longitude: 400 + time: 20 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc + rename: + precipitation: precip + unit_add: + time: 86400 + +copdem30: + alias: copdem30_v2021.1 +copdem30_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning + path: topography/copdem/copdem.vrt + rename: + copdem: elevtn + +copdem30_mask: + alias: copdem30_mask_v2021.1 +copdem30_mask_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning + path: topography/copdem/copdem_mask.vrt + rename: + copdem_mask: mask + +copdem30_masked: + alias: copdem30_masked_v2021.1 +copdem30_masked_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + path: topography/copdem/copdem_masked.vrt + rename: + copdem_masked: elevtn + +corine: + alias: corine_2018_v2020_u1 +corine_2018_v2020_u1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: landuse + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: landuse/corine/CLC2018_CLC2018_V2018_20.tif + +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: topography/dtu10mdt/DTU10MDT_1min_float32.tif + +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif + +eobs: + alias: eobs_v22.0e +eobs_v22.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_orography_v20.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + rename: + elevation: elevtn + +eobs_orography: + alias: eobs_orography_v22.0e +eobs_orography_v22.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + rename: + elevation: elevtn + +eobs_orography_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + rename: + elevation: elevtn + +eobs_orography_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + rename: + elevation: elevtn + +eobs_orography_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + rename: + elevation: elevtn + +era5: + alias: era5_daily +era5_daily: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 250 + longitude: 240 + time: 30 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tmax: temp_max + tmin: temp_min + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + temp_max: -273.15 + temp_min: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + press_msl: 0.01 + +era5_daily_zarr: + alias: era5_daily + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + path: meteo/era5_daily.zarr + +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 125 + longitude: 120 + time: 50 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.adbb2d47 + source_version: ERA5 hourly data on single levels from 1940 to present + path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + precip: 1000 + press_msl: 0.01 + +era5_hourly_zarr: + alias: era5_hourly + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + path: meteo/era5.zarr + +era5_ocean: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 60 + longitude: 60 + time: 720 + combine: by_coords + decode_times: true + parallel: true + meta: + category: ocean + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc + +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 120 + longitude: 125 + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 + path: meteo/era5/meta/era5_orography_2018.nc + rename: + z: elevtn + unit_mult: + elevtn: 0.10197162129779283 + +esa_worldcover: + alias: esa_worldcover_2020_v100 +esa_worldcover_2020_v100: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 36000 + y: 36000 + meta: + category: landuse + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.5571936 + source_version: v100 + path: landuse/esa_worldcover/esa-worldcover.vrt + +fabdem: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: CC BY-NC-SA 4.0 + paper_ref: Hawker et al. (2022) + source_license: CC BY-NC-SA 4.0 + source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 + source_version: 1.0 + path: topography/fabdem/fabdem.vrt + rename: + fabdem: elevtn + +gadm: + alias: gadm_level0 + +gadm_level0: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh + path: geography/gadm/version4_1/gadm_level0.fgb + +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh + path: geography/gadm/version4_1/gadm_level1.fgb + +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh + path: geography/gadm/version4_1/gadm_level2.fgb + +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh + path: geography/gadm/version4_1/gadm_level3.fgb + +gcn250: + alias: gcn250_v1 +gcn250_v1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: landuse/gcn250/GCN250_*.tif + rename: + GCN250_ARCI: cn_dry + GCN250_ARCII: cn_avg + GCN250_ARCIII: cn_wet + +gdp_world: + alias: gdp_world_v1 +gdp_world_v1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio-economic + notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_author: Wilfred Altena + source_license: CC BY-4.0 + source_version: 1.0 + path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb + rename: + GDP: gdp + unit_mult: + gdp: 0.001 + +gebco: + alias: gebco_v2020 +gebco_v2020: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: bathymetry/gebco/gebco.vrt + rename: + gebco: elevtn + +ghs_pop: + alias: ghs_pop_2015_54009_v2019a +ghs_pop_2015_4326_v2019a: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif + +ghs_pop_2015_54009_v2019a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif + +ghs_smod: + alias: ghs_smod_2015_54009_v2019a +ghs_smod_2015_54009_v2016a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + +ghs_smod_2015_54009_v2019a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + +globcover: + alias: globcover_2009_v2.3 +globcover_2009_v2.3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + source_version: v2.3 + path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif + +glofas_era5_v31: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + time: 180 + latitude: 150 + longitude: 360 + combine: by_coords + decode_times: true + parallel: true + meta: + category: hydro + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.5194/essd-12-2043-2020 + paper_ref: Harrigan et al. (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf + source_url: https://doi.org/10.24381/cds.a4fdd6b9 + source_version: v31 + path: hydro/glofas_era5/glofas_v31_{year}.nc + rename: + dis24: discharge + +glofas_uparea: + alias: glofas_era5_v31 + driver: raster + kwargs: + chunks: + x: 150 + y: 360 + path: hydro/glofas_era5/glofas_v31_uparea.tif + rename: + glofas_v31_uparea: uparea + unit_mult: + uparea: 0.000001 + +glw_buffaloes: + alias: glw_buffaloes_v3 +glw_buffaloes_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Bf_2010_Da.tif + +glw_cattle: + alias: glw_cattle_v3 +glw_cattle_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ct_2010_Da.tif + +glw_chicken: + alias: glw_chicken_v3 +glw_chicken_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ch_2010_Da.tif + +glw_ducks: + alias: glw_ducks_v3 +glw_ducks_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Dk_2010_Da.tif + +glw_goats: + alias: glw_goats_v3 +glw_goats_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Gt_2010_Da.tif + +glw_horses: + alias: glw_horses_v3 +glw_horses_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ho_2010_Da.tif + +glw_pigs: + alias: glw_pigs_v3 +glw_pigs_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Pg_2010_Da.tif + +glw_sheeps: + alias: glw_sheeps_v3 +glw_sheeps_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Sh_2010_Da.tif + +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: xlsx + kwargs: + index_col: grdc_no + meta: + category: observed data + notes: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: hydro/grdc/GRDC_Stations.xlsx + rename: + area: uparea + +grip_roads: + alias: grip_roads_v4 +grip_roads_v4: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + source_url: https://www.globio.info/download-grip-dataset + paper_ref: Meijer et al, 2018 + paper_doi: 10.1088/1748-9326/aabd42 + source_license: CC0-1.0 + source_version: v4 + path: infrastructure/grip/GRIP4_world.fgb + rename: + GP_RTP: road_type + GP_RCY: country_code + +grwl: + alias: grwl_v1.01 +grwl_v1.01: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb + +grwl_mask: + alias: grwl_mask_v1.01 +grwl_mask_v1.01: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + category: hydrography + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: hydrography/grwl/tindex.gpkg + +gswo: + alias: gswo_v2019 +gswo_v2019: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 4000 + y: 4000 + meta: + category: hydrography + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: hydrography/gswo/occur.vrt + +gtsm_codec_reanalysis_{freq}_v1: + crs: 4326 + data_type: GeoDataset + driver: netcdf + kwargs: + chunks: + stations: 10 + time: -1 + meta: + category: ocean + paper_doi: 10.3389/fmars.2020.00263 + paper_ref: Muis at al (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf + source_url: https://doi.org/10.24381/cds.8c59054f + source_version: v1 + path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc + placeholders: + freq: [10min, hourly, dailymax] + rename: + station_x_coordinate: lon + station_y_coordinate: lat + stations: index + +guf_bld_2012: + alias: guf_bld_2012_v02 +guf_bld_2012_v02: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: infrastructure/guf/GUF04_DLR_v02.vrt + +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: HydroLAKES.v10_extract + source_author: Arjen Haag + source_version: 1.0 + path: hydrography/lakes/lake-db.fgb + rename: + Depth_avg: Depth_avg + Dis_avg: Dis_avg + Hylak_id: waterbody_id + Lake_area: Area_avg + Pour_lat: yout + Pour_long: xout + Vol_total: Vol_avg + unit_mult: + Area_avg: 1000000.0 + +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_author: Alessia Matano + source_version: 1.0 + nodata: -99 + path: hydrography/reservoirs/reservoir-db.fgb + rename: + Depth_avg: Depth_avg + Dis_avg: Dis_avg + G_CAP_MAX: Capacity_max + G_CAP_MIN: Capacity_min + G_CAP_REP: Capacity_norm + G_DAM_HGT_: Dam_height + Grand_id: waterbody_id + Hylak_id: Hylak_id + Lake_area: Area_avg + Pour_lat: yout + Pour_long: xout + Vol_total: Vol_avg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 + +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: meteo/climate_classification_v2017/Map_KG-Global.tif + +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 720 + y: 720 + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif + +merit: + alias: merit_v1.0.3 +merit_v1.0.3: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + drop_variables: projection + chunks: + lat: 6000 + lon: 6000 + meta: + category: topography + paper_doi: 10.1002/2017GL072874 + paper_ref: Yamazaki et al. (2018) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ + source_version: 1.0.3 + path: topography/merit/merit.nc + rename: + elevation: elevtn + +merit_hydro: + alias: merit_hydro_v1.0 +merit_hydro_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: topography/merit_hydro/*.vrt + rename: + bas: basins + dir: flwdir + elv: elevtn + slp: lndslp + sto: strord + upa: uparea + upg: upgrid + wth: rivwth + +merit_hydro_ihu: + alias: merit_hydro_ihu_30sec_v1.0 +merit_hydro_ihu_30sec_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (2021) + source_license: ODC-By 1.0 + source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + source_doi: 10.5281/zenodo.5166932 + source_version: 1.0 + path: topography/merit_hydro_ihu/30sec/*.tif + rename: + 30sec_basids: basins + 30sec_flwdir: flwdir + 30sec_elevtn: elevtn + 30sec_strord: strord + 30sec_uparea: uparea + 30sec_rivlen: rivlen + 30sec_rivslp: rivslp + +merit_hydro_ihu_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-25-5287-2021 + paper_ref: Eilander et al. (2021) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + path: topography/merit_hydro_ihu/30sec/basins.gpkg + +merit_hydro_index: + alias: merit_hydro_index_v1.0 +merit_hydro_index_v1.0: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-25-5287-2021 + paper_ref: Eilander et al. (2021) + source_license: CC-BY-NC 4.0 + path: topography/merit_hydro/basin_index.fgb + +merit_hydro_patch: + alias: merit_hydro_patch_v1.0 +merit_hydro_patch_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 Deltares patch + path: topography/merit_hydro/patches/*.vrt + rename: + bas: basins + dir: flwdir + elv: elevtn + slp: lndslp + sto: strord + upa: uparea + upg: upgrid + wth: rivwth + +modis_lai: + alias: modis_mcd15a3h_v006 +modis_mcd15a3h_v006: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + concat: true + meta: + category: landuse + notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif + unit_mult: + LAI: 0.1 + +osm_coastlines: + alias: osm_coastlines_v20200109 +osm_coastlines_v20200109: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_author: OpenStreetMap + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: geography/osm/osm_coastlines-db.fgb + rename: + fid: coastline_id + +osm_landareas: + alias: osm_landareas_v20200109 +osm_landareas_v20200109: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_author: OpenStreetMap + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: geography/osm/osm_landareas-db.fgb + rename: + fid: land_id + +pcr_globwb: + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + meta: + category: water demand + notes: last downloaded 2023-11-23 + paper_doi: 10.5281/zenodo.1045339 + paper_ref: Sutanudjaja, E. H., et al (2017) + source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR + source_version: 2017.11b1 + processing_script: hydro/pcr_globwb/prep_glob.py + variants: + - version: 1990 + path: hydro/pcr_globwb/glob_1990.zarr + - version: 1995 + path: hydro/pcr_globwb/glob_1995.zarr + - version: 2000 + path: hydro/pcr_globwb/glob_2000.zarr + - version: 2005 + path: hydro/pcr_globwb/glob_2005.zarr + nodata: -9999 + rename: + domesticNettoDemand: dom_net + domesticGrossDemand: dom_gross + industryNettoDemand: ind_net + industryGrossDemand: ind_gross + livestockNettoDemand: lsk_net + livestockGrossDemand: lsk_gross + unit_mult: + dom_net: 1000 + dom_gross: 1000 + ind_net: 1000 + ind_gross: 1000 + lsk_net: 1000 + lsk_gross: 1000 + +rgi: + alias: rgi_v0.6 +rgi_v0.6: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: Randolph Glacier Inventory + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: hydrography/rgi/rgi.fgb + rename: + C3S_ID: C3S_id + GLIMSID: GLIMS_id + ID: simple_id + RGIID: RGI_id + +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: hydrography/rivers_lin2019/rivers_ge30m.fgb + rename: + width_m: rivwth + Q2: qbankfull + +simard: + alias: simard_v2011 +simard_v2011: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: landuse/simard/sdat_10023_canopy_height_simard.tif + +SM2RAIN_ASCAT_monthly_025_v1.4: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 360 + longitude: 720 + time: 84 + meta: + category: meteo + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution + paper_doi: 10.5194/essd-11-1583-2019 + paper_ref: Brocca et al. (2019) + source_license: https://creativecommons.org/licenses/by/4.0/legalcode + source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc + rename: + rainfall: precip + +SM2RAIN_ASCAT_monthly_05_v1.4: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 180 + longitude: 360 + time: 84 + meta: + category: meteo + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution + paper_doi: 10.5194/essd-11-1583-2019 + paper_ref: Brocca et al. (2019) + source_license: https://creativecommons.org/licenses/by/4.0/legalcode + source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc + rename: + rainfall: precip + +soilgrids: + alias: soilgrids_v1.0 +soilgrids_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soil/soilgrids_v1.0/*_250m_ll.tif + rename: + BLDFIE_M_sl1_250m_ll: bd_sl1 + BLDFIE_M_sl2_250m_ll: bd_sl2 + BLDFIE_M_sl3_250m_ll: bd_sl3 + BLDFIE_M_sl4_250m_ll: bd_sl4 + BLDFIE_M_sl5_250m_ll: bd_sl5 + BLDFIE_M_sl6_250m_ll: bd_sl6 + BLDFIE_M_sl7_250m_ll: bd_sl7 + CLYPPT_M_sl1_250m_ll: clyppt_sl1 + CLYPPT_M_sl2_250m_ll: clyppt_sl2 + CLYPPT_M_sl3_250m_ll: clyppt_sl3 + CLYPPT_M_sl4_250m_ll: clyppt_sl4 + CLYPPT_M_sl5_250m_ll: clyppt_sl5 + CLYPPT_M_sl6_250m_ll: clyppt_sl6 + CLYPPT_M_sl7_250m_ll: clyppt_sl7 + ORCDRC_M_sl1_250m_ll: oc_sl1 + ORCDRC_M_sl2_250m_ll: oc_sl2 + ORCDRC_M_sl3_250m_ll: oc_sl3 + ORCDRC_M_sl4_250m_ll: oc_sl4 + ORCDRC_M_sl5_250m_ll: oc_sl5 + ORCDRC_M_sl6_250m_ll: oc_sl6 + ORCDRC_M_sl7_250m_ll: oc_sl7 + PHIHOX_M_sl1_250m_ll: ph_sl1 + PHIHOX_M_sl2_250m_ll: ph_sl2 + PHIHOX_M_sl3_250m_ll: ph_sl3 + PHIHOX_M_sl4_250m_ll: ph_sl4 + PHIHOX_M_sl5_250m_ll: ph_sl5 + PHIHOX_M_sl6_250m_ll: ph_sl6 + PHIHOX_M_sl7_250m_ll: ph_sl7 + SLTPPT_M_sl1_250m_ll: sltppt_sl1 + SLTPPT_M_sl2_250m_ll: sltppt_sl2 + SLTPPT_M_sl3_250m_ll: sltppt_sl3 + SLTPPT_M_sl4_250m_ll: sltppt_sl4 + SLTPPT_M_sl5_250m_ll: sltppt_sl5 + SLTPPT_M_sl6_250m_ll: sltppt_sl6 + SLTPPT_M_sl7_250m_ll: sltppt_sl7 + SNDPPT_M_sl1_250m_ll: sndppt_sl1 + SNDPPT_M_sl2_250m_ll: sndppt_sl2 + SNDPPT_M_sl3_250m_ll: sndppt_sl3 + SNDPPT_M_sl4_250m_ll: sndppt_sl4 + SNDPPT_M_sl5_250m_ll: sndppt_sl5 + SNDPPT_M_sl6_250m_ll: sndppt_sl6 + SNDPPT_M_sl7_250m_ll: sndppt_sl7 + SoilThickness_250m_ll: soilthickness + TAXOUSDA_250m_ll: tax_usda + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + +soilgrids_2020: + alias: soilgrids_v2.0 +soilgrids_v2.0: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + source_version: 2020 + path: soil/soilgrids_v2.0/*/*_mean.vrt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 + +vito: + alias: vito_2015_v2.0.2 +vito_2015_v2.0.2: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif + +vito_2016_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518026 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2017_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518036 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2018_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2019_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3939050 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif + +wb_countries: + alias: wb_countries_v20200319 +wb_countries_v20200319: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio-economic + source_author: World Bank + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + source_license: CC-BY 4.0 + timestamp: February 2020 + path: geography/wb/WB_countries_Admin0.fgb + rename: + ISO_A3: country_iso + ISO_N3: country_code + POP_EST: population + GDP_MD_EST: gdp_pc + GDP_kD_PPP: gdp + unit_mult: + gdp_pc: 1000 + +worldclim: + alias: worldclim_v2.0 +worldclim_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + lat: 3600 + lon: 3600 + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + nodata: -999.0 + path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc + rename: + prec: precip + +worldpop_2020_constrained: + data_type: RasterDataset + driver: raster + kwargs: + chunks: auto + meta: + category: socio-economic + paper_doi: 10.1371/journal.pone.0107042 + paper_ref: Stevens et al. (2015) + source_license: CC BY 4.0 + source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 + nodata: -99999 + path: socio_economic/worldpop/ppp_2020_constrained.vrt + rename: + ppp_2020_constrained: population + +worldpop_2020_UNadj_constrained: + alias: worldpop_2020_constrained + path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt + rename: + ppp_2020_UNadj_constrained: population + +wsf_bld_2015: + alias: wsf_bld_2015_v1 +wsf_bld_2015_v1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.1038/s41597-020-00580-5 + paper_ref: Marconcini at al (2020) + source_license: CC0 1.0 + source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc + path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data/v0.6.0/data_catalog.yml similarity index 98% rename from data/catalogs/deltares_data.yml rename to data/catalogs/deltares_data/v0.6.0/data_catalog.yml index bfaac07ad..48b627a86 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data/v0.6.0/data_catalog.yml @@ -1,9 +1,8 @@ --- meta: root: p:/wflow_global/hydromt - version: 2024.1.30 - hydromt_version: '>=0.9, <1.0' - + version: v0.6.0 + name: deltares_data basin_atlas_level12_v10: crs: 4326 @@ -141,7 +140,7 @@ copdem30_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem.vrt rename: @@ -160,7 +159,7 @@ copdem30_mask_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem_mask.vrt rename: @@ -179,7 +178,7 @@ copdem30_masked_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn @@ -1085,7 +1084,6 @@ glw_sheeps_v3: source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Sh_2010_Da.tif - grdc: crs: 4326 data_type: GeoDataFrame @@ -1503,14 +1501,14 @@ pcr_globwb: source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py variants: - - version: 1990 - path: hydro/pcr_globwb/glob_1990.zarr - - version: 1995 - path: hydro/pcr_globwb/glob_1995.zarr - - version: 2000 - path: hydro/pcr_globwb/glob_2000.zarr - - version: 2005 - path: hydro/pcr_globwb/glob_2005.zarr + - version: 1990 + path: hydro/pcr_globwb/glob_1990.zarr + - version: 1995 + path: hydro/pcr_globwb/glob_1995.zarr + - version: 2000 + path: hydro/pcr_globwb/glob_2000.zarr + - version: 2005 + path: hydro/pcr_globwb/glob_2005.zarr nodata: -9999 rename: domesticNettoDemand: dom_net @@ -1632,7 +1630,8 @@ soilgrids_v1.0: y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" @@ -1721,7 +1720,8 @@ soilgrids_v2.0: y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" diff --git a/data/catalogs/gcs_cmip6_data/registry.txt b/data/catalogs/gcs_cmip6_data/registry.txt new file mode 100644 index 000000000..7351cb9f2 --- /dev/null +++ b/data/catalogs/gcs_cmip6_data/registry.txt @@ -0,0 +1 @@ +v0.1.0/data_catalog.yml c8aab2c2068809a52e5e40a38e68d1a27d25346cf51724010a24f1bfad66a1c1 diff --git a/data/catalogs/gcs_cmip6_data.yml b/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml similarity index 84% rename from data/catalogs/gcs_cmip6_data.yml rename to data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml index b933c6dc0..2904536b4 100644 --- a/data/catalogs/gcs_cmip6_data.yml +++ b/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml @@ -1,7 +1,7 @@ --- meta: - version: 2024.1.30 - hydromt_version: '>=0.8.1, <1.0' + version: v0.1.0 + name: gcs_cmip6_data cmip6_{model}_historical_{member}_{timestep}: crs: 4326 @@ -21,9 +21,32 @@ cmip6_{model}_historical_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [IPSL/IPSL-CM6A-LR, SNU/SAM0-UNICON, NCAR/CESM2, NCAR/CESM2-WACCM, INM/INM-CM4-8, INM/INM-CM5-0, NOAA-GFDL/GFDL-ESM4, NCC/NorESM2-LM, NIMS-KMA/KACE-1-0-G, - CAS/FGOALS-f3-L, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, CSIRO/ACCESS-ESM1-5, NCAR/CESM2-WACCM-FV2, NCAR/CESM2-FV2, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, - NCC/NorCPM1, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-CM2-HR4, CMCC/CMCC-ESM2, IPSL/IPSL-CM6A-LR-INCA, E3SM-Project/E3SM-1-0] + model: + [ + IPSL/IPSL-CM6A-LR, + SNU/SAM0-UNICON, + NCAR/CESM2, + NCAR/CESM2-WACCM, + INM/INM-CM4-8, + INM/INM-CM5-0, + NOAA-GFDL/GFDL-ESM4, + NCC/NorESM2-LM, + NIMS-KMA/KACE-1-0-G, + CAS/FGOALS-f3-L, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + CSIRO/ACCESS-ESM1-5, + NCAR/CESM2-WACCM-FV2, + NCAR/CESM2-FV2, + CMCC/CMCC-CM2-SR5, + AS-RCEC/TaiESM1, + NCC/NorCPM1, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-CM2-HR4, + CMCC/CMCC-ESM2, + IPSL/IPSL-CM6A-LR-INCA, + E3SM-Project/E3SM-1-0, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR', 'BCC/BCC-ESM1', 'CCCma/CanESM5', 'MRI/MRI-ESM2-0', # 'HAMMOZ-Consortium/MPI-ESM-1-2-HAM', 'MPI-M/MPI-ESM1-2-LR', 'MPI-M/MPI-ESM1-2-HR', 'NUIST/NESM3', # 'CAS/FGOALS-g3', 'MIROC/MIROC6', 'KIOST/KIOST-ESM', 'CCCR-IITM/IITM-ESM', 'AWI/AWI-ESM-1-1-LR', @@ -97,8 +120,18 @@ cmip6_{model}_ssp126_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, IPSL/IPSL-CM6A-LR, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, - CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + INM/INM-CM4-8, + INM/INM-CM5-0, + IPSL/IPSL-CM6A-LR, + NIMS-KMA/KACE-1-0-G, + NCC/NorESM2-MM, + CMCC/CMCC-CM2-SR5, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-ESM2, + ] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','DKRZ/MPI-ESM1-2-HR','MPI-M/MPI-ESM1-2-LR', # 'NUIST/NESM3', 'MIROC/MIROC6','MRI/MRI-ESM2-0','KIOST/KIOST-ESM','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','CCCR-IITM/IITM-ESM','EC-Earth-Consortium/EC-Earth3-Veg-LR', @@ -135,8 +168,21 @@ cmip6_{model}_ssp245_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, NCC/NorESM2-LM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, - NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, CMCC/CMCC-ESM2, AS-RCEC/TaiESM1] + model: + [ + NOAA-GFDL/GFDL-ESM4, + IPSL/IPSL-CM6A-LR, + INM/INM-CM4-8, + INM/INM-CM5-0, + NCAR/CESM2-WACCM, + NCC/NorESM2-LM, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + NIMS-KMA/KACE-1-0-G, + CMCC/CMCC-CM2-SR5, + CMCC/CMCC-ESM2, + AS-RCEC/TaiESM1, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', # 'AWI/AWI-CM-1-1-MR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','DKRZ/MPI-ESM1-2-HR','NUIST/NESM3', @@ -173,8 +219,21 @@ cmip6_{model}_ssp370_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, NCC/NorESM2-LM, - NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + IPSL/IPSL-CM6A-LR, + INM/INM-CM4-8, + INM/INM-CM5-0, + NCAR/CESM2-WACCM, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + NCC/NorESM2-LM, + NIMS-KMA/KACE-1-0-G, + CMCC/CMCC-CM2-SR5, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-ESM2, + ] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','BCC/BCC-ESM1','DKRZ/MPI-ESM1-2-HR', # EC-Earth-Consortium/EC-Earth3-Veg','EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-AerChem', # 'EC-Earth-Consortium/EC-Earth3-Veg-LR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','HAMMOZ-Consortium/MPI-ESM-1-2-HAM', @@ -279,8 +338,18 @@ cmip6_{model}_ssp585_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, NCC/NorESM2-LM, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, - CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + INM/INM-CM4-8, + INM/INM-CM5-0, + NIMS-KMA/KACE-1-0-G, + NCC/NorESM2-MM, + NCC/NorESM2-LM, + CMCC/CMCC-CM2-SR5, + AS-RCEC/TaiESM1, + CMCC/CMCC-ESM2, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','MPI-M/MPI-ESM1-2-LR', # 'DKRZ/MPI-ESM1-2-HR','MIROC/MIROC6','MRI/MRI-ESM2-0','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', diff --git a/data/catalogs/update_versions.py b/data/catalogs/update_versions.py new file mode 100644 index 000000000..31deea94a --- /dev/null +++ b/data/catalogs/update_versions.py @@ -0,0 +1,11 @@ +"""Script to update the registry.txt file for each predefined catalog.""" + +from pathlib import Path + +from hydromt.predefined_catalog import create_registry_file + +if __name__ == "__main__": + root = Path(__file__).parent + cat_roots = [d for d in root.iterdir() if d.is_dir()] + for cat_root in cat_roots: + create_registry_file(cat_root) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index f7cae9857..ccb24fa3a 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -1,4 +1,6 @@ --- +# NOTE this file has been deprecated and will be removed in future versions +# # list of predefined data catalogs # # : @@ -16,7 +18,7 @@ deltares_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/deltares_data.yml versions: - v2024.1.30: main + v2024.1.30: 50863d777404a4a91b5f66bf285b3edaa56713b1 v2023.12.21: 392206b21b26e62e00ae76db7ffc61a3b95e2175 v2023.12.19: bf25e79dcbda67612a75588cd782d57abe3881de v2023.2: 0bf8e2a1e716095dc6df54a5e9114ce88da0701b @@ -26,13 +28,13 @@ deltares_data: gcs_cmip6_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/gcs_cmip6_data.yml versions: - v2024.1.30: main + v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 v2023.2: 0144d5dadfb76a9f2bdb22226b484e83c9751c34 notes: This data uses CMIP6 data stored in Google Cloud Service. aws_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/aws_data.yml versions: - v2024.1.30: main + v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: diff --git a/docs/api.rst b/docs/api.rst index f08d0e99b..ecb7382d8 100644 --- a/docs/api.rst +++ b/docs/api.rst @@ -73,10 +73,8 @@ Add data sources data_catalog.DataCatalog.add_source data_catalog.DataCatalog.update data_catalog.DataCatalog.from_predefined_catalogs - data_catalog.DataCatalog.from_archive data_catalog.DataCatalog.from_yml data_catalog.DataCatalog.from_dict - data_catalog.DataCatalog.set_predefined_catalogs .. _api_data_catalog_get: @@ -92,6 +90,19 @@ Get data data_catalog.DataCatalog.get_dataframe data_catalog.DataCatalog.get_dataset + +Predefined data catalog +======================= + +.. autosummary:: + :toctree: _generated + + predefined_catalog.PredefinedCatalog + predefined_catalog.PredefinedCatalog.get_catalog_file + predefined_catalog.create_registry_file + + + DataAdapter =========== diff --git a/docs/changelog.rst b/docs/changelog.rst index 1069a5304..416449094 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -9,11 +9,18 @@ The format is based on `Keep a Changelog`_, and this project adheres to Unreleased ========== +New +--- +- New `PredefinedCatalog` class to handle predefined catalog version based on pooch registry files. (#849) + + Changed ------- - Development environment is now set up via pixi instead of mamba / conda. See the documentation for more information on how to install. - Use the native data CRS when determining zoom levels over the data catalog crs. (#851) - Improved `flw.d8_from_dem` method with different options to use river vector data to aid the flow direction derivation. (#305) +- DataCatalog.predefined_catalogs retrieves predefined_catalogs specified in predefined_catalogs.py. There is no need for setting the predefined_catalogs anymore. (#844) + Fixed ----- @@ -25,6 +32,10 @@ Fixed - Fixed incorrect renaming of single variable raster datasets (#883) - Provide better error message for 0D geometry arrays in GeoDataset (#885) +Deprecated +---------- +- The `DataCatalog.from_archive` method is deprecated. Use `DataCatalog.from_yml` with the root pointing to the archive instead. (#849) + v0.9.4 (2024-02-26) =================== This release fixes a performance regression when reading geometry masks, relaxed warnings for empty raster datasets and updated the documention of the new hydromt commands. diff --git a/docs/conf.py b/docs/conf.py index 7a5d551b4..140446283 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -132,7 +132,6 @@ def clean_str(s): "other", ] data_cat = hydromt.DataCatalog() -data_cat.set_predefined_catalogs(r"../data/predefined_catalogs.yml") predefined_catalogs = data_cat.predefined_catalogs for name in predefined_catalogs: try: diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index e674c76dc..31abdd8a8 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -92,7 +92,7 @@ "outputs": [], "source": [ "# instantiate instance of Data Catalog\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/export_data.ipynb b/examples/export_data.ipynb index ebeb19887..4f4b40eb6 100644 --- a/examples/export_data.ipynb +++ b/examples/export_data.ipynb @@ -56,7 +56,7 @@ "# Download and read artifacts for the Piave basin to `~/.hydromt_data/`.\n", "data_catalog = hydromt.DataCatalog(\n", " logger=logger,\n", - " data_libs=[\"artifact_data\"],\n", + " data_libs=[\"artifact_data=v0.0.8\"],\n", ")" ] }, diff --git a/examples/reading_point_data.ipynb b/examples/reading_point_data.ipynb index 12a6c149d..5badce96b 100644 --- a/examples/reading_point_data.ipynb +++ b/examples/reading_point_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/reading_raster_data.ipynb b/examples/reading_raster_data.ipynb index 23a975151..6eb3fb94a 100644 --- a/examples/reading_raster_data.ipynb +++ b/examples/reading_raster_data.ipynb @@ -40,7 +40,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/reading_vector_data.ipynb b/examples/reading_vector_data.ipynb index e9340ca7c..dc7916411 100644 --- a/examples/reading_vector_data.ipynb +++ b/examples/reading_vector_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_flow_directions.ipynb b/examples/working_with_flow_directions.ipynb index ede0c1594..6a827c0d8 100644 --- a/examples/working_with_flow_directions.ipynb +++ b/examples/working_with_flow_directions.ipynb @@ -51,7 +51,7 @@ "# initialize a logger\n", "logger = setuplog(\"flow direction data\", log_level=10)\n", "# initialize a data catalog based on the pre-defined artifact_data catalog\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data\"], logger=logger)\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"], logger=logger)\n", "\n", "# we load the flow direction (flwdir); elevation (elevtn) and upstream area (uparea) layers\n", "ds = data_catalog.get_rasterdataset(\n", diff --git a/examples/working_with_geodatasets.ipynb b/examples/working_with_geodatasets.ipynb index ecb939af6..ca7cc56dc 100644 --- a/examples/working_with_geodatasets.ipynb +++ b/examples/working_with_geodatasets.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_meshmodel.ipynb b/examples/working_with_meshmodel.ipynb index 7772be559..d4e2f34cb 100644 --- a/examples/working_with_meshmodel.ipynb +++ b/examples/working_with_meshmodel.ipynb @@ -175,7 +175,7 @@ "mod = hydromt.MeshModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] diff --git a/examples/working_with_models.ipynb b/examples/working_with_models.ipynb index 4a5101a9f..70290be58 100644 --- a/examples/working_with_models.ipynb +++ b/examples/working_with_models.ipynb @@ -192,7 +192,7 @@ "mod = hydromt.GridModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] @@ -462,7 +462,7 @@ "mod3 = hydromt.GridModel(\n", " root=root3,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")\n", "\n", diff --git a/examples/working_with_raster.ipynb b/examples/working_with_raster.ipynb index 6d7cc69be..2f93200e8 100644 --- a/examples/working_with_raster.ipynb +++ b/examples/working_with_raster.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_tiled_raster_data.ipynb b/examples/working_with_tiled_raster_data.ipynb index d442fc7f5..f5e3a7fce 100644 --- a/examples/working_with_tiled_raster_data.ipynb +++ b/examples/working_with_tiled_raster_data.ipynb @@ -30,7 +30,7 @@ "logger = setuplog(\"tiling\", log_level=20)\n", "\n", "# get some elevation data from the data catalog\n", - "data_lib = \"artifact_data\"\n", + "data_lib = \"artifact_data=v0.0.8\"\n", "data_cat = DataCatalog(data_lib, logger=logger)\n", "source = \"merit_hydro\"\n", "da0 = data_cat.get_rasterdataset(source, variables=[\"elevtn\"])\n", diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 9402c31d3..22575a478 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -2,16 +2,16 @@ # -*- coding: utf-8 -*- """DataCatalog module for HydroMT.""" + from __future__ import annotations import copy import itertools import logging import os -import shutil import warnings from datetime import datetime -from os.path import abspath, basename, isdir, isfile, join +from os.path import abspath, basename, isfile, join from pathlib import Path from typing import ( Dict, @@ -26,6 +26,7 @@ import geopandas as gpd import numpy as np import pandas as pd +import pooch import requests import xarray as xr import yaml @@ -35,10 +36,14 @@ from pystac import CatalogType, MediaType from hydromt.nodata import NoDataException, NoDataStrategy, _exec_nodata_strat +from hydromt.predefined_catalog import ( + PREDEFINED_CATALOGS, + PredefinedCatalog, + _copy_file, +) from hydromt.typing import Bbox, ErrorHandleMethod, SourceSpecDict, TimeRange from hydromt.utils import partition_dictionaries -from . import __version__ from .data_adapter import ( DataAdapter, DataFrameAdapter, @@ -47,7 +52,7 @@ GeoDatasetAdapter, RasterDatasetAdapter, ) -from .data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator +from .data_adapter.caching import HYDROMT_DATADIR, _uri_validator logger = logging.getLogger(__name__) @@ -59,11 +64,9 @@ class DataCatalog(object): - """Base class for the data catalog object.""" - # root URL with data_catalog file - _url = r"https://raw.githubusercontent.com/Deltares/hydromt/main/data/predefined_catalogs.yml" + _format_version = "v0" # format version of the data catalog _cache_dir = HYDROMT_DATADIR def __init__( @@ -107,7 +110,7 @@ def __init__( elif not isinstance(data_libs, list): # make sure data_libs is a list data_libs = np.atleast_1d(data_libs).tolist() self._sources = {} # dictionary of DataAdapter - self._catalogs = {} # dictionary of predefined Catalogs + self._catalogs: Dict[str, PredefinedCatalog] = {} self._fallback_lib = fallback_lib self.logger = logger @@ -254,7 +257,7 @@ def from_stac_catalog( def predefined_catalogs(self) -> Dict: """Return all predefined catalogs.""" if not self._catalogs: - self.set_predefined_catalogs() + self._set_predefined_catalogs() return self._catalogs def get_source_bbox( @@ -607,60 +610,15 @@ def update_sources(self, **kwargs) -> None: """Add data sources to library or update them.""" self.update(**kwargs) - def set_predefined_catalogs( - self, urlpath: Optional[Union[Path, str]] = None - ) -> Dict: - """Initialise the predefined catalogs.""" - # get predefined_catalogs - urlpath = self._url if urlpath is None else urlpath - cache_path = join(self._cache_dir, basename(urlpath)) - try: - # download file locally; overwrite existing file - _copyfile(urlpath, cache_path) - except Exception: # if offline - self.logger.warning( - "Downloading the predefined catalogs failed;" - "check your internet connection" - ) - pass - if isfile(cache_path): - self._catalogs = _yml_from_uri_or_path(cache_path) - if self._catalogs is None: - raise ConnectionError( - "Predefined catalogs not found; check your internet connection." + def _set_predefined_catalogs(self) -> Dict: + """Set initialized predefined catalogs to _catalogs attribute.""" + for k, cat in PREDEFINED_CATALOGS.items(): + self._catalogs[k] = cat( + format_version=self._format_version, cache_dir=self._cache_dir ) return self._catalogs - def from_artifacts( - self, name: str = "artifact_data", version: str = "latest" - ) -> DataCatalog: - """Parse artifacts. - - Deprecated method. Use - :py:func:`hydromt.data_catalog.DataCatalog.from_predefined_catalogs` instead. - - Parameters - ---------- - name : str, optional - Catalog name. If None (default) sample data is downloaded. - version : str, optional - Release version. By default it takes the latest known release. - - Returns - ------- - DataCatalog - DataCatalog object with parsed artifact data. - """ - warnings.warn( - '"from_artifacts" is deprecated. Use "from_predefined_catalogs instead".', - DeprecationWarning, - stacklevel=2, - ) - return self.from_predefined_catalogs(name, version) - - def from_predefined_catalogs( - self, name: str, version: str = "latest" - ) -> DataCatalog: + def from_predefined_catalogs(self, name: str, version: str = "latest") -> None: """Add data sources from a predefined data catalog. Parameters @@ -670,10 +628,6 @@ def from_predefined_catalogs( version : str, optional Catlog release version. By default it takes the latest known release. - Returns - ------- - DataCatalog - DataCatalog object with parsed predefined catalog added. """ if "=" in name: name, version = name.split("=")[0], name.split("=")[-1] @@ -681,105 +635,58 @@ def from_predefined_catalogs( raise ValueError( f'Catalog with name "{name}" not found in predefined catalogs' ) - urlpath = self.predefined_catalogs[name].get("urlpath") - versions_dict = self.predefined_catalogs[name].get("versions") - if version == "latest" or not isinstance(version, str): - # if a specific version is requested, we don't have to try others - versions = list(versions_dict.keys()) - if len(versions) > 1: - version = versions[np.argmax([Version(v) for v in versions])] - else: - version = versions[0] - - if version not in versions_dict: - raise RuntimeError( - f"Unknown version requested {version}. " - f"options are :{versions_dict.keys()}" - ) - possible_catalg_versions = [(Version(k), v) for k, v in versions_dict.items()] - possible_catalg_versions_sorted = reversed(sorted(possible_catalg_versions)) - - for _, identifier in possible_catalg_versions_sorted: - try: - urlpath = urlpath.format(version=identifier) - if urlpath.split(".")[-1] in ["gz", "zip"]: - self.logger.info(f"Reading data catalog archive {name} {version}") - self.from_archive(urlpath, name=name, version=version) - else: - self.logger.info(f"Reading data catalog {name} {version}") - self.from_yml(urlpath, catalog_name=name) - return self - except RuntimeError: - continue - - raise RuntimeError("No compatible compatible catalog version could be found") - - def from_archive( - self, - urlpath: Union[Path, str], - version: Optional[str] = None, - name: Optional[str] = None, - ) -> DataCatalog: - """Read and cache a data archive including a data_catalog.yml file. - - Parameters - ---------- - urlpath : str, Path - Path or url to data archive. - version : str, optional - Version of data archive, by default None. - name : str, optional - Name of data catalog, by default None. - - Returns - ------- - DataCatalog - DataCatalog object with parsed data archive added. - """ - # add depreaction warning - root = self._cache_archive(urlpath, version=version, name=name) - yml_fn = join(root, "data_catalog.yml") - # parse catalog - return self.from_yml(yml_fn, catalog_name=name) + # cache and get path to data_datalog.yml file of the catalog with + catalog_path = self.predefined_catalogs[name].get_catalog_file(version) + # read catalog + self.logger.info(f"Reading data catalog {name} {version}") + self.from_yml(catalog_path, catalog_name=name) def _cache_archive( self, - archive_fn: Union[Path, str], - version: Optional[str] = None, - name: Optional[str] = None, - ) -> DataCatalog: - """Cache a data archive. + archive_uri: str, + name: str, + version: str = "latest", + sha256: Optional[str] = None, + ) -> str: + """Cache a data archive to the cache directory. + + The archive is unpacked and cached to // Parameters ---------- - archive_fn : str, Path - Path or url to data archive. + archive_uri : str + uri to data archive. + name : str + Name of data catalog version : str, optional - Version of data archive, by default None. - name : str, optional - Name of data catalog, by default None. + Version of data archive, by default 'latest'. + sha256 : str, optional + SHA256 hash of the archive, by default None. Returns ------- - DataCatalog - DataCatalog object with parsed data archive added. + str + Path to the datacatalog of the cached data archive + """ - name = basename(archive_fn).split(".")[0] if name is None else name - root = join(self._cache_dir, name) - if version is not None: - root = join(root, version) - archive_dst_fn = join(root, basename(archive_fn)) - # copy archive to cache - if not isdir(root): - self.logger.debug(f"Caching data from {archive_fn}") - os.makedirs(root, exist_ok=True) - _copyfile(archive_fn, archive_dst_fn) - # unpack data and remove archive - if isfile(archive_dst_fn): - self.logger.debug(f"Unpacking data from {archive_fn}") - shutil.unpack_archive(archive_dst_fn, root) - os.remove(archive_dst_fn) - return root + root = Path(self._cache_dir, name, version) + extract_dir = root / Path(archive_uri).stem + # retrieve and unpack archive + kwargs = {} + if Path(archive_uri).suffix == ".zip": + kwargs.update(processor=pooch.Unzip(extract_dir=extract_dir)) + elif Path(archive_uri).suffix == ".gz": + kwargs.update(processor=pooch.Untar(extract_dir=extract_dir)) + if Path(archive_uri).exists(): # check if arhive is a local file + kwargs.update(donwloader=_copy_file) + pooch.retrieve( + archive_uri, + known_hash=sha256, + path=str(root), + fname=Path(archive_uri).name, + **kwargs, + ) + return extract_dir def from_yml( self, @@ -813,6 +720,8 @@ def from_yml( root: category: version: + name: + sha256: # only if the root is an archive : path: data_type: @@ -866,15 +775,6 @@ def from_yml( # read meta data meta = yml.pop("meta", meta) - # check version required hydromt version - requested_version = meta.get("hydromt_version", None) - if requested_version is not None: - allow_dev = meta.get("allow_dev_version", True) - if not self._is_compatible(__version__, requested_version, allow_dev): - raise RuntimeError( - f"Data catalog requires Hydromt Version {requested_version} which " - f"is incompattible with current hydromt verison {__version__}." - ) if catalog_name is None: catalog_name = cast( str, meta.get("name", "".join(basename(urlpath).split(".")[:-1])) @@ -884,12 +784,12 @@ def from_yml( root = meta.get("root", os.path.dirname(urlpath)) if root.split(".")[-1] in ["gz", "zip"]: # if root is an archive, unpack it at the cache dir - root = self._cache_archive(root, name=catalog_name, version=version) - # save catalog to cache - with open(join(root, f"{catalog_name}.yml"), "w") as f: - data_dict = {"meta": {k: v for k, v in meta.items() if k != "root"}} - data_dict.update(yml) - yaml.dump(data_dict, f, default_flow_style=False, sort_keys=False) + root = self._cache_archive( + archive_uri=root, + name=catalog_name, + version=version, + sha256=meta.get("sha256", None), + ) self.from_dict( yml, catalog_name=catalog_name, @@ -1866,8 +1766,7 @@ def _parse_data_source_dict( def _yml_from_uri_or_path(uri_or_path: Union[Path, str]) -> Dict: if _uri_validator(str(uri_or_path)): with requests.get(uri_or_path, stream=True) as r: - if r.status_code != 200: - raise IOError(f"URL {r.content}: {uri_or_path}") + r.raise_for_status() yml = yaml.load(r.text, Loader=yaml.FullLoader) else: with open(uri_or_path, "r") as stream: diff --git a/hydromt/predefined_catalog.py b/hydromt/predefined_catalog.py new file mode 100644 index 000000000..754bfa583 --- /dev/null +++ b/hydromt/predefined_catalog.py @@ -0,0 +1,261 @@ +"""Implementation of the predefined data catalogs entry points.""" + +import logging +import shutil +import sys +from pathlib import Path +from typing import Callable, ClassVar, Optional + +import packaging.version +import pooch + +from hydromt.data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator + +logger = logging.getLogger(__name__) + +# this is the default location of the predefined catalogs +# in the test environment this is set to local data/catalogs directory using a global fixture +GIT_ROOT = r"https://github.com/Deltares/hydromt/blob/main/data/catalogs" + +__all__ = [ + "PredefinedCatalog", + "DeltaresDataCatalog", + "ArtifactDataCatalog", + "AWSDataCatalog", + "GCSCMIP6DataCatalog", + "create_registry_file", +] + + +def create_registry_file(root: Path, registry_path: Optional[Path] = None) -> None: + """Create a registry file for all catalog files in the root directory. + + The root directory should contain a /data_catalog.yml file per version. + By default the root directory is the cache directory of the catalog instance. + + Parameters + ---------- + root: Path + root directory to search for data_catalog.yml files + """ + # we don't use pooch.create_registry here as we want to only include vaild data_catalog.yml files + registry = {} + for path in root.glob("**/data_catalog.yml"): + key = path.relative_to(root).as_posix() + if not _valid_key(key): + raise ValueError(f"No valid version found in {key}") + if sys.platform == "win32": + # The line endings need to be replaced when operating from windows in order to maintain equality of hashes + _replace_line_endings(path) + file_hash = pooch.file_hash(path) + registry[key] = file_hash + + if not registry: + raise FileNotFoundError(f"No data_catalog.yml files found in {root}") + + if registry_path is None: + registry_path = Path(root / "registry.txt") + with open(registry_path, "w") as f: + for fname, hash in registry.items(): + f.write(f"{fname} {hash}\n") + + +class PredefinedCatalog(object): + """Predefined data catalog. + + A predefined data catalog is a collection of data_catalog.yml files that are stored in a + specific directory structure. The catalog is defined by a base_url and a name. The predefined + catalog can be used to retrieve data_catalog.yml files for specific versions. + + Directory structure: + - /registry.txt + - //data_catalog.yml + + Cached directory structure: + - //registry.txt + - ///data_catalog.yml + """ + + # required class variables to be defined in subclasses + base_url: ClassVar[str] = GIT_ROOT + name: ClassVar[str] = "predefined_catalog" + + def __init__(self, format_version: str = "v0", cache_dir=HYDROMT_DATADIR) -> None: + # init arguments passed by DataCatalog + self._format_version = format_version + self._cache_dir: Path = Path(cache_dir) + # placeholders set by the class + self._pooch: Optional[pooch.Pooch] = None + self._versions: Optional[list[str]] = None + + @property + def registry(self) -> dict: + """Return the registry.""" + return self.pooch.registry + + @property + def pooch(self) -> pooch.Pooch: + """Return a pooch instance with all data catalog files in registry.""" + if self._pooch is None: + self._create_pooch() + self._load_registry_file() + return self._pooch + + @property + def versions(self) -> list[str]: + """Return the versions of the catalog.""" + if not self._versions: + self._versions = self._set_versions() + return self._versions + + def _create_pooch(self) -> None: + self._pooch = pooch.create( + path=self._cache_dir / self.name, + base_url=self.base_url, + retry_if_failed=3, + ) + + def _set_versions(self) -> list[str]: + """Set valid catalog versions.""" + # parse versions from registry, assume registry key is /data_catalog.yml + # keep only versions that match the format_version + keys = self.registry.keys() + _versions = [ + v.split("/")[0] for v in keys if _valid_key(v, self._format_version) + ] + if len(_versions) == 0: + raise RuntimeError( + f"No compatible catalog version could be found for {self.name}." + ) + self._versions = sorted(_versions, key=packaging.version.parse) + return self._versions + + def _load_registry_file(self, overwrite: bool = False) -> None: + """Create a catalog from a yaml file.""" + if self._pooch is None: + self._create_pooch() + if self.registry and not overwrite: + return + registry_path = Path(self._cache_dir / self.name / "registry.txt") + if registry_path.exists(): + registry_path.unlink() + try: # try to retrieve and cache the registry file + _copyfile(f"{self.base_url}/registry.txt", registry_path) + except (ConnectionError, FileNotFoundError): + logger.warning( + f"Failed to retrieve {self.name} versions file from {self.base_url}." + " Creating registry file from cached catalog files." + ) + create_registry_file(registry_path.parent) + if not registry_path.exists(): + raise FileNotFoundError( + f"No cached file found. Failed to retrieve {self.name} versions file" + ) + self.pooch.load_registry(registry_path) + + def get_catalog_file(self, version: Optional[str] = None) -> Optional[Path]: + """Get the cached catalog file path for a specific version. + + Parameters + ---------- + version: str, optional + The version of the catalog to retrieve. If None, the latest version is retrieved. + + Returns + ------- + Path + The path to the cachd catalog file. + """ + if version is None or version == "latest": # get latest version + version = self.versions[-1] + if version not in self.versions: + raise ValueError(f"Version {version} not found in {self.name} catalog") + # get the catalog file + key = f"{version}/data_catalog.yml" + # fetch the file (download if not cached) + path = self.pooch.fetch(key, downloader=self._downloader) + return Path(path) if path else None + + @property + def _downloader(self) -> Optional[Callable]: + if not _uri_validator(self.base_url): + return _copy_file + return None + + +def _valid_key(v: str, format_version: Optional[str] = None) -> bool: + """Check if the key is a valid version.""" + try: + packaging.version.parse(v.split("/")[0]) + return v.startswith(format_version) if format_version else True + except (packaging.version.InvalidVersion, AttributeError): + return False + + +def _copy_file( + url: str, + output_file: str, + pooch: Optional[pooch.Pooch] = None, + check_only: bool = False, +): + """Copy a local file to the cache directory for testing purposes. + + for more info, see: https://www.fatiando.org/pooch/latest/downloaders.html + """ + url = Path(url) + output_file = Path(output_file) + file_exists = url.is_file() + if check_only: + return file_exists + if not file_exists: + raise FileNotFoundError(f"Local file {url} does not exist.") + output_file.parent.mkdir(parents=True, exist_ok=True) + shutil.copyfile(url, output_file) + return output_file + + +class DeltaresDataCatalog(PredefinedCatalog): + """Deltares data catalog.""" + + base_url = f"{GIT_ROOT}/deltares_data" + name = "deltares_data" + + +class ArtifactDataCatalog(PredefinedCatalog): + """Artifact data catalog.""" + + base_url = f"{GIT_ROOT}/artifact_data" + name = "artifact_data" + + +class AWSDataCatalog(PredefinedCatalog): + """AWS data catalog.""" + + base_url = f"{GIT_ROOT}/aws_data" + name = "aws_data" + + +class GCSCMIP6DataCatalog(PredefinedCatalog): + """GCS CMIP6 data catalog.""" + + base_url = f"{GIT_ROOT}/gcs_cmip6_data" + name = "gcs_cmip6_data" + + +# TODO: replace with a entrypoint plugin structure in v1 +PREDEFINED_CATALOGS = { + "artifact_data": ArtifactDataCatalog, + "deltares_data": DeltaresDataCatalog, + "aws_data": AWSDataCatalog, + "gcs_cmip6_data": GCSCMIP6DataCatalog, +} + + +def _replace_line_endings(file_path: Path): + WINDOWS_LINE_ENDING = b"\r\n" + UNIX_LINE_ENDING = b"\n" + with open(file_path, "rb") as open_file: + content = open_file.read() + content = content.replace(WINDOWS_LINE_ENDING, UNIX_LINE_ENDING) + with open(file_path, "wb") as open_file: + open_file.write(content) diff --git a/pixi.lock b/pixi.lock index 97443f5ca..ea38ea77d 100644 --- a/pixi.lock +++ b/pixi.lock @@ -7,10 +7,25 @@ environments: linux-64: - 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sphinx >=3.5 @@ -25356,7 +25368,7 @@ packages: - kind: pypi name: sphinx-click version: 5.1.0 - url: https://files.pythonhosted.org/packages/c5/72/3f1f052aa00fc4c7e9976eb845eeae25dabf4ee73a27618776f9f44009d0/sphinx_click-5.1.0-py3-none-any.whl#sha256=ae97557a4e9ec646045089326c3b90e026c58a45e083b8f35f17d5d6558d08a0 + url: https://files.pythonhosted.org/packages/c5/72/3f1f052aa00fc4c7e9976eb845eeae25dabf4ee73a27618776f9f44009d0/sphinx_click-5.1.0-py3-none-any.whl sha256: ae97557a4e9ec646045089326c3b90e026c58a45e083b8f35f17d5d6558d08a0 requires_dist: - sphinx >=2.0 @@ -25366,7 +25378,7 @@ packages: - kind: pypi name: sphinx-design version: 0.5.0 - url: https://files.pythonhosted.org/packages/17/52/a1e9d72ecf56047df714a3dd0840a5148e4e83c100e8e0046bcea60a1054/sphinx_design-0.5.0-py3-none-any.whl#sha256=1af1267b4cea2eedd6724614f19dcc88fe2e15aff65d06b2f6252cee9c4f4c1e + url: https://files.pythonhosted.org/packages/17/52/a1e9d72ecf56047df714a3dd0840a5148e4e83c100e8e0046bcea60a1054/sphinx_design-0.5.0-py3-none-any.whl sha256: 1af1267b4cea2eedd6724614f19dcc88fe2e15aff65d06b2f6252cee9c4f4c1e requires_dist: - sphinx >=5, <8 diff --git a/pixi.toml b/pixi.toml index 1b8292e62..04613d5e3 100644 --- a/pixi.toml +++ b/pixi.toml @@ -147,6 +147,7 @@ numpy = ">=1.23" packaging = "*" pandas = "*" pip = "*" +pooch = "*" pydantic = "~=2.4" pyflwdir = ">=0.5.4" pyogrio = ">=0.6" diff --git a/pyproject.toml b/pyproject.toml index ed03f8a87..d9eca382d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,6 +23,7 @@ dependencies = [ "numpy>=1.23", # pin necessary to ensure compatability with C headers "packaging", # compare versions of hydromt "pandas", # Dataframes + "pooch", # data fetching "pydantic~=2.4", # Validation "pyflwdir>=0.5.4", # Hight models and derivatives "pyogrio>=0.6", # io for geopandas dataframes diff --git a/tests/conftest.py b/tests/conftest.py index 734bef3ef..a63a19d24 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -11,6 +11,8 @@ from dask import config as dask_config from shapely.geometry import box +from hydromt.predefined_catalog import PREDEFINED_CATALOGS + dask_config.set(scheduler="single-threaded") import hydromt._compat as compat @@ -35,6 +37,31 @@ DATADIR = join(dirname(abspath(__file__)), "data") +@pytest.fixture(autouse=True) +def _local_catalog_eps(monkeypatch) -> dict: + """Set entrypoints to local predefined catalogs.""" + cat_root = Path(__file__).parent.parent / "data" / "catalogs" + for name, cls in PREDEFINED_CATALOGS.items(): + monkeypatch.setattr( + f"hydromt.predefined_catalog.{cls.__name__}.base_url", + str(cat_root / name), + ) + + +@pytest.fixture() +def data_catalog(_local_catalog_eps) -> DataCatalog: + """DataCatalog instance that points to local predefined catalogs.""" + return DataCatalog("artifact_data=v0.0.8") + + +@pytest.fixture(scope="session") +def latest_dd_version_uri(): + cat_root = Path(__file__).parent.parent / "data" / "catalogs" / "deltares_data" + versions = [d.name for d in cat_root.iterdir() if d.is_dir()] + latest_version = sorted(versions)[-1] + return cat_root / latest_version / "data_catalog.yml" + + @pytest.fixture(scope="class") def tmp_dir() -> Path: with TemporaryDirectory() as tempdirname: @@ -349,10 +376,3 @@ def mesh_model(griduda): mod.setup_config(**{"header": {"setting": "value"}}) mod.set_mesh(griduda, "elevtn") return mod - - -@pytest.fixture() -def artifact_data(): - datacatalog = DataCatalog() - datacatalog.from_predefined_catalogs("artifact_data") - return datacatalog diff --git a/tests/test_basin_mask.py b/tests/test_basin_mask.py index 71c713e2e..a82e9f309 100644 --- a/tests/test_basin_mask.py +++ b/tests/test_basin_mask.py @@ -9,8 +9,7 @@ import pytest import xarray as xr -import hydromt -from hydromt import DataCatalog, raster +from hydromt import raster from hydromt.models import MODELS from hydromt.workflows.basin_mask import ( _check_size, @@ -22,14 +21,13 @@ logger = logging.getLogger("tets_basin") -def test_region(tmpdir, world, geodf, rioda): +def test_region(tmpdir, world, geodf, rioda, data_catalog): # prepare test data fn_gdf = str(tmpdir.join("world.geojson")) world.to_file(fn_gdf, driver="GeoJSON") fn_grid = str(tmpdir.join("grid.tif")) rioda.raster.to_raster(fn_grid) - cat = DataCatalog() - cat.from_dict( + data_catalog.from_dict( { "world": { "path": fn_gdf, @@ -62,7 +60,7 @@ def test_region(tmpdir, world, geodf, rioda): assert isinstance(region["geom"], gpd.GeoDataFrame) kind, region = parse_region({"geom": fn_gdf}) assert isinstance(region["geom"], gpd.GeoDataFrame) - kind, region = parse_region({"geom": "world"}, data_catalog=cat) + kind, region = parse_region({"geom": "world"}, data_catalog=data_catalog) assert isinstance(region["geom"], gpd.GeoDataFrame) # geom: points should fail region = {"geom": geodf} @@ -74,7 +72,7 @@ def test_region(tmpdir, world, geodf, rioda): assert isinstance(region["grid"], xr.DataArray) kind, region = parse_region({"grid": fn_grid}) assert isinstance(region["grid"], xr.DataArray) - kind, region = parse_region({"grid": "grid"}, data_catalog=cat) + kind, region = parse_region({"grid": "grid"}, data_catalog=data_catalog) assert isinstance(region["grid"], xr.DataArray) # basid @@ -107,8 +105,7 @@ def test_region(tmpdir, world, geodf, rioda): assert "xy" in region -def test_region_value(): - data_catalog = DataCatalog() +def test_region_value(data_catalog): array = np.array([1001, 1002, 1003, 1004, 1005]) kwarg = _parse_region_value(array, data_catalog=data_catalog) assert kwarg.get("basid") == array.tolist() @@ -137,8 +134,7 @@ def test_check_size(caplog): @pytest.mark.filterwarnings("ignore::UserWarning") -def test_basin(caplog): - data_catalog = hydromt.DataCatalog("artifact_data", logger=logger) +def test_basin(data_catalog): ds = data_catalog.get_rasterdataset("merit_hydro_1k") gdf_bas_index = data_catalog.get_geodataframe("merit_hydro_index") bas_index = data_catalog.get_source("merit_hydro_index") diff --git a/tests/test_data_adapter.py b/tests/test_data_adapter.py index f862c60f9..1d412e4ff 100644 --- a/tests/test_data_adapter.py +++ b/tests/test_data_adapter.py @@ -108,9 +108,9 @@ def test_rasterdataset(rioda, tmpdir): @pytest.mark.skipif(not compat.HAS_GCSFS, reason="GCSFS not installed.") -def test_gcs_cmip6(tmpdir): +def test_gcs_cmip6(): # TODO switch to pre-defined catalogs when pushed to main - catalog_fn = join(CATALOGDIR, "gcs_cmip6_data.yml") + catalog_fn = join(CATALOGDIR, "gcs_cmip6_data", "v0.1.0", "data_catalog.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) ds = data_catalog.get_rasterdataset( "cmip6_NOAA-GFDL/GFDL-ESM4_historical_r1i1p1f1_Amon", @@ -130,7 +130,7 @@ def test_gcs_cmip6(tmpdir): @pytest.mark.skipif(not compat.HAS_S3FS, reason="S3FS not installed.") def test_aws_worldcover(): - catalog_fn = join(CATALOGDIR, "aws_data.yml") + catalog_fn = join(CATALOGDIR, "aws_data", "v0.1.0", "data_catalog.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) da = data_catalog.get_rasterdataset( "esa_worldcover_2020_v100", @@ -161,7 +161,7 @@ def test_http_data(): assert da.raster.shape == (4000, 4000) -def test_rasterdataset_zoomlevels(rioda_large, tmpdir): +def test_rasterdataset_zoomlevels(rioda_large, tmpdir, data_catalog): # write tif with zoom level 1 in name # NOTE zl 0 not written to check correct functioning name = "test_zoom" @@ -176,7 +176,6 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir): } } # test zoom levels in name - data_catalog = DataCatalog() data_catalog.from_dict(yml_dict) rds = cast(RasterDatasetAdapter, data_catalog.get_source(name)) assert rds._parse_zoom_level(None) is None @@ -213,8 +212,8 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir): assert isinstance(da1, xr.Dataset) -def test_rasterdataset_driver_kwargs(artifact_data: DataCatalog, tmpdir): - era5 = artifact_data.get_rasterdataset("era5") +def test_rasterdataset_driver_kwargs(data_catalog: DataCatalog, tmpdir): + era5 = data_catalog.get_rasterdataset("era5") fp1 = join(tmpdir, "era5.zarr") era5.to_zarr(fp1) data_dict = { @@ -251,21 +250,21 @@ def test_rasterdataset_driver_kwargs(artifact_data: DataCatalog, tmpdir): datacatalog.get_source("era5_zarr").to_file(tmpdir, "era5_zarr", driver="zarr") -def test_rasterdataset_unit_attrs(artifact_data: DataCatalog): - era5_dict = {"era5": artifact_data.get_source("era5").to_dict()} +def test_rasterdataset_unit_attrs(data_catalog: DataCatalog): + era5_dict = {"era5": data_catalog.get_source("era5").to_dict()} attrs = { "temp": {"unit": "degrees C", "long_name": "temperature"}, "temp_max": {"unit": "degrees C", "long_name": "maximum temperature"}, "temp_min": {"unit": "degrees C", "long_name": "minimum temperature"}, } era5_dict["era5"].update(dict(attrs=attrs)) - artifact_data.from_dict(era5_dict) - raster = artifact_data.get_rasterdataset("era5") + data_catalog.from_dict(era5_dict) + raster = data_catalog.get_rasterdataset("era5") assert raster["temp"].attrs["unit"] == attrs["temp"]["unit"] assert raster["temp_max"].attrs["long_name"] == attrs["temp_max"]["long_name"] -def test_geodataset(geoda, geodf, ts, tmpdir): +def test_geodataset(geoda, geodf, ts, tmpdir, data_catalog): fn_nc = str(tmpdir.join("test.nc")) fn_gdf = str(tmpdir.join("test.geojson")) fn_csv = str(tmpdir.join("test.csv")) @@ -274,7 +273,6 @@ def test_geodataset(geoda, geodf, ts, tmpdir): geodf.to_file(fn_gdf, driver="GeoJSON") ts.to_csv(fn_csv) hydromt.io.write_xy(fn_csv_locs, geodf) - data_catalog = DataCatalog() # added fn_ts to test if it does not go into xr.open_dataset da1 = data_catalog.get_geodataset( fn_nc, variables=["test1"], bbox=geoda.vector.bounds @@ -324,8 +322,8 @@ def test_geodataset(geoda, geodf, ts, tmpdir): GeoDatasetAdapter(fn_nc).to_file(data_root=td, data_name="test", driver="zarr") -def test_geodataset_unit_attrs(artifact_data: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_attrs(data_catalog: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} attrs = { "waterlevel": { "long_name": "sea surface height above mean sea level", @@ -333,15 +331,15 @@ def test_geodataset_unit_attrs(artifact_data: DataCatalog): } } gtsm_dict["gtsmv3_eu_era5"].update(dict(attrs=attrs)) - artifact_data.from_dict(gtsm_dict) - gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") + data_catalog.from_dict(gtsm_dict) + gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") assert gtsm_geodataarray.attrs["long_name"] == attrs["waterlevel"]["long_name"] assert gtsm_geodataarray.attrs["unit"] == attrs["waterlevel"]["unit"] -def test_geodataset_unit_conversion(artifact_data: DataCatalog): - gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_conversion(data_catalog: DataCatalog): + gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(unit_mult=dict(waterlevel=1000))) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -349,8 +347,8 @@ def test_geodataset_unit_conversion(artifact_data: DataCatalog): assert gtsm_geodataarray1000.equals(gtsm_geodataarray * 1000) -def test_geodataset_set_nodata(artifact_data: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_set_nodata(data_catalog: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(nodata=-99)) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -484,12 +482,11 @@ def test_dataset_to_stac_catalog(tmpdir, timeseries_ds): assert list(stac_item.assets.keys())[0] == "test.nc" -def test_geodataframe(geodf, tmpdir): +def test_geodataframe(geodf, tmpdir, data_catalog): fn_gdf = str(tmpdir.join("test.geojson")) fn_shp = str(tmpdir.join("test.shp")) geodf.to_file(fn_gdf, driver="GeoJSON") geodf.to_file(fn_shp) - data_catalog = DataCatalog() # test read geojson using total bounds gdf1 = data_catalog.get_geodataframe(fn_gdf, bbox=geodf.total_bounds) assert isinstance(gdf1, gpd.GeoDataFrame) @@ -536,20 +533,19 @@ def test_geodataframe(geodf, tmpdir): data_catalog.get_geodataframe("no_file.geojson") -def test_geodataframe_unit_attrs(artifact_data: DataCatalog): - gadm_level1 = {"gadm_level1": artifact_data.get_source("gadm_level1").to_dict()} +def test_geodataframe_unit_attrs(data_catalog: DataCatalog): + gadm_level1 = {"gadm_level1": data_catalog.get_source("gadm_level1").to_dict()} attrs = {"NAME_0": {"long_name": "Country names"}} gadm_level1["gadm_level1"].update(dict(attrs=attrs)) - artifact_data.from_dict(gadm_level1) - gadm_level1_gdf = artifact_data.get_geodataframe("gadm_level1") + data_catalog.from_dict(gadm_level1) + gadm_level1_gdf = data_catalog.get_geodataframe("gadm_level1") assert gadm_level1_gdf["NAME_0"].attrs["long_name"] == "Country names" -def test_dataframe(df, tmpdir): +def test_dataframe(df, tmpdir, data_catalog): # Test reading csv fn_df = str(tmpdir.join("test.csv")) df.to_csv(fn_df) - data_catalog = DataCatalog() df1 = data_catalog.get_dataframe(fn_df, driver_kwargs=dict(index_col=0)) assert isinstance(df1, pd.DataFrame) pd.testing.assert_frame_equal(df, df1) @@ -603,11 +599,10 @@ def test_dataframe_unit_attrs(df: pd.DataFrame, tmpdir): assert np.all(cities_df["test_na"].isna()) -def test_dataframe_time(df_time, tmpdir): +def test_dataframe_time(df_time, tmpdir, data_catalog): # Test time df fn_df_ts = str(tmpdir.join("test_ts.csv")) df_time.to_csv(fn_df_ts) - data_catalog = DataCatalog() dfts1 = data_catalog.get_dataframe( fn_df_ts, driver_kwargs=dict(index_col=0, parse_dates=True) ) @@ -698,12 +693,9 @@ def test_detect_extent(geodf, geoda, rioda, ts): assert np.all(np.equal(rioda_expected_bbox, rioda_detected_bbox)) -def test_to_stac_geodataframe(geodf, tmpdir): +def test_to_stac_geodataframe(geodf, tmpdir, data_catalog): fn_gdf = str(tmpdir.join("test.geojson")) geodf.to_file(fn_gdf, driver="GeoJSON") - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - # geodataframe name = "gadm_level1" adapter = cast(GeoDataFrameAdapter, data_catalog.get_source(name)) @@ -729,10 +721,7 @@ def test_to_stac_geodataframe(geodf, tmpdir): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_raster(): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac_raster(data_catalog): # raster dataset name = "chirps_global" adapter = cast(RasterDatasetAdapter, data_catalog.get_source(name)) @@ -765,10 +754,7 @@ def test_to_stac_raster(): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_geodataset(geoda, tmpdir): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac_geodataset(data_catalog): # geodataset name = "gtsmv3_eu_era5" adapter = cast(GeoDatasetAdapter, data_catalog.get_source(name)) diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 958ffb97a..3229252a1 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -1,7 +1,7 @@ """Tests for the hydromt.data_catalog submodule.""" import os -from os.path import abspath, dirname, isfile, join +from os.path import abspath, dirname, join from pathlib import Path from typing import cast @@ -9,9 +9,9 @@ import numpy as np import pandas as pd import pytest +import requests import xarray as xr -import hydromt.data_catalog from hydromt.data_adapter import ( DataAdapter, GeoDataFrameAdapter, @@ -22,6 +22,7 @@ DataCatalog, _denormalise_data_dict, _parse_data_source_dict, + _yml_from_uri_or_path, ) from hydromt.gis_utils import to_geographic_bbox from hydromt.nodata import NoDataStrategy @@ -108,15 +109,14 @@ def test_parser(): _parse_data_source_dict("test", {}) with pytest.raises(ValueError, match="Data type error unknown"): _parse_data_source_dict("test", {"path": "", "data_type": "error"}) - with pytest.raises( - ValueError, match="alias test not found in data_dict" - ), pytest.deprecated_call(): + with ( + pytest.raises(ValueError, match="alias test not found in data_dict"), + pytest.deprecated_call(), + ): _denormalise_data_dict({"test1": {"alias": "test"}}) -def test_data_catalog_io(tmpdir): - data_catalog = DataCatalog() - _ = data_catalog.sources # load artifact data as fallback +def test_data_catalog_io(tmpdir, data_catalog): # read / write fn_yml = join(tmpdir, "test.yml") data_catalog.to_yml(fn_yml) @@ -129,7 +129,7 @@ def test_data_catalog_io(tmpdir): print(data_catalog.get_source("merit_hydro")) -def test_versioned_catalog_entries(tmpdir): +def test_versioned_catalog_entries(): # make sure the catalogs individually still work legacy_yml_fn = join(DATADIR, "legacy_esa_worldcover.yml") legacy_data_catalog = DataCatalog(data_libs=[legacy_yml_fn]) @@ -213,33 +213,21 @@ def test_versioned_catalog_entries(tmpdir): assert aws_and_legacy_catalog2 == aws_and_legacy_catalog -def test_versioned_catalogs(tmpdir, monkeypatch): - v999_yml_fn = join(tmpdir, "test_sources_v999.yml") - with open(v999_yml_fn, "w") as f: - f.write( - """\ - meta: - hydromt_version: '==999.*' - """ - ) - - DataCatalog().from_predefined_catalogs("deltares_data") - DataCatalog().from_predefined_catalogs("deltares_data", "v2022.7") - - with pytest.raises(RuntimeError, match="Unknown version requested "): - _ = DataCatalog().from_predefined_catalogs("deltares_data", "v1993.7") - - with pytest.raises(RuntimeError, match="Data catalog requires Hydromt Version"): - DataCatalog(data_libs=[v999_yml_fn]) +def test_versioned_catalogs(data_catalog): + data_catalog._sources = {} # reset + data_catalog.from_predefined_catalogs("deltares_data") + assert len(data_catalog.sources) > 0 + data_catalog._sources = {} # reset + data_catalog.from_predefined_catalogs("deltares_data", "v0.5.0") + assert len(data_catalog.sources) > 0 - with monkeypatch.context() as m: - m.setattr(hydromt.data_catalog, "__version__", "999.0.0") - DataCatalog(v999_yml_fn) + with pytest.raises(ValueError, match="Version v1993.7 not found "): + _ = data_catalog.from_predefined_catalogs("deltares_data", "v1993.7") -def test_data_catalog(tmpdir): - data_catalog = DataCatalog() +def test_data_catalog(tmpdir, data_catalog): # initialized with empty dict + data_catalog._sources = {} # reset assert len(data_catalog._sources) == 0 # global data sources from artifacts are automatically added assert len(data_catalog.sources) > 0 @@ -269,12 +257,12 @@ def test_data_catalog(tmpdir): with pytest.deprecated_call(): data_catalog = DataCatalog(deltares_data=False) assert len(data_catalog._sources) == 0 - with pytest.deprecated_call(): - data_catalog.from_artifacts("deltares_data") + data_catalog.from_predefined_catalogs("deltares_data") assert len(data_catalog._sources) > 0 - with pytest.raises( - RuntimeError, match="Unknown version requested" - ), pytest.deprecated_call(): + with ( + pytest.raises(ValueError, match="Version unknown_version not found"), + pytest.deprecated_call(), + ): data_catalog = DataCatalog(deltares_data="unknown_version") # test hydromt version in meta data @@ -283,25 +271,6 @@ def test_data_catalog(tmpdir): data_catalog.to_yml(fn_yml, meta={"hydromt_version": "0.7.0"}) -def test_from_archive(tmpdir): - data_catalog = DataCatalog() - # change cache to tmpdir - data_catalog._cache_dir = str(tmpdir.join(".hydromt_data")) - urlpath = data_catalog.predefined_catalogs["artifact_data"]["urlpath"] - version_hash = list( - data_catalog.predefined_catalogs["artifact_data"]["versions"].values() - )[0] - data_catalog.from_archive(urlpath.format(version=version_hash)) - assert len(data_catalog.iter_sources()) > 0 - source0 = data_catalog.get_source( - next(iter([source_name for source_name, _ in data_catalog.iter_sources()])) - ) - assert ".hydromt_data" in str(source0.path) - # failed to download - with pytest.raises(ConnectionError, match="Data download failed"): - data_catalog.from_archive("https://asdf.com/asdf.zip") - - def test_used_sources(tmpdir): merged_yml_fn = join(DATADIR, "merged_esa_worldcover.yml") data_catalog = DataCatalog(merged_yml_fn) @@ -315,37 +284,33 @@ def test_used_sources(tmpdir): assert sources[0][1].version == source.version -def test_from_yml_with_archive(tmpdir): - yml_fn = join(CATALOGDIR, "artifact_data.yml") - data_catalog = DataCatalog(yml_fn) +def test_from_yml_with_archive(data_catalog): + cache_dir = Path(data_catalog._cache_dir) + data_catalog.from_predefined_catalogs("artifact_data=v0.0.8") sources = list(data_catalog.sources.keys()) assert len(sources) > 0 # as part of the getting the archive a a local # catalog file is written to the same folder # check if this file exists and we can read it - root = dirname(data_catalog.get_source(sources[0]).path) - yml_dst_fn = join(root, "artifact_data.yml") - assert isfile(yml_dst_fn) + yml_dst_fn = Path(cache_dir, "artifact_data", "v0.0.8", "data_catalog.yml") + assert yml_dst_fn.exists() data_catalog1 = DataCatalog(yml_dst_fn) sources = list(data_catalog1.sources.keys()) source = data_catalog1.get_source(sources[0]) - assert dirname(source.path) == root + assert yml_dst_fn.parent == Path(source.path).parent.parent -def test_from_predefined_catalogs(): - data_catalog = DataCatalog() - data_catalog.set_predefined_catalogs( - join(CATALOGDIR, "..", "predefined_catalogs.yml") - ) +def test_from_predefined_catalogs(data_catalog): + assert len(data_catalog.predefined_catalogs) > 0 for name in data_catalog.predefined_catalogs: + data_catalog._sources = {} # reset data_catalog.from_predefined_catalogs(f"{name}=latest") assert len(data_catalog._sources) > 0 - data_catalog._sources = {} # reset with pytest.raises(ValueError, match='Catalog with name "asdf" not found'): data_catalog.from_predefined_catalogs("asdf") -def test_export_global_datasets(tmpdir): +def test_export_global_datasets(tmpdir, data_catalog): DTYPES = { "RasterDatasetAdapter": (xr.DataArray, xr.Dataset), "GeoDatasetAdapter": (xr.DataArray, xr.Dataset), @@ -353,7 +318,7 @@ def test_export_global_datasets(tmpdir): } bbox = [12.0, 46.0, 13.0, 46.5] # Piava river time_tuple = ("2010-02-10", "2010-02-15") - data_catalog = DataCatalog("artifact_data") # read artifacts + data_catalog.from_predefined_catalogs("artifact_data") source_names = [ "era5[precip,temp]", "grwl_mask", @@ -459,8 +424,7 @@ def test_export_dataframe(tmpdir, df, df_time): assert isinstance(obj, dtypes), key -def test_get_rasterdataset(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_rasterdataset(data_catalog): n = len(data_catalog) # raster dataset using three different ways name = "koppen_geiger" @@ -488,8 +452,7 @@ def test_get_rasterdataset(): data_catalog.get_rasterdataset({"name": "test"}) -def test_get_geodataframe(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_geodataframe(data_catalog): n = len(data_catalog) # vector dataset using three different ways name = "osm_coastlines" @@ -513,8 +476,7 @@ def test_get_geodataframe(): data_catalog.get_geodataframe({"name": "test"}) -def test_get_geodataset(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_geodataset(data_catalog): n = len(data_catalog) # geodataset using three different ways name = "gtsmv3_eu_era5" @@ -542,9 +504,8 @@ def test_get_geodataset(): data_catalog.get_geodataset({"name": "test"}) -def test_get_dataset(timeseries_df): +def test_get_dataset(timeseries_df, data_catalog): # get_dataset - data_catalog = DataCatalog("artifact_data") test_dataset = timeseries_df.to_xarray() subset_timeseries = timeseries_df.iloc[[0, len(timeseries_df) // 2]] time_tuple = ( @@ -560,8 +521,7 @@ def test_get_dataset(timeseries_df): assert ds.name == "col1" -def test_get_dataframe(df, tmpdir): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_dataframe(df, tmpdir, data_catalog): n = len(data_catalog) # dataframe using single way name = "test.csv" @@ -586,36 +546,29 @@ def test_get_dataframe(df, tmpdir): data_catalog.get_dataframe({"name": "test"}) -def test_deprecation_warnings(artifact_data): +def test_deprecation_warnings(data_catalog): with pytest.deprecated_call(): # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) - DataCatalog(artifact_data="v0.0.6") + DataCatalog(artifact_data="v0.0.8") with pytest.deprecated_call(): - cat = DataCatalog() - # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') - cat.from_artifacts("artifact_data", version="v0.0.6") - with pytest.deprecated_call(): - fn = artifact_data["chelsa"].path + fn = data_catalog["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) - artifact_data.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) + data_catalog.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) with pytest.deprecated_call(): - fn = artifact_data["gadm_level1"].path + fn = data_catalog["gadm_level1"].path # should be driver_kwargs=dict(assert_gtype='Polygon') - artifact_data.get_geodataframe(fn, assert_gtype="MultiPolygon") + data_catalog.get_geodataframe(fn, assert_gtype="MultiPolygon") with pytest.deprecated_call(): - fn = artifact_data["grdc"].path + fn = data_catalog["grdc"].path # should be driver_kwargs=dict(index_col=0) - artifact_data.get_dataframe(fn, index_col=0) + data_catalog.get_dataframe(fn, index_col=0) with pytest.deprecated_call(): - fn = artifact_data["gtsmv3_eu_era5"].path + fn = data_catalog["gtsmv3_eu_era5"].path # should be driver_kwargs=dict(chunks={'time': 100}) - artifact_data.get_geodataset(fn, chunks={"time": 100}) - + data_catalog.get_geodataset(fn, chunks={"time": 100}) -def test_detect_extent(): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback +def test_detect_extent(data_catalog): # raster dataset name = "chirps_global" bbox = 11.60, 45.20, 13.00, 46.80 @@ -648,10 +601,7 @@ def test_detect_extent(): assert detected_temporal_range == expected_temporal_range -def test_to_stac(tmpdir): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac(tmpdir, data_catalog): _ = data_catalog.get_rasterdataset("chirps_global") _ = data_catalog.get_geodataframe("gadm_level1") _ = data_catalog.get_geodataset("gtsmv3_eu_era5") @@ -674,7 +624,7 @@ def test_to_stac(tmpdir): ) == sorted([Path(join(tmpdir, p, "catalog.json")) for p in ["", *sources, ""]]) -def test_from_stac(tmpdir): +def test_from_stac(): catalog_from_stac = DataCatalog().from_stac_catalog( "./tests/data/stac/catalog.json" ) @@ -682,3 +632,13 @@ def test_from_stac(tmpdir): assert type(catalog_from_stac.get_source("chirps_global")) == RasterDatasetAdapter assert type(catalog_from_stac.get_source("gadm_level1")) == GeoDataFrameAdapter # assert type(catalog_from_stac.get_source("gtsmv3_eu_era5")) == GeoDatasetAdapter + + +def test_yml_from_uri_path(): + uri = "https://google.com/nothinghere" + with pytest.raises(requests.HTTPError): + _yml_from_uri_or_path(uri) + uri = "https://raw.githubusercontent.com/Deltares/hydromt/main/.pre-commit-config.yaml" + yml = _yml_from_uri_or_path(uri) + assert isinstance(yml, dict) + assert len(yml) > 0 diff --git a/tests/test_forcing.py b/tests/test_forcing.py index 63b959657..29147202c 100644 --- a/tests/test_forcing.py +++ b/tests/test_forcing.py @@ -5,14 +5,12 @@ import xarray as xr import hydromt._compat as compat -from hydromt.data_catalog import DataCatalog from hydromt.raster import full_from_transform from hydromt.workflows.forcing import pet, precip -def test_precip(): - cat = DataCatalog() - p_precip = cat.get_rasterdataset("era5", variables="precip") # era hourly +def test_precip(data_catalog): + p_precip = data_catalog.get_rasterdataset("era5", variables="precip") # era hourly # We create a more refined grid p_transform = p_precip.raster.transform @@ -26,7 +24,7 @@ def test_precip(): xr.testing.assert_equal(pout.x, grid.x) # Testing with clim argument - p_clim = cat.get_rasterdataset("worldclim") + p_clim = data_catalog.get_rasterdataset("worldclim") # give it a nodata value in the datacatalog >> issue to # create for the data artifacts p_clim.raster.set_nodata(-999.0) @@ -41,10 +39,9 @@ def test_precip(): @pytest.mark.skipif(not compat.HAS_PYET, reason="pyET not installed.") -def test_pet(): - cat = DataCatalog() - et_data = cat.get_rasterdataset("era5_daily_zarr") - dem = cat.get_rasterdataset("era5_orography").squeeze("time", drop=True) +def test_pet(data_catalog): + et_data = data_catalog.get_rasterdataset("era5_daily_zarr") + dem = data_catalog.get_rasterdataset("era5_orography").squeeze("time", drop=True) peto = pet(et_data, et_data, dem, method="penman-monteith_tdew") diff --git a/tests/test_predefined_catalogs.py b/tests/test_predefined_catalogs.py new file mode 100644 index 000000000..0665e50da --- /dev/null +++ b/tests/test_predefined_catalogs.py @@ -0,0 +1,106 @@ +from pathlib import Path + +import pytest + +from hydromt.predefined_catalog import ( + ArtifactDataCatalog, + PredefinedCatalog, + create_registry_file, +) + + +@pytest.fixture() +def cat_root() -> Path: + return Path(__file__).parent.parent / "data/catalogs" + + +@pytest.fixture() +def tmp_catalog_files(tmpdir): + _base_url = Path(tmpdir) / "test_catalog" + for version in ["v0.1.0", "v0.2.0", "v1.0.0"]: + catalog_path = _base_url / version / "data_catalog.yml" + catalog_path.parent.mkdir(parents=True, exist_ok=True) + catalog_path.write_text("meta:\n version: " + version) + return _base_url + + +@pytest.fixture() +def tmp_catalog_class(tmp_catalog_files) -> type[PredefinedCatalog]: + _base_url = tmp_catalog_files + + # write registry file + create_registry_file(_base_url) + + class TestCatalog(PredefinedCatalog): + name = "test_catalog" + base_url = str(_base_url) + + return TestCatalog + + +def test_predefined_catalog(tmp_catalog_class, tmpdir): + catalog = tmp_catalog_class(format_version="v0", cache_dir=Path(tmpdir) / "cache") + assert catalog.name == "test_catalog" + assert catalog._format_version == "v0" + assert catalog._pooch is None + assert catalog._versions is None + assert ( + catalog.get_catalog_file("v0.1.0") + == catalog._cache_dir / "test_catalog" / "v0.1.0" / "data_catalog.yml" + ) + assert ( + catalog.get_catalog_file() + == catalog._cache_dir / "test_catalog" / "v0.2.0" / "data_catalog.yml" + ) + assert catalog.versions == ["v0.1.0", "v0.2.0"] + + # remove source and cached registry file and check if one is created based on + # the cached catalog files + registry_path = catalog._cache_dir / "test_catalog" / "registry.txt" + registry_path.unlink() + Path(tmp_catalog_class.base_url, "registry.txt").unlink() + catalog._load_registry_file(overwrite=True) + assert registry_path.exists() + + with pytest.raises(ValueError, match="Version v0.0.0 not found"): + catalog.get_catalog_file("v0.0.0") + + +def test_create_registry_file(tmpdir, tmp_catalog_files): + # test create registry file + root = tmp_catalog_files + create_registry_file(root) + registry_path = root / "registry.txt" + assert registry_path.exists() + + # no catalog files + with pytest.raises(FileNotFoundError): + create_registry_file(Path(tmpdir, "not_existing")) + + # create a dummy catalog file with version folder + cat_path = root / "data_catalog.yml" + cat_path.write_text("meta:\n version: v0.1.0") + with pytest.raises(ValueError, match="No valid version found"): + create_registry_file(root) + + +def test_get_versions_artifacts(): + versions = ArtifactDataCatalog().versions + assert len(versions) > 0 + assert "v0.0.8" in versions + + +def test_catalog_versions(cat_root, tmpdir): + # assert all subdirs are catalogs and have a versions.yml file + catalogs = [d for d in cat_root.iterdir() if d.is_dir()] + for cat_dir in catalogs: + registry_file = cat_dir / "registry.txt" + assert registry_file.exists() + tmp_registry_file = Path(tmpdir) / f"{cat_dir.name}_registry.txt" + create_registry_file(cat_dir, tmp_registry_file) + # check if both registry files (incl hashes) are the same + with open(registry_file, "r") as f: + registry = sorted(f.readlines()) + with open(tmp_registry_file, "r") as f: + tmp_registry = sorted(f.readlines()) + assert registry == tmp_registry diff --git a/tests/validators/test_data_catalog_validation.py b/tests/validators/test_data_catalog_validation.py index 34a6e966d..a9c76d0aa 100644 --- a/tests/validators/test_data_catalog_validation.py +++ b/tests/validators/test_data_catalog_validation.py @@ -15,9 +15,8 @@ ) -def test_deltares_data_catalog(): - p = "data/catalogs/deltares_data.yml" - yml_dict = _yml_from_uri_or_path(p) +def test_deltares_data_catalog(latest_dd_version_uri): + yml_dict = _yml_from_uri_or_path(latest_dd_version_uri) # whould raise error if something goes wrong _ = DataCatalogValidator.from_dict(yml_dict) From ce20255ce623140d67c8fdca6dc8afb2a264223d Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 25 Apr 2024 17:03:04 +0200 Subject: [PATCH 076/110] restructured data catalog directory to match main --- .../v.0.0.9/data_catalog.yml} | 0 .../v0.7.0/data_catalog.yml} | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename data/catalogs/{artifact_data.yml => artifact_data/v.0.0.9/data_catalog.yml} (100%) rename data/catalogs/{deltares_data.yml => deltares_data/v0.7.0/data_catalog.yml} (99%) diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data/v.0.0.9/data_catalog.yml similarity index 100% rename from data/catalogs/artifact_data.yml rename to data/catalogs/artifact_data/v.0.0.9/data_catalog.yml diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml similarity index 99% rename from data/catalogs/deltares_data.yml rename to data/catalogs/deltares_data/v0.7.0/data_catalog.yml index c8b3884e4..f1b97d007 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -1,7 +1,7 @@ --- meta: root: p:/wflow_global/hydromt - version: 2024.2 + version: v0.7.0 hydromt_version: '>=0.9, <1.0' From 563949b819e009646a9cc77d4d454a4ed581a99a Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Thu, 25 Apr 2024 19:17:37 +0200 Subject: [PATCH 077/110] Revert "Catalogs refactor" (#909) --- .gitattributes | 2 - .gitignore | 3 - .vscode/extensions.json | 9 + .vscode/launch.json | 13 + .vscode/settings.json | 14 + data/catalogs/README.rst | 7 +- .../data_catalog.yml => artifact_data.yml} | 17 +- data/catalogs/artifact_data/registry.txt | 4 - .../artifact_data/v0.0.6/data_catalog.yml | 712 -- .../artifact_data/v0.0.7/data_catalog.yml | 739 -- .../artifact_data/v0.0.9/data_catalog.yml | 739 -- .../v0.1.0/data_catalog.yml => aws_data.yml} | 5 +- data/catalogs/aws_data/registry.txt | 1 - data/catalogs/changelog.rst | 19 - .../data_catalog.yml => deltares_data.yml} | 34 +- data/catalogs/deltares_data/registry.txt | 2 - .../deltares_data/v0.5.0/data_catalog.yml | 1933 ---- .../data_catalog.yml => gcs_cmip6_data.yml} | 95 +- data/catalogs/gcs_cmip6_data/registry.txt | 1 - data/catalogs/update_versions.py | 11 - data/predefined_catalogs.yml | 8 +- docs/api.rst | 15 +- docs/changelog.rst | 11 - docs/conf.py | 1 + examples/delineate_basin.ipynb | 2 +- examples/export_data.ipynb | 2 +- examples/reading_point_data.ipynb | 2 +- examples/reading_raster_data.ipynb | 2 +- examples/reading_vector_data.ipynb | 2 +- examples/working_with_flow_directions.ipynb | 2 +- examples/working_with_geodatasets.ipynb | 2 +- examples/working_with_meshmodel.ipynb | 2 +- examples/working_with_models.ipynb | 4 +- examples/working_with_raster.ipynb | 2 +- examples/working_with_tiled_raster_data.ipynb | 2 +- hydromt/data_catalog.py | 237 +- hydromt/predefined_catalog.py | 261 - pixi.lock | 8836 ++++++++--------- pixi.toml | 1 - pyproject.toml | 1 - tests/conftest.py | 34 +- tests/test_basin_mask.py | 18 +- tests/test_data_adapter.py | 74 +- tests/test_data_catalog.py | 168 +- tests/test_forcing.py | 15 +- tests/test_predefined_catalogs.py | 106 - .../test_data_catalog_validation.py | 5 +- 47 files changed, 4854 insertions(+), 9321 deletions(-) create mode 100644 .vscode/extensions.json create mode 100644 .vscode/launch.json create mode 100644 .vscode/settings.json rename data/catalogs/{artifact_data/v0.0.8/data_catalog.yml => artifact_data.yml} (97%) delete mode 100644 data/catalogs/artifact_data/registry.txt delete mode 100644 data/catalogs/artifact_data/v0.0.6/data_catalog.yml delete mode 100644 data/catalogs/artifact_data/v0.0.7/data_catalog.yml delete mode 100644 data/catalogs/artifact_data/v0.0.9/data_catalog.yml rename data/catalogs/{aws_data/v0.1.0/data_catalog.yml => aws_data.yml} (88%) delete mode 100644 data/catalogs/aws_data/registry.txt rename data/catalogs/{deltares_data/v0.6.0/data_catalog.yml => deltares_data.yml} (98%) delete mode 100644 data/catalogs/deltares_data/registry.txt delete mode 100644 data/catalogs/deltares_data/v0.5.0/data_catalog.yml rename data/catalogs/{gcs_cmip6_data/v0.1.0/data_catalog.yml => gcs_cmip6_data.yml} (84%) delete mode 100644 data/catalogs/gcs_cmip6_data/registry.txt delete mode 100644 data/catalogs/update_versions.py delete mode 100644 hydromt/predefined_catalog.py delete mode 100644 tests/test_predefined_catalogs.py diff --git a/.gitattributes b/.gitattributes index c6702ae45..d5799bd69 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,4 +1,2 @@ -* text eol=lf - # GitHub syntax highlighting pixi.lock linguist-language=YAML diff --git a/.gitignore b/.gitignore index a3e74545b..ffc641484 100644 --- a/.gitignore +++ b/.gitignore @@ -107,9 +107,6 @@ venv.bak/ .spyderproject .spyproject -# vscode -.vscode/ - # PyCharm .idea diff --git a/.vscode/extensions.json b/.vscode/extensions.json new file mode 100644 index 000000000..414b8a341 --- /dev/null +++ b/.vscode/extensions.json @@ -0,0 +1,9 @@ +{ + "recommendations": [ + "ms-python.python", + "ms-python.debugpy", + "ms-python.vscode-pylance", + "charliermarsh.ruff", + "njpwerner.autodocstring" + ] +} diff --git a/.vscode/launch.json b/.vscode/launch.json new file mode 100644 index 000000000..21ab152d9 --- /dev/null +++ b/.vscode/launch.json @@ -0,0 +1,13 @@ +{ + "version": "0.2.0", + "configurations": [ + { + "name": "Python Debugger: Current File", + "type": "debugpy", + "request": "launch", + "program": "${file}", + "console": "integratedTerminal", + "purpose": ["debug-test"] + } + ] +} diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 000000000..f31a7a366 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,14 @@ +{ + "python.testing.pytestArgs": [ + "tests" + ], + "python.testing.unittestEnabled": false, + "python.testing.pytestEnabled": true, + "[python]": { + "editor.defaultFormatter": "charliermarsh.ruff", + "editor.codeActionsOnSave": { + "source.fixAll": "explicit" + } + }, + "editor.formatOnSave": true +} diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 0e86a6871..58007af48 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -94,10 +94,7 @@ updates ------- - create new branch on github -- make a new folder with the name of the version you are going to create -- copy the latest data catalog into the new folder. -- DO NOT modify old catalogs -- bump the version in the global meta section using semantic versioning -- run update_versions.py, this will create a registry file with the versions and hashes of the data catalogs. It is very important that the files have Linux style line endings (LF) as opposed to windows style line endings (CRLF) to keep hashes consistent. If this is not done, pooch will not be able to find the catalogs. This is done automatically for you (CRLF -> LF) if you are updating from windows. +- make changes and bump the version in the global meta section using `calendar versioning ` - test your yml file (Can the added/changed data sources be read through HydroMT?) - create pull request +- add new version to hydromt\data\predefined_catalogs.yml diff --git a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml b/data/catalogs/artifact_data.yml similarity index 97% rename from data/catalogs/artifact_data/v0.0.8/data_catalog.yml rename to data/catalogs/artifact_data.yml index e4bcfd3c1..e09b16148 100644 --- a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml +++ b/data/catalogs/artifact_data.yml @@ -1,7 +1,7 @@ meta: version: v0.0.8 + hydromt_version: '>=0.9, <1.0' root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz - name: artifact_data chelsa: crs: 4326 @@ -95,8 +95,7 @@ era5: driver: netcdf meta: category: meteo - history: - Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -140,8 +139,7 @@ era5_daily_zarr: driver: zarr meta: category: meteo - history: - Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -248,8 +246,7 @@ gdp_world: meta: category: socio economic source_author: Wilfred Altena - source_info: - data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 source_version: 1.0 @@ -609,8 +606,7 @@ modis_lai: driver: netcdf meta: category: landuse & landcover - notes: - this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) @@ -684,8 +680,7 @@ soilgrids: driver: raster meta: category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ \ distribution version 2.0, european commission and the European soil bureau\ \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt deleted file mode 100644 index e85a01833..000000000 --- a/data/catalogs/artifact_data/registry.txt +++ /dev/null @@ -1,4 +0,0 @@ -v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee -v0.0.8/data_catalog.yml c1cf2229eeb93607ea881fdbced45ebf43471271f0b7d878db8183734274cd88 -v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 diff --git a/data/catalogs/artifact_data/v0.0.6/data_catalog.yml b/data/catalogs/artifact_data/v0.0.6/data_catalog.yml deleted file mode 100644 index e51554f73..000000000 --- a/data/catalogs/artifact_data/v0.0.6/data_catalog.yml +++ /dev/null @@ -1,712 +0,0 @@ -meta: - version: v0.0.6 - root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.6/data.tar.gz - name: artifact_data - -chelsa: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: meteo - paper_doi: 10.1038/sdata.2017.122 - paper_ref: Karger et al. (2017) - source_license: CC BY 4.0 - source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 - path: chelsa.tif -chirps_global: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - paper_doi: 10.3133/ds832 - paper_ref: Funk et al (2014) - source_license: CC - source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 - path: chirps_global.nc - unit_add: - time: 86400 -corine: - data_type: RasterDataset - driver: raster - meta: - category: landuse & landcover - source_author: European Environment Agency - source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata - source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 - path: corine.tif -dtu10mdt: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.1029/2008JC005179 - paper_ref: Andersen and Knudsen (2009) - source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 - unit: m+EGM2008 - path: dtu10mdt.tif -dtu10mdt_egm96: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.1029/2008JC005179 - paper_ref: Andersen and Knudsen (2009) - source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 - unit: m+EGM96 - path: dtu10mdt_egm96.tif -eobs: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: eobs.nc - unit_add: - time: 86400 -eobs_orography: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: eobs_orography.nc -era5: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - history: - Extracted from Copernicus Climate Data Store; resampled by Deltares to - daily frequency - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. (2019) - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels - path: era5.nc - unit_add: - temp: -273.15 - temp_max: -273.15 - temp_min: -273.15 - time: 86400 - unit_mult: - kin: 0.000277778 - kout: 0.000277778 - precip: 1000 - press_msl: 0.01 -era5_hourly: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - history: Extracted from Copernicus Climate Data Store - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. (2019) - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels - path: era5_hourly.nc - unit_add: - temp: -273.15 - unit_mult: - kin: 0.000277778 - kout: 0.000277778 - precip: 1000 - press_msl: 0.01 -era5_orography: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - history: Extracted from Copernicus Climate Data Store - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. 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kwargs: - chunks: - x: 3000 - y: 3000 - mosaic_kwargs: - method: nearest - tileindex: location - meta: - category: null - paper_doi: 10.1126/science.aat0636 - paper_ref: Allen and Pavelsky (2018) - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 - nodata: 0 - path: grwl_tindex.gpkg -gswo: - data_type: RasterDataset - driver: raster - meta: - category: surface water - paper_doi: 10.1038/nature20584 - paper_ref: Pekel et al. (2016) - source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 - nodata: 255 - path: gswo.tif -gtsmv3_eu_era5: - crs: 4326 - data_type: GeoDataset - driver: netcdf - meta: - category: ocean - paper_doi: 10.24381/cds.8c59054f - paper_ref: Copernicus Climate Change Service 2019 - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 - path: gtsmv3_eu_era5.nc -guf_bld_2012: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_doi: 10.1016/j.isprsjprs.2017.10.012 - paper_ref: Esch et al (2017) - source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf - source_url: http://www.dlr.de/guf - path: guf_bld_2012.tif -hydro_lakes: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Arjen Haag - source_info: HydroLAKES.v10_extract - source_version: 1.0 - path: hydro_lakes.gpkg - unit_mult: - Area_avg: 1000000.0 -hydro_reservoirs: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Alessia Matano - source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 - nodata: -99 - path: hydro_reservoirs.gpkg - unit_mult: - Area_avg: 1000000.0 - Capacity_max: 1000000.0 - Capacity_min: 1000000.0 - Capacity_norm: 1000000.0 - Vol_avg: 1000000.0 -koppen_geiger: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: meteo - paper_doi: 10.1127/0941-2948/2006/0130 - paper_ref: Kottek et al. (2006) - source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 - nodata: 0 - path: koppen_geiger.tif -mdt_cnes_cls18: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/os-17-789-2021 - paper_ref: Mulet et al (2021) - source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 - unit: m+GOCO05S - path: mdt_cnes_cls18.tif -merit_hydro: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.1029/2019WR024873 - paper_ref: Yamazaki et al. (2019) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 - path: merit_hydro/{variable}.tif -merit_hydro_1k: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/hess-2020-582 - paper_ref: Eilander et al. 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(in review) - source_license: CC-BY-NC 4.0 - path: merit_hydro_index.gpkg -modis_lai: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: landuse & landcover - notes: - this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the - period '2003-01-01', '2017-12-31' - paper_doi: 10.5067/MODIS/MCD15A3H.006 - paper_ref: Myneni et al (2015) - source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ - source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 - path: modis_lai.nc - unit_mult: - LAI: 0.1 -osm_coastlines: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_coastlines.gpkg -osm_landareas: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_landareas.gpkg -rgi: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - paper_doi: 10.3189/2014JoG13J176 - paper_ref: Pfeffer et al. (2014) - source_info: Randolph Glacier Inventory - source_license: CC BY 4.0 - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 - path: rgi.gpkg -rivers_lin2019_v1: - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - paper_doi: 10.5281/zenodo.3552776 - paper_ref: Lin et al. (2019) - source_license: CC-BY-NC 4.0 - source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 - path: rivers_lin2019_v1.gpkg -simard: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: landuse & landcover - paper_doi: 10.1029/2011JG001708 - paper_ref: Simard et al (2011) - source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - path: simard.tif -soilgrids: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ - \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ - \ distribution version 2.0, european commission and the European soil bureau\ - \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ - \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ - \ Response to european policy support and public data requirements. Land Use\ - \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. 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(2016) - source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 - nodata: 255 - path: gswo.tif -gtsmv3_eu_era5: - crs: 4326 - data_type: GeoDataset - driver: netcdf - meta: - category: ocean - paper_doi: 10.24381/cds.8c59054f - paper_ref: Copernicus Climate Change Service 2019 - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 - path: gtsmv3_eu_era5.nc -guf_bld_2012: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_doi: 10.1016/j.isprsjprs.2017.10.012 - paper_ref: Esch et al (2017) - source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf - source_url: http://www.dlr.de/guf - path: guf_bld_2012.tif -hydro_lakes: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Arjen Haag - source_info: HydroLAKES.v10_extract - source_version: 1.0 - path: hydro_lakes.gpkg - unit_mult: - Area_avg: 1000000.0 -hydro_reservoirs: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Alessia Matano - source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 - nodata: -99 - path: hydro_reservoirs.gpkg - unit_mult: - Area_avg: 1000000.0 - Capacity_max: 1000000.0 - Capacity_min: 1000000.0 - Capacity_norm: 1000000.0 - Vol_avg: 1000000.0 -koppen_geiger: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: meteo - paper_doi: 10.1127/0941-2948/2006/0130 - paper_ref: Kottek et al. (2006) - source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 - nodata: 0 - path: koppen_geiger.tif -mdt_cnes_cls18: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/os-17-789-2021 - paper_ref: Mulet et al (2021) - source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 - unit: m+GOCO05S - path: mdt_cnes_cls18.tif -merit_hydro: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.1029/2019WR024873 - paper_ref: Yamazaki et al. (2019) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 - path: merit_hydro/{variable}.tif -merit_hydro_1k: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/hess-2020-582 - paper_ref: Eilander et al. 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(in review) - source_license: CC-BY-NC 4.0 - path: merit_hydro_index.gpkg -modis_lai: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: landuse & landcover - notes: - this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the - period '2003-01-01', '2017-12-31' - paper_doi: 10.5067/MODIS/MCD15A3H.006 - paper_ref: Myneni et al (2015) - source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ - source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 - path: modis_lai.nc - unit_mult: - LAI: 0.1 -osm_coastlines: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_coastlines.gpkg -osm_landareas: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_landareas.gpkg -rgi: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - paper_doi: 10.3189/2014JoG13J176 - paper_ref: Pfeffer et al. (2014) - source_info: Randolph Glacier Inventory - source_license: CC BY 4.0 - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 - path: rgi.gpkg -rivers_lin2019_v1: - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - paper_doi: 10.5281/zenodo.3552776 - paper_ref: Lin et al. (2019) - source_license: CC-BY-NC 4.0 - source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 - path: rivers_lin2019_v1.gpkg -simard: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: landuse & landcover - paper_doi: 10.1029/2011JG001708 - paper_ref: Simard et al (2011) - source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - path: simard.tif -soilgrids: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ - \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ - \ distribution version 2.0, european commission and the European soil bureau\ - \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ - \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ - \ Response to european policy support and public data requirements. Land Use\ - \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. 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source_license: CC 4.0 - source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 - path: glw_horses.tif -glw_pigs: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_doi: 10.7910/DVN/33N0JG - paper_ref: Gilbert at al (2018) - source_author: glw (Gridded Livestock of World 3 Dataverse) - source_license: CC 4.0 - source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 - path: glw_pigs.tif -glw_sheep: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_doi: 10.7910/DVN/BLWPZN - paper_ref: Gilbert at al (2018) - source_author: glw (Gridded Livestock of World 3 Dataverse) - source_license: CC 4.0 - source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 - path: glw_sheep.tif -grdc: - crs: 4326 - data_type: GeoDataFrame - driver: csv - meta: - category: observed data - source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 - source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 - source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue - path: grdc.csv -grip_roads: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: road - paper_doi: 10.1088/1748-9326/aabd42 - paper_ref: Meijer et al, 2018 - source_license: CC0-1.0 - source_url: https://www.globio.info/download-grip-dataset - source_version: v4 - path: grip_roads.gpkg -grwl: - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - paper_doi: 10.1126/science.aat0636 - paper_ref: Allen and Pavelsky (2018) - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 - path: grwl.gpkg -grwl_mask: - data_type: RasterDataset - driver: raster_tindex - kwargs: - chunks: - x: 3000 - y: 3000 - mosaic_kwargs: - method: nearest - tileindex: location - meta: - paper_doi: 10.1126/science.aat0636 - paper_ref: Allen and Pavelsky (2018) - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 - nodata: 0 - path: grwl_tindex.gpkg -gswo: - data_type: RasterDataset - driver: raster - meta: - category: surface water - paper_doi: 10.1038/nature20584 - paper_ref: Pekel et al. (2016) - source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 - nodata: 255 - path: gswo.tif -gtsmv3_eu_era5: - crs: 4326 - data_type: GeoDataset - driver: netcdf - meta: - category: ocean - paper_doi: 10.24381/cds.8c59054f - paper_ref: Copernicus Climate Change Service 2019 - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 - path: gtsmv3_eu_era5.nc -guf_bld_2012: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_doi: 10.1016/j.isprsjprs.2017.10.012 - paper_ref: Esch et al (2017) - source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf - source_url: http://www.dlr.de/guf - path: guf_bld_2012.tif -hydro_lakes: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Arjen Haag - source_info: HydroLAKES.v10_extract - source_version: 1.0 - path: hydro_lakes.gpkg - unit_mult: - Area_avg: 1000000.0 -hydro_reservoirs: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - source_author: Alessia Matano - source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 - nodata: -99 - path: hydro_reservoirs.gpkg - unit_mult: - Area_avg: 1000000.0 - Capacity_max: 1000000.0 - Capacity_min: 1000000.0 - Capacity_norm: 1000000.0 - Vol_avg: 1000000.0 -koppen_geiger: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: meteo - paper_doi: 10.1127/0941-2948/2006/0130 - paper_ref: Kottek et al. (2006) - source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 - nodata: 0 - path: koppen_geiger.tif -mdt_cnes_cls18: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/os-17-789-2021 - paper_ref: Mulet et al (2021) - source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 - unit: m+GOCO05S - path: mdt_cnes_cls18.tif -merit_hydro: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.1029/2019WR024873 - paper_ref: Yamazaki et al. (2019) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 - path: merit_hydro/{variable}.tif -merit_hydro_1k: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: topography - paper_doi: 10.5194/hess-2020-582 - paper_ref: Eilander et al. (in review) - source_license: CC-BY-NC 4.0 - source_url: https://doi.org/10.5281/zenodo.4138776 - source_version: 0.1 - path: merit_hydro_1k/{variable}.tif -merit_hydro_index: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: topography - paper_doi: 10.5194/hess-2020-582 - paper_ref: Eilander et al. (in review) - source_license: CC-BY-NC 4.0 - path: merit_hydro_index.gpkg -modis_lai: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: landuse & landcover - notes: - this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the - period '2003-01-01', '2017-12-31' - paper_doi: 10.5067/MODIS/MCD15A3H.006 - paper_ref: Myneni et al (2015) - source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ - source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 - path: modis_lai.nc - unit_mult: - LAI: 0.1 -osm_coastlines: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_coastlines.gpkg -osm_landareas: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - source_author: OpenStreetMap - source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: osm_landareas.gpkg -rgi: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - paper_doi: 10.3189/2014JoG13J176 - paper_ref: Pfeffer et al. (2014) - source_info: Randolph Glacier Inventory - source_license: CC BY 4.0 - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 - path: rgi.gpkg -rivers_lin2019_v1: - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - paper_doi: 10.5281/zenodo.3552776 - paper_ref: Lin et al. (2019) - source_license: CC-BY-NC 4.0 - source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 - path: rivers_lin2019_v1.gpkg -simard: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: landuse & landcover - paper_doi: 10.1029/2011JG001708 - paper_ref: Simard et al (2011) - source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - path: simard.tif -soilgrids: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ - \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ - \ distribution version 2.0, european commission and the European soil bureau\ - \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ - \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ - \ Response to european policy support and public data requirements. Land Use\ - \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. (2017) - source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 - path: soilgrids/{variable}.tif - unit_mult: - bd_sl1: 0.001 - bd_sl2: 0.001 - bd_sl3: 0.001 - bd_sl4: 0.001 - bd_sl5: 0.001 - bd_sl6: 0.001 - bd_sl7: 0.001 - oc_sl1: 0.1 - oc_sl2: 0.1 - oc_sl3: 0.1 - oc_sl4: 0.1 - oc_sl5: 0.1 - oc_sl6: 0.1 - oc_sl7: 0.1 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 -vito: - crs: 4326 - data_type: RasterDataset - driver: raster - meta: - category: landuse & landcover - paper_doi: 10.5281/zenodo.3939038 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 - path: vito.tif -wb_countries: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - author: World Bank - category: socio-economic - source_license: CC-BY 4.0 - source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries - timestamp: February 2020 - path: wb_countries.gpkg -worldclim: - crs: 4326 - data_type: RasterDataset - driver: netcdf - meta: - category: meteo - paper_doi: 10.1002/joc.5086 - paper_ref: Fick and Hijmans (2017) - source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 - path: worldclim.nc diff --git a/data/catalogs/aws_data/v0.1.0/data_catalog.yml b/data/catalogs/aws_data.yml similarity index 88% rename from data/catalogs/aws_data/v0.1.0/data_catalog.yml rename to data/catalogs/aws_data.yml index 446a8a2fe..0e2378c2c 100644 --- a/data/catalogs/aws_data/v0.1.0/data_catalog.yml +++ b/data/catalogs/aws_data.yml @@ -1,7 +1,8 @@ --- meta: - version: v0.1.0 - name: aws_data + version: 2024.1.30 + hydromt_version: '>=0.9, <1.0' + esa_worldcover_2020_v100: crs: 4326 diff --git a/data/catalogs/aws_data/registry.txt b/data/catalogs/aws_data/registry.txt deleted file mode 100644 index e1e113d4b..000000000 --- a/data/catalogs/aws_data/registry.txt +++ /dev/null @@ -1 +0,0 @@ -v0.1.0/data_catalog.yml e0e3c4e10bd6ce51014a04b8ca85de0c987b3cfe7bfa16961f772a953a307038 diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index f47ff7746..0748c3a89 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -2,25 +2,6 @@ Change log predefined datasets ============================== -Pre-defined catalog refactor -============================ - -Changed -------- -The pre-defined data catalogs have been moved to their own folders together with -a version.yml. This file describes the different versions and relative paths of -the data catalogs present in the folders. - -- predefined_catalogs.yml is deprecated -- data catalog versions are associated with the SHA-256 hash of the files. -- deltares_data versioning is now in semantic style - -Added ------ -- v0.0.6, v0.0.7, v0.0.9 of the artifact_data -- v0.5.0, v0.6.0 of the deltares_data - - deltares_data ============= diff --git a/data/catalogs/deltares_data/v0.6.0/data_catalog.yml b/data/catalogs/deltares_data.yml similarity index 98% rename from data/catalogs/deltares_data/v0.6.0/data_catalog.yml rename to data/catalogs/deltares_data.yml index 48b627a86..bfaac07ad 100644 --- a/data/catalogs/deltares_data/v0.6.0/data_catalog.yml +++ b/data/catalogs/deltares_data.yml @@ -1,8 +1,9 @@ --- meta: root: p:/wflow_global/hydromt - version: v0.6.0 - name: deltares_data + version: 2024.1.30 + hydromt_version: '>=0.9, <1.0' + basin_atlas_level12_v10: crs: 4326 @@ -140,7 +141,7 @@ copdem30_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" + source_version: '2021_1' nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem.vrt rename: @@ -159,7 +160,7 @@ copdem30_mask_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" + source_version: '2021_1' nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem_mask.vrt rename: @@ -178,7 +179,7 @@ copdem30_masked_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" + source_version: '2021_1' path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn @@ -1084,6 +1085,7 @@ glw_sheeps_v3: source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Sh_2010_Da.tif + grdc: crs: 4326 data_type: GeoDataFrame @@ -1501,14 +1503,14 @@ pcr_globwb: source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py variants: - - version: 1990 - path: hydro/pcr_globwb/glob_1990.zarr - - version: 1995 - path: hydro/pcr_globwb/glob_1995.zarr - - version: 2000 - path: hydro/pcr_globwb/glob_2000.zarr - - version: 2005 - path: hydro/pcr_globwb/glob_2005.zarr + - version: 1990 + path: hydro/pcr_globwb/glob_1990.zarr + - version: 1995 + path: hydro/pcr_globwb/glob_1995.zarr + - version: 2000 + path: hydro/pcr_globwb/glob_2000.zarr + - version: 2005 + path: hydro/pcr_globwb/glob_2005.zarr nodata: -9999 rename: domesticNettoDemand: dom_net @@ -1630,8 +1632,7 @@ soilgrids_v1.0: y: 2400 meta: category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" @@ -1720,8 +1721,7 @@ soilgrids_v2.0: y: 2400 meta: category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt deleted file mode 100644 index 21fbb3c4d..000000000 --- a/data/catalogs/deltares_data/registry.txt +++ /dev/null @@ -1,2 +0,0 @@ -v0.5.0/data_catalog.yml 73c49e04f63229096ccee10051598a615866ec5c5506b0d28d3c93b14b599436 -v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 diff --git a/data/catalogs/deltares_data/v0.5.0/data_catalog.yml b/data/catalogs/deltares_data/v0.5.0/data_catalog.yml deleted file mode 100644 index 1c2a4d100..000000000 --- a/data/catalogs/deltares_data/v0.5.0/data_catalog.yml +++ /dev/null @@ -1,1933 +0,0 @@ ---- -meta: - root: p:/wflow_global/hydromt - version: v0.5.0 - name: deltares_data - -basin_atlas_level12_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - kwargs: - layer: BasinATLAS_v10_lev12 - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 - path: hydrography/hydro_atlas/basin_atlas_v10.gpkg - -river_atlas_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 - path: hydrography/hydro_atlas/river_atlas_v10.gpkg - rename: - dis_m3_pyr: Dis_avg - -lake_atlas_pol_v10: - crs: 4326 - data_type: GeoDataFrame - driver: vector - kwargs: - layer: LakeATLAS_v10_pol - meta: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-022-01425-z - paper_ref: Lehner et al. (2022) - source_license: CC BY 4.0 - source_url: https://www.hydrosheds.org/hydroatlas - source_version: 10 - path: hydrography/hydro_atlas/lake_atlas_v10.gpkg - rename: - dis_m3_pyr: Dis_avg - -chelsa: - alias: chelsa_v1.2 -chelsa_v1.2: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: meteo - paper_doi: 10.1038/sdata.2017.122 - paper_ref: Karger et al. (2017) - source_license: CC BY 4.0 - source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 - path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif - -chirps: - alias: chirps_africa_daily_v2.0 -chirps_africa_daily_v2.0: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - lat: 160 - lon: 150 - time: 20 - combine: by_coords - decode_times: true - parallel: true - meta: - category: meteo - paper_doi: 10.1038/sdata.2015.66 - paper_ref: Funk et al (2015) - source_license: CC - source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 - path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc - rename: - precipitation: precip - unit_add: - time: 86400 - -chirps_global: - alias: chirps_global_daily_v2.0 -chirps_global_daily_v2.0: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 112 - longitude: 400 - time: 20 - combine: by_coords - decode_times: true - parallel: true - meta: - category: meteo - paper_doi: 10.3133/ds832 - paper_ref: Funk et al (2014) - source_license: CC - source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 - path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc - rename: - precipitation: precip - unit_add: - time: 86400 - -copdem30: - alias: copdem30_v2021.1 -copdem30_v2021.1: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" - nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning - path: topography/copdem/copdem.vrt - rename: - copdem: elevtn - -copdem30_mask: - alias: copdem30_mask_v2021.1 -copdem30_mask_v2021.1: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" - nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning - path: topography/copdem/copdem_mask.vrt - rename: - copdem_mask: mask - -copdem30_masked: - alias: copdem30_masked_v2021.1 -copdem30_masked_v2021.1: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 - source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: "2021_1" - path: topography/copdem/copdem_masked.vrt - rename: - copdem_masked: elevtn - -corine: - alias: corine_2018_v2020_u1 -corine_2018_v2020_u1: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 6000 - y: 6000 - meta: - category: landuse - source_author: European Environment Agency - source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata - source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 - path: landuse/corine/CLC2018_CLC2018_V2018_20.tif - -dtu10mdt: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - paper_doi: 10.1029/2008JC005179 - paper_ref: Andersen and Knudsen (2009) - source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 - unit: m+EGM2008 - path: topography/dtu10mdt/DTU10MDT_1min_float32.tif - -dtu10mdt_egm96: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - paper_doi: 10.1029/2008JC005179 - paper_ref: Andersen and Knudsen (2009) - source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 - unit: m+EGM96 - path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif - -eobs: - alias: eobs_v22.0e -eobs_v22.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v23.1e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp - unit_add: - time: 86400 - -eobs_orography_v20.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 20.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc - rename: - elevation: elevtn - -eobs_orography: - alias: eobs_orography_v22.0e -eobs_orography_v22.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - rename: - elevation: elevtn - -eobs_orography_v23.1e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 23.1e - path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - rename: - elevation: elevtn - -eobs_orography_v24.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 24.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - rename: - elevation: elevtn - -eobs_orography_v25.0e: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 100 - longitude: 100 - meta: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 25.0e - path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - rename: - elevation: elevtn - -era5: - alias: era5_daily -era5_daily: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 250 - longitude: 240 - time: 30 - combine: by_coords - decode_times: true - parallel: true - meta: - category: meteo - notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. 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(2019) - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://doi.org/10.24381/cds.bd0915c6 - path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc - -era5_orography: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 120 - longitude: 125 - meta: - category: meteo - notes: Extracted from Copernicus Climate Data Store - paper_doi: 10.1002/qj.3803 - paper_ref: Hersbach et al. (2019) - source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products - source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 - path: meteo/era5/meta/era5_orography_2018.nc - rename: - z: elevtn - unit_mult: - elevtn: 0.10197162129779283 - -esa_worldcover: - alias: esa_worldcover_2020_v100 -esa_worldcover_2020_v100: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 36000 - y: 36000 - meta: - category: landuse - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.5571936 - source_version: v100 - path: landuse/esa_worldcover/esa-worldcover.vrt - -fabdem: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - paper_doi: CC BY-NC-SA 4.0 - paper_ref: Hawker et al. (2022) - source_license: CC BY-NC-SA 4.0 - source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 - source_version: 1.0 - path: topography/fabdem/fabdem.vrt - rename: - fabdem: elevtn - -gadm: - alias: gadm_level0 - -gadm_level0: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: last downloaded 2023-12-18; license required for commercial use - source_author: gadm - source_license: https://gadm.org/license.html - source_url: https://gadm.org/download_world.html - source_version: 4.1 - processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh - path: geography/gadm/version4_1/gadm_level0.fgb - -gadm_level1: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: last downloaded 2023-12-18; license required for commercial use - source_author: gadm - source_license: https://gadm.org/license.html - source_url: https://gadm.org/download_world.html - source_version: 4.1 - processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh - path: geography/gadm/version4_1/gadm_level1.fgb - -gadm_level2: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: last downloaded 2023-12-18; license required for commercial use - source_author: gadm - source_license: https://gadm.org/license.html - source_url: https://gadm.org/download_world.html - source_version: 4.1 - processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh - path: geography/gadm/version4_1/gadm_level2.fgb - -gadm_level3: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: last downloaded 2023-12-18; license required for commercial use - source_author: gadm - source_license: https://gadm.org/license.html - source_url: https://gadm.org/download_world.html - source_version: 4.1 - processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh - path: geography/gadm/version4_1/gadm_level3.fgb - -gcn250: - alias: gcn250_v1 -gcn250_v1: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: soil - paper_doi: 10.1038/s41597-019-0155-x - paper_ref: Jaafar et al. (2019) - source_license: CC BY 4.0 - source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 - nodata: 255 - path: landuse/gcn250/GCN250_*.tif - rename: - GCN250_ARCI: cn_dry - GCN250_ARCII: cn_avg - GCN250_ARCIII: cn_wet - -gdp_world: - alias: gdp_world_v1 -gdp_world_v1: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: socio-economic - notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) - source_author: Wilfred Altena - source_license: CC BY-4.0 - source_version: 1.0 - path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb - rename: - GDP: gdp - unit_mult: - gdp: 0.001 - -gebco: - alias: gebco_v2020 -gebco_v2020: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: topography - paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 - paper_ref: Weatherall et al (2020) - source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 - source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ - source_version: 2020 - unit: m+MSL - path: bathymetry/gebco/gebco.vrt - rename: - gebco: elevtn - -ghs_pop: - alias: ghs_pop_2015_54009_v2019a -ghs_pop_2015_4326_v2019a: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F - paper_ref: Schiavina et al (2019) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 - path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif - -ghs_pop_2015_54009_v2019a: - crs: "ESRI:54009" - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 1000 - y: 1000 - meta: - category: socio-economic - paper_doi: 10.2760/062975 - paper_ref: Florczyk et al (2019) - source_license: CC BY 4.0 - source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop - path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif - -ghs_smod: - alias: ghs_smod_2015_54009_v2019a -ghs_smod_2015_54009_v2016a: - crs: "ESRI:54009" - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_ref: Pesaresi and Freire (2016) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - -ghs_smod_2015_54009_v2019a: - crs: "ESRI:54009" - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 - path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif - -globcover: - alias: globcover_2009_v2.3 -globcover_2009_v2.3: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.1594/PANGAEA.787668 - paper_ref: Arino et al (2012) - source_license: CC-BY-3.0 - source_url: http://due.esrin.esa.int/page_globcover.php - source_version: v2.3 - path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif - -glofas_era5_v31: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - time: 180 - latitude: 150 - longitude: 360 - combine: by_coords - decode_times: true - parallel: true - meta: - category: hydro - notes: Extracted from Copernicus Climate Data Store - paper_doi: 10.5194/essd-12-2043-2020 - paper_ref: Harrigan et al. 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chunks: - x: 3600 - y: 3600 - meta: - category: socio-economic - paper_doi: 10.7910/DVN/BLWPZN - paper_ref: Gilbert at al (2018) - source_author: glw (Gridded Livestock of World 3 Dataverse) - source_license: CC 4.0 - source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 - path: socio_economic/glw/5_Sh_2010_Da.tif - -grdc: - crs: 4326 - data_type: GeoDataFrame - driver: xlsx - kwargs: - index_col: grdc_no - meta: - category: observed data - notes: GRDC-Station Catalogue, last downloaded 2020-07-16 - source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 - source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue - path: hydro/grdc/GRDC_Stations.xlsx - rename: - area: uparea - -grip_roads: - alias: grip_roads_v4 -grip_roads_v4: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: road - source_url: https://www.globio.info/download-grip-dataset - paper_ref: Meijer et al, 2018 - paper_doi: 10.1088/1748-9326/aabd42 - source_license: CC0-1.0 - source_version: v4 - path: infrastructure/grip/GRIP4_world.fgb - rename: - GP_RTP: road_type - GP_RCY: country_code - -grwl: - alias: grwl_v1.01 -grwl_v1.01: - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - paper_doi: 10.1126/science.aat0636 - paper_ref: Allen and Pavelsky (2018) - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 - path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb - -grwl_mask: - alias: grwl_mask_v1.01 -grwl_mask_v1.01: - data_type: RasterDataset - driver: raster_tindex - kwargs: - chunks: - x: 3000 - y: 3000 - mosaic_kwargs: - method: nearest - tileindex: location - meta: - category: hydrography - paper_doi: 10.1126/science.aat0636 - paper_ref: Allen and Pavelsky (2018) - source_license: CC BY 4.0 - source_url: https://doi.org/10.5281/zenodo.1297434 - 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(2016) - source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 - nodata: 255 - path: hydrography/gswo/occur.vrt - -gtsm_codec_reanalysis_{freq}_v1: - crs: 4326 - data_type: GeoDataset - driver: netcdf - kwargs: - chunks: - stations: 10 - time: -1 - meta: - category: ocean - paper_doi: 10.3389/fmars.2020.00263 - paper_ref: Muis at al (2020) - source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf - source_url: https://doi.org/10.24381/cds.8c59054f - source_version: v1 - path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc - placeholders: - freq: [10min, hourly, dailymax] - rename: - station_x_coordinate: lon - station_y_coordinate: lat - stations: index - -guf_bld_2012: - alias: guf_bld_2012_v02 -guf_bld_2012_v02: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 1000 - y: 1000 - meta: - category: socio-economic - paper_doi: 10.1016/j.isprsjprs.2017.10.012 - paper_ref: Esch et al (2017) - source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf - source_url: http://www.dlr.de/guf - path: infrastructure/guf/GUF04_DLR_v02.vrt - -hydro_lakes: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - notes: HydroLAKES.v10_extract - source_author: Arjen Haag - source_version: 1.0 - path: hydrography/lakes/lake-db.fgb - rename: - Depth_avg: Depth_avg - Dis_avg: Dis_avg - Hylak_id: waterbody_id - Lake_area: Area_avg - Pour_lat: yout - Pour_long: xout - Vol_total: Vol_avg - unit_mult: - Area_avg: 1000000.0 - -hydro_reservoirs: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_author: Alessia Matano - source_version: 1.0 - nodata: -99 - path: hydrography/reservoirs/reservoir-db.fgb - rename: - Depth_avg: Depth_avg - Dis_avg: Dis_avg - G_CAP_MAX: Capacity_max - G_CAP_MIN: Capacity_min - G_CAP_REP: Capacity_norm - G_DAM_HGT_: Dam_height - Grand_id: waterbody_id - Hylak_id: Hylak_id - Lake_area: Area_avg - Pour_lat: yout - Pour_long: xout - Vol_total: Vol_avg - unit_mult: - Area_avg: 1000000.0 - Capacity_max: 1000000.0 - Capacity_min: 1000000.0 - Capacity_norm: 1000000.0 - Vol_avg: 1000000.0 - -koppen_geiger: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: meteo - paper_doi: 10.1127/0941-2948/2006/0130 - paper_ref: Kottek et al. (2006) - source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 - nodata: 0 - path: meteo/climate_classification_v2017/Map_KG-Global.tif - -mdt_cnes_cls18: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 720 - y: 720 - meta: - category: topography - paper_doi: 10.5194/os-17-789-2021 - paper_ref: Mulet et al (2021) - source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 - unit: m+GOCO05S - path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif - -merit: - alias: merit_v1.0.3 -merit_v1.0.3: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - drop_variables: projection - chunks: - lat: 6000 - lon: 6000 - meta: - category: topography - paper_doi: 10.1002/2017GL072874 - paper_ref: Yamazaki et al. (2018) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ - source_version: 1.0.3 - path: topography/merit/merit.nc - rename: - elevation: elevtn - -merit_hydro: - alias: merit_hydro_v1.0 -merit_hydro_v1.0: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 6000 - y: 6000 - meta: - category: topography - paper_doi: 10.1029/2019WR024873 - paper_ref: Yamazaki et al. (2019) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 - path: topography/merit_hydro/*.vrt - rename: - bas: basins - dir: flwdir - elv: elevtn - slp: lndslp - sto: strord - upa: uparea - upg: upgrid - wth: rivwth - -merit_hydro_ihu: - alias: merit_hydro_ihu_30sec_v1.0 -merit_hydro_ihu_30sec_v1.0: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 6000 - y: 6000 - meta: - category: topography - paper_doi: 10.5194/hess-2020-582 - paper_ref: Eilander et al. (2021) - source_license: ODC-By 1.0 - source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk - source_doi: 10.5281/zenodo.5166932 - source_version: 1.0 - path: topography/merit_hydro_ihu/30sec/*.tif - rename: - 30sec_basids: basins - 30sec_flwdir: flwdir - 30sec_elevtn: elevtn - 30sec_strord: strord - 30sec_uparea: uparea - 30sec_rivlen: rivlen - 30sec_rivslp: rivslp - -merit_hydro_ihu_index: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: topography - paper_doi: 10.5194/hess-25-5287-2021 - paper_ref: Eilander et al. (2021) - source_license: CC-BY-NC 4.0 - source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk - path: topography/merit_hydro_ihu/30sec/basins.gpkg - -merit_hydro_index: - alias: merit_hydro_index_v1.0 -merit_hydro_index_v1.0: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: topography - paper_doi: 10.5194/hess-25-5287-2021 - paper_ref: Eilander et al. (2021) - source_license: CC-BY-NC 4.0 - path: topography/merit_hydro/basin_index.fgb - -merit_hydro_patch: - alias: merit_hydro_patch_v1.0 -merit_hydro_patch_v1.0: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 6000 - y: 6000 - meta: - category: topography - paper_doi: 10.1029/2019WR024873 - paper_ref: Yamazaki et al. (2019) - source_license: CC-BY-NC 4.0 or ODbL 1.0 - source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 Deltares patch - path: topography/merit_hydro/patches/*.vrt - rename: - bas: basins - dir: flwdir - elv: elevtn - slp: lndslp - sto: strord - upa: uparea - upg: upgrid - wth: rivwth - -modis_lai: - alias: modis_mcd15a3h_v006 -modis_mcd15a3h_v006: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - concat: true - meta: - category: landuse - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' - paper_doi: 10.5067/MODIS/MCD15A3H.006 - paper_ref: Myneni et al (2015) - source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ - source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 - path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif - unit_mult: - LAI: 0.1 - -osm_coastlines: - alias: osm_coastlines_v20200109 -osm_coastlines_v20200109: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 - source_author: OpenStreetMap - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: geography/osm/osm_coastlines-db.fgb - rename: - fid: coastline_id - -osm_landareas: - alias: osm_landareas_v20200109 -osm_landareas_v20200109: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: geography - notes: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 - source_author: OpenStreetMap - source_license: ODbL - source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 - path: geography/osm/osm_landareas-db.fgb - rename: - fid: land_id - -pcr_globwb: - crs: 4326 - data_type: RasterDataset - driver: zarr - kwargs: - chunks: auto - meta: - category: water demand - notes: last downloaded 2023-11-23 - paper_doi: 10.5281/zenodo.1045339 - paper_ref: Sutanudjaja, E. H., et al (2017) - source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR - source_version: 2017.11b1 - processing_script: hydro/pcr_globwb/prep_glob.py - variants: - - version: 1990 - path: hydro/pcr_globwb/glob_1990.zarr - - version: 1995 - path: hydro/pcr_globwb/glob_1995.zarr - - version: 2000 - path: hydro/pcr_globwb/glob_2000.zarr - - version: 2005 - path: hydro/pcr_globwb/glob_2005.zarr - nodata: -9999 - rename: - domesticNettoDemand: dom_net - domesticGrossDemand: dom_gross - industryNettoDemand: ind_net - industryGrossDemand: ind_gross - livestockNettoDemand: lsk_net - livestockGrossDemand: lsk_gross - unit_mult: - dom_net: 1000 - dom_gross: 1000 - ind_net: 1000 - ind_gross: 1000 - lsk_net: 1000 - lsk_gross: 1000 - -rgi: - alias: rgi_v0.6 -rgi_v0.6: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: surface water - notes: Randolph Glacier Inventory - paper_doi: 10.3189/2014JoG13J176 - paper_ref: Pfeffer et al. (2014) - source_license: CC BY 4.0 - source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 - path: hydrography/rgi/rgi.fgb - rename: - C3S_ID: C3S_id - GLIMSID: GLIMS_id - ID: simple_id - RGIID: RGI_id - -rivers_lin2019_v1: - data_type: GeoDataFrame - driver: vector - meta: - category: hydrography - paper_doi: 10.5281/zenodo.3552776 - paper_ref: Lin et al. (2019) - source_license: CC-BY-NC 4.0 - source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 - path: hydrography/rivers_lin2019/rivers_ge30m.fgb - rename: - width_m: rivwth - Q2: qbankfull - -simard: - alias: simard_v2011 -simard_v2011: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.1029/2011JG001708 - paper_ref: Simard et al (2011) - source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 - path: landuse/simard/sdat_10023_canopy_height_simard.tif - -SM2RAIN_ASCAT_monthly_025_v1.4: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 360 - longitude: 720 - time: 84 - meta: - category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution - paper_doi: 10.5194/essd-11-1583-2019 - paper_ref: Brocca et al. (2019) - source_license: https://creativecommons.org/licenses/by/4.0/legalcode - source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc - rename: - rainfall: precip - -SM2RAIN_ASCAT_monthly_05_v1.4: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - latitude: 180 - longitude: 360 - time: 84 - meta: - category: meteo - notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution - paper_doi: 10.5194/essd-11-1583-2019 - paper_ref: Brocca et al. (2019) - source_license: https://creativecommons.org/licenses/by/4.0/legalcode - source_url: https://zenodo.org/record/4570192#.YueKJWNByUl - path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc - rename: - rainfall: precip - -soilgrids: - alias: soilgrids_v1.0 -soilgrids_v1.0: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 2400 - y: 2400 - meta: - category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: 10.1371/journal.pone.0169748 - paper_ref: Hengl et al. (2017) - source_license: ODbL - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 - path: soil/soilgrids_v1.0/*_250m_ll.tif - rename: - BLDFIE_M_sl1_250m_ll: bd_sl1 - BLDFIE_M_sl2_250m_ll: bd_sl2 - BLDFIE_M_sl3_250m_ll: bd_sl3 - BLDFIE_M_sl4_250m_ll: bd_sl4 - BLDFIE_M_sl5_250m_ll: bd_sl5 - BLDFIE_M_sl6_250m_ll: bd_sl6 - BLDFIE_M_sl7_250m_ll: bd_sl7 - CLYPPT_M_sl1_250m_ll: clyppt_sl1 - CLYPPT_M_sl2_250m_ll: clyppt_sl2 - CLYPPT_M_sl3_250m_ll: clyppt_sl3 - CLYPPT_M_sl4_250m_ll: clyppt_sl4 - CLYPPT_M_sl5_250m_ll: clyppt_sl5 - CLYPPT_M_sl6_250m_ll: clyppt_sl6 - CLYPPT_M_sl7_250m_ll: clyppt_sl7 - ORCDRC_M_sl1_250m_ll: oc_sl1 - ORCDRC_M_sl2_250m_ll: oc_sl2 - ORCDRC_M_sl3_250m_ll: oc_sl3 - ORCDRC_M_sl4_250m_ll: oc_sl4 - ORCDRC_M_sl5_250m_ll: oc_sl5 - ORCDRC_M_sl6_250m_ll: oc_sl6 - ORCDRC_M_sl7_250m_ll: oc_sl7 - PHIHOX_M_sl1_250m_ll: ph_sl1 - PHIHOX_M_sl2_250m_ll: ph_sl2 - PHIHOX_M_sl3_250m_ll: ph_sl3 - PHIHOX_M_sl4_250m_ll: ph_sl4 - PHIHOX_M_sl5_250m_ll: ph_sl5 - PHIHOX_M_sl6_250m_ll: ph_sl6 - PHIHOX_M_sl7_250m_ll: ph_sl7 - SLTPPT_M_sl1_250m_ll: sltppt_sl1 - SLTPPT_M_sl2_250m_ll: sltppt_sl2 - SLTPPT_M_sl3_250m_ll: sltppt_sl3 - SLTPPT_M_sl4_250m_ll: sltppt_sl4 - SLTPPT_M_sl5_250m_ll: sltppt_sl5 - SLTPPT_M_sl6_250m_ll: sltppt_sl6 - SLTPPT_M_sl7_250m_ll: sltppt_sl7 - SNDPPT_M_sl1_250m_ll: sndppt_sl1 - SNDPPT_M_sl2_250m_ll: sndppt_sl2 - SNDPPT_M_sl3_250m_ll: sndppt_sl3 - SNDPPT_M_sl4_250m_ll: sndppt_sl4 - SNDPPT_M_sl5_250m_ll: sndppt_sl5 - SNDPPT_M_sl6_250m_ll: sndppt_sl6 - SNDPPT_M_sl7_250m_ll: sndppt_sl7 - SoilThickness_250m_ll: soilthickness - TAXOUSDA_250m_ll: tax_usda - unit_mult: - bd_sl1: 0.001 - bd_sl2: 0.001 - bd_sl3: 0.001 - bd_sl4: 0.001 - bd_sl5: 0.001 - bd_sl6: 0.001 - bd_sl7: 0.001 - oc_sl1: 0.1 - oc_sl2: 0.1 - oc_sl3: 0.1 - oc_sl4: 0.1 - oc_sl5: 0.1 - oc_sl6: 0.1 - oc_sl7: 0.1 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - -soilgrids_2020: - alias: soilgrids_v2.0 -soilgrids_v2.0: - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 2400 - y: 2400 - meta: - category: soil - notes: - "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil - database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, - P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. - Land Use Policy 29 (2), 329–338. \n" - paper_doi: https://doi.org/10.5194/soil-2020-65 - paper_ref: de Sousa et al. (2020) - source_license: CC BY 4.0 - source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids - source_version: 2020 - path: soil/soilgrids_v2.0/*/*_mean.vrt - rename: - bdod_0-5cm_mean: bd_sl1 - bdod_5-15cm_mean: bd_sl2 - bdod_15-30cm_mean: bd_sl3 - bdod_30-60cm_mean: bd_sl4 - bdod_60-100cm_mean: bd_sl5 - bdod_100-200cm_mean: bd_sl6 - clay_0-5cm_mean: clyppt_sl1 - clay_5-15cm_mean: clyppt_sl2 - clay_15-30cm_mean: clyppt_sl3 - clay_30-60cm_mean: clyppt_sl4 - clay_60-100cm_mean: clyppt_sl5 - clay_100-200cm_mean: clyppt_sl6 - soc_0-5cm_mean: oc_sl1 - soc_5-15cm_mean: oc_sl2 - soc_15-30cm_mean: oc_sl3 - soc_30-60cm_mean: oc_sl4 - soc_60-100cm_mean: oc_sl5 - soc_100-200cm_mean: oc_sl6 - phh2o_0-5cm_mean: ph_sl1 - phh2o_5-15cm_mean: ph_sl2 - phh2o_15-30cm_mean: ph_sl3 - phh2o_30-60cm_mean: ph_sl4 - phh2o_60-100cm_mean: ph_sl5 - phh2o_100-200cm_mean: ph_sl6 - silt_0-5cm_mean: sltppt_sl1 - silt_5-15cm_mean: sltppt_sl2 - silt_15-30cm_mean: sltppt_sl3 - silt_30-60cm_mean: sltppt_sl4 - silt_60-100cm_mean: sltppt_sl5 - silt_100-200cm_mean: sltppt_sl6 - sand_0-5cm_mean: sndppt_sl1 - sand_5-15cm_mean: sndppt_sl2 - sand_15-30cm_mean: sndppt_sl3 - sand_30-60cm_mean: sndppt_sl4 - sand_60-100cm_mean: sndppt_sl5 - sand_100-200cm_mean: sndppt_sl6 - SoilThickness_250_mean: soilthickness - TAXOUSDA_250_mean: tax_usda - unit_mult: - bd_sl1: 0.01 - bd_sl2: 0.01 - bd_sl3: 0.01 - bd_sl4: 0.01 - bd_sl5: 0.01 - bd_sl6: 0.01 - bd_sl7: 0.01 - oc_sl1: 0.01 - oc_sl2: 0.01 - oc_sl3: 0.01 - oc_sl4: 0.01 - oc_sl5: 0.01 - oc_sl6: 0.01 - oc_sl7: 0.01 - ph_sl1: 0.1 - ph_sl2: 0.1 - ph_sl3: 0.1 - ph_sl4: 0.1 - ph_sl5: 0.1 - ph_sl6: 0.1 - ph_sl7: 0.1 - clyppt_sl1: 0.1 - clyppt_sl2: 0.1 - clyppt_sl3: 0.1 - clyppt_sl4: 0.1 - clyppt_sl5: 0.1 - clyppt_sl6: 0.1 - clyppt_sl7: 0.1 - sltppt_sl1: 0.1 - sltppt_sl2: 0.1 - sltppt_sl3: 0.1 - sltppt_sl4: 0.1 - sltppt_sl5: 0.1 - sltppt_sl6: 0.1 - sltppt_sl7: 0.1 - sndppt_sl1: 0.1 - sndppt_sl2: 0.1 - sndppt_sl3: 0.1 - sndppt_sl4: 0.1 - sndppt_sl5: 0.1 - sndppt_sl6: 0.1 - sndppt_sl7: 0.1 - -vito: - alias: vito_2015_v2.0.2 -vito_2015_v2.0.2: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.5281/zenodo.3939038 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 - path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif - -vito_2016_v3.0.1: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.5281/zenodo.3518026 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 - path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif - -vito_2017_v3.0.1: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.5281/zenodo.3518036 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 - path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif - -vito_2018_v3.0.1: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.5281/zenodo.3518038 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 - path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif - -vito_2019_v3.0.1: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 3600 - y: 3600 - meta: - category: landuse - paper_doi: 10.5281/zenodo.3939050 - paper_ref: Buchhorn et al (2020) - source_url: https://land.copernicus.eu/global/products/lc - source_version: v3.0.1 - path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif - -wb_countries: - alias: wb_countries_v20200319 -wb_countries_v20200319: - crs: 4326 - data_type: GeoDataFrame - driver: vector - meta: - category: socio-economic - source_author: World Bank - source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries - source_license: CC-BY 4.0 - timestamp: February 2020 - path: geography/wb/WB_countries_Admin0.fgb - rename: - ISO_A3: country_iso - ISO_N3: country_code - POP_EST: population - GDP_MD_EST: gdp_pc - GDP_kD_PPP: gdp - unit_mult: - gdp_pc: 1000 - -worldclim: - alias: worldclim_v2.0 -worldclim_v2.0: - crs: 4326 - data_type: RasterDataset - driver: netcdf - kwargs: - chunks: - lat: 3600 - lon: 3600 - meta: - category: meteo - paper_doi: 10.1002/joc.5086 - paper_ref: Fick and Hijmans (2017) - source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 - nodata: -999.0 - path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc - rename: - prec: precip - -worldpop_2020_constrained: - data_type: RasterDataset - driver: raster - kwargs: - chunks: auto - meta: - category: socio-economic - paper_doi: 10.1371/journal.pone.0107042 - paper_ref: Stevens et al. (2015) - source_license: CC BY 4.0 - source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 - nodata: -99999 - path: socio_economic/worldpop/ppp_2020_constrained.vrt - rename: - ppp_2020_constrained: population - -worldpop_2020_UNadj_constrained: - alias: worldpop_2020_constrained - path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt - rename: - ppp_2020_UNadj_constrained: population - -wsf_bld_2015: - alias: wsf_bld_2015_v1 -wsf_bld_2015_v1: - crs: 4326 - data_type: RasterDataset - driver: raster - kwargs: - chunks: - x: 1000 - y: 1000 - meta: - category: socio-economic - paper_doi: 10.1038/s41597-020-00580-5 - paper_ref: Marconcini at al (2020) - source_license: CC0 1.0 - source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc - path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt diff --git a/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml b/data/catalogs/gcs_cmip6_data.yml similarity index 84% rename from data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml rename to data/catalogs/gcs_cmip6_data.yml index 2904536b4..b933c6dc0 100644 --- a/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml +++ b/data/catalogs/gcs_cmip6_data.yml @@ -1,7 +1,7 @@ --- meta: - version: v0.1.0 - name: gcs_cmip6_data + version: 2024.1.30 + hydromt_version: '>=0.8.1, <1.0' cmip6_{model}_historical_{member}_{timestep}: crs: 4326 @@ -21,32 +21,9 @@ cmip6_{model}_historical_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: - [ - IPSL/IPSL-CM6A-LR, - SNU/SAM0-UNICON, - NCAR/CESM2, - NCAR/CESM2-WACCM, - INM/INM-CM4-8, - INM/INM-CM5-0, - NOAA-GFDL/GFDL-ESM4, - NCC/NorESM2-LM, - NIMS-KMA/KACE-1-0-G, - CAS/FGOALS-f3-L, - CSIRO-ARCCSS/ACCESS-CM2, - NCC/NorESM2-MM, - CSIRO/ACCESS-ESM1-5, - NCAR/CESM2-WACCM-FV2, - NCAR/CESM2-FV2, - CMCC/CMCC-CM2-SR5, - AS-RCEC/TaiESM1, - NCC/NorCPM1, - IPSL/IPSL-CM5A2-INCA, - CMCC/CMCC-CM2-HR4, - CMCC/CMCC-ESM2, - IPSL/IPSL-CM6A-LR-INCA, - E3SM-Project/E3SM-1-0, - ] + model: [IPSL/IPSL-CM6A-LR, SNU/SAM0-UNICON, NCAR/CESM2, NCAR/CESM2-WACCM, INM/INM-CM4-8, INM/INM-CM5-0, NOAA-GFDL/GFDL-ESM4, NCC/NorESM2-LM, NIMS-KMA/KACE-1-0-G, + CAS/FGOALS-f3-L, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, CSIRO/ACCESS-ESM1-5, NCAR/CESM2-WACCM-FV2, NCAR/CESM2-FV2, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, + NCC/NorCPM1, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-CM2-HR4, CMCC/CMCC-ESM2, IPSL/IPSL-CM6A-LR-INCA, E3SM-Project/E3SM-1-0] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR', 'BCC/BCC-ESM1', 'CCCma/CanESM5', 'MRI/MRI-ESM2-0', # 'HAMMOZ-Consortium/MPI-ESM-1-2-HAM', 'MPI-M/MPI-ESM1-2-LR', 'MPI-M/MPI-ESM1-2-HR', 'NUIST/NESM3', # 'CAS/FGOALS-g3', 'MIROC/MIROC6', 'KIOST/KIOST-ESM', 'CCCR-IITM/IITM-ESM', 'AWI/AWI-ESM-1-1-LR', @@ -120,18 +97,8 @@ cmip6_{model}_ssp126_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: - [ - NOAA-GFDL/GFDL-ESM4, - INM/INM-CM4-8, - INM/INM-CM5-0, - IPSL/IPSL-CM6A-LR, - NIMS-KMA/KACE-1-0-G, - NCC/NorESM2-MM, - CMCC/CMCC-CM2-SR5, - IPSL/IPSL-CM5A2-INCA, - CMCC/CMCC-ESM2, - ] + model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, IPSL/IPSL-CM6A-LR, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-ESM2] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','DKRZ/MPI-ESM1-2-HR','MPI-M/MPI-ESM1-2-LR', # 'NUIST/NESM3', 'MIROC/MIROC6','MRI/MRI-ESM2-0','KIOST/KIOST-ESM','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','CCCR-IITM/IITM-ESM','EC-Earth-Consortium/EC-Earth3-Veg-LR', @@ -168,21 +135,8 @@ cmip6_{model}_ssp245_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: - [ - NOAA-GFDL/GFDL-ESM4, - IPSL/IPSL-CM6A-LR, - INM/INM-CM4-8, - INM/INM-CM5-0, - NCAR/CESM2-WACCM, - NCC/NorESM2-LM, - CSIRO-ARCCSS/ACCESS-CM2, - NCC/NorESM2-MM, - NIMS-KMA/KACE-1-0-G, - CMCC/CMCC-CM2-SR5, - CMCC/CMCC-ESM2, - AS-RCEC/TaiESM1, - ] + model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, NCC/NorESM2-LM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, + NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, CMCC/CMCC-ESM2, AS-RCEC/TaiESM1] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', # 'AWI/AWI-CM-1-1-MR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','DKRZ/MPI-ESM1-2-HR','NUIST/NESM3', @@ -219,21 +173,8 @@ cmip6_{model}_ssp370_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: - [ - NOAA-GFDL/GFDL-ESM4, - IPSL/IPSL-CM6A-LR, - INM/INM-CM4-8, - INM/INM-CM5-0, - NCAR/CESM2-WACCM, - CSIRO-ARCCSS/ACCESS-CM2, - NCC/NorESM2-MM, - NCC/NorESM2-LM, - NIMS-KMA/KACE-1-0-G, - CMCC/CMCC-CM2-SR5, - IPSL/IPSL-CM5A2-INCA, - CMCC/CMCC-ESM2, - ] + model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, NCC/NorESM2-LM, + NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-ESM2] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','BCC/BCC-ESM1','DKRZ/MPI-ESM1-2-HR', # EC-Earth-Consortium/EC-Earth3-Veg','EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-AerChem', # 'EC-Earth-Consortium/EC-Earth3-Veg-LR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','HAMMOZ-Consortium/MPI-ESM-1-2-HAM', @@ -338,18 +279,8 @@ cmip6_{model}_ssp585_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: - [ - NOAA-GFDL/GFDL-ESM4, - INM/INM-CM4-8, - INM/INM-CM5-0, - NIMS-KMA/KACE-1-0-G, - NCC/NorESM2-MM, - NCC/NorESM2-LM, - CMCC/CMCC-CM2-SR5, - AS-RCEC/TaiESM1, - CMCC/CMCC-ESM2, - ] + model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, NCC/NorESM2-LM, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, + CMCC/CMCC-ESM2] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','MPI-M/MPI-ESM1-2-LR', # 'DKRZ/MPI-ESM1-2-HR','MIROC/MIROC6','MRI/MRI-ESM2-0','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', diff --git a/data/catalogs/gcs_cmip6_data/registry.txt b/data/catalogs/gcs_cmip6_data/registry.txt deleted file mode 100644 index 7351cb9f2..000000000 --- a/data/catalogs/gcs_cmip6_data/registry.txt +++ /dev/null @@ -1 +0,0 @@ -v0.1.0/data_catalog.yml c8aab2c2068809a52e5e40a38e68d1a27d25346cf51724010a24f1bfad66a1c1 diff --git a/data/catalogs/update_versions.py b/data/catalogs/update_versions.py deleted file mode 100644 index 31deea94a..000000000 --- a/data/catalogs/update_versions.py +++ /dev/null @@ -1,11 +0,0 @@ -"""Script to update the registry.txt file for each predefined catalog.""" - -from pathlib import Path - -from hydromt.predefined_catalog import create_registry_file - -if __name__ == "__main__": - root = Path(__file__).parent - cat_roots = [d for d in root.iterdir() if d.is_dir()] - for cat_root in cat_roots: - create_registry_file(cat_root) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index ccb24fa3a..f7cae9857 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -1,6 +1,4 @@ --- -# NOTE this file has been deprecated and will be removed in future versions -# # list of predefined data catalogs # # : @@ -18,7 +16,7 @@ deltares_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/deltares_data.yml versions: - v2024.1.30: 50863d777404a4a91b5f66bf285b3edaa56713b1 + v2024.1.30: main v2023.12.21: 392206b21b26e62e00ae76db7ffc61a3b95e2175 v2023.12.19: bf25e79dcbda67612a75588cd782d57abe3881de v2023.2: 0bf8e2a1e716095dc6df54a5e9114ce88da0701b @@ -28,13 +26,13 @@ deltares_data: gcs_cmip6_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/gcs_cmip6_data.yml versions: - v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 + v2024.1.30: main v2023.2: 0144d5dadfb76a9f2bdb22226b484e83c9751c34 notes: This data uses CMIP6 data stored in Google Cloud Service. aws_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/aws_data.yml versions: - v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 + v2024.1.30: main v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: diff --git a/docs/api.rst b/docs/api.rst index ecb7382d8..f08d0e99b 100644 --- a/docs/api.rst +++ b/docs/api.rst @@ -73,8 +73,10 @@ Add data sources data_catalog.DataCatalog.add_source data_catalog.DataCatalog.update data_catalog.DataCatalog.from_predefined_catalogs + data_catalog.DataCatalog.from_archive data_catalog.DataCatalog.from_yml data_catalog.DataCatalog.from_dict + data_catalog.DataCatalog.set_predefined_catalogs .. _api_data_catalog_get: @@ -90,19 +92,6 @@ Get data data_catalog.DataCatalog.get_dataframe data_catalog.DataCatalog.get_dataset - -Predefined data catalog -======================= - -.. autosummary:: - :toctree: _generated - - predefined_catalog.PredefinedCatalog - predefined_catalog.PredefinedCatalog.get_catalog_file - predefined_catalog.create_registry_file - - - DataAdapter =========== diff --git a/docs/changelog.rst b/docs/changelog.rst index 416449094..1069a5304 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -9,18 +9,11 @@ The format is based on `Keep a Changelog`_, and this project adheres to Unreleased ========== -New ---- -- New `PredefinedCatalog` class to handle predefined catalog version based on pooch registry files. (#849) - - Changed ------- - Development environment is now set up via pixi instead of mamba / conda. See the documentation for more information on how to install. - Use the native data CRS when determining zoom levels over the data catalog crs. (#851) - Improved `flw.d8_from_dem` method with different options to use river vector data to aid the flow direction derivation. (#305) -- DataCatalog.predefined_catalogs retrieves predefined_catalogs specified in predefined_catalogs.py. There is no need for setting the predefined_catalogs anymore. (#844) - Fixed ----- @@ -32,10 +25,6 @@ Fixed - Fixed incorrect renaming of single variable raster datasets (#883) - Provide better error message for 0D geometry arrays in GeoDataset (#885) -Deprecated ----------- -- The `DataCatalog.from_archive` method is deprecated. Use `DataCatalog.from_yml` with the root pointing to the archive instead. (#849) - v0.9.4 (2024-02-26) =================== This release fixes a performance regression when reading geometry masks, relaxed warnings for empty raster datasets and updated the documention of the new hydromt commands. diff --git a/docs/conf.py b/docs/conf.py index 140446283..7a5d551b4 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -132,6 +132,7 @@ def clean_str(s): "other", ] data_cat = hydromt.DataCatalog() +data_cat.set_predefined_catalogs(r"../data/predefined_catalogs.yml") predefined_catalogs = data_cat.predefined_catalogs for name in predefined_catalogs: try: diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index 31abdd8a8..e674c76dc 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -92,7 +92,7 @@ "outputs": [], "source": [ "# instantiate instance of Data Catalog\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/export_data.ipynb b/examples/export_data.ipynb index 4f4b40eb6..ebeb19887 100644 --- a/examples/export_data.ipynb +++ b/examples/export_data.ipynb @@ -56,7 +56,7 @@ "# Download and read artifacts for the Piave basin to `~/.hydromt_data/`.\n", "data_catalog = hydromt.DataCatalog(\n", " logger=logger,\n", - " data_libs=[\"artifact_data=v0.0.8\"],\n", + " data_libs=[\"artifact_data\"],\n", ")" ] }, diff --git a/examples/reading_point_data.ipynb b/examples/reading_point_data.ipynb index 5badce96b..12a6c149d 100644 --- a/examples/reading_point_data.ipynb +++ b/examples/reading_point_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/reading_raster_data.ipynb b/examples/reading_raster_data.ipynb index 6eb3fb94a..23a975151 100644 --- a/examples/reading_raster_data.ipynb +++ b/examples/reading_raster_data.ipynb @@ -40,7 +40,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/reading_vector_data.ipynb b/examples/reading_vector_data.ipynb index dc7916411..e9340ca7c 100644 --- a/examples/reading_vector_data.ipynb +++ b/examples/reading_vector_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/working_with_flow_directions.ipynb b/examples/working_with_flow_directions.ipynb index 6a827c0d8..ede0c1594 100644 --- a/examples/working_with_flow_directions.ipynb +++ b/examples/working_with_flow_directions.ipynb @@ -51,7 +51,7 @@ "# initialize a logger\n", "logger = setuplog(\"flow direction data\", log_level=10)\n", "# initialize a data catalog based on the pre-defined artifact_data catalog\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"], logger=logger)\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data\"], logger=logger)\n", "\n", "# we load the flow direction (flwdir); elevation (elevtn) and upstream area (uparea) layers\n", "ds = data_catalog.get_rasterdataset(\n", diff --git a/examples/working_with_geodatasets.ipynb b/examples/working_with_geodatasets.ipynb index ca7cc56dc..ecb939af6 100644 --- a/examples/working_with_geodatasets.ipynb +++ b/examples/working_with_geodatasets.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/working_with_meshmodel.ipynb b/examples/working_with_meshmodel.ipynb index d4e2f34cb..7772be559 100644 --- a/examples/working_with_meshmodel.ipynb +++ b/examples/working_with_meshmodel.ipynb @@ -175,7 +175,7 @@ "mod = hydromt.MeshModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] diff --git a/examples/working_with_models.ipynb b/examples/working_with_models.ipynb index 70290be58..4a5101a9f 100644 --- a/examples/working_with_models.ipynb +++ b/examples/working_with_models.ipynb @@ -192,7 +192,7 @@ "mod = hydromt.GridModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] @@ -462,7 +462,7 @@ "mod3 = hydromt.GridModel(\n", " root=root3,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")\n", "\n", diff --git a/examples/working_with_raster.ipynb b/examples/working_with_raster.ipynb index 2f93200e8..6d7cc69be 100644 --- a/examples/working_with_raster.ipynb +++ b/examples/working_with_raster.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" ] }, { diff --git a/examples/working_with_tiled_raster_data.ipynb b/examples/working_with_tiled_raster_data.ipynb index f5e3a7fce..d442fc7f5 100644 --- a/examples/working_with_tiled_raster_data.ipynb +++ b/examples/working_with_tiled_raster_data.ipynb @@ -30,7 +30,7 @@ "logger = setuplog(\"tiling\", log_level=20)\n", "\n", "# get some elevation data from the data catalog\n", - "data_lib = \"artifact_data=v0.0.8\"\n", + "data_lib = \"artifact_data\"\n", "data_cat = DataCatalog(data_lib, logger=logger)\n", "source = \"merit_hydro\"\n", "da0 = data_cat.get_rasterdataset(source, variables=[\"elevtn\"])\n", diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 22575a478..9402c31d3 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -2,16 +2,16 @@ # -*- coding: utf-8 -*- """DataCatalog module for HydroMT.""" - from __future__ import annotations import copy import itertools import logging import os +import shutil import warnings from datetime import datetime -from os.path import abspath, basename, isfile, join +from os.path import abspath, basename, isdir, isfile, join from pathlib import Path from typing import ( Dict, @@ -26,7 +26,6 @@ import geopandas as gpd import numpy as np import pandas as pd -import pooch import requests import xarray as xr import yaml @@ -36,14 +35,10 @@ from pystac import CatalogType, MediaType from hydromt.nodata import NoDataException, NoDataStrategy, _exec_nodata_strat -from hydromt.predefined_catalog import ( - PREDEFINED_CATALOGS, - PredefinedCatalog, - _copy_file, -) from hydromt.typing import Bbox, ErrorHandleMethod, SourceSpecDict, TimeRange from hydromt.utils import partition_dictionaries +from . import __version__ from .data_adapter import ( DataAdapter, DataFrameAdapter, @@ -52,7 +47,7 @@ GeoDatasetAdapter, RasterDatasetAdapter, ) -from .data_adapter.caching import HYDROMT_DATADIR, _uri_validator +from .data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator logger = logging.getLogger(__name__) @@ -64,9 +59,11 @@ class DataCatalog(object): + """Base class for the data catalog object.""" - _format_version = "v0" # format version of the data catalog + # root URL with data_catalog file + _url = r"https://raw.githubusercontent.com/Deltares/hydromt/main/data/predefined_catalogs.yml" _cache_dir = HYDROMT_DATADIR def __init__( @@ -110,7 +107,7 @@ def __init__( elif not isinstance(data_libs, list): # make sure data_libs is a list data_libs = np.atleast_1d(data_libs).tolist() self._sources = {} # dictionary of DataAdapter - self._catalogs: Dict[str, PredefinedCatalog] = {} + self._catalogs = {} # dictionary of predefined Catalogs self._fallback_lib = fallback_lib self.logger = logger @@ -257,7 +254,7 @@ def from_stac_catalog( def predefined_catalogs(self) -> Dict: """Return all predefined catalogs.""" if not self._catalogs: - self._set_predefined_catalogs() + self.set_predefined_catalogs() return self._catalogs def get_source_bbox( @@ -610,15 +607,60 @@ def update_sources(self, **kwargs) -> None: """Add data sources to library or update them.""" self.update(**kwargs) - def _set_predefined_catalogs(self) -> Dict: - """Set initialized predefined catalogs to _catalogs attribute.""" - for k, cat in PREDEFINED_CATALOGS.items(): - self._catalogs[k] = cat( - format_version=self._format_version, cache_dir=self._cache_dir + def set_predefined_catalogs( + self, urlpath: Optional[Union[Path, str]] = None + ) -> Dict: + """Initialise the predefined catalogs.""" + # get predefined_catalogs + urlpath = self._url if urlpath is None else urlpath + cache_path = join(self._cache_dir, basename(urlpath)) + try: + # download file locally; overwrite existing file + _copyfile(urlpath, cache_path) + except Exception: # if offline + self.logger.warning( + "Downloading the predefined catalogs failed;" + "check your internet connection" + ) + pass + if isfile(cache_path): + self._catalogs = _yml_from_uri_or_path(cache_path) + if self._catalogs is None: + raise ConnectionError( + "Predefined catalogs not found; check your internet connection." ) return self._catalogs - def from_predefined_catalogs(self, name: str, version: str = "latest") -> None: + def from_artifacts( + self, name: str = "artifact_data", version: str = "latest" + ) -> DataCatalog: + """Parse artifacts. + + Deprecated method. Use + :py:func:`hydromt.data_catalog.DataCatalog.from_predefined_catalogs` instead. + + Parameters + ---------- + name : str, optional + Catalog name. If None (default) sample data is downloaded. + version : str, optional + Release version. By default it takes the latest known release. + + Returns + ------- + DataCatalog + DataCatalog object with parsed artifact data. + """ + warnings.warn( + '"from_artifacts" is deprecated. Use "from_predefined_catalogs instead".', + DeprecationWarning, + stacklevel=2, + ) + return self.from_predefined_catalogs(name, version) + + def from_predefined_catalogs( + self, name: str, version: str = "latest" + ) -> DataCatalog: """Add data sources from a predefined data catalog. Parameters @@ -628,6 +670,10 @@ def from_predefined_catalogs(self, name: str, version: str = "latest") -> None: version : str, optional Catlog release version. By default it takes the latest known release. + Returns + ------- + DataCatalog + DataCatalog object with parsed predefined catalog added. """ if "=" in name: name, version = name.split("=")[0], name.split("=")[-1] @@ -635,58 +681,105 @@ def from_predefined_catalogs(self, name: str, version: str = "latest") -> None: raise ValueError( f'Catalog with name "{name}" not found in predefined catalogs' ) - # cache and get path to data_datalog.yml file of the catalog with - catalog_path = self.predefined_catalogs[name].get_catalog_file(version) - # read catalog - self.logger.info(f"Reading data catalog {name} {version}") - self.from_yml(catalog_path, catalog_name=name) + urlpath = self.predefined_catalogs[name].get("urlpath") + versions_dict = self.predefined_catalogs[name].get("versions") + if version == "latest" or not isinstance(version, str): + # if a specific version is requested, we don't have to try others + versions = list(versions_dict.keys()) + if len(versions) > 1: + version = versions[np.argmax([Version(v) for v in versions])] + else: + version = versions[0] - def _cache_archive( - self, - archive_uri: str, - name: str, - version: str = "latest", - sha256: Optional[str] = None, - ) -> str: - """Cache a data archive to the cache directory. + if version not in versions_dict: + raise RuntimeError( + f"Unknown version requested {version}. " + f"options are :{versions_dict.keys()}" + ) + possible_catalg_versions = [(Version(k), v) for k, v in versions_dict.items()] + possible_catalg_versions_sorted = reversed(sorted(possible_catalg_versions)) + + for _, identifier in possible_catalg_versions_sorted: + try: + urlpath = urlpath.format(version=identifier) + if urlpath.split(".")[-1] in ["gz", "zip"]: + self.logger.info(f"Reading data catalog archive {name} {version}") + self.from_archive(urlpath, name=name, version=version) + else: + self.logger.info(f"Reading data catalog {name} {version}") + self.from_yml(urlpath, catalog_name=name) + return self + except RuntimeError: + continue + + raise RuntimeError("No compatible compatible catalog version could be found") - The archive is unpacked and cached to // + def from_archive( + self, + urlpath: Union[Path, str], + version: Optional[str] = None, + name: Optional[str] = None, + ) -> DataCatalog: + """Read and cache a data archive including a data_catalog.yml file. Parameters ---------- - archive_uri : str - uri to data archive. - name : str - Name of data catalog + urlpath : str, Path + Path or url to data archive. version : str, optional - Version of data archive, by default 'latest'. - sha256 : str, optional - SHA256 hash of the archive, by default None. + Version of data archive, by default None. + name : str, optional + Name of data catalog, by default None. Returns ------- - str - Path to the datacatalog of the cached data archive + DataCatalog + DataCatalog object with parsed data archive added. + """ + # add depreaction warning + root = self._cache_archive(urlpath, version=version, name=name) + yml_fn = join(root, "data_catalog.yml") + # parse catalog + return self.from_yml(yml_fn, catalog_name=name) + + def _cache_archive( + self, + archive_fn: Union[Path, str], + version: Optional[str] = None, + name: Optional[str] = None, + ) -> DataCatalog: + """Cache a data archive. + + Parameters + ---------- + archive_fn : str, Path + Path or url to data archive. + version : str, optional + Version of data archive, by default None. + name : str, optional + Name of data catalog, by default None. + Returns + ------- + DataCatalog + DataCatalog object with parsed data archive added. """ - root = Path(self._cache_dir, name, version) - extract_dir = root / Path(archive_uri).stem - # retrieve and unpack archive - kwargs = {} - if Path(archive_uri).suffix == ".zip": - kwargs.update(processor=pooch.Unzip(extract_dir=extract_dir)) - elif Path(archive_uri).suffix == ".gz": - kwargs.update(processor=pooch.Untar(extract_dir=extract_dir)) - if Path(archive_uri).exists(): # check if arhive is a local file - kwargs.update(donwloader=_copy_file) - pooch.retrieve( - archive_uri, - known_hash=sha256, - path=str(root), - fname=Path(archive_uri).name, - **kwargs, - ) - return extract_dir + name = basename(archive_fn).split(".")[0] if name is None else name + root = join(self._cache_dir, name) + if version is not None: + root = join(root, version) + archive_dst_fn = join(root, basename(archive_fn)) + # copy archive to cache + if not isdir(root): + self.logger.debug(f"Caching data from {archive_fn}") + os.makedirs(root, exist_ok=True) + _copyfile(archive_fn, archive_dst_fn) + # unpack data and remove archive + if isfile(archive_dst_fn): + self.logger.debug(f"Unpacking data from {archive_fn}") + shutil.unpack_archive(archive_dst_fn, root) + os.remove(archive_dst_fn) + return root def from_yml( self, @@ -720,8 +813,6 @@ def from_yml( root: category: version: - name: - sha256: # only if the root is an archive : path: data_type: @@ -775,6 +866,15 @@ def from_yml( # read meta data meta = yml.pop("meta", meta) + # check version required hydromt version + requested_version = meta.get("hydromt_version", None) + if requested_version is not None: + allow_dev = meta.get("allow_dev_version", True) + if not self._is_compatible(__version__, requested_version, allow_dev): + raise RuntimeError( + f"Data catalog requires Hydromt Version {requested_version} which " + f"is incompattible with current hydromt verison {__version__}." + ) if catalog_name is None: catalog_name = cast( str, meta.get("name", "".join(basename(urlpath).split(".")[:-1])) @@ -784,12 +884,12 @@ def from_yml( root = meta.get("root", os.path.dirname(urlpath)) if root.split(".")[-1] in ["gz", "zip"]: # if root is an archive, unpack it at the cache dir - root = self._cache_archive( - archive_uri=root, - name=catalog_name, - version=version, - sha256=meta.get("sha256", None), - ) + root = self._cache_archive(root, name=catalog_name, version=version) + # save catalog to cache + with open(join(root, f"{catalog_name}.yml"), "w") as f: + data_dict = {"meta": {k: v for k, v in meta.items() if k != "root"}} + data_dict.update(yml) + yaml.dump(data_dict, f, default_flow_style=False, sort_keys=False) self.from_dict( yml, catalog_name=catalog_name, @@ -1766,7 +1866,8 @@ def _parse_data_source_dict( def _yml_from_uri_or_path(uri_or_path: Union[Path, str]) -> Dict: if _uri_validator(str(uri_or_path)): with requests.get(uri_or_path, stream=True) as r: - r.raise_for_status() + if r.status_code != 200: + raise IOError(f"URL {r.content}: {uri_or_path}") yml = yaml.load(r.text, Loader=yaml.FullLoader) else: with open(uri_or_path, "r") as stream: diff --git a/hydromt/predefined_catalog.py b/hydromt/predefined_catalog.py deleted file mode 100644 index 754bfa583..000000000 --- a/hydromt/predefined_catalog.py +++ /dev/null @@ -1,261 +0,0 @@ -"""Implementation of the predefined data catalogs entry points.""" - -import logging -import shutil -import sys -from pathlib import Path -from typing import Callable, ClassVar, Optional - -import packaging.version -import pooch - -from hydromt.data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator - -logger = logging.getLogger(__name__) - -# this is the default location of the predefined catalogs -# in the test environment this is set to local data/catalogs directory using a global fixture -GIT_ROOT = r"https://github.com/Deltares/hydromt/blob/main/data/catalogs" - -__all__ = [ - "PredefinedCatalog", - "DeltaresDataCatalog", - "ArtifactDataCatalog", - "AWSDataCatalog", - "GCSCMIP6DataCatalog", - "create_registry_file", -] - - -def create_registry_file(root: Path, registry_path: Optional[Path] = None) -> None: - """Create a registry file for all catalog files in the root directory. - - The root directory should contain a /data_catalog.yml file per version. - By default the root directory is the cache directory of the catalog instance. - - Parameters - ---------- - root: Path - root directory to search for data_catalog.yml files - """ - # we don't use pooch.create_registry here as we want to only include vaild data_catalog.yml files - registry = {} - for path in root.glob("**/data_catalog.yml"): - key = path.relative_to(root).as_posix() - if not _valid_key(key): - raise ValueError(f"No valid version found in {key}") - if sys.platform == "win32": - # The line endings need to be replaced when operating from windows in order to maintain equality of hashes - _replace_line_endings(path) - file_hash = pooch.file_hash(path) - registry[key] = file_hash - - if not registry: - raise FileNotFoundError(f"No data_catalog.yml files found in {root}") - - if registry_path is None: - registry_path = Path(root / "registry.txt") - with open(registry_path, "w") as f: - for fname, hash in registry.items(): - f.write(f"{fname} {hash}\n") - - -class PredefinedCatalog(object): - """Predefined data catalog. - - A predefined data catalog is a collection of data_catalog.yml files that are stored in a - specific directory structure. The catalog is defined by a base_url and a name. The predefined - catalog can be used to retrieve data_catalog.yml files for specific versions. - - Directory structure: - - /registry.txt - - //data_catalog.yml - - Cached directory structure: - - //registry.txt - - ///data_catalog.yml - """ - - # required class variables to be defined in subclasses - base_url: ClassVar[str] = GIT_ROOT - name: ClassVar[str] = "predefined_catalog" - - def __init__(self, format_version: str = "v0", cache_dir=HYDROMT_DATADIR) -> None: - # init arguments passed by DataCatalog - self._format_version = format_version - self._cache_dir: Path = Path(cache_dir) - # placeholders set by the class - self._pooch: Optional[pooch.Pooch] = None - self._versions: Optional[list[str]] = None - - @property - def registry(self) -> dict: - """Return the registry.""" - return self.pooch.registry - - @property - def pooch(self) -> pooch.Pooch: - """Return a pooch instance with all data catalog files in registry.""" - if self._pooch is None: - self._create_pooch() - self._load_registry_file() - return self._pooch - - @property - def versions(self) -> list[str]: - """Return the versions of the catalog.""" - if not self._versions: - self._versions = self._set_versions() - return self._versions - - def _create_pooch(self) -> None: - self._pooch = pooch.create( - path=self._cache_dir / self.name, - base_url=self.base_url, - retry_if_failed=3, - ) - - def _set_versions(self) -> list[str]: - """Set valid catalog versions.""" - # parse versions from registry, assume registry key is /data_catalog.yml - # keep only versions that match the format_version - keys = self.registry.keys() - _versions = [ - v.split("/")[0] for v in keys if _valid_key(v, self._format_version) - ] - if len(_versions) == 0: - raise RuntimeError( - f"No compatible catalog version could be found for {self.name}." - ) - self._versions = sorted(_versions, key=packaging.version.parse) - return self._versions - - def _load_registry_file(self, overwrite: bool = False) -> None: - """Create a catalog from a yaml file.""" - if self._pooch is None: - self._create_pooch() - if self.registry and not overwrite: - return - registry_path = Path(self._cache_dir / self.name / "registry.txt") - if registry_path.exists(): - registry_path.unlink() - try: # try to retrieve and cache the registry file - _copyfile(f"{self.base_url}/registry.txt", registry_path) - except (ConnectionError, FileNotFoundError): - logger.warning( - f"Failed to retrieve {self.name} versions file from {self.base_url}." - " Creating registry file from cached catalog files." - ) - create_registry_file(registry_path.parent) - if not registry_path.exists(): - raise FileNotFoundError( - f"No cached file found. Failed to retrieve {self.name} versions file" - ) - self.pooch.load_registry(registry_path) - - def get_catalog_file(self, version: Optional[str] = None) -> Optional[Path]: - """Get the cached catalog file path for a specific version. - - Parameters - ---------- - version: str, optional - The version of the catalog to retrieve. If None, the latest version is retrieved. - - Returns - ------- - Path - The path to the cachd catalog file. - """ - if version is None or version == "latest": # get latest version - version = self.versions[-1] - if version not in self.versions: - raise ValueError(f"Version {version} not found in {self.name} catalog") - # get the catalog file - key = f"{version}/data_catalog.yml" - # fetch the file (download if not cached) - path = self.pooch.fetch(key, downloader=self._downloader) - return Path(path) if path else None - - @property - def _downloader(self) -> Optional[Callable]: - if not _uri_validator(self.base_url): - return _copy_file - return None - - -def _valid_key(v: str, format_version: Optional[str] = None) -> bool: - """Check if the key is a valid version.""" - try: - packaging.version.parse(v.split("/")[0]) - return v.startswith(format_version) if format_version else True - except (packaging.version.InvalidVersion, AttributeError): - return False - - -def _copy_file( - url: str, - output_file: str, - pooch: Optional[pooch.Pooch] = None, - check_only: bool = False, -): - """Copy a local file to the cache directory for testing purposes. - - for more info, see: https://www.fatiando.org/pooch/latest/downloaders.html - """ - url = Path(url) - output_file = Path(output_file) - file_exists = url.is_file() - if check_only: - return file_exists - if not file_exists: - raise FileNotFoundError(f"Local file {url} does not exist.") - output_file.parent.mkdir(parents=True, exist_ok=True) - shutil.copyfile(url, output_file) - return output_file - - -class DeltaresDataCatalog(PredefinedCatalog): - """Deltares data catalog.""" - - base_url = f"{GIT_ROOT}/deltares_data" - name = "deltares_data" - - -class ArtifactDataCatalog(PredefinedCatalog): - """Artifact data catalog.""" - - base_url = f"{GIT_ROOT}/artifact_data" - name = "artifact_data" - - -class AWSDataCatalog(PredefinedCatalog): - """AWS data catalog.""" - - base_url = f"{GIT_ROOT}/aws_data" - name = "aws_data" - - -class GCSCMIP6DataCatalog(PredefinedCatalog): - """GCS CMIP6 data catalog.""" - - base_url = f"{GIT_ROOT}/gcs_cmip6_data" - name = "gcs_cmip6_data" - - -# TODO: replace with a entrypoint plugin structure in v1 -PREDEFINED_CATALOGS = { - "artifact_data": ArtifactDataCatalog, - "deltares_data": DeltaresDataCatalog, - "aws_data": AWSDataCatalog, - "gcs_cmip6_data": GCSCMIP6DataCatalog, -} - - -def _replace_line_endings(file_path: Path): - WINDOWS_LINE_ENDING = b"\r\n" - UNIX_LINE_ENDING = b"\n" - with open(file_path, "rb") as open_file: - content = open_file.read() - content = content.replace(WINDOWS_LINE_ENDING, UNIX_LINE_ENDING) - with open(file_path, "wb") as open_file: - open_file.write(content) diff --git a/pixi.lock b/pixi.lock index ea38ea77d..97443f5ca 100644 --- a/pixi.lock +++ b/pixi.lock @@ -7,25 +7,10 @@ environments: linux-64: - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2 - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2 - - conda: https://conda.anaconda.org/conda-forge/noarch/accessible-pygments-0.0.4-pyhd8ed1ab_0.conda - 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sphinx >=3.5 @@ -25368,7 +25356,7 @@ packages: - kind: pypi name: sphinx-click version: 5.1.0 - url: https://files.pythonhosted.org/packages/c5/72/3f1f052aa00fc4c7e9976eb845eeae25dabf4ee73a27618776f9f44009d0/sphinx_click-5.1.0-py3-none-any.whl + url: https://files.pythonhosted.org/packages/c5/72/3f1f052aa00fc4c7e9976eb845eeae25dabf4ee73a27618776f9f44009d0/sphinx_click-5.1.0-py3-none-any.whl#sha256=ae97557a4e9ec646045089326c3b90e026c58a45e083b8f35f17d5d6558d08a0 sha256: ae97557a4e9ec646045089326c3b90e026c58a45e083b8f35f17d5d6558d08a0 requires_dist: - sphinx >=2.0 @@ -25378,7 +25366,7 @@ packages: - kind: pypi name: sphinx-design version: 0.5.0 - url: https://files.pythonhosted.org/packages/17/52/a1e9d72ecf56047df714a3dd0840a5148e4e83c100e8e0046bcea60a1054/sphinx_design-0.5.0-py3-none-any.whl + url: https://files.pythonhosted.org/packages/17/52/a1e9d72ecf56047df714a3dd0840a5148e4e83c100e8e0046bcea60a1054/sphinx_design-0.5.0-py3-none-any.whl#sha256=1af1267b4cea2eedd6724614f19dcc88fe2e15aff65d06b2f6252cee9c4f4c1e sha256: 1af1267b4cea2eedd6724614f19dcc88fe2e15aff65d06b2f6252cee9c4f4c1e requires_dist: - sphinx >=5, <8 diff --git a/pixi.toml b/pixi.toml index 04613d5e3..1b8292e62 100644 --- a/pixi.toml +++ b/pixi.toml @@ -147,7 +147,6 @@ numpy = ">=1.23" packaging = "*" pandas = "*" pip = "*" -pooch = "*" pydantic = "~=2.4" pyflwdir = ">=0.5.4" pyogrio = ">=0.6" diff --git a/pyproject.toml b/pyproject.toml index d9eca382d..ed03f8a87 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,7 +23,6 @@ dependencies = [ "numpy>=1.23", # pin necessary to ensure compatability with C headers "packaging", # compare versions of hydromt "pandas", # Dataframes - "pooch", # data fetching "pydantic~=2.4", # Validation "pyflwdir>=0.5.4", # Hight models and derivatives "pyogrio>=0.6", # io for geopandas dataframes diff --git a/tests/conftest.py b/tests/conftest.py index a63a19d24..734bef3ef 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -11,8 +11,6 @@ from dask import config as dask_config from shapely.geometry import box -from hydromt.predefined_catalog import PREDEFINED_CATALOGS - dask_config.set(scheduler="single-threaded") import hydromt._compat as compat @@ -37,31 +35,6 @@ DATADIR = join(dirname(abspath(__file__)), "data") -@pytest.fixture(autouse=True) -def _local_catalog_eps(monkeypatch) -> dict: - """Set entrypoints to local predefined catalogs.""" - cat_root = Path(__file__).parent.parent / "data" / "catalogs" - for name, cls in PREDEFINED_CATALOGS.items(): - monkeypatch.setattr( - f"hydromt.predefined_catalog.{cls.__name__}.base_url", - str(cat_root / name), - ) - - -@pytest.fixture() -def data_catalog(_local_catalog_eps) -> DataCatalog: - """DataCatalog instance that points to local predefined catalogs.""" - return DataCatalog("artifact_data=v0.0.8") - - -@pytest.fixture(scope="session") -def latest_dd_version_uri(): - cat_root = Path(__file__).parent.parent / "data" / "catalogs" / "deltares_data" - versions = [d.name for d in cat_root.iterdir() if d.is_dir()] - latest_version = sorted(versions)[-1] - return cat_root / latest_version / "data_catalog.yml" - - @pytest.fixture(scope="class") def tmp_dir() -> Path: with TemporaryDirectory() as tempdirname: @@ -376,3 +349,10 @@ def mesh_model(griduda): mod.setup_config(**{"header": {"setting": "value"}}) mod.set_mesh(griduda, "elevtn") return mod + + +@pytest.fixture() +def artifact_data(): + datacatalog = DataCatalog() + datacatalog.from_predefined_catalogs("artifact_data") + return datacatalog diff --git a/tests/test_basin_mask.py b/tests/test_basin_mask.py index a82e9f309..71c713e2e 100644 --- a/tests/test_basin_mask.py +++ b/tests/test_basin_mask.py @@ -9,7 +9,8 @@ import pytest import xarray as xr -from hydromt import raster +import hydromt +from hydromt import DataCatalog, raster from hydromt.models import MODELS from hydromt.workflows.basin_mask import ( _check_size, @@ -21,13 +22,14 @@ logger = logging.getLogger("tets_basin") -def test_region(tmpdir, world, geodf, rioda, data_catalog): +def test_region(tmpdir, world, geodf, rioda): # prepare test data fn_gdf = str(tmpdir.join("world.geojson")) world.to_file(fn_gdf, driver="GeoJSON") fn_grid = str(tmpdir.join("grid.tif")) rioda.raster.to_raster(fn_grid) - data_catalog.from_dict( + cat = DataCatalog() + cat.from_dict( { "world": { "path": fn_gdf, @@ -60,7 +62,7 @@ def test_region(tmpdir, world, geodf, rioda, data_catalog): assert isinstance(region["geom"], gpd.GeoDataFrame) kind, region = parse_region({"geom": fn_gdf}) assert isinstance(region["geom"], gpd.GeoDataFrame) - kind, region = parse_region({"geom": "world"}, data_catalog=data_catalog) + kind, region = parse_region({"geom": "world"}, data_catalog=cat) assert isinstance(region["geom"], gpd.GeoDataFrame) # geom: points should fail region = {"geom": geodf} @@ -72,7 +74,7 @@ def test_region(tmpdir, world, geodf, rioda, data_catalog): assert isinstance(region["grid"], xr.DataArray) kind, region = parse_region({"grid": fn_grid}) assert isinstance(region["grid"], xr.DataArray) - kind, region = parse_region({"grid": "grid"}, data_catalog=data_catalog) + kind, region = parse_region({"grid": "grid"}, data_catalog=cat) assert isinstance(region["grid"], xr.DataArray) # basid @@ -105,7 +107,8 @@ def test_region(tmpdir, world, geodf, rioda, data_catalog): assert "xy" in region -def test_region_value(data_catalog): +def test_region_value(): + data_catalog = DataCatalog() array = np.array([1001, 1002, 1003, 1004, 1005]) kwarg = _parse_region_value(array, data_catalog=data_catalog) assert kwarg.get("basid") == array.tolist() @@ -134,7 +137,8 @@ def test_check_size(caplog): @pytest.mark.filterwarnings("ignore::UserWarning") -def test_basin(data_catalog): +def test_basin(caplog): + data_catalog = hydromt.DataCatalog("artifact_data", logger=logger) ds = data_catalog.get_rasterdataset("merit_hydro_1k") gdf_bas_index = data_catalog.get_geodataframe("merit_hydro_index") bas_index = data_catalog.get_source("merit_hydro_index") diff --git a/tests/test_data_adapter.py b/tests/test_data_adapter.py index 1d412e4ff..f862c60f9 100644 --- a/tests/test_data_adapter.py +++ b/tests/test_data_adapter.py @@ -108,9 +108,9 @@ def test_rasterdataset(rioda, tmpdir): @pytest.mark.skipif(not compat.HAS_GCSFS, reason="GCSFS not installed.") -def test_gcs_cmip6(): +def test_gcs_cmip6(tmpdir): # TODO switch to pre-defined catalogs when pushed to main - catalog_fn = join(CATALOGDIR, "gcs_cmip6_data", "v0.1.0", "data_catalog.yml") + catalog_fn = join(CATALOGDIR, "gcs_cmip6_data.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) ds = data_catalog.get_rasterdataset( "cmip6_NOAA-GFDL/GFDL-ESM4_historical_r1i1p1f1_Amon", @@ -130,7 +130,7 @@ def test_gcs_cmip6(): @pytest.mark.skipif(not compat.HAS_S3FS, reason="S3FS not installed.") def test_aws_worldcover(): - catalog_fn = join(CATALOGDIR, "aws_data", "v0.1.0", "data_catalog.yml") + catalog_fn = join(CATALOGDIR, "aws_data.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) da = data_catalog.get_rasterdataset( "esa_worldcover_2020_v100", @@ -161,7 +161,7 @@ def test_http_data(): assert da.raster.shape == (4000, 4000) -def test_rasterdataset_zoomlevels(rioda_large, tmpdir, data_catalog): +def test_rasterdataset_zoomlevels(rioda_large, tmpdir): # write tif with zoom level 1 in name # NOTE zl 0 not written to check correct functioning name = "test_zoom" @@ -176,6 +176,7 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir, data_catalog): } } # test zoom levels in name + data_catalog = DataCatalog() data_catalog.from_dict(yml_dict) rds = cast(RasterDatasetAdapter, data_catalog.get_source(name)) assert rds._parse_zoom_level(None) is None @@ -212,8 +213,8 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir, data_catalog): assert isinstance(da1, xr.Dataset) -def test_rasterdataset_driver_kwargs(data_catalog: DataCatalog, tmpdir): - era5 = data_catalog.get_rasterdataset("era5") +def test_rasterdataset_driver_kwargs(artifact_data: DataCatalog, tmpdir): + era5 = artifact_data.get_rasterdataset("era5") fp1 = join(tmpdir, "era5.zarr") era5.to_zarr(fp1) data_dict = { @@ -250,21 +251,21 @@ def test_rasterdataset_driver_kwargs(data_catalog: DataCatalog, tmpdir): datacatalog.get_source("era5_zarr").to_file(tmpdir, "era5_zarr", driver="zarr") -def test_rasterdataset_unit_attrs(data_catalog: DataCatalog): - era5_dict = {"era5": data_catalog.get_source("era5").to_dict()} +def test_rasterdataset_unit_attrs(artifact_data: DataCatalog): + era5_dict = {"era5": artifact_data.get_source("era5").to_dict()} attrs = { "temp": {"unit": "degrees C", "long_name": "temperature"}, "temp_max": {"unit": "degrees C", "long_name": "maximum temperature"}, "temp_min": {"unit": "degrees C", "long_name": "minimum temperature"}, } era5_dict["era5"].update(dict(attrs=attrs)) - data_catalog.from_dict(era5_dict) - raster = data_catalog.get_rasterdataset("era5") + artifact_data.from_dict(era5_dict) + raster = artifact_data.get_rasterdataset("era5") assert raster["temp"].attrs["unit"] == attrs["temp"]["unit"] assert raster["temp_max"].attrs["long_name"] == attrs["temp_max"]["long_name"] -def test_geodataset(geoda, geodf, ts, tmpdir, data_catalog): +def test_geodataset(geoda, geodf, ts, tmpdir): fn_nc = str(tmpdir.join("test.nc")) fn_gdf = str(tmpdir.join("test.geojson")) fn_csv = str(tmpdir.join("test.csv")) @@ -273,6 +274,7 @@ def test_geodataset(geoda, geodf, ts, tmpdir, data_catalog): geodf.to_file(fn_gdf, driver="GeoJSON") ts.to_csv(fn_csv) hydromt.io.write_xy(fn_csv_locs, geodf) + data_catalog = DataCatalog() # added fn_ts to test if it does not go into xr.open_dataset da1 = data_catalog.get_geodataset( fn_nc, variables=["test1"], bbox=geoda.vector.bounds @@ -322,8 +324,8 @@ def test_geodataset(geoda, geodf, ts, tmpdir, data_catalog): GeoDatasetAdapter(fn_nc).to_file(data_root=td, data_name="test", driver="zarr") -def test_geodataset_unit_attrs(data_catalog: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_attrs(artifact_data: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} attrs = { "waterlevel": { "long_name": "sea surface height above mean sea level", @@ -331,15 +333,15 @@ def test_geodataset_unit_attrs(data_catalog: DataCatalog): } } gtsm_dict["gtsmv3_eu_era5"].update(dict(attrs=attrs)) - data_catalog.from_dict(gtsm_dict) - gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") + artifact_data.from_dict(gtsm_dict) + gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") assert gtsm_geodataarray.attrs["long_name"] == attrs["waterlevel"]["long_name"] assert gtsm_geodataarray.attrs["unit"] == attrs["waterlevel"]["unit"] -def test_geodataset_unit_conversion(data_catalog: DataCatalog): - gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") - gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_conversion(artifact_data: DataCatalog): + gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") + gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(unit_mult=dict(waterlevel=1000))) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -347,8 +349,8 @@ def test_geodataset_unit_conversion(data_catalog: DataCatalog): assert gtsm_geodataarray1000.equals(gtsm_geodataarray * 1000) -def test_geodataset_set_nodata(data_catalog: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_set_nodata(artifact_data: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(nodata=-99)) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -482,11 +484,12 @@ def test_dataset_to_stac_catalog(tmpdir, timeseries_ds): assert list(stac_item.assets.keys())[0] == "test.nc" -def test_geodataframe(geodf, tmpdir, data_catalog): +def test_geodataframe(geodf, tmpdir): fn_gdf = str(tmpdir.join("test.geojson")) fn_shp = str(tmpdir.join("test.shp")) geodf.to_file(fn_gdf, driver="GeoJSON") geodf.to_file(fn_shp) + data_catalog = DataCatalog() # test read geojson using total bounds gdf1 = data_catalog.get_geodataframe(fn_gdf, bbox=geodf.total_bounds) assert isinstance(gdf1, gpd.GeoDataFrame) @@ -533,19 +536,20 @@ def test_geodataframe(geodf, tmpdir, data_catalog): data_catalog.get_geodataframe("no_file.geojson") -def test_geodataframe_unit_attrs(data_catalog: DataCatalog): - gadm_level1 = {"gadm_level1": data_catalog.get_source("gadm_level1").to_dict()} +def test_geodataframe_unit_attrs(artifact_data: DataCatalog): + gadm_level1 = {"gadm_level1": artifact_data.get_source("gadm_level1").to_dict()} attrs = {"NAME_0": {"long_name": "Country names"}} gadm_level1["gadm_level1"].update(dict(attrs=attrs)) - data_catalog.from_dict(gadm_level1) - gadm_level1_gdf = data_catalog.get_geodataframe("gadm_level1") + artifact_data.from_dict(gadm_level1) + gadm_level1_gdf = artifact_data.get_geodataframe("gadm_level1") assert gadm_level1_gdf["NAME_0"].attrs["long_name"] == "Country names" -def test_dataframe(df, tmpdir, data_catalog): +def test_dataframe(df, tmpdir): # Test reading csv fn_df = str(tmpdir.join("test.csv")) df.to_csv(fn_df) + data_catalog = DataCatalog() df1 = data_catalog.get_dataframe(fn_df, driver_kwargs=dict(index_col=0)) assert isinstance(df1, pd.DataFrame) pd.testing.assert_frame_equal(df, df1) @@ -599,10 +603,11 @@ def test_dataframe_unit_attrs(df: pd.DataFrame, tmpdir): assert np.all(cities_df["test_na"].isna()) -def test_dataframe_time(df_time, tmpdir, data_catalog): +def test_dataframe_time(df_time, tmpdir): # Test time df fn_df_ts = str(tmpdir.join("test_ts.csv")) df_time.to_csv(fn_df_ts) + data_catalog = DataCatalog() dfts1 = data_catalog.get_dataframe( fn_df_ts, driver_kwargs=dict(index_col=0, parse_dates=True) ) @@ -693,9 +698,12 @@ def test_detect_extent(geodf, geoda, rioda, ts): assert np.all(np.equal(rioda_expected_bbox, rioda_detected_bbox)) -def test_to_stac_geodataframe(geodf, tmpdir, data_catalog): +def test_to_stac_geodataframe(geodf, tmpdir): fn_gdf = str(tmpdir.join("test.geojson")) geodf.to_file(fn_gdf, driver="GeoJSON") + data_catalog = DataCatalog() # read artifacts + _ = data_catalog.sources # load artifact data as fallback + # geodataframe name = "gadm_level1" adapter = cast(GeoDataFrameAdapter, data_catalog.get_source(name)) @@ -721,7 +729,10 @@ def test_to_stac_geodataframe(geodf, tmpdir, data_catalog): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_raster(data_catalog): +def test_to_stac_raster(): + data_catalog = DataCatalog() # read artifacts + _ = data_catalog.sources # load artifact data as fallback + # raster dataset name = "chirps_global" adapter = cast(RasterDatasetAdapter, data_catalog.get_source(name)) @@ -754,7 +765,10 @@ def test_to_stac_raster(data_catalog): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_geodataset(data_catalog): +def test_to_stac_geodataset(geoda, tmpdir): + data_catalog = DataCatalog() # read artifacts + _ = data_catalog.sources # load artifact data as fallback + # geodataset name = "gtsmv3_eu_era5" adapter = cast(GeoDatasetAdapter, data_catalog.get_source(name)) diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 3229252a1..958ffb97a 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -1,7 +1,7 @@ """Tests for the hydromt.data_catalog submodule.""" import os -from os.path import abspath, dirname, join +from os.path import abspath, dirname, isfile, join from pathlib import Path from typing import cast @@ -9,9 +9,9 @@ import numpy as np import pandas as pd import pytest -import requests import xarray as xr +import hydromt.data_catalog from hydromt.data_adapter import ( DataAdapter, GeoDataFrameAdapter, @@ -22,7 +22,6 @@ DataCatalog, _denormalise_data_dict, _parse_data_source_dict, - _yml_from_uri_or_path, ) from hydromt.gis_utils import to_geographic_bbox from hydromt.nodata import NoDataStrategy @@ -109,14 +108,15 @@ def test_parser(): _parse_data_source_dict("test", {}) with pytest.raises(ValueError, match="Data type error unknown"): _parse_data_source_dict("test", {"path": "", "data_type": "error"}) - with ( - pytest.raises(ValueError, match="alias test not found in data_dict"), - pytest.deprecated_call(), - ): + with pytest.raises( + ValueError, match="alias test not found in data_dict" + ), pytest.deprecated_call(): _denormalise_data_dict({"test1": {"alias": "test"}}) -def test_data_catalog_io(tmpdir, data_catalog): +def test_data_catalog_io(tmpdir): + data_catalog = DataCatalog() + _ = data_catalog.sources # load artifact data as fallback # read / write fn_yml = join(tmpdir, "test.yml") data_catalog.to_yml(fn_yml) @@ -129,7 +129,7 @@ def test_data_catalog_io(tmpdir, data_catalog): print(data_catalog.get_source("merit_hydro")) -def test_versioned_catalog_entries(): +def test_versioned_catalog_entries(tmpdir): # make sure the catalogs individually still work legacy_yml_fn = join(DATADIR, "legacy_esa_worldcover.yml") legacy_data_catalog = DataCatalog(data_libs=[legacy_yml_fn]) @@ -213,21 +213,33 @@ def test_versioned_catalog_entries(): assert aws_and_legacy_catalog2 == aws_and_legacy_catalog -def test_versioned_catalogs(data_catalog): - data_catalog._sources = {} # reset - data_catalog.from_predefined_catalogs("deltares_data") - assert len(data_catalog.sources) > 0 - data_catalog._sources = {} # reset - data_catalog.from_predefined_catalogs("deltares_data", "v0.5.0") - assert len(data_catalog.sources) > 0 +def test_versioned_catalogs(tmpdir, monkeypatch): + v999_yml_fn = join(tmpdir, "test_sources_v999.yml") + with open(v999_yml_fn, "w") as f: + f.write( + """\ + meta: + hydromt_version: '==999.*' + """ + ) + + DataCatalog().from_predefined_catalogs("deltares_data") + DataCatalog().from_predefined_catalogs("deltares_data", "v2022.7") + + with pytest.raises(RuntimeError, match="Unknown version requested "): + _ = DataCatalog().from_predefined_catalogs("deltares_data", "v1993.7") - with pytest.raises(ValueError, match="Version v1993.7 not found "): - _ = data_catalog.from_predefined_catalogs("deltares_data", "v1993.7") + with pytest.raises(RuntimeError, match="Data catalog requires Hydromt Version"): + DataCatalog(data_libs=[v999_yml_fn]) + with monkeypatch.context() as m: + m.setattr(hydromt.data_catalog, "__version__", "999.0.0") + DataCatalog(v999_yml_fn) -def test_data_catalog(tmpdir, data_catalog): + +def test_data_catalog(tmpdir): + data_catalog = DataCatalog() # initialized with empty dict - data_catalog._sources = {} # reset assert len(data_catalog._sources) == 0 # global data sources from artifacts are automatically added assert len(data_catalog.sources) > 0 @@ -257,12 +269,12 @@ def test_data_catalog(tmpdir, data_catalog): with pytest.deprecated_call(): data_catalog = DataCatalog(deltares_data=False) assert len(data_catalog._sources) == 0 - data_catalog.from_predefined_catalogs("deltares_data") + with pytest.deprecated_call(): + data_catalog.from_artifacts("deltares_data") assert len(data_catalog._sources) > 0 - with ( - pytest.raises(ValueError, match="Version unknown_version not found"), - pytest.deprecated_call(), - ): + with pytest.raises( + RuntimeError, match="Unknown version requested" + ), pytest.deprecated_call(): data_catalog = DataCatalog(deltares_data="unknown_version") # test hydromt version in meta data @@ -271,6 +283,25 @@ def test_data_catalog(tmpdir, data_catalog): data_catalog.to_yml(fn_yml, meta={"hydromt_version": "0.7.0"}) +def test_from_archive(tmpdir): + data_catalog = DataCatalog() + # change cache to tmpdir + data_catalog._cache_dir = str(tmpdir.join(".hydromt_data")) + urlpath = data_catalog.predefined_catalogs["artifact_data"]["urlpath"] + version_hash = list( + data_catalog.predefined_catalogs["artifact_data"]["versions"].values() + )[0] + data_catalog.from_archive(urlpath.format(version=version_hash)) + assert len(data_catalog.iter_sources()) > 0 + source0 = data_catalog.get_source( + next(iter([source_name for source_name, _ in data_catalog.iter_sources()])) + ) + assert ".hydromt_data" in str(source0.path) + # failed to download + with pytest.raises(ConnectionError, match="Data download failed"): + data_catalog.from_archive("https://asdf.com/asdf.zip") + + def test_used_sources(tmpdir): merged_yml_fn = join(DATADIR, "merged_esa_worldcover.yml") data_catalog = DataCatalog(merged_yml_fn) @@ -284,33 +315,37 @@ def test_used_sources(tmpdir): assert sources[0][1].version == source.version -def test_from_yml_with_archive(data_catalog): - cache_dir = Path(data_catalog._cache_dir) - data_catalog.from_predefined_catalogs("artifact_data=v0.0.8") +def test_from_yml_with_archive(tmpdir): + yml_fn = join(CATALOGDIR, "artifact_data.yml") + data_catalog = DataCatalog(yml_fn) sources = list(data_catalog.sources.keys()) assert len(sources) > 0 # as part of the getting the archive a a local # catalog file is written to the same folder # check if this file exists and we can read it - yml_dst_fn = Path(cache_dir, "artifact_data", "v0.0.8", "data_catalog.yml") - assert yml_dst_fn.exists() + root = dirname(data_catalog.get_source(sources[0]).path) + yml_dst_fn = join(root, "artifact_data.yml") + assert isfile(yml_dst_fn) data_catalog1 = DataCatalog(yml_dst_fn) sources = list(data_catalog1.sources.keys()) source = data_catalog1.get_source(sources[0]) - assert yml_dst_fn.parent == Path(source.path).parent.parent + assert dirname(source.path) == root -def test_from_predefined_catalogs(data_catalog): - assert len(data_catalog.predefined_catalogs) > 0 +def test_from_predefined_catalogs(): + data_catalog = DataCatalog() + data_catalog.set_predefined_catalogs( + join(CATALOGDIR, "..", "predefined_catalogs.yml") + ) for name in data_catalog.predefined_catalogs: - data_catalog._sources = {} # reset data_catalog.from_predefined_catalogs(f"{name}=latest") assert len(data_catalog._sources) > 0 + data_catalog._sources = {} # reset with pytest.raises(ValueError, match='Catalog with name "asdf" not found'): data_catalog.from_predefined_catalogs("asdf") -def test_export_global_datasets(tmpdir, data_catalog): +def test_export_global_datasets(tmpdir): DTYPES = { "RasterDatasetAdapter": (xr.DataArray, xr.Dataset), "GeoDatasetAdapter": (xr.DataArray, xr.Dataset), @@ -318,7 +353,7 @@ def test_export_global_datasets(tmpdir, data_catalog): } bbox = [12.0, 46.0, 13.0, 46.5] # Piava river time_tuple = ("2010-02-10", "2010-02-15") - data_catalog.from_predefined_catalogs("artifact_data") + data_catalog = DataCatalog("artifact_data") # read artifacts source_names = [ "era5[precip,temp]", "grwl_mask", @@ -424,7 +459,8 @@ def test_export_dataframe(tmpdir, df, df_time): assert isinstance(obj, dtypes), key -def test_get_rasterdataset(data_catalog): +def test_get_rasterdataset(): + data_catalog = DataCatalog("artifact_data") # read artifacts n = len(data_catalog) # raster dataset using three different ways name = "koppen_geiger" @@ -452,7 +488,8 @@ def test_get_rasterdataset(data_catalog): data_catalog.get_rasterdataset({"name": "test"}) -def test_get_geodataframe(data_catalog): +def test_get_geodataframe(): + data_catalog = DataCatalog("artifact_data") # read artifacts n = len(data_catalog) # vector dataset using three different ways name = "osm_coastlines" @@ -476,7 +513,8 @@ def test_get_geodataframe(data_catalog): data_catalog.get_geodataframe({"name": "test"}) -def test_get_geodataset(data_catalog): +def test_get_geodataset(): + data_catalog = DataCatalog("artifact_data") # read artifacts n = len(data_catalog) # geodataset using three different ways name = "gtsmv3_eu_era5" @@ -504,8 +542,9 @@ def test_get_geodataset(data_catalog): data_catalog.get_geodataset({"name": "test"}) -def test_get_dataset(timeseries_df, data_catalog): +def test_get_dataset(timeseries_df): # get_dataset + data_catalog = DataCatalog("artifact_data") test_dataset = timeseries_df.to_xarray() subset_timeseries = timeseries_df.iloc[[0, len(timeseries_df) // 2]] time_tuple = ( @@ -521,7 +560,8 @@ def test_get_dataset(timeseries_df, data_catalog): assert ds.name == "col1" -def test_get_dataframe(df, tmpdir, data_catalog): +def test_get_dataframe(df, tmpdir): + data_catalog = DataCatalog("artifact_data") # read artifacts n = len(data_catalog) # dataframe using single way name = "test.csv" @@ -546,29 +586,36 @@ def test_get_dataframe(df, tmpdir, data_catalog): data_catalog.get_dataframe({"name": "test"}) -def test_deprecation_warnings(data_catalog): +def test_deprecation_warnings(artifact_data): with pytest.deprecated_call(): # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) - DataCatalog(artifact_data="v0.0.8") + DataCatalog(artifact_data="v0.0.6") with pytest.deprecated_call(): - fn = data_catalog["chelsa"].path + cat = DataCatalog() + # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') + cat.from_artifacts("artifact_data", version="v0.0.6") + with pytest.deprecated_call(): + fn = artifact_data["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) - data_catalog.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) + artifact_data.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) with pytest.deprecated_call(): - fn = data_catalog["gadm_level1"].path + fn = artifact_data["gadm_level1"].path # should be driver_kwargs=dict(assert_gtype='Polygon') - data_catalog.get_geodataframe(fn, assert_gtype="MultiPolygon") + artifact_data.get_geodataframe(fn, assert_gtype="MultiPolygon") with pytest.deprecated_call(): - fn = data_catalog["grdc"].path + fn = artifact_data["grdc"].path # should be driver_kwargs=dict(index_col=0) - data_catalog.get_dataframe(fn, index_col=0) + artifact_data.get_dataframe(fn, index_col=0) with pytest.deprecated_call(): - fn = data_catalog["gtsmv3_eu_era5"].path + fn = artifact_data["gtsmv3_eu_era5"].path # should be driver_kwargs=dict(chunks={'time': 100}) - data_catalog.get_geodataset(fn, chunks={"time": 100}) + artifact_data.get_geodataset(fn, chunks={"time": 100}) + +def test_detect_extent(): + data_catalog = DataCatalog() # read artifacts + _ = data_catalog.sources # load artifact data as fallback -def test_detect_extent(data_catalog): # raster dataset name = "chirps_global" bbox = 11.60, 45.20, 13.00, 46.80 @@ -601,7 +648,10 @@ def test_detect_extent(data_catalog): assert detected_temporal_range == expected_temporal_range -def test_to_stac(tmpdir, data_catalog): +def test_to_stac(tmpdir): + data_catalog = DataCatalog() # read artifacts + _ = data_catalog.sources # load artifact data as fallback + _ = data_catalog.get_rasterdataset("chirps_global") _ = data_catalog.get_geodataframe("gadm_level1") _ = data_catalog.get_geodataset("gtsmv3_eu_era5") @@ -624,7 +674,7 @@ def test_to_stac(tmpdir, data_catalog): ) == sorted([Path(join(tmpdir, p, "catalog.json")) for p in ["", *sources, ""]]) -def test_from_stac(): +def test_from_stac(tmpdir): catalog_from_stac = DataCatalog().from_stac_catalog( "./tests/data/stac/catalog.json" ) @@ -632,13 +682,3 @@ def test_from_stac(): assert type(catalog_from_stac.get_source("chirps_global")) == RasterDatasetAdapter assert type(catalog_from_stac.get_source("gadm_level1")) == GeoDataFrameAdapter # assert type(catalog_from_stac.get_source("gtsmv3_eu_era5")) == GeoDatasetAdapter - - -def test_yml_from_uri_path(): - uri = "https://google.com/nothinghere" - with pytest.raises(requests.HTTPError): - _yml_from_uri_or_path(uri) - uri = "https://raw.githubusercontent.com/Deltares/hydromt/main/.pre-commit-config.yaml" - yml = _yml_from_uri_or_path(uri) - assert isinstance(yml, dict) - assert len(yml) > 0 diff --git a/tests/test_forcing.py b/tests/test_forcing.py index 29147202c..63b959657 100644 --- a/tests/test_forcing.py +++ b/tests/test_forcing.py @@ -5,12 +5,14 @@ import xarray as xr import hydromt._compat as compat +from hydromt.data_catalog import DataCatalog from hydromt.raster import full_from_transform from hydromt.workflows.forcing import pet, precip -def test_precip(data_catalog): - p_precip = data_catalog.get_rasterdataset("era5", variables="precip") # era hourly +def test_precip(): + cat = DataCatalog() + p_precip = cat.get_rasterdataset("era5", variables="precip") # era hourly # We create a more refined grid p_transform = p_precip.raster.transform @@ -24,7 +26,7 @@ def test_precip(data_catalog): xr.testing.assert_equal(pout.x, grid.x) # Testing with clim argument - p_clim = data_catalog.get_rasterdataset("worldclim") + p_clim = cat.get_rasterdataset("worldclim") # give it a nodata value in the datacatalog >> issue to # create for the data artifacts p_clim.raster.set_nodata(-999.0) @@ -39,9 +41,10 @@ def test_precip(data_catalog): @pytest.mark.skipif(not compat.HAS_PYET, reason="pyET not installed.") -def test_pet(data_catalog): - et_data = data_catalog.get_rasterdataset("era5_daily_zarr") - dem = data_catalog.get_rasterdataset("era5_orography").squeeze("time", drop=True) +def test_pet(): + cat = DataCatalog() + et_data = cat.get_rasterdataset("era5_daily_zarr") + dem = cat.get_rasterdataset("era5_orography").squeeze("time", drop=True) peto = pet(et_data, et_data, dem, method="penman-monteith_tdew") diff --git a/tests/test_predefined_catalogs.py b/tests/test_predefined_catalogs.py deleted file mode 100644 index 0665e50da..000000000 --- a/tests/test_predefined_catalogs.py +++ /dev/null @@ -1,106 +0,0 @@ -from pathlib import Path - -import pytest - -from hydromt.predefined_catalog import ( - ArtifactDataCatalog, - PredefinedCatalog, - create_registry_file, -) - - -@pytest.fixture() -def cat_root() -> Path: - return Path(__file__).parent.parent / "data/catalogs" - - -@pytest.fixture() -def tmp_catalog_files(tmpdir): - _base_url = Path(tmpdir) / "test_catalog" - for version in ["v0.1.0", "v0.2.0", "v1.0.0"]: - catalog_path = _base_url / version / "data_catalog.yml" - catalog_path.parent.mkdir(parents=True, exist_ok=True) - catalog_path.write_text("meta:\n version: " + version) - return _base_url - - -@pytest.fixture() -def tmp_catalog_class(tmp_catalog_files) -> type[PredefinedCatalog]: - _base_url = tmp_catalog_files - - # write registry file - create_registry_file(_base_url) - - class TestCatalog(PredefinedCatalog): - name = "test_catalog" - base_url = str(_base_url) - - return TestCatalog - - -def test_predefined_catalog(tmp_catalog_class, tmpdir): - catalog = tmp_catalog_class(format_version="v0", cache_dir=Path(tmpdir) / "cache") - assert catalog.name == "test_catalog" - assert catalog._format_version == "v0" - assert catalog._pooch is None - assert catalog._versions is None - assert ( - catalog.get_catalog_file("v0.1.0") - == catalog._cache_dir / "test_catalog" / "v0.1.0" / "data_catalog.yml" - ) - assert ( - catalog.get_catalog_file() - == catalog._cache_dir / "test_catalog" / "v0.2.0" / "data_catalog.yml" - ) - assert catalog.versions == ["v0.1.0", "v0.2.0"] - - # remove source and cached registry file and check if one is created based on - # the cached catalog files - registry_path = catalog._cache_dir / "test_catalog" / "registry.txt" - registry_path.unlink() - Path(tmp_catalog_class.base_url, "registry.txt").unlink() - catalog._load_registry_file(overwrite=True) - assert registry_path.exists() - - with pytest.raises(ValueError, match="Version v0.0.0 not found"): - catalog.get_catalog_file("v0.0.0") - - -def test_create_registry_file(tmpdir, tmp_catalog_files): - # test create registry file - root = tmp_catalog_files - create_registry_file(root) - registry_path = root / "registry.txt" - assert registry_path.exists() - - # no catalog files - with pytest.raises(FileNotFoundError): - create_registry_file(Path(tmpdir, "not_existing")) - - # create a dummy catalog file with version folder - cat_path = root / "data_catalog.yml" - cat_path.write_text("meta:\n version: v0.1.0") - with pytest.raises(ValueError, match="No valid version found"): - create_registry_file(root) - - -def test_get_versions_artifacts(): - versions = ArtifactDataCatalog().versions - assert len(versions) > 0 - assert "v0.0.8" in versions - - -def test_catalog_versions(cat_root, tmpdir): - # assert all subdirs are catalogs and have a versions.yml file - catalogs = [d for d in cat_root.iterdir() if d.is_dir()] - for cat_dir in catalogs: - registry_file = cat_dir / "registry.txt" - assert registry_file.exists() - tmp_registry_file = Path(tmpdir) / f"{cat_dir.name}_registry.txt" - create_registry_file(cat_dir, tmp_registry_file) - # check if both registry files (incl hashes) are the same - with open(registry_file, "r") as f: - registry = sorted(f.readlines()) - with open(tmp_registry_file, "r") as f: - tmp_registry = sorted(f.readlines()) - assert registry == tmp_registry diff --git a/tests/validators/test_data_catalog_validation.py b/tests/validators/test_data_catalog_validation.py index a9c76d0aa..34a6e966d 100644 --- a/tests/validators/test_data_catalog_validation.py +++ b/tests/validators/test_data_catalog_validation.py @@ -15,8 +15,9 @@ ) -def test_deltares_data_catalog(latest_dd_version_uri): - yml_dict = _yml_from_uri_or_path(latest_dd_version_uri) +def test_deltares_data_catalog(): + p = "data/catalogs/deltares_data.yml" + yml_dict = _yml_from_uri_or_path(p) # whould raise error if something goes wrong _ = DataCatalogValidator.from_dict(yml_dict) From f1fad0ef457ce9623fb5969f52bd8bf6f28140f6 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Fri, 3 May 2024 07:03:05 +0000 Subject: [PATCH 078/110] Update pixi lock file (#914) Co-authored-by: GitHub --- pixi.lock | 10747 ++++++++++++++++++++++++++-------------------------- 1 file changed, 5473 insertions(+), 5274 deletions(-) diff --git a/pixi.lock b/pixi.lock index 97443f5ca..d19fb4d9e 100644 --- a/pixi.lock +++ b/pixi.lock @@ -7,28 +7,29 @@ environments: linux-64: - 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libgcc-ng >=12 - libxcb >=1.15,<1.16.0a0 @@ -26944,8 +27142,8 @@ packages: - xorg-xproto license: MIT license_family: MIT - size: 828692 - timestamp: 1697056910935 + size: 828060 + timestamp: 1712415742569 - kind: conda name: xorg-libxau version: 1.0.11 @@ -27098,13 +27296,13 @@ packages: timestamp: 1607291557628 - kind: conda name: xugrid - version: 0.9.0 + version: 0.10.0 build: pyhd8ed1ab_0 subdir: noarch noarch: python - url: https://conda.anaconda.org/conda-forge/noarch/xugrid-0.9.0-pyhd8ed1ab_0.conda - sha256: 0757cdbf0f92e68a3134588027511ea4c4f49002d397619c59bd73ab85ad4165 - md5: d6ef5b0239c439c99a37142f93b2c98b + url: https://conda.anaconda.org/conda-forge/noarch/xugrid-0.10.0-pyhd8ed1ab_0.conda + sha256: cf9b0c63b573405d5ac34a35819d98c10884abb0d49b19af0fc7414f8f44fa00 + md5: 7ef2f388e3b2adcecfed74591bff2451 depends: - dask - geopandas @@ -27121,25 +27319,25 @@ packages: license_family: MIT purls: - pkg:pypi/xugrid - size: 93360 - timestamp: 1707992771856 + size: 94214 + timestamp: 1714580639671 - kind: conda name: xyzservices - version: 2023.10.1 + version: 2024.4.0 build: pyhd8ed1ab_0 subdir: noarch noarch: python - url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2023.10.1-pyhd8ed1ab_0.conda - sha256: da655e2e0a742fddefeeaf2dd828b62a1820a3755d13341e1a555a10fcb9cf81 - md5: 1e0d85c0e2fef9539218da185b285f54 + url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2024.4.0-pyhd8ed1ab_0.conda + sha256: 4e095631b52a78bbd9b53f28eb79b0c8f448d9509cf0451e99c2f3f85576f114 + md5: 93dffc47dadbe36a1a644f3f50d4979d depends: - python >=3.8 license: BSD-3-Clause license_family: BSD purls: - pkg:pypi/xyzservices - size: 36184 - timestamp: 1698325478381 + size: 46179 + timestamp: 1712210047952 - kind: conda name: xz version: 5.2.6 @@ -27314,55 +27512,56 @@ packages: timestamp: 1705508499991 - kind: conda name: zarr - version: 2.17.1 + version: 2.17.2 build: pyhd8ed1ab_0 subdir: noarch noarch: python - url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.17.1-pyhd8ed1ab_0.conda - 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krb5 >=1.21.2,<1.22.0a0 - libgcc-ng >=12 - libsodium >=1.0.18,<1.0.19.0a0 - libstdcxx-ng >=12 license: MPL-2.0 license_family: MOZILLA - size: 343438 - timestamp: 1709135220800 + size: 351803 + timestamp: 1714545110790 - kind: conda name: zeromq version: 4.3.5 - build: h63175ca_1 - build_number: 1 + build: he0c23c2_3 + build_number: 3 subdir: win-64 - url: https://conda.anaconda.org/conda-forge/win-64/zeromq-4.3.5-h63175ca_1.conda - sha256: c9089e80a724a4d21f9df4bcc99ccbddb93c8cce3f6b0c9cb74b4f98b641dfc2 - md5: e8867cc4d023f41f54bd64a33436b0a1 + url: https://conda.anaconda.org/conda-forge/win-64/zeromq-4.3.5-he0c23c2_3.conda + sha256: 8aecdcafccb73417d6a8d5c99b2b89644cd1e739e9419b70db2b97ddd344a58a + md5: a15710475b7ec416900e60560f6839ee depends: - libsodium >=1.0.18,<1.0.19.0a0 - ucrt >=10.0.20348.0 @@ -27370,8 +27569,8 @@ packages: - vc14_runtime >=14.29.30139 license: MPL-2.0 license_family: MOZILLA - size: 4199151 - timestamp: 1709135717106 + size: 4196272 + timestamp: 1714545389805 - kind: conda name: zict version: 3.0.0 From 4b4012d778897e650b43c6b6386cd42ca2eb1046 Mon Sep 17 00:00:00 2001 From: deltamarnix <150045289+deltamarnix@users.noreply.github.com> Date: Fri, 10 May 2024 13:23:59 +0200 Subject: [PATCH 079/110] Update pixi to 0.21.1 (#919) --- .github/workflows/check-data-catalogs.yml | 4 ++-- .github/workflows/docs.yml | 4 ++-- .github/workflows/pixi_auto_update.yml | 4 ++-- .github/workflows/tests.yml | 4 ++-- 4 files changed, 8 insertions(+), 8 deletions(-) diff --git a/.github/workflows/check-data-catalogs.yml b/.github/workflows/check-data-catalogs.yml index c9840d305..0da0840bc 100644 --- a/.github/workflows/check-data-catalogs.yml +++ b/.github/workflows/check-data-catalogs.yml @@ -29,9 +29,9 @@ jobs: steps: - uses: actions/checkout@v3 - - uses: prefix-dev/setup-pixi@v0.5.1 + - uses: prefix-dev/setup-pixi@v0.6.0 with: - pixi-version: "v0.15.2" + pixi-version: "v0.21.1" environments: min-py311 - name: Prepare pixi run: | diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 99e6b19e2..717876e8b 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -33,9 +33,9 @@ jobs: steps: - name: checkout code uses: actions/checkout@v3 - - uses: prefix-dev/setup-pixi@v0.5.1 + - uses: prefix-dev/setup-pixi@v0.6.0 with: - pixi-version: "v0.15.2" + pixi-version: "v0.21.1" environments: full-py311 - name: Prepare pixi run: | diff --git a/.github/workflows/pixi_auto_update.yml b/.github/workflows/pixi_auto_update.yml index 84523f6fd..d14f53097 100644 --- a/.github/workflows/pixi_auto_update.yml +++ b/.github/workflows/pixi_auto_update.yml @@ -14,9 +14,9 @@ jobs: - uses: actions/checkout@v4 with: ssh-key: ${{ secrets.SSH_PRIVATE_KEY }} - - uses: prefix-dev/setup-pixi@v0.5.1 + - uses: prefix-dev/setup-pixi@v0.6.0 with: - pixi-version: "v0.15.2" + pixi-version: "v0.21.1" cache: false - name: Update pixi lock file run: | diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index b6dfcc7e5..a9c74bdaa 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -48,9 +48,9 @@ jobs: steps: - uses: actions/checkout@v4 - - uses: prefix-dev/setup-pixi@v0.5.1 + - uses: prefix-dev/setup-pixi@v0.6.0 with: - pixi-version: "v0.15.2" + pixi-version: "v0.21.1" environments: full-py${{ matrix.python-version }} - name: Prepare pixi run: | From 39cc2c51510c320242a59b2c6c34fbbeb77f418d Mon Sep 17 00:00:00 2001 From: Sam Vente Date: Mon, 13 May 2024 15:41:21 +0200 Subject: [PATCH 080/110] Refactor Catalogs (#921) Co-authored-by: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Co-authored-by: Tjalling-dejong --- .gitattributes | 2 + .github/pull_request_template.md | 15 +- .github/workflows/docs.yml | 2 +- .github/workflows/tests.yml | 2 +- data/catalogs/README.rst | 54 +- data/catalogs/artifact_data/registry.txt | 4 + .../artifact_data/v0.0.6/data_catalog.yml | 712 ++++++ .../artifact_data/v0.0.7/data_catalog.yml | 739 ++++++ .../v0.0.8/data_catalog.yml} | 17 +- .../artifact_data/v0.0.9/data_catalog.yml | 739 ++++++ data/catalogs/aws_data/registry.txt | 1 + .../v0.1.0/data_catalog.yml} | 5 +- data/catalogs/changelog.rst | 19 + data/catalogs/deltares_data/registry.txt | 2 + .../deltares_data/v0.5.0/data_catalog.yml | 1980 +++++++++++++++++ .../v0.6.0/data_catalog.yml} | 34 +- data/catalogs/gcs_cmip6_data/registry.txt | 1 + .../v0.1.0/data_catalog.yml} | 95 +- data/catalogs/update_versions.py | 11 + data/predefined_catalogs.yml | 8 +- docs/api.rst | 15 +- docs/changelog.rst | 11 + docs/conf.py | 4 +- examples/delineate_basin.ipynb | 2 +- examples/export_data.ipynb | 2 +- examples/prep_data_catalog.ipynb | 2 +- examples/reading_point_data.ipynb | 2 +- examples/reading_raster_data.ipynb | 2 +- examples/reading_vector_data.ipynb | 2 +- examples/working_with_flow_directions.ipynb | 2 +- examples/working_with_geodatasets.ipynb | 2 +- examples/working_with_meshmodel.ipynb | 2 +- examples/working_with_models.ipynb | 4 +- examples/working_with_raster.ipynb | 2 +- examples/working_with_tiled_raster_data.ipynb | 2 +- hydromt/data_catalog.py | 237 +- hydromt/predefined_catalog.py | 261 +++ pixi.lock | 1757 +++++++-------- pixi.toml | 1 + pyproject.toml | 3 +- tests/conftest.py | 34 +- tests/test_basin_mask.py | 18 +- tests/test_data_adapter.py | 74 +- tests/test_data_catalog.py | 168 +- tests/test_forcing.py | 15 +- tests/test_predefined_catalogs.py | 106 + .../test_data_catalog_validation.py | 5 +- 47 files changed, 5868 insertions(+), 1309 deletions(-) create mode 100644 data/catalogs/artifact_data/registry.txt create mode 100644 data/catalogs/artifact_data/v0.0.6/data_catalog.yml create mode 100644 data/catalogs/artifact_data/v0.0.7/data_catalog.yml rename data/catalogs/{artifact_data.yml => artifact_data/v0.0.8/data_catalog.yml} (97%) create mode 100644 data/catalogs/artifact_data/v0.0.9/data_catalog.yml create mode 100644 data/catalogs/aws_data/registry.txt rename data/catalogs/{aws_data.yml => aws_data/v0.1.0/data_catalog.yml} (88%) create mode 100644 data/catalogs/deltares_data/registry.txt create mode 100644 data/catalogs/deltares_data/v0.5.0/data_catalog.yml rename data/catalogs/{deltares_data.yml => deltares_data/v0.6.0/data_catalog.yml} (98%) create mode 100644 data/catalogs/gcs_cmip6_data/registry.txt rename data/catalogs/{gcs_cmip6_data.yml => gcs_cmip6_data/v0.1.0/data_catalog.yml} (84%) create mode 100644 data/catalogs/update_versions.py create mode 100644 hydromt/predefined_catalog.py create mode 100644 tests/test_predefined_catalogs.py diff --git a/.gitattributes b/.gitattributes index d5799bd69..c6702ae45 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,2 +1,4 @@ +* text eol=lf + # GitHub syntax highlighting pixi.lock linguist-language=YAML diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index 430612ed8..80b7c578d 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -4,13 +4,20 @@ Fixes # ## Explanation Explain how you addressed the bug/feature request, what choices you made and why. -## Checklist +## General Checklist - [ ] Updated tests or added new tests - [ ] Branch is up to date with `main` - [ ] Tests & pre-commit hooks pass -- [ ] Updated documentation if needed -- [ ] Updated changelog.rst if needed -- [ ] For predefined catalogs: update the catalog version in the file itself, the references in data/predefined_catalogs.yml, and the changelog in data/changelog.rst +- [ ] Updated documentation +- [ ] Updated changelog.rst + +## Data/Catalog checklist +- [ ] `data/catalogs/predefined_catalogs.yml` has not been modified. +- [ ] None of the old `data_catalog.yml` files have been chagned +- [ ] `data/chagnelog.rst` has been updated +- [ ] new file uses `LF` line endings (done automatically if you used `update_versions.py`) +- [ ] New file has been tested locally +- [ ] Tests have been added using the new file in the test suite ## Additional Notes (optional) Add any additional notes or information that may be helpful. diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 717876e8b..632be315f 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -27,7 +27,7 @@ jobs: test-docs: defaults: run: - shell: bash -l {0} + shell: bash -e -l {0} timeout-minutes: 30 runs-on: ubuntu-latest steps: diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index a9c74bdaa..cc7f69a28 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -32,7 +32,7 @@ jobs: build: defaults: run: - shell: bash -l {0} + shell: bash -e -l {0} strategy: fail-fast: false matrix: diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst index 58007af48..a92b67550 100644 --- a/data/catalogs/README.rst +++ b/data/catalogs/README.rst @@ -11,25 +11,24 @@ deltares_data The HydroMT Deltares Data is managed by the HydroMT team. For adding new data to the deltares_data.yml please follow the conventions given hereinafter. -The data is currently only stored on the deltares server: p:/wflow_global/hydromt +The data is currently only stored on the deltares network drive: p:/wflow_global/hydromt -preferred data formats to download +Preferred data formats to download ----------------------------------- vector data: flatgeobuf (because they contain a spatial index and are therefore much faster) raster data (2D): cloud optimized geotiff raster data (3D): zarr -data storage (p:/wflow_global/hydromt) --------------------------------------- +Data storage in the Deltares network drive (p:/wflow_global/hydromt) +-------------------------------------------------------------------- data used by the geoserver: -DO NOT CHAGE WITHOUT CONSULTATION +DO NOT CHANGE WITHOUT CONSULTATION - alosdem - copdem writing convention: -- lower case -- with underscores +- snake_case (i.e. lower case with underscores) folder structure: - no subcategories @@ -62,24 +61,21 @@ folder structure: deltares_data.yml ------------------ writing convention: -- lower case -- with underscore +- snake_case (i.e. lower case with underscores) - the key "data_type" follows this convention but the data type itself is written in cam case (RasterDataset/GeoDataFrame/GeoDataset) - two spaces for indentation data versioning: - data always refers to a specific version -- version is indicated within the name of the alias - short name refers to that version -- convention: [data_name]_v[version_number] -- e.g. eobs_v22.0e +- convention: `[data_name]_v[version_number]` (e.g. `eobs_v22.0e`) structure per data set: - use placeholders where possible - order the data sets alphabetically - order the components of each data set alphabetically - for adding meta data use the following optional keys: - +```yaml category: notes: paper_doi: @@ -89,12 +85,32 @@ source_license: source_url: source_version: unit: +``` -updates +Updates ------- -- create new branch on github -- make changes and bump the version in the global meta section using `calendar versioning ` -- test your yml file (Can the added/changed data sources be read through HydroMT?) -- create pull request -- add new version to hydromt\data\predefined_catalogs.yml +To preserve reproducibility for older versions of the catalogs, we DO NOT modify old catalogs in any way. Even adding different whitespaces to the file is problematic because of how they are retrieved. Instead, we use a versioning system for the catalog files themselves. If you want to update one of the catalogs, follow the following steps + +1. create new branch on github +2. make a new folder with the name of the version you are going to create +3. add the new version of the data catalog to this new folder, and make sure it is called `data_catalog.yml`. You can also copy the latest data catalog into the new folder and simply edit the copied version. +4. bump the version in the global meta section using semantic versioning +5. run update_versions.py, this will create a registry file with the versions and SHA256 hashes of the data catalogs. It is very important that the files have Linux style line endings (LF) as opposed to windows style line endings (CRLF) to keep hashes consistent. If this is not done, pooch will not be able to find the catalogs. This is done automatically for you (CRLF -> LF) if you are updating from windows. +6. test your yml file, (for more information on testing see section below). +7. create a pull request targeting the main branch +8. Once the pull request get's merged into the `main` branch, it should be available to all HydroMT users. + +Testing +------- +If you want to make catalogs for HydroMT testing purposes, or to update a catalog with new data, we must first ensure that HydroMT can properly read and use your data. To do this, we need to test the data with HydroMT in our CI environment on github. DO NOT modify the `data/catalogs/predefined_catalogs.yml` file to do this. The use of this file is deprecated and it is maintained for backwards compatibility, but should no longer be used. + +Testing a new data catalog should be fairly straight forward once it is created. The level of testing we require to add new catalogs can varry depending on the size, importance, and popularity of the set. In order of importance the tests that should be done are: + +1. Instantiate a catalog, and retrieve the dataset from it using the appropriate `get_*` function (e.g. `get_rasterdataset` for raster data) +2. The dataset should slice properly in whatever ways are appropriate. (e.g. requesting a dataset with only certain variables should return only that data if the driver supports it) +3. If the dataset requires special logic to merge several parts please add tests to demostrate the correct working of this as well. +4. Units should be acounted for properly using properties such as `unit`, `unti_add`, and `unit_mult` where appropriate +5. Whatever domain specific quality assurance should be done, to avoid for example, rounding errors near the boundaries. + +At least, point one needs to be verified locally by the author of the PR, and preferably a test should be made for it in our CI as well. Depending on context we may ask you to verify other points (on this list) as well. diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt new file mode 100644 index 000000000..e85a01833 --- /dev/null +++ b/data/catalogs/artifact_data/registry.txt @@ -0,0 +1,4 @@ +v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 +v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee +v0.0.8/data_catalog.yml c1cf2229eeb93607ea881fdbced45ebf43471271f0b7d878db8183734274cd88 +v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 diff --git a/data/catalogs/artifact_data/v0.0.6/data_catalog.yml b/data/catalogs/artifact_data/v0.0.6/data_catalog.yml new file mode 100644 index 000000000..e51554f73 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.6/data_catalog.yml @@ -0,0 +1,712 @@ +meta: + version: v0.0.6 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.6/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + category: null + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/artifact_data/v0.0.7/data_catalog.yml b/data/catalogs/artifact_data/v0.0.7/data_catalog.yml new file mode 100644 index 000000000..4d549a7c3 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.7/data_catalog.yml @@ -0,0 +1,739 @@ +meta: + version: v0.0.7 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.7/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_daily_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5_daily_zarr.zarr +era5_hourly_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly_zarr.zarr +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/artifact_data.yml b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml similarity index 97% rename from data/catalogs/artifact_data.yml rename to data/catalogs/artifact_data/v0.0.8/data_catalog.yml index e09b16148..e4bcfd3c1 100644 --- a/data/catalogs/artifact_data.yml +++ b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml @@ -1,7 +1,7 @@ meta: version: v0.0.8 - hydromt_version: '>=0.9, <1.0' root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz + name: artifact_data chelsa: crs: 4326 @@ -95,7 +95,8 @@ era5: driver: netcdf meta: category: meteo - history: Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -139,7 +140,8 @@ era5_daily_zarr: driver: zarr meta: category: meteo - history: Extracted from Copernicus Climate Data Store; resampled by Deltares to + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency paper_doi: 10.1002/qj.3803 paper_ref: Hersbach et al. (2019) @@ -246,7 +248,8 @@ gdp_world: meta: category: socio economic source_author: Wilfred Altena - source_info: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 source_version: 1.0 @@ -606,7 +609,8 @@ modis_lai: driver: netcdf meta: category: landuse & landcover - notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' paper_doi: 10.5067/MODIS/MCD15A3H.006 paper_ref: Myneni et al (2015) @@ -680,7 +684,8 @@ soilgrids: driver: raster meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ \ distribution version 2.0, european commission and the European soil bureau\ \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ diff --git a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml new file mode 100644 index 000000000..518ea84c5 --- /dev/null +++ b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml @@ -0,0 +1,739 @@ +meta: + version: v0.0.9 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.9/data.tar.gz + name: artifact_data + +chelsa: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: chelsa.tif +chirps_global: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: chirps_global.nc + unit_add: + time: 86400 +corine: + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: corine.tif +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: dtu10mdt.tif +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: dtu10mdt_egm96.tif +eobs: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs.nc + unit_add: + time: 86400 +eobs_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: eobs_orography.nc +era5: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5.nc + unit_add: + temp: -273.15 + temp_max: -273.15 + temp_min: -273.15 + time: 86400 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly.nc + unit_add: + temp: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + precip: 1000 + press_msl: 0.01 +era5_daily_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: + Extracted from Copernicus Climate Data Store; resampled by Deltares to + daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: era5_daily_zarr.zarr +era5_hourly_zarr: + crs: 4326 + data_type: RasterDataset + driver: zarr + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_hourly_zarr.zarr +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + history: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 hourly data on pressure levels + path: era5_orography.nc + unit_mult: + elevtn: 0.10197162129779283 +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level1.gpkg +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level2.gpkg +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2020-10-19; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 1.0 + path: gadm_level3.gpkg +gcn250: + data_type: RasterDataset + driver: raster + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: gcn250/{variable}.tif +gdp_world: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio economic + source_author: Wilfred Altena + source_info: + data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_license: CC BY-4.0 + source_version: 1.0 + path: gdp_world.gpkg +gebco: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: gebco.tif +ghs-smod_2015_v2: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif +ghs_pop_2015: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: ghs_pop_2015.tif +ghs_pop_2015_54009: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: ghs_pop_2015_54009.tif +ghs_smod_2015: + crs: 54009 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: ghs_smod_2015.tif +globcover: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + path: globcover.tif +glw_buffaloes: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_buffaloes.tif +glw_cattle: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_cattle.tif +glw_chicken: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_chicken.tif +glw_ducks: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_ducks.tif +glw_goats: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_goats.tif +glw_horses: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_horses.tif +glw_pigs: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_pigs.tif +glw_sheep: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: glw_sheep.tif +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: csv + meta: + category: observed data + source_info: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: grdc.csv +grip_roads: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + paper_doi: 10.1088/1748-9326/aabd42 + paper_ref: Meijer et al, 2018 + source_license: CC0-1.0 + source_url: https://www.globio.info/download-grip-dataset + source_version: v4 + path: grip_roads.gpkg +grwl: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: grwl.gpkg +grwl_mask: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: grwl_tindex.gpkg +gswo: + data_type: RasterDataset + driver: raster + meta: + category: surface water + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: gswo.tif +gtsmv3_eu_era5: + crs: 4326 + data_type: GeoDataset + driver: netcdf + meta: + category: ocean + paper_doi: 10.24381/cds.8c59054f + paper_ref: Copernicus Climate Change Service 2019 + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview + source_version: GTSM v3.0 + path: gtsmv3_eu_era5.nc +guf_bld_2012: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: socio economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: guf_bld_2012.tif +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Arjen Haag + source_info: HydroLAKES.v10_extract + source_version: 1.0 + path: hydro_lakes.gpkg + unit_mult: + Area_avg: 1000000.0 +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + source_author: Alessia Matano + source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_version: 1.0 + nodata: -99 + path: hydro_reservoirs.gpkg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: koppen_geiger.tif +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: mdt_cnes_cls18.tif +merit_hydro: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: merit_hydro/{variable}.tif +merit_hydro_1k: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + source_url: https://doi.org/10.5281/zenodo.4138776 + source_version: 0.1 + path: merit_hydro_1k/{variable}.tif +merit_hydro_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (in review) + source_license: CC-BY-NC 4.0 + path: merit_hydro_index.gpkg +modis_lai: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: landuse & landcover + notes: + this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the + period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: modis_lai.nc + unit_mult: + LAI: 0.1 +osm_coastlines: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_coastlines.gpkg +osm_landareas: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + source_author: OpenStreetMap + source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: osm_landareas.gpkg +rgi: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_info: Randolph Glacier Inventory + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: rgi.gpkg +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: rivers_lin2019_v1.gpkg +simard: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: simard.tif +soilgrids: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia\ + \ (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database\ + \ distribution version 2.0, european commission and the European soil bureau\ + \ network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van\ + \ Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre:\ + \ Response to european policy support and public data requirements. Land Use\ + \ Policy 29 (2), 329\xE2\u20AC\u201C338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soilgrids/{variable}.tif + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 +vito: + crs: 4326 + data_type: RasterDataset + driver: raster + meta: + category: landuse & landcover + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: vito.tif +wb_countries: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + author: World Bank + category: socio-economic + source_license: CC-BY 4.0 + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + timestamp: February 2020 + path: wb_countries.gpkg +worldclim: + crs: 4326 + data_type: RasterDataset + driver: netcdf + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + path: worldclim.nc diff --git a/data/catalogs/aws_data/registry.txt b/data/catalogs/aws_data/registry.txt new file mode 100644 index 000000000..e1e113d4b --- /dev/null +++ b/data/catalogs/aws_data/registry.txt @@ -0,0 +1 @@ +v0.1.0/data_catalog.yml e0e3c4e10bd6ce51014a04b8ca85de0c987b3cfe7bfa16961f772a953a307038 diff --git a/data/catalogs/aws_data.yml b/data/catalogs/aws_data/v0.1.0/data_catalog.yml similarity index 88% rename from data/catalogs/aws_data.yml rename to data/catalogs/aws_data/v0.1.0/data_catalog.yml index 0e2378c2c..446a8a2fe 100644 --- a/data/catalogs/aws_data.yml +++ b/data/catalogs/aws_data/v0.1.0/data_catalog.yml @@ -1,8 +1,7 @@ --- meta: - version: 2024.1.30 - hydromt_version: '>=0.9, <1.0' - + version: v0.1.0 + name: aws_data esa_worldcover_2020_v100: crs: 4326 diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 0748c3a89..f47ff7746 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -2,6 +2,25 @@ Change log predefined datasets ============================== +Pre-defined catalog refactor +============================ + +Changed +------- +The pre-defined data catalogs have been moved to their own folders together with +a version.yml. This file describes the different versions and relative paths of +the data catalogs present in the folders. + +- predefined_catalogs.yml is deprecated +- data catalog versions are associated with the SHA-256 hash of the files. +- deltares_data versioning is now in semantic style + +Added +----- +- v0.0.6, v0.0.7, v0.0.9 of the artifact_data +- v0.5.0, v0.6.0 of the deltares_data + + deltares_data ============= diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt new file mode 100644 index 000000000..c7ed1691b --- /dev/null +++ b/data/catalogs/deltares_data/registry.txt @@ -0,0 +1,2 @@ +v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 +v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef diff --git a/data/catalogs/deltares_data/v0.5.0/data_catalog.yml b/data/catalogs/deltares_data/v0.5.0/data_catalog.yml new file mode 100644 index 000000000..a54d5eee3 --- /dev/null +++ b/data/catalogs/deltares_data/v0.5.0/data_catalog.yml @@ -0,0 +1,1980 @@ +--- +meta: + root: p:/wflow_global/hydromt + version: v0.5.0 + name: deltares_data + +basin_atlas_level12_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + kwargs: + layer: BasinATLAS_v10_lev12 + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/basin_atlas_v10.gpkg + +river_atlas_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/river_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + +lake_atlas_pol_v10: + crs: 4326 + data_type: GeoDataFrame + driver: vector + kwargs: + layer: LakeATLAS_v10_pol + meta: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + source_license: CC BY 4.0 + source_url: https://www.hydrosheds.org/hydroatlas + source_version: 10 + path: hydrography/hydro_atlas/lake_atlas_v10.gpkg + rename: + dis_m3_pyr: Dis_avg + +chelsa: + alias: chelsa_v1.2 +chelsa_v1.2: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: meteo + paper_doi: 10.1038/sdata.2017.122 + paper_ref: Karger et al. (2017) + source_license: CC BY 4.0 + source_url: http://chelsa-climate.org/downloads/ + source_version: 1.2 + path: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif + +chirps: + alias: chirps_africa_daily_v2.0 +chirps_africa_daily_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + lat: 160 + lon: 150 + time: 20 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + paper_doi: 10.1038/sdata.2015.66 + paper_ref: Funk et al (2015) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc + rename: + precipitation: precip + unit_add: + time: 86400 + +chirps_global: + alias: chirps_global_daily_v2.0 +chirps_global_daily_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 112 + longitude: 400 + time: 20 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + paper_doi: 10.3133/ds832 + paper_ref: Funk et al (2014) + source_license: CC + source_url: https://www.chc.ucsb.edu/data/chirps + source_version: v2.0 + path: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc + rename: + precipitation: precip + unit_add: + time: 86400 + +copdem30: + alias: copdem30_v2021.1 +copdem30_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning + path: topography/copdem/copdem.vrt + rename: + copdem: elevtn + +copdem30_mask: + alias: copdem30_mask_v2021.1 +copdem30_mask_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning + path: topography/copdem/copdem_mask.vrt + rename: + copdem_mask: mask + +copdem30_masked: + alias: copdem30_masked_v2021.1 +copdem30_masked_v2021.1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 + source_version: "2021_1" + path: topography/copdem/copdem_masked.vrt + rename: + copdem_masked: elevtn + +corine: + alias: corine_2018_v2020_u1 +corine_2018_v2020_u1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: landuse + source_author: European Environment Agency + source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 + source_version: v.2020_20u1 + path: landuse/corine/CLC2018_CLC2018_V2018_20.tif + +dtu10mdt: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM2008 + path: topography/dtu10mdt/DTU10MDT_1min_float32.tif + +dtu10mdt_egm96: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.1029/2008JC005179 + paper_ref: Andersen and Knudsen (2009) + source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography + source_version: 2010 + unit: m+EGM96 + path: topography/dtu10mdt/DTU10MDT_1min_egm96.tif + +eobs: + alias: eobs_v22.0e +eobs_v22.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_v29.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + time: 100 + combine: by_coords + parallel: true + preprocess: round_latlon + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 29.0e + path: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc + rename: + pp: press_msl + qq: kin + rr: precip + tg: temp + unit_add: + time: 86400 + +eobs_orography_v20.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 20.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + rename: + elevation: elevtn + +eobs_orography: + alias: eobs_orography_v22.0e +eobs_orography_v22.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 22.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + rename: + elevation: elevtn + +eobs_orography_v23.1e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 23.1e + path: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + rename: + elevation: elevtn + +eobs_orography_v24.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 24.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + rename: + elevation: elevtn + +eobs_orography_v25.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 25.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + rename: + elevation: elevtn + +eobs_orography_v29.0e: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 100 + longitude: 100 + meta: + category: meteo + paper_doi: 10.1029/2017JD028200 + paper_ref: Cornes et al (2018) + source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles + source_version: 29.0e + path: meteo/eobs/elev_ens_0.1deg_reg_v29.0e.nc + rename: + elevation: elevtn + +era5: + alias: era5_daily +era5_daily: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 250 + longitude: 240 + time: 30 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store; resampled by Deltares to daily frequency + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + source_version: ERA5 daily data on pressure levels + path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tmax: temp_max + tmin: temp_min + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + temp_max: -273.15 + temp_min: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + press_msl: 0.01 + +era5_daily_zarr: + alias: era5_daily + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + path: meteo/era5_daily.zarr + +era5_hourly: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 125 + longitude: 120 + time: 50 + combine: by_coords + decode_times: true + parallel: true + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.adbb2d47 + source_version: ERA5 hourly data on single levels from 1940 to present + path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + rename: + d2m: temp_dew + msl: press_msl + ssrd: kin + t2m: temp + tisr: kout + tp: precip + u10: wind10_u + v10: wind10_v + unit_add: + temp: -273.15 + temp_dew: -273.15 + unit_mult: + kin: 0.000277778 + kout: 0.000277778 + ssr: 0.000277778 + precip: 1000 + press_msl: 0.01 + +era5_hourly_zarr: + alias: era5_hourly + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + path: meteo/era5.zarr + +era5_ocean: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 60 + longitude: 60 + time: 720 + combine: by_coords + decode_times: true + parallel: true + meta: + category: ocean + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://doi.org/10.24381/cds.bd0915c6 + path: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc + +era5_orography: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 120 + longitude: 125 + meta: + category: meteo + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.1002/qj.3803 + paper_ref: Hersbach et al. (2019) + source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products + source_url: https://apps.ecmwf.int/codes/grib/param-db?id=129 + path: meteo/era5/meta/era5_orography_2018.nc + rename: + z: elevtn + unit_mult: + elevtn: 0.10197162129779283 + +esa_worldcover: + alias: esa_worldcover_2020_v100 +esa_worldcover_2020_v100: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 36000 + y: 36000 + meta: + category: landuse + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.5571936 + source_version: v100 + path: landuse/esa_worldcover/esa-worldcover.vrt + +fabdem: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: CC BY-NC-SA 4.0 + paper_ref: Hawker et al. (2022) + source_license: CC BY-NC-SA 4.0 + source_url: https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7 + source_version: 1.0 + path: topography/fabdem/fabdem.vrt + rename: + fabdem: elevtn + +gadm: + alias: gadm_level0 + +gadm_level0: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_0.sh + path: geography/gadm/version4_1/gadm_level0.fgb + +gadm_level1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_1.sh + path: geography/gadm/version4_1/gadm_level1.fgb + +gadm_level2: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_2.sh + path: geography/gadm/version4_1/gadm_level2.fgb + +gadm_level3: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: last downloaded 2023-12-18; license required for commercial use + source_author: gadm + source_license: https://gadm.org/license.html + source_url: https://gadm.org/download_world.html + source_version: 4.1 + processing_script: geography/gadm/version4_1/run_dissolve_level_3.sh + path: geography/gadm/version4_1/gadm_level3.fgb + +gcn250: + alias: gcn250_v1 +gcn250_v1: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: soil + paper_doi: 10.1038/s41597-019-0155-x + paper_ref: Jaafar et al. (2019) + source_license: CC BY 4.0 + source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 + source_version: v1 + nodata: 255 + path: landuse/gcn250/GCN250_*.tif + rename: + GCN250_ARCI: cn_dry + GCN250_ARCII: cn_avg + GCN250_ARCIII: cn_wet + +gdp_world: + alias: gdp_world_v1 +gdp_world_v1: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio-economic + notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) + source_author: Wilfred Altena + source_license: CC BY-4.0 + source_version: 1.0 + path: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb + rename: + GDP: gdp + unit_mult: + gdp: 0.001 + +gebco: + alias: gebco_v2020 +gebco_v2020: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: topography + paper_doi: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9 + paper_ref: Weatherall et al (2020) + source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 + source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ + source_version: 2020 + unit: m+MSL + path: bathymetry/gebco/gebco.vrt + rename: + gebco: elevtn + +ghs_pop: + alias: ghs_pop_2015_54009_v2019a +ghs_pop_2015_4326_v2019a: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.2905/0C6B9751-A71F-4062-830B-43C9F432370F + paper_ref: Schiavina et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f + source_version: R2019A_v1.0 + path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif + +ghs_pop_2015_54009_v2019a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.2760/062975 + paper_ref: Florczyk et al (2019) + source_license: CC BY 4.0 + source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + path: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif + +ghs_smod: + alias: ghs_smod_2015_54009_v2019a +ghs_smod_2015_54009_v2016a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_ref: Pesaresi and Freire (2016) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + source_version: R2016A_v1.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + +ghs_smod_2015_54009_v2019a: + crs: "ESRI:54009" + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_author: JRC-ISPRA EC + source_license: https://data.jrc.ec.europa.eu/licence/com_reuse + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + source_version: R2019A_v2.0 + path: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + +globcover: + alias: globcover_2009_v2.3 +globcover_2009_v2.3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.1594/PANGAEA.787668 + paper_ref: Arino et al (2012) + source_license: CC-BY-3.0 + source_url: http://due.esrin.esa.int/page_globcover.php + source_version: v2.3 + path: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif + +glofas_era5_v31: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + time: 180 + latitude: 150 + longitude: 360 + combine: by_coords + decode_times: true + parallel: true + meta: + category: hydro + notes: Extracted from Copernicus Climate Data Store + paper_doi: 10.5194/essd-12-2043-2020 + paper_ref: Harrigan et al. (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf + source_url: https://doi.org/10.24381/cds.a4fdd6b9 + source_version: v31 + path: hydro/glofas_era5/glofas_v31_{year}.nc + rename: + dis24: discharge + +glofas_uparea: + alias: glofas_era5_v31 + driver: raster + kwargs: + chunks: + x: 150 + y: 360 + path: hydro/glofas_era5/glofas_v31_uparea.tif + rename: + glofas_v31_uparea: uparea + unit_mult: + uparea: 0.000001 + +glw_buffaloes: + alias: glw_buffaloes_v3 +glw_buffaloes_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/5U8MWI + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Bf_2010_Da.tif + +glw_cattle: + alias: glw_cattle_v3 +glw_cattle_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/GIVQ75 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ct_2010_Da.tif + +glw_chicken: + alias: glw_chicken_v3 +glw_chicken_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/SUFASB + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ch_2010_Da.tif + +glw_ducks: + alias: glw_ducks_v3 +glw_ducks_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/ICHCBH + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Dk_2010_Da.tif + +glw_goats: + alias: glw_goats_v3 +glw_goats_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/OCPH42 + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Gt_2010_Da.tif + +glw_horses: + alias: glw_horses_v3 +glw_horses_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/7Q52MV + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Ho_2010_Da.tif + +glw_pigs: + alias: glw_pigs_v3 +glw_pigs_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/33N0JG + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Pg_2010_Da.tif + +glw_sheeps: + alias: glw_sheeps_v3 +glw_sheeps_v3: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: socio-economic + paper_doi: 10.7910/DVN/BLWPZN + paper_ref: Gilbert at al (2018) + source_author: glw (Gridded Livestock of World 3 Dataverse) + source_license: CC 4.0 + source_url: https://dataverse.harvard.edu/dataverse/glw_3 + source_version: GLW 3, last downloaded 2020-06-11 + path: socio_economic/glw/5_Sh_2010_Da.tif + +grdc: + crs: 4326 + data_type: GeoDataFrame + driver: xlsx + kwargs: + index_col: grdc_no + meta: + category: observed data + notes: GRDC-Station Catalogue, last downloaded 2020-07-16 + source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 + source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue + path: hydro/grdc/GRDC_Stations.xlsx + rename: + area: uparea + +grip_roads: + alias: grip_roads_v4 +grip_roads_v4: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: road + source_url: https://www.globio.info/download-grip-dataset + paper_ref: Meijer et al, 2018 + paper_doi: 10.1088/1748-9326/aabd42 + source_license: CC0-1.0 + source_version: v4 + path: infrastructure/grip/GRIP4_world.fgb + rename: + GP_RTP: road_type + GP_RCY: country_code + +grwl: + alias: grwl_v1.01 +grwl_v1.01: + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + path: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb + +grwl_mask: + alias: grwl_mask_v1.01 +grwl_mask_v1.01: + data_type: RasterDataset + driver: raster_tindex + kwargs: + chunks: + x: 3000 + y: 3000 + mosaic_kwargs: + method: nearest + tileindex: location + meta: + category: hydrography + paper_doi: 10.1126/science.aat0636 + paper_ref: Allen and Pavelsky (2018) + source_license: CC BY 4.0 + source_url: https://doi.org/10.5281/zenodo.1297434 + source_version: 1.01 + nodata: 0 + path: hydrography/grwl/tindex.gpkg + +gswo: + alias: gswo_v2019 +gswo_v2019: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 4000 + y: 4000 + meta: + category: hydrography + paper_doi: 10.1038/nature20584 + paper_ref: Pekel et al. (2016) + source_url: https://global-surface-water.appspot.com/download + source_version: v1_1_2019 + nodata: 255 + path: hydrography/gswo/occur.vrt + +gtsm_codec_reanalysis_{freq}_v1: + crs: 4326 + data_type: GeoDataset + driver: netcdf + kwargs: + chunks: + stations: 10 + time: -1 + meta: + category: ocean + paper_doi: 10.3389/fmars.2020.00263 + paper_ref: Muis at al (2020) + source_license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf + source_url: https://doi.org/10.24381/cds.8c59054f + source_version: v1 + path: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc + placeholders: + freq: [10min, hourly, dailymax] + rename: + station_x_coordinate: lon + station_y_coordinate: lat + stations: index + +guf_bld_2012: + alias: guf_bld_2012_v02 +guf_bld_2012_v02: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.1016/j.isprsjprs.2017.10.012 + paper_ref: Esch et al (2017) + source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf + source_url: http://www.dlr.de/guf + path: infrastructure/guf/GUF04_DLR_v02.vrt + +hydro_lakes: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: HydroLAKES.v10_extract + source_author: Arjen Haag + source_version: 1.0 + path: hydrography/lakes/lake-db.fgb + rename: + Depth_avg: Depth_avg + Dis_avg: Dis_avg + Hylak_id: waterbody_id + Lake_area: Area_avg + Pour_lat: yout + Pour_long: xout + Vol_total: Vol_avg + unit_mult: + Area_avg: 1000000.0 + +hydro_reservoirs: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + source_author: Alessia Matano + source_version: 1.0 + nodata: -99 + path: hydrography/reservoirs/reservoir-db.fgb + rename: + Depth_avg: Depth_avg + Dis_avg: Dis_avg + G_CAP_MAX: Capacity_max + G_CAP_MIN: Capacity_min + G_CAP_REP: Capacity_norm + G_DAM_HGT_: Dam_height + Grand_id: waterbody_id + Hylak_id: Hylak_id + Lake_area: Area_avg + Pour_lat: yout + Pour_long: xout + Vol_total: Vol_avg + unit_mult: + Area_avg: 1000000.0 + Capacity_max: 1000000.0 + Capacity_min: 1000000.0 + Capacity_norm: 1000000.0 + Vol_avg: 1000000.0 + +koppen_geiger: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: meteo + paper_doi: 10.1127/0941-2948/2006/0130 + paper_ref: Kottek et al. (2006) + source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm + source_version: 2017 + nodata: 0 + path: meteo/climate_classification_v2017/Map_KG-Global.tif + +mdt_cnes_cls18: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 720 + y: 720 + meta: + category: topography + paper_doi: 10.5194/os-17-789-2021 + paper_ref: Mulet et al (2021) + source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html + source_version: 18 + unit: m+GOCO05S + path: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif + +merit: + alias: merit_v1.0.3 +merit_v1.0.3: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + drop_variables: projection + chunks: + lat: 6000 + lon: 6000 + meta: + category: topography + paper_doi: 10.1002/2017GL072874 + paper_ref: Yamazaki et al. (2018) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ + source_version: 1.0.3 + path: topography/merit/merit.nc + rename: + elevation: elevtn + +merit_hydro: + alias: merit_hydro_v1.0 +merit_hydro_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 + path: topography/merit_hydro/*.vrt + rename: + bas: basins + dir: flwdir + elv: elevtn + slp: lndslp + sto: strord + upa: uparea + upg: upgrid + wth: rivwth + +merit_hydro_ihu: + alias: merit_hydro_ihu_30sec_v1.0 +merit_hydro_ihu_30sec_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.5194/hess-2020-582 + paper_ref: Eilander et al. (2021) + source_license: ODC-By 1.0 + source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + source_doi: 10.5281/zenodo.5166932 + source_version: 1.0 + path: topography/merit_hydro_ihu/30sec/*.tif + rename: + 30sec_basids: basins + 30sec_flwdir: flwdir + 30sec_elevtn: elevtn + 30sec_strord: strord + 30sec_uparea: uparea + 30sec_rivlen: rivlen + 30sec_rivslp: rivslp + +merit_hydro_ihu_index: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-25-5287-2021 + paper_ref: Eilander et al. (2021) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/5166932#.YVbxJ5pByUk + path: topography/merit_hydro_ihu/30sec/basins.gpkg + +merit_hydro_index: + alias: merit_hydro_index_v1.0 +merit_hydro_index_v1.0: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: topography + paper_doi: 10.5194/hess-25-5287-2021 + paper_ref: Eilander et al. (2021) + source_license: CC-BY-NC 4.0 + path: topography/merit_hydro/basin_index.fgb + +merit_hydro_patch: + alias: merit_hydro_patch_v1.0 +merit_hydro_patch_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 6000 + y: 6000 + meta: + category: topography + paper_doi: 10.1029/2019WR024873 + paper_ref: Yamazaki et al. (2019) + source_license: CC-BY-NC 4.0 or ODbL 1.0 + source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro + source_version: 1.0 Deltares patch + path: topography/merit_hydro/patches/*.vrt + rename: + bas: basins + dir: flwdir + elv: elevtn + slp: lndslp + sto: strord + upa: uparea + upg: upgrid + wth: rivwth + +modis_lai: + alias: modis_mcd15a3h_v006 +modis_mcd15a3h_v006: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + concat: true + meta: + category: landuse + notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') for the period '2003-01-01', '2017-12-31' + paper_doi: 10.5067/MODIS/MCD15A3H.006 + paper_ref: Myneni et al (2015) + source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ + source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ + source_version: MCD15A3H V006 + path: landuse/modis/MODIS_MCD15A3H_LAI/*.tif + unit_mult: + LAI: 0.1 + +osm_coastlines: + alias: osm_coastlines_v20200109 +osm_coastlines_v20200109: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 + source_author: OpenStreetMap + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: geography/osm/osm_coastlines-db.fgb + rename: + fid: coastline_id + +osm_landareas: + alias: osm_landareas_v20200109 +osm_landareas_v20200109: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: geography + notes: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 + source_author: OpenStreetMap + source_license: ODbL + source_url: https://osmdata.openstreetmap.de/data/coastlines.html + source_version: 1.0 + path: geography/osm/osm_landareas-db.fgb + rename: + fid: land_id + +pcr_globwb: + crs: 4326 + data_type: RasterDataset + driver: zarr + kwargs: + chunks: auto + meta: + category: water demand + notes: last downloaded 2023-11-23 + paper_doi: 10.5281/zenodo.1045339 + paper_ref: Sutanudjaja, E. H., et al (2017) + source_url: https://zenodo.org/records/1045339#.XWUr7E2P5aR + source_version: 2017.11b1 + processing_script: hydro/pcr_globwb/prep_glob.py + variants: + - version: 1990 + path: hydro/pcr_globwb/glob_1990.zarr + - version: 1995 + path: hydro/pcr_globwb/glob_1995.zarr + - version: 2000 + path: hydro/pcr_globwb/glob_2000.zarr + - version: 2005 + path: hydro/pcr_globwb/glob_2005.zarr + nodata: -9999 + rename: + domesticNettoDemand: dom_net + domesticGrossDemand: dom_gross + industryNettoDemand: ind_net + industryGrossDemand: ind_gross + livestockNettoDemand: lsk_net + livestockGrossDemand: lsk_gross + unit_mult: + dom_net: 1000 + dom_gross: 1000 + ind_net: 1000 + ind_gross: 1000 + lsk_net: 1000 + lsk_gross: 1000 + +rgi: + alias: rgi_v0.6 +rgi_v0.6: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: surface water + notes: Randolph Glacier Inventory + paper_doi: 10.3189/2014JoG13J176 + paper_ref: Pfeffer et al. (2014) + source_license: CC BY 4.0 + source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview + source_version: 6.0 + path: hydrography/rgi/rgi.fgb + rename: + C3S_ID: C3S_id + GLIMSID: GLIMS_id + ID: simple_id + RGIID: RGI_id + +rivers_lin2019_v1: + data_type: GeoDataFrame + driver: vector + meta: + category: hydrography + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + source_license: CC-BY-NC 4.0 + source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + source_version: 1 + path: hydrography/rivers_lin2019/rivers_ge30m.fgb + rename: + width_m: rivwth + Q2: qbankfull + +simard: + alias: simard_v2011 +simard_v2011: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.1029/2011JG001708 + paper_ref: Simard et al (2011) + source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 + path: landuse/simard/sdat_10023_canopy_height_simard.tif + +SM2RAIN_ASCAT_monthly_025_v1.4: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 360 + longitude: 720 + time: 84 + meta: + category: meteo + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.25-degree resolution + paper_doi: 10.5194/essd-11-1583-2019 + paper_ref: Brocca et al. (2019) + source_license: https://creativecommons.org/licenses/by/4.0/legalcode + source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc + rename: + rainfall: precip + +SM2RAIN_ASCAT_monthly_05_v1.4: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + latitude: 180 + longitude: 360 + time: 84 + meta: + category: meteo + notes: crs guessed as it is neither mentioned in the data nor in the literature, 0.5-degree resolution + paper_doi: 10.5194/essd-11-1583-2019 + paper_ref: Brocca et al. (2019) + source_license: https://creativecommons.org/licenses/by/4.0/legalcode + source_url: https://zenodo.org/record/4570192#.YueKJWNByUl + path: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc + rename: + rainfall: precip + +soilgrids: + alias: soilgrids_v1.0 +soilgrids_v1.0: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: 10.1371/journal.pone.0169748 + paper_ref: Hengl et al. (2017) + source_license: ODbL + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 + source_version: 2017 + path: soil/soilgrids_v1.0/*_250m_ll.tif + rename: + BLDFIE_M_sl1_250m_ll: bd_sl1 + BLDFIE_M_sl2_250m_ll: bd_sl2 + BLDFIE_M_sl3_250m_ll: bd_sl3 + BLDFIE_M_sl4_250m_ll: bd_sl4 + BLDFIE_M_sl5_250m_ll: bd_sl5 + BLDFIE_M_sl6_250m_ll: bd_sl6 + BLDFIE_M_sl7_250m_ll: bd_sl7 + CLYPPT_M_sl1_250m_ll: clyppt_sl1 + CLYPPT_M_sl2_250m_ll: clyppt_sl2 + CLYPPT_M_sl3_250m_ll: clyppt_sl3 + CLYPPT_M_sl4_250m_ll: clyppt_sl4 + CLYPPT_M_sl5_250m_ll: clyppt_sl5 + CLYPPT_M_sl6_250m_ll: clyppt_sl6 + CLYPPT_M_sl7_250m_ll: clyppt_sl7 + ORCDRC_M_sl1_250m_ll: oc_sl1 + ORCDRC_M_sl2_250m_ll: oc_sl2 + ORCDRC_M_sl3_250m_ll: oc_sl3 + ORCDRC_M_sl4_250m_ll: oc_sl4 + ORCDRC_M_sl5_250m_ll: oc_sl5 + ORCDRC_M_sl6_250m_ll: oc_sl6 + ORCDRC_M_sl7_250m_ll: oc_sl7 + PHIHOX_M_sl1_250m_ll: ph_sl1 + PHIHOX_M_sl2_250m_ll: ph_sl2 + PHIHOX_M_sl3_250m_ll: ph_sl3 + PHIHOX_M_sl4_250m_ll: ph_sl4 + PHIHOX_M_sl5_250m_ll: ph_sl5 + PHIHOX_M_sl6_250m_ll: ph_sl6 + PHIHOX_M_sl7_250m_ll: ph_sl7 + SLTPPT_M_sl1_250m_ll: sltppt_sl1 + SLTPPT_M_sl2_250m_ll: sltppt_sl2 + SLTPPT_M_sl3_250m_ll: sltppt_sl3 + SLTPPT_M_sl4_250m_ll: sltppt_sl4 + SLTPPT_M_sl5_250m_ll: sltppt_sl5 + SLTPPT_M_sl6_250m_ll: sltppt_sl6 + SLTPPT_M_sl7_250m_ll: sltppt_sl7 + SNDPPT_M_sl1_250m_ll: sndppt_sl1 + SNDPPT_M_sl2_250m_ll: sndppt_sl2 + SNDPPT_M_sl3_250m_ll: sndppt_sl3 + SNDPPT_M_sl4_250m_ll: sndppt_sl4 + SNDPPT_M_sl5_250m_ll: sndppt_sl5 + SNDPPT_M_sl6_250m_ll: sndppt_sl6 + SNDPPT_M_sl7_250m_ll: sndppt_sl7 + SoilThickness_250m_ll: soilthickness + TAXOUSDA_250m_ll: tax_usda + unit_mult: + bd_sl1: 0.001 + bd_sl2: 0.001 + bd_sl3: 0.001 + bd_sl4: 0.001 + bd_sl5: 0.001 + bd_sl6: 0.001 + bd_sl7: 0.001 + oc_sl1: 0.1 + oc_sl2: 0.1 + oc_sl3: 0.1 + oc_sl4: 0.1 + oc_sl5: 0.1 + oc_sl6: 0.1 + oc_sl7: 0.1 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + +soilgrids_2020: + alias: soilgrids_v2.0 +soilgrids_v2.0: + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 2400 + y: 2400 + meta: + category: soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, + P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. + Land Use Policy 29 (2), 329–338. \n" + paper_doi: https://doi.org/10.5194/soil-2020-65 + paper_ref: de Sousa et al. (2020) + source_license: CC BY 4.0 + source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids + source_version: 2020 + path: soil/soilgrids_v2.0/*/*_mean.vrt + rename: + bdod_0-5cm_mean: bd_sl1 + bdod_5-15cm_mean: bd_sl2 + bdod_15-30cm_mean: bd_sl3 + bdod_30-60cm_mean: bd_sl4 + bdod_60-100cm_mean: bd_sl5 + bdod_100-200cm_mean: bd_sl6 + clay_0-5cm_mean: clyppt_sl1 + clay_5-15cm_mean: clyppt_sl2 + clay_15-30cm_mean: clyppt_sl3 + clay_30-60cm_mean: clyppt_sl4 + clay_60-100cm_mean: clyppt_sl5 + clay_100-200cm_mean: clyppt_sl6 + soc_0-5cm_mean: oc_sl1 + soc_5-15cm_mean: oc_sl2 + soc_15-30cm_mean: oc_sl3 + soc_30-60cm_mean: oc_sl4 + soc_60-100cm_mean: oc_sl5 + soc_100-200cm_mean: oc_sl6 + phh2o_0-5cm_mean: ph_sl1 + phh2o_5-15cm_mean: ph_sl2 + phh2o_15-30cm_mean: ph_sl3 + phh2o_30-60cm_mean: ph_sl4 + phh2o_60-100cm_mean: ph_sl5 + phh2o_100-200cm_mean: ph_sl6 + silt_0-5cm_mean: sltppt_sl1 + silt_5-15cm_mean: sltppt_sl2 + silt_15-30cm_mean: sltppt_sl3 + silt_30-60cm_mean: sltppt_sl4 + silt_60-100cm_mean: sltppt_sl5 + silt_100-200cm_mean: sltppt_sl6 + sand_0-5cm_mean: sndppt_sl1 + sand_5-15cm_mean: sndppt_sl2 + sand_15-30cm_mean: sndppt_sl3 + sand_30-60cm_mean: sndppt_sl4 + sand_60-100cm_mean: sndppt_sl5 + sand_100-200cm_mean: sndppt_sl6 + SoilThickness_250_mean: soilthickness + TAXOUSDA_250_mean: tax_usda + unit_mult: + bd_sl1: 0.01 + bd_sl2: 0.01 + bd_sl3: 0.01 + bd_sl4: 0.01 + bd_sl5: 0.01 + bd_sl6: 0.01 + bd_sl7: 0.01 + oc_sl1: 0.01 + oc_sl2: 0.01 + oc_sl3: 0.01 + oc_sl4: 0.01 + oc_sl5: 0.01 + oc_sl6: 0.01 + oc_sl7: 0.01 + ph_sl1: 0.1 + ph_sl2: 0.1 + ph_sl3: 0.1 + ph_sl4: 0.1 + ph_sl5: 0.1 + ph_sl6: 0.1 + ph_sl7: 0.1 + clyppt_sl1: 0.1 + clyppt_sl2: 0.1 + clyppt_sl3: 0.1 + clyppt_sl4: 0.1 + clyppt_sl5: 0.1 + clyppt_sl6: 0.1 + clyppt_sl7: 0.1 + sltppt_sl1: 0.1 + sltppt_sl2: 0.1 + sltppt_sl3: 0.1 + sltppt_sl4: 0.1 + sltppt_sl5: 0.1 + sltppt_sl6: 0.1 + sltppt_sl7: 0.1 + sndppt_sl1: 0.1 + sndppt_sl2: 0.1 + sndppt_sl3: 0.1 + sndppt_sl4: 0.1 + sndppt_sl5: 0.1 + sndppt_sl6: 0.1 + sndppt_sl7: 0.1 + +vito: + alias: vito_2015_v2.0.2 +vito_2015_v2.0.2: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3939038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v2.0.2 + path: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif + +vito_2016_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518026 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2017_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518036 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2018_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3518038 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif + +vito_2019_v3.0.1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 3600 + y: 3600 + meta: + category: landuse + paper_doi: 10.5281/zenodo.3939050 + paper_ref: Buchhorn et al (2020) + source_url: https://land.copernicus.eu/global/products/lc + source_version: v3.0.1 + path: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif + +wb_countries: + alias: wb_countries_v20200319 +wb_countries_v20200319: + crs: 4326 + data_type: GeoDataFrame + driver: vector + meta: + category: socio-economic + source_author: World Bank + source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries + source_license: CC-BY 4.0 + timestamp: February 2020 + path: geography/wb/WB_countries_Admin0.fgb + rename: + ISO_A3: country_iso + ISO_N3: country_code + POP_EST: population + GDP_MD_EST: gdp_pc + GDP_kD_PPP: gdp + unit_mult: + gdp_pc: 1000 + +worldclim: + alias: worldclim_v2.0 +worldclim_v2.0: + crs: 4326 + data_type: RasterDataset + driver: netcdf + kwargs: + chunks: + lat: 3600 + lon: 3600 + meta: + category: meteo + paper_doi: 10.1002/joc.5086 + paper_ref: Fick and Hijmans (2017) + source_url: https://www.worldclim.org/data/worldclim21.html + source_version: 2 + nodata: -999.0 + path: meteo/worldclim_v2.0/wc2.0_30s_prec.nc + rename: + prec: precip + +worldpop_2020_constrained: + data_type: RasterDataset + driver: raster + kwargs: + chunks: auto + meta: + category: socio-economic + paper_doi: 10.1371/journal.pone.0107042 + paper_ref: Stevens et al. (2015) + source_license: CC BY 4.0 + source_url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 + nodata: -99999 + path: socio_economic/worldpop/ppp_2020_constrained.vrt + rename: + ppp_2020_constrained: population + +worldpop_2020_UNadj_constrained: + alias: worldpop_2020_constrained + path: socio_economic/worldpop/ppp_2020_UNadj_constrained.vrt + rename: + ppp_2020_UNadj_constrained: population + +wsf_bld_2015: + alias: wsf_bld_2015_v1 +wsf_bld_2015_v1: + crs: 4326 + data_type: RasterDataset + driver: raster + kwargs: + chunks: + x: 1000 + y: 1000 + meta: + category: socio-economic + paper_doi: 10.1038/s41597-020-00580-5 + paper_ref: Marconcini at al (2020) + source_license: CC0 1.0 + source_url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc + path: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt diff --git a/data/catalogs/deltares_data.yml b/data/catalogs/deltares_data/v0.6.0/data_catalog.yml similarity index 98% rename from data/catalogs/deltares_data.yml rename to data/catalogs/deltares_data/v0.6.0/data_catalog.yml index bfaac07ad..48b627a86 100644 --- a/data/catalogs/deltares_data.yml +++ b/data/catalogs/deltares_data/v0.6.0/data_catalog.yml @@ -1,9 +1,8 @@ --- meta: root: p:/wflow_global/hydromt - version: 2024.1.30 - hydromt_version: '>=0.9, <1.0' - + version: v0.6.0 + name: deltares_data basin_atlas_level12_v10: crs: 4326 @@ -141,7 +140,7 @@ copdem30_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" nodata: -9999 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem.vrt rename: @@ -160,7 +159,7 @@ copdem30_mask_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" nodata: -1 # copdem has no actual nodata, this is to suppress a missing nodata warning path: topography/copdem/copdem_mask.vrt rename: @@ -179,7 +178,7 @@ copdem30_masked_v2021.1: category: topography source_license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 source_url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - source_version: '2021_1' + source_version: "2021_1" path: topography/copdem/copdem_masked.vrt rename: copdem_masked: elevtn @@ -1085,7 +1084,6 @@ glw_sheeps_v3: source_version: GLW 3, last downloaded 2020-06-11 path: socio_economic/glw/5_Sh_2010_Da.tif - grdc: crs: 4326 data_type: GeoDataFrame @@ -1503,14 +1501,14 @@ pcr_globwb: source_version: 2017.11b1 processing_script: hydro/pcr_globwb/prep_glob.py variants: - - version: 1990 - path: hydro/pcr_globwb/glob_1990.zarr - - version: 1995 - path: hydro/pcr_globwb/glob_1995.zarr - - version: 2000 - path: hydro/pcr_globwb/glob_2000.zarr - - version: 2005 - path: hydro/pcr_globwb/glob_2005.zarr + - version: 1990 + path: hydro/pcr_globwb/glob_1990.zarr + - version: 1995 + path: hydro/pcr_globwb/glob_1995.zarr + - version: 2000 + path: hydro/pcr_globwb/glob_2000.zarr + - version: 2005 + path: hydro/pcr_globwb/glob_2005.zarr nodata: -9999 rename: domesticNettoDemand: dom_net @@ -1632,7 +1630,8 @@ soilgrids_v1.0: y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau\n network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" @@ -1721,7 +1720,8 @@ soilgrids_v2.0: y: 2400 meta: category: soil - notes: "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil + notes: + "soilthickness is based on 1) soilgrids (global) and 2) dataset for Eurasia (ESDAC, 2004; Panagos et al., 2012): ESDAC, 2004. The european soil database distribution version 2.0, european commission and the European soil bureau network. esdac.jrc.ec.europa.eu, accessed: 2017-11-17. Panagos, P., Van Liedekerke, M., Jones, A., Montanarella, L., 2012. European soil data centre: Response to european policy support and public data requirements. Land Use Policy 29 (2), 329–338. \n" diff --git a/data/catalogs/gcs_cmip6_data/registry.txt b/data/catalogs/gcs_cmip6_data/registry.txt new file mode 100644 index 000000000..7351cb9f2 --- /dev/null +++ b/data/catalogs/gcs_cmip6_data/registry.txt @@ -0,0 +1 @@ +v0.1.0/data_catalog.yml c8aab2c2068809a52e5e40a38e68d1a27d25346cf51724010a24f1bfad66a1c1 diff --git a/data/catalogs/gcs_cmip6_data.yml b/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml similarity index 84% rename from data/catalogs/gcs_cmip6_data.yml rename to data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml index b933c6dc0..2904536b4 100644 --- a/data/catalogs/gcs_cmip6_data.yml +++ b/data/catalogs/gcs_cmip6_data/v0.1.0/data_catalog.yml @@ -1,7 +1,7 @@ --- meta: - version: 2024.1.30 - hydromt_version: '>=0.8.1, <1.0' + version: v0.1.0 + name: gcs_cmip6_data cmip6_{model}_historical_{member}_{timestep}: crs: 4326 @@ -21,9 +21,32 @@ cmip6_{model}_historical_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [IPSL/IPSL-CM6A-LR, SNU/SAM0-UNICON, NCAR/CESM2, NCAR/CESM2-WACCM, INM/INM-CM4-8, INM/INM-CM5-0, NOAA-GFDL/GFDL-ESM4, NCC/NorESM2-LM, NIMS-KMA/KACE-1-0-G, - CAS/FGOALS-f3-L, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, CSIRO/ACCESS-ESM1-5, NCAR/CESM2-WACCM-FV2, NCAR/CESM2-FV2, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, - NCC/NorCPM1, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-CM2-HR4, CMCC/CMCC-ESM2, IPSL/IPSL-CM6A-LR-INCA, E3SM-Project/E3SM-1-0] + model: + [ + IPSL/IPSL-CM6A-LR, + SNU/SAM0-UNICON, + NCAR/CESM2, + NCAR/CESM2-WACCM, + INM/INM-CM4-8, + INM/INM-CM5-0, + NOAA-GFDL/GFDL-ESM4, + NCC/NorESM2-LM, + NIMS-KMA/KACE-1-0-G, + CAS/FGOALS-f3-L, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + CSIRO/ACCESS-ESM1-5, + NCAR/CESM2-WACCM-FV2, + NCAR/CESM2-FV2, + CMCC/CMCC-CM2-SR5, + AS-RCEC/TaiESM1, + NCC/NorCPM1, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-CM2-HR4, + CMCC/CMCC-ESM2, + IPSL/IPSL-CM6A-LR-INCA, + E3SM-Project/E3SM-1-0, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR', 'BCC/BCC-ESM1', 'CCCma/CanESM5', 'MRI/MRI-ESM2-0', # 'HAMMOZ-Consortium/MPI-ESM-1-2-HAM', 'MPI-M/MPI-ESM1-2-LR', 'MPI-M/MPI-ESM1-2-HR', 'NUIST/NESM3', # 'CAS/FGOALS-g3', 'MIROC/MIROC6', 'KIOST/KIOST-ESM', 'CCCR-IITM/IITM-ESM', 'AWI/AWI-ESM-1-1-LR', @@ -97,8 +120,18 @@ cmip6_{model}_ssp126_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, IPSL/IPSL-CM6A-LR, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, - CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + INM/INM-CM4-8, + INM/INM-CM5-0, + IPSL/IPSL-CM6A-LR, + NIMS-KMA/KACE-1-0-G, + NCC/NorESM2-MM, + CMCC/CMCC-CM2-SR5, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-ESM2, + ] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','DKRZ/MPI-ESM1-2-HR','MPI-M/MPI-ESM1-2-LR', # 'NUIST/NESM3', 'MIROC/MIROC6','MRI/MRI-ESM2-0','KIOST/KIOST-ESM','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','CCCR-IITM/IITM-ESM','EC-Earth-Consortium/EC-Earth3-Veg-LR', @@ -135,8 +168,21 @@ cmip6_{model}_ssp245_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, NCC/NorESM2-LM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, - NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, CMCC/CMCC-ESM2, AS-RCEC/TaiESM1] + model: + [ + NOAA-GFDL/GFDL-ESM4, + IPSL/IPSL-CM6A-LR, + INM/INM-CM4-8, + INM/INM-CM5-0, + NCAR/CESM2-WACCM, + NCC/NorESM2-LM, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + NIMS-KMA/KACE-1-0-G, + CMCC/CMCC-CM2-SR5, + CMCC/CMCC-ESM2, + AS-RCEC/TaiESM1, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', # 'AWI/AWI-CM-1-1-MR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','DKRZ/MPI-ESM1-2-HR','NUIST/NESM3', @@ -173,8 +219,21 @@ cmip6_{model}_ssp370_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, IPSL/IPSL-CM6A-LR, INM/INM-CM4-8, INM/INM-CM5-0, NCAR/CESM2-WACCM, CSIRO-ARCCSS/ACCESS-CM2, NCC/NorESM2-MM, NCC/NorESM2-LM, - NIMS-KMA/KACE-1-0-G, CMCC/CMCC-CM2-SR5, IPSL/IPSL-CM5A2-INCA, CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + IPSL/IPSL-CM6A-LR, + INM/INM-CM4-8, + INM/INM-CM5-0, + NCAR/CESM2-WACCM, + CSIRO-ARCCSS/ACCESS-CM2, + NCC/NorESM2-MM, + NCC/NorESM2-LM, + NIMS-KMA/KACE-1-0-G, + CMCC/CMCC-CM2-SR5, + IPSL/IPSL-CM5A2-INCA, + CMCC/CMCC-ESM2, + ] # model: ['BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','BCC/BCC-ESM1','DKRZ/MPI-ESM1-2-HR', # EC-Earth-Consortium/EC-Earth3-Veg','EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-AerChem', # 'EC-Earth-Consortium/EC-Earth3-Veg-LR','MRI/MRI-ESM2-0','MPI-M/MPI-ESM1-2-LR','HAMMOZ-Consortium/MPI-ESM-1-2-HAM', @@ -279,8 +338,18 @@ cmip6_{model}_ssp585_{member}_{timestep}: source_url: https://console.cloud.google.com/marketplace/details/noaa-public/cmip6?_ga=2.136097265.-1784288694.1541379221&pli=1 source_version: 1.3.1 placeholders: - model: [NOAA-GFDL/GFDL-ESM4, INM/INM-CM4-8, INM/INM-CM5-0, NIMS-KMA/KACE-1-0-G, NCC/NorESM2-MM, NCC/NorESM2-LM, CMCC/CMCC-CM2-SR5, AS-RCEC/TaiESM1, - CMCC/CMCC-ESM2] + model: + [ + NOAA-GFDL/GFDL-ESM4, + INM/INM-CM4-8, + INM/INM-CM5-0, + NIMS-KMA/KACE-1-0-G, + NCC/NorESM2-MM, + NCC/NorESM2-LM, + CMCC/CMCC-CM2-SR5, + AS-RCEC/TaiESM1, + CMCC/CMCC-ESM2, + ] # model: ['NOAA-GFDL/GFDL-CM4','BCC/BCC-CSM2-MR','CCCma/CanESM5','AWI/AWI-CM-1-1-MR','MPI-M/MPI-ESM1-2-LR', # 'DKRZ/MPI-ESM1-2-HR','MIROC/MIROC6','MRI/MRI-ESM2-0','EC-Earth-Consortium/EC-Earth3-Veg', # 'EC-Earth-Consortium/EC-Earth3','EC-Earth-Consortium/EC-Earth3-Veg-LR','EC-Earth-Consortium/EC-Earth3-CC', diff --git a/data/catalogs/update_versions.py b/data/catalogs/update_versions.py new file mode 100644 index 000000000..31deea94a --- /dev/null +++ b/data/catalogs/update_versions.py @@ -0,0 +1,11 @@ +"""Script to update the registry.txt file for each predefined catalog.""" + +from pathlib import Path + +from hydromt.predefined_catalog import create_registry_file + +if __name__ == "__main__": + root = Path(__file__).parent + cat_roots = [d for d in root.iterdir() if d.is_dir()] + for cat_root in cat_roots: + create_registry_file(cat_root) diff --git a/data/predefined_catalogs.yml b/data/predefined_catalogs.yml index f7cae9857..ccb24fa3a 100644 --- a/data/predefined_catalogs.yml +++ b/data/predefined_catalogs.yml @@ -1,4 +1,6 @@ --- +# NOTE this file has been deprecated and will be removed in future versions +# # list of predefined data catalogs # # : @@ -16,7 +18,7 @@ deltares_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/deltares_data.yml versions: - v2024.1.30: main + v2024.1.30: 50863d777404a4a91b5f66bf285b3edaa56713b1 v2023.12.21: 392206b21b26e62e00ae76db7ffc61a3b95e2175 v2023.12.19: bf25e79dcbda67612a75588cd782d57abe3881de v2023.2: 0bf8e2a1e716095dc6df54a5e9114ce88da0701b @@ -26,13 +28,13 @@ deltares_data: gcs_cmip6_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/gcs_cmip6_data.yml versions: - v2024.1.30: main + v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 v2023.2: 0144d5dadfb76a9f2bdb22226b484e83c9751c34 notes: This data uses CMIP6 data stored in Google Cloud Service. aws_data: urlpath: https://raw.githubusercontent.com/Deltares/hydromt/{version}/data/catalogs/aws_data.yml versions: - v2024.1.30: main + v2024.1.30: 503f9a400e8df89ecca240091d8eba9de1fedf75 v2023.2: 897e5c5272875f1c066f393798b7ae59721c9e9d notes: This data are stored in public Amazon Web Services. artifact_data: diff --git a/docs/api.rst b/docs/api.rst index f08d0e99b..ecb7382d8 100644 --- a/docs/api.rst +++ b/docs/api.rst @@ -73,10 +73,8 @@ Add data sources data_catalog.DataCatalog.add_source data_catalog.DataCatalog.update data_catalog.DataCatalog.from_predefined_catalogs - data_catalog.DataCatalog.from_archive data_catalog.DataCatalog.from_yml data_catalog.DataCatalog.from_dict - data_catalog.DataCatalog.set_predefined_catalogs .. _api_data_catalog_get: @@ -92,6 +90,19 @@ Get data data_catalog.DataCatalog.get_dataframe data_catalog.DataCatalog.get_dataset + +Predefined data catalog +======================= + +.. autosummary:: + :toctree: _generated + + predefined_catalog.PredefinedCatalog + predefined_catalog.PredefinedCatalog.get_catalog_file + predefined_catalog.create_registry_file + + + DataAdapter =========== diff --git a/docs/changelog.rst b/docs/changelog.rst index 1069a5304..416449094 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -9,11 +9,18 @@ The format is based on `Keep a Changelog`_, and this project adheres to Unreleased ========== +New +--- +- New `PredefinedCatalog` class to handle predefined catalog version based on pooch registry files. (#849) + + Changed ------- - Development environment is now set up via pixi instead of mamba / conda. See the documentation for more information on how to install. - Use the native data CRS when determining zoom levels over the data catalog crs. (#851) - Improved `flw.d8_from_dem` method with different options to use river vector data to aid the flow direction derivation. (#305) +- DataCatalog.predefined_catalogs retrieves predefined_catalogs specified in predefined_catalogs.py. There is no need for setting the predefined_catalogs anymore. (#844) + Fixed ----- @@ -25,6 +32,10 @@ Fixed - Fixed incorrect renaming of single variable raster datasets (#883) - Provide better error message for 0D geometry arrays in GeoDataset (#885) +Deprecated +---------- +- The `DataCatalog.from_archive` method is deprecated. Use `DataCatalog.from_yml` with the root pointing to the archive instead. (#849) + v0.9.4 (2024-02-26) =================== This release fixes a performance regression when reading geometry masks, relaxed warnings for empty raster datasets and updated the documention of the new hydromt commands. diff --git a/docs/conf.py b/docs/conf.py index 7a5d551b4..e787c1db1 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -132,7 +132,6 @@ def clean_str(s): "other", ] data_cat = hydromt.DataCatalog() -data_cat.set_predefined_catalogs(r"../data/predefined_catalogs.yml") predefined_catalogs = data_cat.predefined_catalogs for name in predefined_catalogs: try: @@ -140,8 +139,7 @@ def clean_str(s): except OSError as e: print(e) continue - note = predefined_catalogs[name].get("notes", "") - write_nested_dropdown(name, data_cat, note=note, categories=categories) + write_nested_dropdown(name, data_cat, categories=categories) data_cat._sources = {} # reset with open("_generated/predefined_catalogs.rst", "w") as f: f.writelines( diff --git a/examples/delineate_basin.ipynb b/examples/delineate_basin.ipynb index e674c76dc..31abdd8a8 100644 --- a/examples/delineate_basin.ipynb +++ b/examples/delineate_basin.ipynb @@ -92,7 +92,7 @@ "outputs": [], "source": [ "# instantiate instance of Data Catalog\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/export_data.ipynb b/examples/export_data.ipynb index ebeb19887..4f4b40eb6 100644 --- a/examples/export_data.ipynb +++ b/examples/export_data.ipynb @@ -56,7 +56,7 @@ "# Download and read artifacts for the Piave basin to `~/.hydromt_data/`.\n", "data_catalog = hydromt.DataCatalog(\n", " logger=logger,\n", - " data_libs=[\"artifact_data\"],\n", + " data_libs=[\"artifact_data=v0.0.8\"],\n", ")" ] }, diff --git a/examples/prep_data_catalog.ipynb b/examples/prep_data_catalog.ipynb index c74066a24..84fb96443 100644 --- a/examples/prep_data_catalog.ipynb +++ b/examples/prep_data_catalog.ipynb @@ -85,7 +85,7 @@ "outputs": [], "source": [ "# the artifact data is stored in the following location\n", - "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.6\")\n", + "root = os.path.join(data_catalog._cache_dir, \"artifact_data\", \"v0.0.6\", \"data.tar\")\n", "# let's print some of the file that are there\n", "for item in os.listdir(root)[-10:]:\n", " print(item)" diff --git a/examples/reading_point_data.ipynb b/examples/reading_point_data.ipynb index 12a6c149d..5badce96b 100644 --- a/examples/reading_point_data.ipynb +++ b/examples/reading_point_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/reading_raster_data.ipynb b/examples/reading_raster_data.ipynb index 23a975151..6eb3fb94a 100644 --- a/examples/reading_raster_data.ipynb +++ b/examples/reading_raster_data.ipynb @@ -40,7 +40,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/reading_vector_data.ipynb b/examples/reading_vector_data.ipynb index e9340ca7c..dc7916411 100644 --- a/examples/reading_vector_data.ipynb +++ b/examples/reading_vector_data.ipynb @@ -42,7 +42,7 @@ "outputs": [], "source": [ "# Download artifacts for the Piave basin to `~/.hydromt_data/`.\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_flow_directions.ipynb b/examples/working_with_flow_directions.ipynb index ede0c1594..6a827c0d8 100644 --- a/examples/working_with_flow_directions.ipynb +++ b/examples/working_with_flow_directions.ipynb @@ -51,7 +51,7 @@ "# initialize a logger\n", "logger = setuplog(\"flow direction data\", log_level=10)\n", "# initialize a data catalog based on the pre-defined artifact_data catalog\n", - "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data\"], logger=logger)\n", + "data_catalog = hydromt.DataCatalog(data_libs=[\"artifact_data=v0.0.8\"], logger=logger)\n", "\n", "# we load the flow direction (flwdir); elevation (elevtn) and upstream area (uparea) layers\n", "ds = data_catalog.get_rasterdataset(\n", diff --git a/examples/working_with_geodatasets.ipynb b/examples/working_with_geodatasets.ipynb index ecb939af6..ca7cc56dc 100644 --- a/examples/working_with_geodatasets.ipynb +++ b/examples/working_with_geodatasets.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "dc = DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_meshmodel.ipynb b/examples/working_with_meshmodel.ipynb index 7772be559..d4e2f34cb 100644 --- a/examples/working_with_meshmodel.ipynb +++ b/examples/working_with_meshmodel.ipynb @@ -175,7 +175,7 @@ "mod = hydromt.MeshModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] diff --git a/examples/working_with_models.ipynb b/examples/working_with_models.ipynb index 4a5101a9f..70290be58 100644 --- a/examples/working_with_models.ipynb +++ b/examples/working_with_models.ipynb @@ -192,7 +192,7 @@ "mod = hydromt.GridModel(\n", " root=root,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")" ] @@ -462,7 +462,7 @@ "mod3 = hydromt.GridModel(\n", " root=root3,\n", " mode=\"w\",\n", - " data_libs=[\"artifact_data\", \"data/vito_reclass.yml\"],\n", + " data_libs=[\"artifact_data=v0.0.8\", \"data/vito_reclass.yml\"],\n", " logger=logger,\n", ")\n", "\n", diff --git a/examples/working_with_raster.ipynb b/examples/working_with_raster.ipynb index 6d7cc69be..2f93200e8 100644 --- a/examples/working_with_raster.ipynb +++ b/examples/working_with_raster.ipynb @@ -18,7 +18,7 @@ "from hydromt.log import setuplog\n", "\n", "logger = setuplog(\"raster data\", log_level=10)\n", - "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data\"])" + "data_catalog = hydromt.DataCatalog(logger=logger, data_libs=[\"artifact_data=v0.0.8\"])" ] }, { diff --git a/examples/working_with_tiled_raster_data.ipynb b/examples/working_with_tiled_raster_data.ipynb index d442fc7f5..f5e3a7fce 100644 --- a/examples/working_with_tiled_raster_data.ipynb +++ b/examples/working_with_tiled_raster_data.ipynb @@ -30,7 +30,7 @@ "logger = setuplog(\"tiling\", log_level=20)\n", "\n", "# get some elevation data from the data catalog\n", - "data_lib = \"artifact_data\"\n", + "data_lib = \"artifact_data=v0.0.8\"\n", "data_cat = DataCatalog(data_lib, logger=logger)\n", "source = \"merit_hydro\"\n", "da0 = data_cat.get_rasterdataset(source, variables=[\"elevtn\"])\n", diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 9402c31d3..22575a478 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -2,16 +2,16 @@ # -*- coding: utf-8 -*- """DataCatalog module for HydroMT.""" + from __future__ import annotations import copy import itertools import logging import os -import shutil import warnings from datetime import datetime -from os.path import abspath, basename, isdir, isfile, join +from os.path import abspath, basename, isfile, join from pathlib import Path from typing import ( Dict, @@ -26,6 +26,7 @@ import geopandas as gpd import numpy as np import pandas as pd +import pooch import requests import xarray as xr import yaml @@ -35,10 +36,14 @@ from pystac import CatalogType, MediaType from hydromt.nodata import NoDataException, NoDataStrategy, _exec_nodata_strat +from hydromt.predefined_catalog import ( + PREDEFINED_CATALOGS, + PredefinedCatalog, + _copy_file, +) from hydromt.typing import Bbox, ErrorHandleMethod, SourceSpecDict, TimeRange from hydromt.utils import partition_dictionaries -from . import __version__ from .data_adapter import ( DataAdapter, DataFrameAdapter, @@ -47,7 +52,7 @@ GeoDatasetAdapter, RasterDatasetAdapter, ) -from .data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator +from .data_adapter.caching import HYDROMT_DATADIR, _uri_validator logger = logging.getLogger(__name__) @@ -59,11 +64,9 @@ class DataCatalog(object): - """Base class for the data catalog object.""" - # root URL with data_catalog file - _url = r"https://raw.githubusercontent.com/Deltares/hydromt/main/data/predefined_catalogs.yml" + _format_version = "v0" # format version of the data catalog _cache_dir = HYDROMT_DATADIR def __init__( @@ -107,7 +110,7 @@ def __init__( elif not isinstance(data_libs, list): # make sure data_libs is a list data_libs = np.atleast_1d(data_libs).tolist() self._sources = {} # dictionary of DataAdapter - self._catalogs = {} # dictionary of predefined Catalogs + self._catalogs: Dict[str, PredefinedCatalog] = {} self._fallback_lib = fallback_lib self.logger = logger @@ -254,7 +257,7 @@ def from_stac_catalog( def predefined_catalogs(self) -> Dict: """Return all predefined catalogs.""" if not self._catalogs: - self.set_predefined_catalogs() + self._set_predefined_catalogs() return self._catalogs def get_source_bbox( @@ -607,60 +610,15 @@ def update_sources(self, **kwargs) -> None: """Add data sources to library or update them.""" self.update(**kwargs) - def set_predefined_catalogs( - self, urlpath: Optional[Union[Path, str]] = None - ) -> Dict: - """Initialise the predefined catalogs.""" - # get predefined_catalogs - urlpath = self._url if urlpath is None else urlpath - cache_path = join(self._cache_dir, basename(urlpath)) - try: - # download file locally; overwrite existing file - _copyfile(urlpath, cache_path) - except Exception: # if offline - self.logger.warning( - "Downloading the predefined catalogs failed;" - "check your internet connection" - ) - pass - if isfile(cache_path): - self._catalogs = _yml_from_uri_or_path(cache_path) - if self._catalogs is None: - raise ConnectionError( - "Predefined catalogs not found; check your internet connection." + def _set_predefined_catalogs(self) -> Dict: + """Set initialized predefined catalogs to _catalogs attribute.""" + for k, cat in PREDEFINED_CATALOGS.items(): + self._catalogs[k] = cat( + format_version=self._format_version, cache_dir=self._cache_dir ) return self._catalogs - def from_artifacts( - self, name: str = "artifact_data", version: str = "latest" - ) -> DataCatalog: - """Parse artifacts. - - Deprecated method. Use - :py:func:`hydromt.data_catalog.DataCatalog.from_predefined_catalogs` instead. - - Parameters - ---------- - name : str, optional - Catalog name. If None (default) sample data is downloaded. - version : str, optional - Release version. By default it takes the latest known release. - - Returns - ------- - DataCatalog - DataCatalog object with parsed artifact data. - """ - warnings.warn( - '"from_artifacts" is deprecated. Use "from_predefined_catalogs instead".', - DeprecationWarning, - stacklevel=2, - ) - return self.from_predefined_catalogs(name, version) - - def from_predefined_catalogs( - self, name: str, version: str = "latest" - ) -> DataCatalog: + def from_predefined_catalogs(self, name: str, version: str = "latest") -> None: """Add data sources from a predefined data catalog. Parameters @@ -670,10 +628,6 @@ def from_predefined_catalogs( version : str, optional Catlog release version. By default it takes the latest known release. - Returns - ------- - DataCatalog - DataCatalog object with parsed predefined catalog added. """ if "=" in name: name, version = name.split("=")[0], name.split("=")[-1] @@ -681,105 +635,58 @@ def from_predefined_catalogs( raise ValueError( f'Catalog with name "{name}" not found in predefined catalogs' ) - urlpath = self.predefined_catalogs[name].get("urlpath") - versions_dict = self.predefined_catalogs[name].get("versions") - if version == "latest" or not isinstance(version, str): - # if a specific version is requested, we don't have to try others - versions = list(versions_dict.keys()) - if len(versions) > 1: - version = versions[np.argmax([Version(v) for v in versions])] - else: - version = versions[0] - - if version not in versions_dict: - raise RuntimeError( - f"Unknown version requested {version}. " - f"options are :{versions_dict.keys()}" - ) - possible_catalg_versions = [(Version(k), v) for k, v in versions_dict.items()] - possible_catalg_versions_sorted = reversed(sorted(possible_catalg_versions)) - - for _, identifier in possible_catalg_versions_sorted: - try: - urlpath = urlpath.format(version=identifier) - if urlpath.split(".")[-1] in ["gz", "zip"]: - self.logger.info(f"Reading data catalog archive {name} {version}") - self.from_archive(urlpath, name=name, version=version) - else: - self.logger.info(f"Reading data catalog {name} {version}") - self.from_yml(urlpath, catalog_name=name) - return self - except RuntimeError: - continue - - raise RuntimeError("No compatible compatible catalog version could be found") - - def from_archive( - self, - urlpath: Union[Path, str], - version: Optional[str] = None, - name: Optional[str] = None, - ) -> DataCatalog: - """Read and cache a data archive including a data_catalog.yml file. - - Parameters - ---------- - urlpath : str, Path - Path or url to data archive. - version : str, optional - Version of data archive, by default None. - name : str, optional - Name of data catalog, by default None. - - Returns - ------- - DataCatalog - DataCatalog object with parsed data archive added. - """ - # add depreaction warning - root = self._cache_archive(urlpath, version=version, name=name) - yml_fn = join(root, "data_catalog.yml") - # parse catalog - return self.from_yml(yml_fn, catalog_name=name) + # cache and get path to data_datalog.yml file of the catalog with + catalog_path = self.predefined_catalogs[name].get_catalog_file(version) + # read catalog + self.logger.info(f"Reading data catalog {name} {version}") + self.from_yml(catalog_path, catalog_name=name) def _cache_archive( self, - archive_fn: Union[Path, str], - version: Optional[str] = None, - name: Optional[str] = None, - ) -> DataCatalog: - """Cache a data archive. + archive_uri: str, + name: str, + version: str = "latest", + sha256: Optional[str] = None, + ) -> str: + """Cache a data archive to the cache directory. + + The archive is unpacked and cached to // Parameters ---------- - archive_fn : str, Path - Path or url to data archive. + archive_uri : str + uri to data archive. + name : str + Name of data catalog version : str, optional - Version of data archive, by default None. - name : str, optional - Name of data catalog, by default None. + Version of data archive, by default 'latest'. + sha256 : str, optional + SHA256 hash of the archive, by default None. Returns ------- - DataCatalog - DataCatalog object with parsed data archive added. + str + Path to the datacatalog of the cached data archive + """ - name = basename(archive_fn).split(".")[0] if name is None else name - root = join(self._cache_dir, name) - if version is not None: - root = join(root, version) - archive_dst_fn = join(root, basename(archive_fn)) - # copy archive to cache - if not isdir(root): - self.logger.debug(f"Caching data from {archive_fn}") - os.makedirs(root, exist_ok=True) - _copyfile(archive_fn, archive_dst_fn) - # unpack data and remove archive - if isfile(archive_dst_fn): - self.logger.debug(f"Unpacking data from {archive_fn}") - shutil.unpack_archive(archive_dst_fn, root) - os.remove(archive_dst_fn) - return root + root = Path(self._cache_dir, name, version) + extract_dir = root / Path(archive_uri).stem + # retrieve and unpack archive + kwargs = {} + if Path(archive_uri).suffix == ".zip": + kwargs.update(processor=pooch.Unzip(extract_dir=extract_dir)) + elif Path(archive_uri).suffix == ".gz": + kwargs.update(processor=pooch.Untar(extract_dir=extract_dir)) + if Path(archive_uri).exists(): # check if arhive is a local file + kwargs.update(donwloader=_copy_file) + pooch.retrieve( + archive_uri, + known_hash=sha256, + path=str(root), + fname=Path(archive_uri).name, + **kwargs, + ) + return extract_dir def from_yml( self, @@ -813,6 +720,8 @@ def from_yml( root: category: version: + name: + sha256: # only if the root is an archive : path: data_type: @@ -866,15 +775,6 @@ def from_yml( # read meta data meta = yml.pop("meta", meta) - # check version required hydromt version - requested_version = meta.get("hydromt_version", None) - if requested_version is not None: - allow_dev = meta.get("allow_dev_version", True) - if not self._is_compatible(__version__, requested_version, allow_dev): - raise RuntimeError( - f"Data catalog requires Hydromt Version {requested_version} which " - f"is incompattible with current hydromt verison {__version__}." - ) if catalog_name is None: catalog_name = cast( str, meta.get("name", "".join(basename(urlpath).split(".")[:-1])) @@ -884,12 +784,12 @@ def from_yml( root = meta.get("root", os.path.dirname(urlpath)) if root.split(".")[-1] in ["gz", "zip"]: # if root is an archive, unpack it at the cache dir - root = self._cache_archive(root, name=catalog_name, version=version) - # save catalog to cache - with open(join(root, f"{catalog_name}.yml"), "w") as f: - data_dict = {"meta": {k: v for k, v in meta.items() if k != "root"}} - data_dict.update(yml) - yaml.dump(data_dict, f, default_flow_style=False, sort_keys=False) + root = self._cache_archive( + archive_uri=root, + name=catalog_name, + version=version, + sha256=meta.get("sha256", None), + ) self.from_dict( yml, catalog_name=catalog_name, @@ -1866,8 +1766,7 @@ def _parse_data_source_dict( def _yml_from_uri_or_path(uri_or_path: Union[Path, str]) -> Dict: if _uri_validator(str(uri_or_path)): with requests.get(uri_or_path, stream=True) as r: - if r.status_code != 200: - raise IOError(f"URL {r.content}: {uri_or_path}") + r.raise_for_status() yml = yaml.load(r.text, Loader=yaml.FullLoader) else: with open(uri_or_path, "r") as stream: diff --git a/hydromt/predefined_catalog.py b/hydromt/predefined_catalog.py new file mode 100644 index 000000000..215c93aac --- /dev/null +++ b/hydromt/predefined_catalog.py @@ -0,0 +1,261 @@ +"""Implementation of the predefined data catalogs entry points.""" + +import logging +import shutil +import sys +from pathlib import Path +from typing import Callable, ClassVar, Optional + +import packaging.version +import pooch + +from hydromt.data_adapter.caching import HYDROMT_DATADIR, _copyfile, _uri_validator + +logger = logging.getLogger(__name__) + +# this is the default location of the predefined catalogs +# in the test environment this is set to local data/catalogs directory using a global fixture +GIT_ROOT = r"https://raw.githubusercontent.com/Deltares/hydromt/main/data/catalogs" + +__all__ = [ + "PredefinedCatalog", + "DeltaresDataCatalog", + "ArtifactDataCatalog", + "AWSDataCatalog", + "GCSCMIP6DataCatalog", + "create_registry_file", +] + + +def create_registry_file(root: Path, registry_path: Optional[Path] = None) -> None: + """Create a registry file for all catalog files in the root directory. + + The root directory should contain a /data_catalog.yml file per version. + By default the root directory is the cache directory of the catalog instance. + + Parameters + ---------- + root: Path + root directory to search for data_catalog.yml files + """ + # we don't use pooch.create_registry here as we want to only include vaild data_catalog.yml files + registry = {} + for path in root.glob("**/data_catalog.yml"): + key = path.relative_to(root).as_posix() + if not _valid_key(key): + raise ValueError(f"No valid version found in {key}") + if sys.platform == "win32": + # The line endings need to be replaced when operating from windows in order to maintain equality of hashes + _replace_line_endings(path) + file_hash = pooch.file_hash(path) + registry[key] = file_hash + + if not registry: + raise FileNotFoundError(f"No data_catalog.yml files found in {root}") + + if registry_path is None: + registry_path = Path(root / "registry.txt") + with open(registry_path, "w") as f: + for fname, hash in registry.items(): + f.write(f"{fname} {hash}\n") + + +class PredefinedCatalog(object): + """Predefined data catalog. + + A predefined data catalog is a collection of data_catalog.yml files that are stored in a + specific directory structure. The catalog is defined by a base_url and a name. The predefined + catalog can be used to retrieve data_catalog.yml files for specific versions. + + Directory structure: + - /registry.txt + - //data_catalog.yml + + Cached directory structure: + - //registry.txt + - ///data_catalog.yml + """ + + # required class variables to be defined in subclasses + base_url: ClassVar[str] = GIT_ROOT + name: ClassVar[str] = "predefined_catalog" + + def __init__(self, format_version: str = "v0", cache_dir=HYDROMT_DATADIR) -> None: + # init arguments passed by DataCatalog + self._format_version = format_version + self._cache_dir: Path = Path(cache_dir) + # placeholders set by the class + self._pooch: Optional[pooch.Pooch] = None + self._versions: Optional[list[str]] = None + + @property + def registry(self) -> dict: + """Return the registry.""" + return self.pooch.registry + + @property + def pooch(self) -> pooch.Pooch: + """Return a pooch instance with all data catalog files in registry.""" + if self._pooch is None: + self._create_pooch() + self._load_registry_file() + return self._pooch + + @property + def versions(self) -> list[str]: + """Return the versions of the catalog.""" + if not self._versions: + self._versions = self._get_versions() + return self._versions + + def _create_pooch(self) -> None: + self._pooch = pooch.create( + path=self._cache_dir / self.name, + base_url=self.base_url, + retry_if_failed=3, + ) + + def _get_versions(self) -> list[str]: + """Set valid catalog versions.""" + # parse versions from registry, assume registry key is /data_catalog.yml + # keep only versions that match the format_version + keys = self.registry.keys() + _versions = [ + v.split("/")[0] for v in keys if _valid_key(v, self._format_version) + ] + if len(_versions) == 0: + raise RuntimeError( + f"No compatible catalog version could be found for {self.name}." + ) + self._versions = sorted(_versions, key=packaging.version.parse) + return self._versions + + def _load_registry_file(self, overwrite: bool = False) -> None: + """Create a catalog from a yaml file.""" + if self._pooch is None: + self._create_pooch() + if self.registry and not overwrite: + return + registry_path = Path(self._cache_dir / self.name / "registry.txt") + if registry_path.exists(): + registry_path.unlink() + try: # try to retrieve and cache the registry file + _copyfile(f"{self.base_url}/registry.txt", registry_path) + except (ConnectionError, FileNotFoundError): + logger.warning( + f"Failed to retrieve {self.name} versions file from {self.base_url}." + " Creating registry file from cached catalog files." + ) + create_registry_file(registry_path.parent) + if not registry_path.exists(): + raise FileNotFoundError( + f"No cached file found. Failed to retrieve {self.name} versions file" + ) + self.pooch.load_registry(registry_path) + + def get_catalog_file(self, version: Optional[str] = None) -> Optional[Path]: + """Get the cached catalog file path for a specific version. + + Parameters + ---------- + version: str, optional + The version of the catalog to retrieve. If None, the latest version is retrieved. + + Returns + ------- + Path + The path to the cachd catalog file. + """ + if version is None or version == "latest": # get latest version + version = self.versions[-1] + if version not in self.versions: + raise ValueError(f"Version {version} not found in {self.name} catalog") + # get the catalog file + key = f"{version}/data_catalog.yml" + # fetch the file (download if not cached) + path = self.pooch.fetch(key, downloader=self._downloader) + return Path(path) if path else None + + @property + def _downloader(self) -> Optional[Callable]: + if not _uri_validator(self.base_url): + return _copy_file + return None + + +def _valid_key(v: str, format_version: Optional[str] = None) -> bool: + """Check if the key is a valid version.""" + try: + packaging.version.parse(v.split("/")[0]) + return v.startswith(format_version) if format_version else True + except (packaging.version.InvalidVersion, AttributeError): + return False + + +def _copy_file( + url: str, + output_file: str, + pooch: Optional[pooch.Pooch] = None, + check_only: bool = False, +): + """Copy a local file to the cache directory for testing purposes. + + for more info, see: https://www.fatiando.org/pooch/latest/downloaders.html + """ + url = Path(url) + output_file = Path(output_file) + file_exists = url.is_file() + if check_only: + return file_exists + if not file_exists: + raise FileNotFoundError(f"Local file {url} does not exist.") + output_file.parent.mkdir(parents=True, exist_ok=True) + shutil.copyfile(url, output_file) + return output_file + + +class DeltaresDataCatalog(PredefinedCatalog): + """Deltares data catalog.""" + + base_url = f"{GIT_ROOT}/deltares_data" + name = "deltares_data" + + +class ArtifactDataCatalog(PredefinedCatalog): + """Artifact data catalog.""" + + base_url = f"{GIT_ROOT}/artifact_data" + name = "artifact_data" + + +class AWSDataCatalog(PredefinedCatalog): + """AWS data catalog.""" + + base_url = f"{GIT_ROOT}/aws_data" + name = "aws_data" + + +class GCSCMIP6DataCatalog(PredefinedCatalog): + """GCS CMIP6 data catalog.""" + + base_url = f"{GIT_ROOT}/gcs_cmip6_data" + name = "gcs_cmip6_data" + + +# TODO: replace with a entrypoint plugin structure in v1 +PREDEFINED_CATALOGS = { + "artifact_data": ArtifactDataCatalog, + "deltares_data": DeltaresDataCatalog, + "aws_data": AWSDataCatalog, + "gcs_cmip6_data": GCSCMIP6DataCatalog, +} + + +def _replace_line_endings(file_path: Path): + WINDOWS_LINE_ENDING = b"\r\n" + UNIX_LINE_ENDING = b"\n" + with open(file_path, "rb") as open_file: + content = open_file.read() + content = content.replace(WINDOWS_LINE_ENDING, UNIX_LINE_ENDING) + with open(file_path, "wb") as open_file: + open_file.write(content) diff --git a/pixi.lock b/pixi.lock index d19fb4d9e..32413ddf4 100644 --- a/pixi.lock +++ b/pixi.lock @@ -44,9 +44,9 @@ environments: - 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kind: conda name: zstd - version: 1.5.5 - build: h12be248_0 + version: 1.5.6 + build: h0ea2cb4_0 subdir: win-64 - url: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.5-h12be248_0.conda - sha256: d540dd56c5ec772b60e4ce7d45f67f01c6614942225885911964ea1e70bb99e3 - md5: 792bb5da68bf0a6cac6a6072ecb8dbeb + url: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.6-h0ea2cb4_0.conda + sha256: 768e30dc513568491818fb068ee867c57c514b553915536da09e5d10b4ebf3c3 + md5: 9a17230f95733c04dc40a2b1e5491d74 depends: - libzlib >=1.2.13,<1.3.0a0 - ucrt >=10.0.20348.0 @@ -27654,21 +27659,21 @@ packages: - vc14_runtime >=14.29.30139 license: BSD-3-Clause license_family: BSD - size: 343428 - timestamp: 1693151615801 + size: 349143 + timestamp: 1714723445995 - kind: conda name: zstd - version: 1.5.5 - build: hfc55251_0 + version: 1.5.6 + build: ha6fb4c9_0 subdir: linux-64 - url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.5-hfc55251_0.conda - sha256: 607cbeb1a533be98ba96cf5cdf0ddbb101c78019f1fda063261871dad6248609 - md5: 04b88013080254850d6c01ed54810589 + url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.6-ha6fb4c9_0.conda + sha256: c558b9cc01d9c1444031bd1ce4b9cff86f9085765f17627a6cd85fc623c8a02b + md5: 4d056880988120e29d75bfff282e0f45 depends: - libgcc-ng >=12 - libstdcxx-ng >=12 - libzlib >=1.2.13,<1.3.0a0 license: BSD-3-Clause license_family: BSD - size: 545199 - timestamp: 1693151163452 + size: 554846 + timestamp: 1714722996770 diff --git a/pixi.toml b/pixi.toml index 1b8292e62..04613d5e3 100644 --- a/pixi.toml +++ b/pixi.toml @@ -147,6 +147,7 @@ numpy = ">=1.23" packaging = "*" pandas = "*" pip = "*" +pooch = "*" pydantic = "~=2.4" pyflwdir = ">=0.5.4" pyogrio = ">=0.6" diff --git a/pyproject.toml b/pyproject.toml index ed03f8a87..9be654dda 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,6 +23,7 @@ dependencies = [ "numpy>=1.23", # pin necessary to ensure compatability with C headers "packaging", # compare versions of hydromt "pandas", # Dataframes + "pooch", # data fetching "pydantic~=2.4", # Validation "pyflwdir>=0.5.4", # Hight models and derivatives "pyogrio>=0.6", # io for geopandas dataframes @@ -37,7 +38,7 @@ dependencies = [ "tomli", # parsing toml files "tomli-w", # writing toml files "universal_pathlib>=0.2", # provides path compatability between different filesystems - "xarray", # ndim data arrays + "xarray==2024.3.0", # ndim data arrays "xmltodict", # xml parser also used to read VRT "zarr", # zarr ] diff --git a/tests/conftest.py b/tests/conftest.py index 734bef3ef..a63a19d24 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -11,6 +11,8 @@ from dask import config as dask_config from shapely.geometry import box +from hydromt.predefined_catalog import PREDEFINED_CATALOGS + dask_config.set(scheduler="single-threaded") import hydromt._compat as compat @@ -35,6 +37,31 @@ DATADIR = join(dirname(abspath(__file__)), "data") +@pytest.fixture(autouse=True) +def _local_catalog_eps(monkeypatch) -> dict: + """Set entrypoints to local predefined catalogs.""" + cat_root = Path(__file__).parent.parent / "data" / "catalogs" + for name, cls in PREDEFINED_CATALOGS.items(): + monkeypatch.setattr( + f"hydromt.predefined_catalog.{cls.__name__}.base_url", + str(cat_root / name), + ) + + +@pytest.fixture() +def data_catalog(_local_catalog_eps) -> DataCatalog: + """DataCatalog instance that points to local predefined catalogs.""" + return DataCatalog("artifact_data=v0.0.8") + + +@pytest.fixture(scope="session") +def latest_dd_version_uri(): + cat_root = Path(__file__).parent.parent / "data" / "catalogs" / "deltares_data" + versions = [d.name for d in cat_root.iterdir() if d.is_dir()] + latest_version = sorted(versions)[-1] + return cat_root / latest_version / "data_catalog.yml" + + @pytest.fixture(scope="class") def tmp_dir() -> Path: with TemporaryDirectory() as tempdirname: @@ -349,10 +376,3 @@ def mesh_model(griduda): mod.setup_config(**{"header": {"setting": "value"}}) mod.set_mesh(griduda, "elevtn") return mod - - -@pytest.fixture() -def artifact_data(): - datacatalog = DataCatalog() - datacatalog.from_predefined_catalogs("artifact_data") - return datacatalog diff --git a/tests/test_basin_mask.py b/tests/test_basin_mask.py index 71c713e2e..a82e9f309 100644 --- a/tests/test_basin_mask.py +++ b/tests/test_basin_mask.py @@ -9,8 +9,7 @@ import pytest import xarray as xr -import hydromt -from hydromt import DataCatalog, raster +from hydromt import raster from hydromt.models import MODELS from hydromt.workflows.basin_mask import ( _check_size, @@ -22,14 +21,13 @@ logger = logging.getLogger("tets_basin") -def test_region(tmpdir, world, geodf, rioda): +def test_region(tmpdir, world, geodf, rioda, data_catalog): # prepare test data fn_gdf = str(tmpdir.join("world.geojson")) world.to_file(fn_gdf, driver="GeoJSON") fn_grid = str(tmpdir.join("grid.tif")) rioda.raster.to_raster(fn_grid) - cat = DataCatalog() - cat.from_dict( + data_catalog.from_dict( { "world": { "path": fn_gdf, @@ -62,7 +60,7 @@ def test_region(tmpdir, world, geodf, rioda): assert isinstance(region["geom"], gpd.GeoDataFrame) kind, region = parse_region({"geom": fn_gdf}) assert isinstance(region["geom"], gpd.GeoDataFrame) - kind, region = parse_region({"geom": "world"}, data_catalog=cat) + kind, region = parse_region({"geom": "world"}, data_catalog=data_catalog) assert isinstance(region["geom"], gpd.GeoDataFrame) # geom: points should fail region = {"geom": geodf} @@ -74,7 +72,7 @@ def test_region(tmpdir, world, geodf, rioda): assert isinstance(region["grid"], xr.DataArray) kind, region = parse_region({"grid": fn_grid}) assert isinstance(region["grid"], xr.DataArray) - kind, region = parse_region({"grid": "grid"}, data_catalog=cat) + kind, region = parse_region({"grid": "grid"}, data_catalog=data_catalog) assert isinstance(region["grid"], xr.DataArray) # basid @@ -107,8 +105,7 @@ def test_region(tmpdir, world, geodf, rioda): assert "xy" in region -def test_region_value(): - data_catalog = DataCatalog() +def test_region_value(data_catalog): array = np.array([1001, 1002, 1003, 1004, 1005]) kwarg = _parse_region_value(array, data_catalog=data_catalog) assert kwarg.get("basid") == array.tolist() @@ -137,8 +134,7 @@ def test_check_size(caplog): @pytest.mark.filterwarnings("ignore::UserWarning") -def test_basin(caplog): - data_catalog = hydromt.DataCatalog("artifact_data", logger=logger) +def test_basin(data_catalog): ds = data_catalog.get_rasterdataset("merit_hydro_1k") gdf_bas_index = data_catalog.get_geodataframe("merit_hydro_index") bas_index = data_catalog.get_source("merit_hydro_index") diff --git a/tests/test_data_adapter.py b/tests/test_data_adapter.py index f862c60f9..1d412e4ff 100644 --- a/tests/test_data_adapter.py +++ b/tests/test_data_adapter.py @@ -108,9 +108,9 @@ def test_rasterdataset(rioda, tmpdir): @pytest.mark.skipif(not compat.HAS_GCSFS, reason="GCSFS not installed.") -def test_gcs_cmip6(tmpdir): +def test_gcs_cmip6(): # TODO switch to pre-defined catalogs when pushed to main - catalog_fn = join(CATALOGDIR, "gcs_cmip6_data.yml") + catalog_fn = join(CATALOGDIR, "gcs_cmip6_data", "v0.1.0", "data_catalog.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) ds = data_catalog.get_rasterdataset( "cmip6_NOAA-GFDL/GFDL-ESM4_historical_r1i1p1f1_Amon", @@ -130,7 +130,7 @@ def test_gcs_cmip6(tmpdir): @pytest.mark.skipif(not compat.HAS_S3FS, reason="S3FS not installed.") def test_aws_worldcover(): - catalog_fn = join(CATALOGDIR, "aws_data.yml") + catalog_fn = join(CATALOGDIR, "aws_data", "v0.1.0", "data_catalog.yml") data_catalog = DataCatalog(data_libs=[catalog_fn]) da = data_catalog.get_rasterdataset( "esa_worldcover_2020_v100", @@ -161,7 +161,7 @@ def test_http_data(): assert da.raster.shape == (4000, 4000) -def test_rasterdataset_zoomlevels(rioda_large, tmpdir): +def test_rasterdataset_zoomlevels(rioda_large, tmpdir, data_catalog): # write tif with zoom level 1 in name # NOTE zl 0 not written to check correct functioning name = "test_zoom" @@ -176,7 +176,6 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir): } } # test zoom levels in name - data_catalog = DataCatalog() data_catalog.from_dict(yml_dict) rds = cast(RasterDatasetAdapter, data_catalog.get_source(name)) assert rds._parse_zoom_level(None) is None @@ -213,8 +212,8 @@ def test_rasterdataset_zoomlevels(rioda_large, tmpdir): assert isinstance(da1, xr.Dataset) -def test_rasterdataset_driver_kwargs(artifact_data: DataCatalog, tmpdir): - era5 = artifact_data.get_rasterdataset("era5") +def test_rasterdataset_driver_kwargs(data_catalog: DataCatalog, tmpdir): + era5 = data_catalog.get_rasterdataset("era5") fp1 = join(tmpdir, "era5.zarr") era5.to_zarr(fp1) data_dict = { @@ -251,21 +250,21 @@ def test_rasterdataset_driver_kwargs(artifact_data: DataCatalog, tmpdir): datacatalog.get_source("era5_zarr").to_file(tmpdir, "era5_zarr", driver="zarr") -def test_rasterdataset_unit_attrs(artifact_data: DataCatalog): - era5_dict = {"era5": artifact_data.get_source("era5").to_dict()} +def test_rasterdataset_unit_attrs(data_catalog: DataCatalog): + era5_dict = {"era5": data_catalog.get_source("era5").to_dict()} attrs = { "temp": {"unit": "degrees C", "long_name": "temperature"}, "temp_max": {"unit": "degrees C", "long_name": "maximum temperature"}, "temp_min": {"unit": "degrees C", "long_name": "minimum temperature"}, } era5_dict["era5"].update(dict(attrs=attrs)) - artifact_data.from_dict(era5_dict) - raster = artifact_data.get_rasterdataset("era5") + data_catalog.from_dict(era5_dict) + raster = data_catalog.get_rasterdataset("era5") assert raster["temp"].attrs["unit"] == attrs["temp"]["unit"] assert raster["temp_max"].attrs["long_name"] == attrs["temp_max"]["long_name"] -def test_geodataset(geoda, geodf, ts, tmpdir): +def test_geodataset(geoda, geodf, ts, tmpdir, data_catalog): fn_nc = str(tmpdir.join("test.nc")) fn_gdf = str(tmpdir.join("test.geojson")) fn_csv = str(tmpdir.join("test.csv")) @@ -274,7 +273,6 @@ def test_geodataset(geoda, geodf, ts, tmpdir): geodf.to_file(fn_gdf, driver="GeoJSON") ts.to_csv(fn_csv) hydromt.io.write_xy(fn_csv_locs, geodf) - data_catalog = DataCatalog() # added fn_ts to test if it does not go into xr.open_dataset da1 = data_catalog.get_geodataset( fn_nc, variables=["test1"], bbox=geoda.vector.bounds @@ -324,8 +322,8 @@ def test_geodataset(geoda, geodf, ts, tmpdir): GeoDatasetAdapter(fn_nc).to_file(data_root=td, data_name="test", driver="zarr") -def test_geodataset_unit_attrs(artifact_data: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_attrs(data_catalog: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} attrs = { "waterlevel": { "long_name": "sea surface height above mean sea level", @@ -333,15 +331,15 @@ def test_geodataset_unit_attrs(artifact_data: DataCatalog): } } gtsm_dict["gtsmv3_eu_era5"].update(dict(attrs=attrs)) - artifact_data.from_dict(gtsm_dict) - gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") + data_catalog.from_dict(gtsm_dict) + gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") assert gtsm_geodataarray.attrs["long_name"] == attrs["waterlevel"]["long_name"] assert gtsm_geodataarray.attrs["unit"] == attrs["waterlevel"]["unit"] -def test_geodataset_unit_conversion(artifact_data: DataCatalog): - gtsm_geodataarray = artifact_data.get_geodataset("gtsmv3_eu_era5") - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_unit_conversion(data_catalog: DataCatalog): + gtsm_geodataarray = data_catalog.get_geodataset("gtsmv3_eu_era5") + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(unit_mult=dict(waterlevel=1000))) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -349,8 +347,8 @@ def test_geodataset_unit_conversion(artifact_data: DataCatalog): assert gtsm_geodataarray1000.equals(gtsm_geodataarray * 1000) -def test_geodataset_set_nodata(artifact_data: DataCatalog): - gtsm_dict = {"gtsmv3_eu_era5": artifact_data.get_source("gtsmv3_eu_era5").to_dict()} +def test_geodataset_set_nodata(data_catalog: DataCatalog): + gtsm_dict = {"gtsmv3_eu_era5": data_catalog.get_source("gtsmv3_eu_era5").to_dict()} gtsm_dict["gtsmv3_eu_era5"].update(dict(nodata=-99)) datacatalog = DataCatalog() datacatalog.from_dict(gtsm_dict) @@ -484,12 +482,11 @@ def test_dataset_to_stac_catalog(tmpdir, timeseries_ds): assert list(stac_item.assets.keys())[0] == "test.nc" -def test_geodataframe(geodf, tmpdir): +def test_geodataframe(geodf, tmpdir, data_catalog): fn_gdf = str(tmpdir.join("test.geojson")) fn_shp = str(tmpdir.join("test.shp")) geodf.to_file(fn_gdf, driver="GeoJSON") geodf.to_file(fn_shp) - data_catalog = DataCatalog() # test read geojson using total bounds gdf1 = data_catalog.get_geodataframe(fn_gdf, bbox=geodf.total_bounds) assert isinstance(gdf1, gpd.GeoDataFrame) @@ -536,20 +533,19 @@ def test_geodataframe(geodf, tmpdir): data_catalog.get_geodataframe("no_file.geojson") -def test_geodataframe_unit_attrs(artifact_data: DataCatalog): - gadm_level1 = {"gadm_level1": artifact_data.get_source("gadm_level1").to_dict()} +def test_geodataframe_unit_attrs(data_catalog: DataCatalog): + gadm_level1 = {"gadm_level1": data_catalog.get_source("gadm_level1").to_dict()} attrs = {"NAME_0": {"long_name": "Country names"}} gadm_level1["gadm_level1"].update(dict(attrs=attrs)) - artifact_data.from_dict(gadm_level1) - gadm_level1_gdf = artifact_data.get_geodataframe("gadm_level1") + data_catalog.from_dict(gadm_level1) + gadm_level1_gdf = data_catalog.get_geodataframe("gadm_level1") assert gadm_level1_gdf["NAME_0"].attrs["long_name"] == "Country names" -def test_dataframe(df, tmpdir): +def test_dataframe(df, tmpdir, data_catalog): # Test reading csv fn_df = str(tmpdir.join("test.csv")) df.to_csv(fn_df) - data_catalog = DataCatalog() df1 = data_catalog.get_dataframe(fn_df, driver_kwargs=dict(index_col=0)) assert isinstance(df1, pd.DataFrame) pd.testing.assert_frame_equal(df, df1) @@ -603,11 +599,10 @@ def test_dataframe_unit_attrs(df: pd.DataFrame, tmpdir): assert np.all(cities_df["test_na"].isna()) -def test_dataframe_time(df_time, tmpdir): +def test_dataframe_time(df_time, tmpdir, data_catalog): # Test time df fn_df_ts = str(tmpdir.join("test_ts.csv")) df_time.to_csv(fn_df_ts) - data_catalog = DataCatalog() dfts1 = data_catalog.get_dataframe( fn_df_ts, driver_kwargs=dict(index_col=0, parse_dates=True) ) @@ -698,12 +693,9 @@ def test_detect_extent(geodf, geoda, rioda, ts): assert np.all(np.equal(rioda_expected_bbox, rioda_detected_bbox)) -def test_to_stac_geodataframe(geodf, tmpdir): +def test_to_stac_geodataframe(geodf, tmpdir, data_catalog): fn_gdf = str(tmpdir.join("test.geojson")) geodf.to_file(fn_gdf, driver="GeoJSON") - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - # geodataframe name = "gadm_level1" adapter = cast(GeoDataFrameAdapter, data_catalog.get_source(name)) @@ -729,10 +721,7 @@ def test_to_stac_geodataframe(geodf, tmpdir): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_raster(): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac_raster(data_catalog): # raster dataset name = "chirps_global" adapter = cast(RasterDatasetAdapter, data_catalog.get_source(name)) @@ -765,10 +754,7 @@ def test_to_stac_raster(): assert adapter.to_stac_catalog(on_error=ErrorHandleMethod.SKIP) is None -def test_to_stac_geodataset(geoda, tmpdir): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac_geodataset(data_catalog): # geodataset name = "gtsmv3_eu_era5" adapter = cast(GeoDatasetAdapter, data_catalog.get_source(name)) diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 958ffb97a..3229252a1 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -1,7 +1,7 @@ """Tests for the hydromt.data_catalog submodule.""" import os -from os.path import abspath, dirname, isfile, join +from os.path import abspath, dirname, join from pathlib import Path from typing import cast @@ -9,9 +9,9 @@ import numpy as np import pandas as pd import pytest +import requests import xarray as xr -import hydromt.data_catalog from hydromt.data_adapter import ( DataAdapter, GeoDataFrameAdapter, @@ -22,6 +22,7 @@ DataCatalog, _denormalise_data_dict, _parse_data_source_dict, + _yml_from_uri_or_path, ) from hydromt.gis_utils import to_geographic_bbox from hydromt.nodata import NoDataStrategy @@ -108,15 +109,14 @@ def test_parser(): _parse_data_source_dict("test", {}) with pytest.raises(ValueError, match="Data type error unknown"): _parse_data_source_dict("test", {"path": "", "data_type": "error"}) - with pytest.raises( - ValueError, match="alias test not found in data_dict" - ), pytest.deprecated_call(): + with ( + pytest.raises(ValueError, match="alias test not found in data_dict"), + pytest.deprecated_call(), + ): _denormalise_data_dict({"test1": {"alias": "test"}}) -def test_data_catalog_io(tmpdir): - data_catalog = DataCatalog() - _ = data_catalog.sources # load artifact data as fallback +def test_data_catalog_io(tmpdir, data_catalog): # read / write fn_yml = join(tmpdir, "test.yml") data_catalog.to_yml(fn_yml) @@ -129,7 +129,7 @@ def test_data_catalog_io(tmpdir): print(data_catalog.get_source("merit_hydro")) -def test_versioned_catalog_entries(tmpdir): +def test_versioned_catalog_entries(): # make sure the catalogs individually still work legacy_yml_fn = join(DATADIR, "legacy_esa_worldcover.yml") legacy_data_catalog = DataCatalog(data_libs=[legacy_yml_fn]) @@ -213,33 +213,21 @@ def test_versioned_catalog_entries(tmpdir): assert aws_and_legacy_catalog2 == aws_and_legacy_catalog -def test_versioned_catalogs(tmpdir, monkeypatch): - v999_yml_fn = join(tmpdir, "test_sources_v999.yml") - with open(v999_yml_fn, "w") as f: - f.write( - """\ - meta: - hydromt_version: '==999.*' - """ - ) - - DataCatalog().from_predefined_catalogs("deltares_data") - DataCatalog().from_predefined_catalogs("deltares_data", "v2022.7") - - with pytest.raises(RuntimeError, match="Unknown version requested "): - _ = DataCatalog().from_predefined_catalogs("deltares_data", "v1993.7") - - with pytest.raises(RuntimeError, match="Data catalog requires Hydromt Version"): - DataCatalog(data_libs=[v999_yml_fn]) +def test_versioned_catalogs(data_catalog): + data_catalog._sources = {} # reset + data_catalog.from_predefined_catalogs("deltares_data") + assert len(data_catalog.sources) > 0 + data_catalog._sources = {} # reset + data_catalog.from_predefined_catalogs("deltares_data", "v0.5.0") + assert len(data_catalog.sources) > 0 - with monkeypatch.context() as m: - m.setattr(hydromt.data_catalog, "__version__", "999.0.0") - DataCatalog(v999_yml_fn) + with pytest.raises(ValueError, match="Version v1993.7 not found "): + _ = data_catalog.from_predefined_catalogs("deltares_data", "v1993.7") -def test_data_catalog(tmpdir): - data_catalog = DataCatalog() +def test_data_catalog(tmpdir, data_catalog): # initialized with empty dict + data_catalog._sources = {} # reset assert len(data_catalog._sources) == 0 # global data sources from artifacts are automatically added assert len(data_catalog.sources) > 0 @@ -269,12 +257,12 @@ def test_data_catalog(tmpdir): with pytest.deprecated_call(): data_catalog = DataCatalog(deltares_data=False) assert len(data_catalog._sources) == 0 - with pytest.deprecated_call(): - data_catalog.from_artifacts("deltares_data") + data_catalog.from_predefined_catalogs("deltares_data") assert len(data_catalog._sources) > 0 - with pytest.raises( - RuntimeError, match="Unknown version requested" - ), pytest.deprecated_call(): + with ( + pytest.raises(ValueError, match="Version unknown_version not found"), + pytest.deprecated_call(), + ): data_catalog = DataCatalog(deltares_data="unknown_version") # test hydromt version in meta data @@ -283,25 +271,6 @@ def test_data_catalog(tmpdir): data_catalog.to_yml(fn_yml, meta={"hydromt_version": "0.7.0"}) -def test_from_archive(tmpdir): - data_catalog = DataCatalog() - # change cache to tmpdir - data_catalog._cache_dir = str(tmpdir.join(".hydromt_data")) - urlpath = data_catalog.predefined_catalogs["artifact_data"]["urlpath"] - version_hash = list( - data_catalog.predefined_catalogs["artifact_data"]["versions"].values() - )[0] - data_catalog.from_archive(urlpath.format(version=version_hash)) - assert len(data_catalog.iter_sources()) > 0 - source0 = data_catalog.get_source( - next(iter([source_name for source_name, _ in data_catalog.iter_sources()])) - ) - assert ".hydromt_data" in str(source0.path) - # failed to download - with pytest.raises(ConnectionError, match="Data download failed"): - data_catalog.from_archive("https://asdf.com/asdf.zip") - - def test_used_sources(tmpdir): merged_yml_fn = join(DATADIR, "merged_esa_worldcover.yml") data_catalog = DataCatalog(merged_yml_fn) @@ -315,37 +284,33 @@ def test_used_sources(tmpdir): assert sources[0][1].version == source.version -def test_from_yml_with_archive(tmpdir): - yml_fn = join(CATALOGDIR, "artifact_data.yml") - data_catalog = DataCatalog(yml_fn) +def test_from_yml_with_archive(data_catalog): + cache_dir = Path(data_catalog._cache_dir) + data_catalog.from_predefined_catalogs("artifact_data=v0.0.8") sources = list(data_catalog.sources.keys()) assert len(sources) > 0 # as part of the getting the archive a a local # catalog file is written to the same folder # check if this file exists and we can read it - root = dirname(data_catalog.get_source(sources[0]).path) - yml_dst_fn = join(root, "artifact_data.yml") - assert isfile(yml_dst_fn) + yml_dst_fn = Path(cache_dir, "artifact_data", "v0.0.8", "data_catalog.yml") + assert yml_dst_fn.exists() data_catalog1 = DataCatalog(yml_dst_fn) sources = list(data_catalog1.sources.keys()) source = data_catalog1.get_source(sources[0]) - assert dirname(source.path) == root + assert yml_dst_fn.parent == Path(source.path).parent.parent -def test_from_predefined_catalogs(): - data_catalog = DataCatalog() - data_catalog.set_predefined_catalogs( - join(CATALOGDIR, "..", "predefined_catalogs.yml") - ) +def test_from_predefined_catalogs(data_catalog): + assert len(data_catalog.predefined_catalogs) > 0 for name in data_catalog.predefined_catalogs: + data_catalog._sources = {} # reset data_catalog.from_predefined_catalogs(f"{name}=latest") assert len(data_catalog._sources) > 0 - data_catalog._sources = {} # reset with pytest.raises(ValueError, match='Catalog with name "asdf" not found'): data_catalog.from_predefined_catalogs("asdf") -def test_export_global_datasets(tmpdir): +def test_export_global_datasets(tmpdir, data_catalog): DTYPES = { "RasterDatasetAdapter": (xr.DataArray, xr.Dataset), "GeoDatasetAdapter": (xr.DataArray, xr.Dataset), @@ -353,7 +318,7 @@ def test_export_global_datasets(tmpdir): } bbox = [12.0, 46.0, 13.0, 46.5] # Piava river time_tuple = ("2010-02-10", "2010-02-15") - data_catalog = DataCatalog("artifact_data") # read artifacts + data_catalog.from_predefined_catalogs("artifact_data") source_names = [ "era5[precip,temp]", "grwl_mask", @@ -459,8 +424,7 @@ def test_export_dataframe(tmpdir, df, df_time): assert isinstance(obj, dtypes), key -def test_get_rasterdataset(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_rasterdataset(data_catalog): n = len(data_catalog) # raster dataset using three different ways name = "koppen_geiger" @@ -488,8 +452,7 @@ def test_get_rasterdataset(): data_catalog.get_rasterdataset({"name": "test"}) -def test_get_geodataframe(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_geodataframe(data_catalog): n = len(data_catalog) # vector dataset using three different ways name = "osm_coastlines" @@ -513,8 +476,7 @@ def test_get_geodataframe(): data_catalog.get_geodataframe({"name": "test"}) -def test_get_geodataset(): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_geodataset(data_catalog): n = len(data_catalog) # geodataset using three different ways name = "gtsmv3_eu_era5" @@ -542,9 +504,8 @@ def test_get_geodataset(): data_catalog.get_geodataset({"name": "test"}) -def test_get_dataset(timeseries_df): +def test_get_dataset(timeseries_df, data_catalog): # get_dataset - data_catalog = DataCatalog("artifact_data") test_dataset = timeseries_df.to_xarray() subset_timeseries = timeseries_df.iloc[[0, len(timeseries_df) // 2]] time_tuple = ( @@ -560,8 +521,7 @@ def test_get_dataset(timeseries_df): assert ds.name == "col1" -def test_get_dataframe(df, tmpdir): - data_catalog = DataCatalog("artifact_data") # read artifacts +def test_get_dataframe(df, tmpdir, data_catalog): n = len(data_catalog) # dataframe using single way name = "test.csv" @@ -586,36 +546,29 @@ def test_get_dataframe(df, tmpdir): data_catalog.get_dataframe({"name": "test"}) -def test_deprecation_warnings(artifact_data): +def test_deprecation_warnings(data_catalog): with pytest.deprecated_call(): # should be DataCatalog(data_libs=['artifact_data=v0.0.6']) - DataCatalog(artifact_data="v0.0.6") + DataCatalog(artifact_data="v0.0.8") with pytest.deprecated_call(): - cat = DataCatalog() - # should be cat.from_predefined_catalogs('artifact_data', 'v0.0.6') - cat.from_artifacts("artifact_data", version="v0.0.6") - with pytest.deprecated_call(): - fn = artifact_data["chelsa"].path + fn = data_catalog["chelsa"].path # should be driver_kwargs=dict(chunks={'x': 100, 'y': 100}) - artifact_data.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) + data_catalog.get_rasterdataset(fn, chunks={"x": 100, "y": 100}) with pytest.deprecated_call(): - fn = artifact_data["gadm_level1"].path + fn = data_catalog["gadm_level1"].path # should be driver_kwargs=dict(assert_gtype='Polygon') - artifact_data.get_geodataframe(fn, assert_gtype="MultiPolygon") + data_catalog.get_geodataframe(fn, assert_gtype="MultiPolygon") with pytest.deprecated_call(): - fn = artifact_data["grdc"].path + fn = data_catalog["grdc"].path # should be driver_kwargs=dict(index_col=0) - artifact_data.get_dataframe(fn, index_col=0) + data_catalog.get_dataframe(fn, index_col=0) with pytest.deprecated_call(): - fn = artifact_data["gtsmv3_eu_era5"].path + fn = data_catalog["gtsmv3_eu_era5"].path # should be driver_kwargs=dict(chunks={'time': 100}) - artifact_data.get_geodataset(fn, chunks={"time": 100}) - + data_catalog.get_geodataset(fn, chunks={"time": 100}) -def test_detect_extent(): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback +def test_detect_extent(data_catalog): # raster dataset name = "chirps_global" bbox = 11.60, 45.20, 13.00, 46.80 @@ -648,10 +601,7 @@ def test_detect_extent(): assert detected_temporal_range == expected_temporal_range -def test_to_stac(tmpdir): - data_catalog = DataCatalog() # read artifacts - _ = data_catalog.sources # load artifact data as fallback - +def test_to_stac(tmpdir, data_catalog): _ = data_catalog.get_rasterdataset("chirps_global") _ = data_catalog.get_geodataframe("gadm_level1") _ = data_catalog.get_geodataset("gtsmv3_eu_era5") @@ -674,7 +624,7 @@ def test_to_stac(tmpdir): ) == sorted([Path(join(tmpdir, p, "catalog.json")) for p in ["", *sources, ""]]) -def test_from_stac(tmpdir): +def test_from_stac(): catalog_from_stac = DataCatalog().from_stac_catalog( "./tests/data/stac/catalog.json" ) @@ -682,3 +632,13 @@ def test_from_stac(tmpdir): assert type(catalog_from_stac.get_source("chirps_global")) == RasterDatasetAdapter assert type(catalog_from_stac.get_source("gadm_level1")) == GeoDataFrameAdapter # assert type(catalog_from_stac.get_source("gtsmv3_eu_era5")) == GeoDatasetAdapter + + +def test_yml_from_uri_path(): + uri = "https://google.com/nothinghere" + with pytest.raises(requests.HTTPError): + _yml_from_uri_or_path(uri) + uri = "https://raw.githubusercontent.com/Deltares/hydromt/main/.pre-commit-config.yaml" + yml = _yml_from_uri_or_path(uri) + assert isinstance(yml, dict) + assert len(yml) > 0 diff --git a/tests/test_forcing.py b/tests/test_forcing.py index 63b959657..29147202c 100644 --- a/tests/test_forcing.py +++ b/tests/test_forcing.py @@ -5,14 +5,12 @@ import xarray as xr import hydromt._compat as compat -from hydromt.data_catalog import DataCatalog from hydromt.raster import full_from_transform from hydromt.workflows.forcing import pet, precip -def test_precip(): - cat = DataCatalog() - p_precip = cat.get_rasterdataset("era5", variables="precip") # era hourly +def test_precip(data_catalog): + p_precip = data_catalog.get_rasterdataset("era5", variables="precip") # era hourly # We create a more refined grid p_transform = p_precip.raster.transform @@ -26,7 +24,7 @@ def test_precip(): xr.testing.assert_equal(pout.x, grid.x) # Testing with clim argument - p_clim = cat.get_rasterdataset("worldclim") + p_clim = data_catalog.get_rasterdataset("worldclim") # give it a nodata value in the datacatalog >> issue to # create for the data artifacts p_clim.raster.set_nodata(-999.0) @@ -41,10 +39,9 @@ def test_precip(): @pytest.mark.skipif(not compat.HAS_PYET, reason="pyET not installed.") -def test_pet(): - cat = DataCatalog() - et_data = cat.get_rasterdataset("era5_daily_zarr") - dem = cat.get_rasterdataset("era5_orography").squeeze("time", drop=True) +def test_pet(data_catalog): + et_data = data_catalog.get_rasterdataset("era5_daily_zarr") + dem = data_catalog.get_rasterdataset("era5_orography").squeeze("time", drop=True) peto = pet(et_data, et_data, dem, method="penman-monteith_tdew") diff --git a/tests/test_predefined_catalogs.py b/tests/test_predefined_catalogs.py new file mode 100644 index 000000000..0665e50da --- /dev/null +++ b/tests/test_predefined_catalogs.py @@ -0,0 +1,106 @@ +from pathlib import Path + +import pytest + +from hydromt.predefined_catalog import ( + ArtifactDataCatalog, + PredefinedCatalog, + create_registry_file, +) + + +@pytest.fixture() +def cat_root() -> Path: + return Path(__file__).parent.parent / "data/catalogs" + + +@pytest.fixture() +def tmp_catalog_files(tmpdir): + _base_url = Path(tmpdir) / "test_catalog" + for version in ["v0.1.0", "v0.2.0", "v1.0.0"]: + catalog_path = _base_url / version / "data_catalog.yml" + catalog_path.parent.mkdir(parents=True, exist_ok=True) + catalog_path.write_text("meta:\n version: " + version) + return _base_url + + +@pytest.fixture() +def tmp_catalog_class(tmp_catalog_files) -> type[PredefinedCatalog]: + _base_url = tmp_catalog_files + + # write registry file + create_registry_file(_base_url) + + class TestCatalog(PredefinedCatalog): + name = "test_catalog" + base_url = str(_base_url) + + return TestCatalog + + +def test_predefined_catalog(tmp_catalog_class, tmpdir): + catalog = tmp_catalog_class(format_version="v0", cache_dir=Path(tmpdir) / "cache") + assert catalog.name == "test_catalog" + assert catalog._format_version == "v0" + assert catalog._pooch is None + assert catalog._versions is None + assert ( + catalog.get_catalog_file("v0.1.0") + == catalog._cache_dir / "test_catalog" / "v0.1.0" / "data_catalog.yml" + ) + assert ( + catalog.get_catalog_file() + == catalog._cache_dir / "test_catalog" / "v0.2.0" / "data_catalog.yml" + ) + assert catalog.versions == ["v0.1.0", "v0.2.0"] + + # remove source and cached registry file and check if one is created based on + # the cached catalog files + registry_path = catalog._cache_dir / "test_catalog" / "registry.txt" + registry_path.unlink() + Path(tmp_catalog_class.base_url, "registry.txt").unlink() + catalog._load_registry_file(overwrite=True) + assert registry_path.exists() + + with pytest.raises(ValueError, match="Version v0.0.0 not found"): + catalog.get_catalog_file("v0.0.0") + + +def test_create_registry_file(tmpdir, tmp_catalog_files): + # test create registry file + root = tmp_catalog_files + create_registry_file(root) + registry_path = root / "registry.txt" + assert registry_path.exists() + + # no catalog files + with pytest.raises(FileNotFoundError): + create_registry_file(Path(tmpdir, "not_existing")) + + # create a dummy catalog file with version folder + cat_path = root / "data_catalog.yml" + cat_path.write_text("meta:\n version: v0.1.0") + with pytest.raises(ValueError, match="No valid version found"): + create_registry_file(root) + + +def test_get_versions_artifacts(): + versions = ArtifactDataCatalog().versions + assert len(versions) > 0 + assert "v0.0.8" in versions + + +def test_catalog_versions(cat_root, tmpdir): + # assert all subdirs are catalogs and have a versions.yml file + catalogs = [d for d in cat_root.iterdir() if d.is_dir()] + for cat_dir in catalogs: + registry_file = cat_dir / "registry.txt" + assert registry_file.exists() + tmp_registry_file = Path(tmpdir) / f"{cat_dir.name}_registry.txt" + create_registry_file(cat_dir, tmp_registry_file) + # check if both registry files (incl hashes) are the same + with open(registry_file, "r") as f: + registry = sorted(f.readlines()) + with open(tmp_registry_file, "r") as f: + tmp_registry = sorted(f.readlines()) + assert registry == tmp_registry diff --git a/tests/validators/test_data_catalog_validation.py b/tests/validators/test_data_catalog_validation.py index 34a6e966d..a9c76d0aa 100644 --- a/tests/validators/test_data_catalog_validation.py +++ b/tests/validators/test_data_catalog_validation.py @@ -15,9 +15,8 @@ ) -def test_deltares_data_catalog(): - p = "data/catalogs/deltares_data.yml" - yml_dict = _yml_from_uri_or_path(p) +def test_deltares_data_catalog(latest_dd_version_uri): + yml_dict = _yml_from_uri_or_path(latest_dd_version_uri) # whould raise error if something goes wrong _ = DataCatalogValidator.from_dict(yml_dict) From 08478c21653785d752edfef6ca95579418ca36c1 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 15 May 2024 11:51:02 +0200 Subject: [PATCH 081/110] fixed failing tests --- data/catalogs/deltares_data/registry.txt | 4 ++-- tests/test_data_catalog.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index 1b2d40746..bd416abad 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,3 +1,3 @@ -v0.6.0/data_catalog.yml 665fab293944a5c0bd56d8af11f1eccd58fb5d94eb55f06e8ac33192f5f42738 +v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef -v0.7.0/data_catalog.yml 0c79d6070daa21e739daf01b3ebb4a2f9e2c2ba3be4b68bdfe14ecfc6efa09b9 +v0.7.0/data_catalog.yml 16f281de2cf269483bba60e8463ca4bcc9a90fdd20cef7a9ae35e7e453252dbf diff --git a/tests/test_data_catalog.py b/tests/test_data_catalog.py index 7489234df..ea973f4f4 100644 --- a/tests/test_data_catalog.py +++ b/tests/test_data_catalog.py @@ -303,7 +303,7 @@ def test_from_yml_with_archive(data_catalog): data_catalog1 = DataCatalog(yml_dst_fn) sources = list(data_catalog1.sources.keys()) source = data_catalog1.get_source(sources[0]) - assert yml_dst_fn.parent == Path(source.path).parent.parent + assert yml_dst_fn.parent == Path(source.path).parent def test_from_predefined_catalogs(data_catalog): From fb8be0d3db7c70bbe1184d3c22a3bf29506911f7 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 15 May 2024 14:34:02 +0200 Subject: [PATCH 082/110] updated parse_predefined_catalogs.py --- docs/parse_predefined_catalogs.py | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/docs/parse_predefined_catalogs.py b/docs/parse_predefined_catalogs.py index 90ce21174..cb0ae9c85 100644 --- a/docs/parse_predefined_catalogs.py +++ b/docs/parse_predefined_catalogs.py @@ -1,3 +1,5 @@ + +from typing import Union import os import numpy as np import pandas as pd @@ -54,7 +56,7 @@ def write_nested_dropdown(name, df_dict: dict, note: str=""): df = df_dict[version]#.reset_index().set_index(["name", "provider", "version"]) df = df.sort_index() name_str = f"{version}" - if i == 0: + if i == len(df_dict)-1: name_str += " (latest)" write_panel(f, name_str, level=1) write_panel(f, "", level=2, item="tab-set") @@ -96,7 +98,7 @@ def write_sources_panel(f, df, level, sources=None): ) write_panel(f, source, summary, level=level) -def parse_item(k: str, v: str | list | dict) -> str: +def parse_item(k: str, v: Union[str , list , dict]) -> str: def _parse_dict(d: dict) -> str: return " ".join([f"**{k}:** {_parse(v)}" for k, v in d.items()]) def _parse_list(l: list) -> str: @@ -121,26 +123,24 @@ def _parse(v): return f":{k}: {v}" def write_predefined_catalogs_to_rst_panels( - predefined_catalog_uri: Path = Path(FILE_ROOT, r"../data/predefined_catalogs.yml"), git_raw_uri: str = r"https://raw.githubusercontent.com/Deltares/hydromt", ) -> None: """Generate panels rst files from data catalogs to include in docs""" os.makedirs(Path(FILE_ROOT, "_generated"), exist_ok=True) data_cat = DataCatalog() - data_cat.set_predefined_catalogs(predefined_catalog_uri) predefined_catalogs = data_cat.predefined_catalogs paths = [] for name in predefined_catalogs: - urlpath = predefined_catalogs[name].get("urlpath", "") - note = predefined_catalogs[name].get("notes", "") + urlpath = predefined_catalogs[name].base_url + df_dict = {} - for iversion, version in enumerate(predefined_catalogs[name].get("versions", [])): + for iversion, version in enumerate(predefined_catalogs[name].versions): if iversion >= N_VERSIONS: break - githash = predefined_catalogs[name]['versions'][version] - if urlpath.startswith(git_raw_uri) and githash == "main": + + if urlpath.startswith(git_raw_uri): # make sure to load the latest version from current branch - local_path = Path(FILE_ROOT, urlpath.replace(f'{git_raw_uri}/{{version}}', '../')) + local_path = predefined_catalogs[name].get_catalog_file(version) data_cat.from_yml(local_path, catalog_name=name) else: try: @@ -151,7 +151,7 @@ def write_predefined_catalogs_to_rst_panels( df = data_cat.to_dataframe().sort_index().drop_duplicates("path") df_dict[version] = df.copy() data_cat._sources = {} # reset - path = write_nested_dropdown(name, df_dict, note=note) + path = write_nested_dropdown(name, df_dict) paths.append(path) with open(Path(FILE_ROOT, "_generated/predefined_catalogs.rst"), "w") as f: f.writelines( From 57a930d0a74ba14b505d872fb939a716f77161d6 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 15 May 2024 16:02:46 +0200 Subject: [PATCH 083/110] updated artifact_data v0.0.8 --- data/catalogs/artifact_data/registry.txt | 2 +- data/catalogs/artifact_data/v0.0.8/data_catalog.yml | 1 + hydromt/data_catalog.py | 2 +- 3 files changed, 3 insertions(+), 2 deletions(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index f95a52093..3ee7980c4 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,4 +1,4 @@ v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v0.0.8/data_catalog.yml 4f8eafbc1e3464a4247bbd2138bfbe8851b827a1edf3770c69987e8315ddb3de +v0.0.8/data_catalog.yml f332438ef26ede5a863674a4cd1e7fe0380a17a3f6ef57956cd7ba15a2fd5b04 v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee diff --git a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml index 8bd9529ad..c0d27104e 100644 --- a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml +++ b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml @@ -1,6 +1,7 @@ meta: hydromt_version: '>=0.9, <1.0' version: v0.0.8 + root: https://github.com/DirkEilander/hydromt-artifacts/releases/download/v0.0.8/data.tar.gz name: artifact_data chelsa: diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 263220906..7126671c5 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -678,7 +678,7 @@ def _cache_archive( elif Path(archive_uri).suffix == ".gz": kwargs.update(processor=pooch.Untar(extract_dir=extract_dir)) if Path(archive_uri).exists(): # check if arhive is a local file - kwargs.update(donwloader=_copy_file) + kwargs.update(downloader=_copy_file) pooch.retrieve( archive_uri, known_hash=sha256, From dac67429b7a9f99808c209e70f598f5d399145a5 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 15 May 2024 16:32:21 +0200 Subject: [PATCH 084/110] bug fixed archive extraction --- hydromt/data_catalog.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/hydromt/data_catalog.py b/hydromt/data_catalog.py index 7126671c5..b1ca2f47c 100644 --- a/hydromt/data_catalog.py +++ b/hydromt/data_catalog.py @@ -670,9 +670,9 @@ def _cache_archive( """ root = Path(self._cache_dir, name, version) - extract_dir = root / Path(archive_uri).stem + extract_dir = root # retrieve and unpack archive - kwargs = {} + kwargs: dict = {} if Path(archive_uri).suffix == ".zip": kwargs.update(processor=pooch.Unzip(extract_dir=extract_dir)) elif Path(archive_uri).suffix == ".gz": @@ -686,7 +686,7 @@ def _cache_archive( fname=Path(archive_uri).name, **kwargs, ) - return extract_dir + return str(extract_dir) def from_yml( self, From 0e8b9df71b69d90634265b6b4079fa0470b16c1c Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Wed, 15 May 2024 17:25:09 +0200 Subject: [PATCH 085/110] updated data catalog changelog --- data/catalogs/README.rst | 118 ------------------------------------ data/catalogs/changelog.rst | 84 +++++++++++++++++++++++++ 2 files changed, 84 insertions(+), 118 deletions(-) delete mode 100644 data/catalogs/README.rst diff --git a/data/catalogs/README.rst b/data/catalogs/README.rst deleted file mode 100644 index 853c95439..000000000 --- a/data/catalogs/README.rst +++ /dev/null @@ -1,118 +0,0 @@ -======================== -Predefined Data Catalogs -======================== - -This readme file contains information about the predefined data catalogs which be accessed through HydroMT. -The data can be browsed through in the (predefined data catalogs of the HydroMT docs)[https://deltares.github.io/hydromt/latest/user_guide/data_existing_cat.html] -For more information regarding working with data catalogs we refer the user to the (HydroMT user guide)[https://deltares.github.io/hydromt/latest/user_guide/data_main.html] - -deltares_data -============= - -The HydroMT Deltares Data is managed by the HydroMT team. -For adding new data to the deltares_data.yml please follow the conventions given hereinafter. -The data is currently only stored on the deltares network drive: p:/wflow_global/hydromt - -Preferred data formats to download ------------------------------------ -vector data: flatgeobuf (because they contain a spatial index and are therefore much faster) -raster data (2D): cloud optimized geotiff -raster data (3D): zarr - -Data storage in the Deltares network drive (p:/wflow_global/hydromt) --------------------------------------------------------------------- - -data used by the geoserver: -DO NOT CHANGE WITHOUT CONSULTATION -- alosdem -- copdem - -writing convention: -- snake_case (i.e. lower case with underscores) - -folder structure: -- no subcategories - - 1. data type (category) - bathymetry - geography - hydro - hydrography - infrastructure - landuse - meteo - ocean - sociao_economic - soil - topography - 2. data name - e.g.: - era5 - eobs - grdc - osm - ... -(3. parameter) - e.g.: - t2m - msl - ... - -deltares_data.yml ------------------- -writing convention: -- snake_case (i.e. lower case with underscores) -- the key "data_type" follows this convention but the data type itself is written in cam case (RasterDataset/GeoDataFrame/GeoDataset) -- two spaces for indentation - -data versioning: -- data always refers to a specific version -- short name refers to that version -- convention: `[data_name]_v[version_number]` (e.g. `eobs_v22.0e`) - -structure per data set: -- use placeholders where possible -- order the data sets alphabetically -- order the components of each data set alphabetically -- for adding meta data use the following optional keys: - -meta: - category: - notes: - paper_doi: - paper_ref: - source_author: (if different from paper_ref) - source_license: - source_url: - source_spatial_extent: - source_temporal_extent: - processing_script: - processing_notes: - -Updates -------- - -To preserve reproducibility for older versions of the catalogs, we DO NOT modify old catalogs in any way. Even adding different whitespaces to the file is problematic because of how they are retrieved. Instead, we use a versioning system for the catalog files themselves. If you want to update one of the catalogs, follow the following steps - -1. create new branch on github -2. make a new folder with the name of the version you are going to create -3. add the new version of the data catalog to this new folder, and make sure it is called `data_catalog.yml`. You can also copy the latest data catalog into the new folder and simply edit the copied version. -4. bump the version in the global meta section using semantic versioning -5. run update_versions.py, this will create a registry file with the versions and SHA256 hashes of the data catalogs. It is very important that the files have Linux style line endings (LF) as opposed to windows style line endings (CRLF) to keep hashes consistent. If this is not done, pooch will not be able to find the catalogs. This is done automatically for you (CRLF -> LF) if you are updating from windows. -6. test your yml file, (for more information on testing see section below). -7. create a pull request targeting the main branch -8. Once the pull request get's merged into the `main` branch, it should be available to all HydroMT users. - -Testing -------- -If you want to make catalogs for HydroMT testing purposes, or to update a catalog with new data, we must first ensure that HydroMT can properly read and use your data. To do this, we need to test the data with HydroMT in our CI environment on github. DO NOT modify the `data/catalogs/predefined_catalogs.yml` file to do this. The use of this file is deprecated and it is maintained for backwards compatibility, but should no longer be used. - -Testing a new data catalog should be fairly straight forward once it is created. The level of testing we require to add new catalogs can varry depending on the size, importance, and popularity of the set. In order of importance the tests that should be done are: - -1. Instantiate a catalog, and retrieve the dataset from it using the appropriate `get_*` function (e.g. `get_rasterdataset` for raster data) -2. The dataset should slice properly in whatever ways are appropriate. (e.g. requesting a dataset with only certain variables should return only that data if the driver supports it) -3. If the dataset requires special logic to merge several parts please add tests to demostrate the correct working of this as well. -4. Units should be acounted for properly using properties such as `unit`, `unti_add`, and `unit_mult` where appropriate -5. Whatever domain specific quality assurance should be done, to avoid for example, rounding errors near the boundaries. - -At least, point one needs to be verified locally by the author of the PR, and preferably a test should be made for it in our CI as well. Depending on context we may ask you to verify other points (on this list) as well. diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index f47ff7746..88a1abcb9 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -24,6 +24,90 @@ Added deltares_data ============= +version v0.7.0 +-------------- + +added +^^^^^ +- version argument to data source where applicable +- variants argument for data sources that are of the same dataset but different versions +- processing_script / processing_notes arguments to data sources that have been (pre-) processed +- temporal extent of datasets that have a temporal dimension. +- spatial extents to datasets + +changed +^^^^^^^ +- removed source_version from data source meta +- kwargs to driver_kwargs +- updated source_url if url was not working anymore +- sorted datasets by alphabetical order +- Removed version from dataset names +- prefixed 'hydro' where for all HydroSHEDS datasets +- added the epoch of the dataset to the name of the dataset + +See table below for mapping of old and new names: + ++--------------------------------+---------------------------+ +| Old name | New name | ++================================+===========================+ +| basin_atlas_level12_v10 | hydro_basin_atlas_level12 | ++--------------------------------+---------------------------+ +| eobs_v.. | eobs | ++--------------------------------+---------------------------+ +| eobs_orography_v.. | eobs_orography | ++--------------------------------+---------------------------+ +| lake_atlas_pol_v10 | hydro_lake_atlas_pol | ++--------------------------------+---------------------------+ +| river_atlas_v10 | hydro_river_atlas | ++--------------------------------+---------------------------+ +| ghs_pop_2015_54009_v2019a | ghs_pop_2015 | ++--------------------------------+---------------------------+ +| ghs_smod_2015_54009_v2019a | ghs_smod_2015 | ++--------------------------------+---------------------------+ +| glofas_era5_v31 | glofas_era5 | ++--------------------------------+---------------------------+ +| guf_bld_2012 | guf_bld_2012 | ++--------------------------------+---------------------------+ +| rivers_lin2019_v1 | hydro_rivers_lin2019 | ++--------------------------------+---------------------------+ +| SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | ++--------------------------------+---------------------------+ +| SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | ++--------------------------------+---------------------------+ +| vito | vito_2015 | ++--------------------------------+---------------------------+ +| vito_2015_v2.0.2 | vito_2015 | ++--------------------------------+---------------------------+ +| vito_2016_v3.0.1 | vito_2016 | ++--------------------------------+---------------------------+ +| vito_2017_v3.0.1 | vito_2017 | ++--------------------------------+---------------------------+ +| vito_2018_v3.0.1 | vito_2018 | ++--------------------------------+---------------------------+ +| vito_2019_v3.0.1 | vito_2019 | ++--------------------------------+---------------------------+ +| esa_worldcover | esa_worldcover_2020 | ++--------------------------------+---------------------------+ +| corine | corine_2018 | ++--------------------------------+---------------------------+ +| globcover | globcover_2009 | ++--------------------------------+---------------------------+ + + +- Some datasets have multiple versions, for these datasets the default can be changed if +you do not supply a version in your config file. See the table below for which dataset +the default version has changed. + ++----------------+-----------------+--------------------------+ +| Dataset name | Default version | Previous default version | ++================+=================+==========================+ +| eobs | 25.0e | 22.0e | ++----------------+-----------------+--------------------------+ +| eobs_orography | 25.0e | 22.0e | ++----------------+-----------------+--------------------------+ + + + version: 2024.1.30 --------------- From c9ffc6379cb160f3fe7a6b48b45d2c58f544a9fd Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 16 May 2024 09:59:31 +0200 Subject: [PATCH 086/110] updated artifact data catalog --- .../artifact_data/v0.0.9/data_catalog.yml | 154 ++++++++++++------ data/catalogs/changelog.md | 148 ----------------- data/catalogs/changelog.rst | 2 +- 3 files changed, 103 insertions(+), 201 deletions(-) delete mode 100644 data/catalogs/changelog.md diff --git a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml index 518ea84c5..d3879a9ac 100644 --- a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml +++ b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml @@ -13,8 +13,9 @@ chelsa: paper_ref: Karger et al. (2017) source_license: CC BY 4.0 source_url: http://chelsa-climate.org/downloads/ - source_version: 1.2 + version: 1.2 path: chelsa.tif + chirps_global: crs: 4326 data_type: RasterDataset @@ -25,10 +26,11 @@ chirps_global: paper_ref: Funk et al (2014) source_license: CC source_url: https://www.chc.ucsb.edu/data/chirps - source_version: v2.0 + version: v2.0 path: chirps_global.nc unit_add: time: 86400 + corine: data_type: RasterDataset driver: raster @@ -37,8 +39,9 @@ corine: source_author: European Environment Agency source_license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata source_url: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 - source_version: v.2020_20u1 + version: v.2020_20u1 path: corine.tif + dtu10mdt: crs: 4326 data_type: RasterDataset @@ -48,9 +51,10 @@ dtu10mdt: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM2008 + version: 2010 path: dtu10mdt.tif + dtu10mdt_egm96: crs: 4326 data_type: RasterDataset @@ -60,9 +64,10 @@ dtu10mdt_egm96: paper_doi: 10.1029/2008JC005179 paper_ref: Andersen and Knudsen (2009) source_url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography - source_version: 2010 unit: m+EGM96 + version: 2010 path: dtu10mdt_egm96.tif + eobs: crs: 4326 data_type: RasterDataset @@ -73,10 +78,11 @@ eobs: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs.nc unit_add: time: 86400 + eobs_orography: crs: 4326 data_type: RasterDataset @@ -87,8 +93,9 @@ eobs_orography: paper_ref: Cornes et al (2018) source_license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles source_url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - source_version: 22.0e + version: 22.0e path: eobs_orography.nc + era5: crs: 4326 data_type: RasterDataset @@ -102,7 +109,7 @@ era5: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels + version: ERA5 daily data on pressure levels path: era5.nc unit_add: temp: -273.15 @@ -114,6 +121,7 @@ era5: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_hourly: crs: 4326 data_type: RasterDataset @@ -125,7 +133,6 @@ era5_hourly: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly.nc unit_add: temp: -273.15 @@ -134,6 +141,7 @@ era5_hourly: kout: 0.000277778 precip: 1000 press_msl: 0.01 + era5_daily_zarr: crs: 4326 data_type: RasterDataset @@ -147,8 +155,8 @@ era5_daily_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 daily data on pressure levels path: era5_daily_zarr.zarr + era5_hourly_zarr: crs: 4326 data_type: RasterDataset @@ -160,8 +168,8 @@ era5_hourly_zarr: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_hourly_zarr.zarr + era5_orography: crs: 4326 data_type: RasterDataset @@ -173,10 +181,10 @@ era5_orography: paper_ref: Hersbach et al. (2019) source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://doi.org/10.24381/cds.bd0915c6 - source_version: ERA5 hourly data on pressure levels path: era5_orography.nc unit_mult: elevtn: 0.10197162129779283 + gadm_level1: crs: 4326 data_type: GeoDataFrame @@ -187,8 +195,9 @@ gadm_level1: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level1.gpkg + gadm_level2: crs: 4326 data_type: GeoDataFrame @@ -199,8 +208,9 @@ gadm_level2: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level2.gpkg + gadm_level3: crs: 4326 data_type: GeoDataFrame @@ -211,8 +221,9 @@ gadm_level3: source_author: gadm source_license: https://gadm.org/license.html source_url: https://gadm.org/download_world.html - source_version: 1.0 + version: 1.0 path: gadm_level3.gpkg + gcn250: data_type: RasterDataset driver: raster @@ -222,9 +233,10 @@ gcn250: paper_ref: Jaafar et al. (2019) source_license: CC BY 4.0 source_url: https://doi.org/10.6084/m9.figshare.7756202.v1 - source_version: v1 nodata: 255 + version: v1 path: gcn250/{variable}.tif + gdp_world: crs: 4326 data_type: GeoDataFrame @@ -236,8 +248,9 @@ gdp_world: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) source_license: CC BY-4.0 - source_version: 1.0 + version: 1.0 path: gdp_world.gpkg + gebco: crs: 4326 data_type: RasterDataset @@ -248,11 +261,11 @@ gebco: paper_ref: Weatherall et al (2020) source_license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 source_url: https://www.bodc.ac.uk/data/open_download/gebco/gebco_2020/geotiff/ - source_version: 2020 unit: m+MSL + version: 2020 path: gebco.tif ghs-smod_2015_v2: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: @@ -262,8 +275,9 @@ ghs-smod_2015_v2: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - source_version: R2019A_v2.0 + version: R2019A_v2.0 path: ghs-smod_2015_v2.tif + ghs_pop_2015: crs: 4326 data_type: RasterDataset @@ -275,10 +289,11 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - source_version: R2019A_v1.0 + path: ghs_pop_2015.tif + ghs_pop_2015_54009: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: @@ -287,9 +302,11 @@ ghs_pop_2015_54009: paper_ref: Florczyk et al (2019) source_license: CC BY 4.0 source_url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop + version: R2019A_v1.0 path: ghs_pop_2015_54009.tif + ghs_smod_2015: - crs: 54009 + crs: ESRI:54009 data_type: RasterDataset driver: raster meta: @@ -298,8 +315,9 @@ ghs_smod_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - source_version: R2016A_v1.0 + version: R2016A_v1.0 path: ghs_smod_2015.tif + globcover: crs: 4326 data_type: RasterDataset @@ -311,6 +329,7 @@ globcover: source_license: CC-BY-3.0 source_url: http://due.esrin.esa.int/page_globcover.php path: globcover.tif + glw_buffaloes: crs: 4326 data_type: RasterDataset @@ -322,8 +341,9 @@ glw_buffaloes: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_buffaloes.tif + glw_cattle: crs: 4326 data_type: RasterDataset @@ -335,8 +355,9 @@ glw_cattle: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_cattle.tif + glw_chicken: crs: 4326 data_type: RasterDataset @@ -348,8 +369,9 @@ glw_chicken: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_chicken.tif + glw_ducks: crs: 4326 data_type: RasterDataset @@ -361,8 +383,9 @@ glw_ducks: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_ducks.tif + glw_goats: crs: 4326 data_type: RasterDataset @@ -374,8 +397,9 @@ glw_goats: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_goats.tif + glw_horses: crs: 4326 data_type: RasterDataset @@ -387,8 +411,9 @@ glw_horses: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_horses.tif + glw_pigs: crs: 4326 data_type: RasterDataset @@ -400,8 +425,9 @@ glw_pigs: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_pigs.tif + glw_sheep: crs: 4326 data_type: RasterDataset @@ -413,8 +439,9 @@ glw_sheep: source_author: glw (Gridded Livestock of World 3 Dataverse) source_license: CC 4.0 source_url: https://dataverse.harvard.edu/dataverse/glw_3 - source_version: GLW 3, last downloaded 2020-06-11 + version: 3 path: glw_sheep.tif + grdc: crs: 4326 data_type: GeoDataFrame @@ -425,6 +452,7 @@ grdc: source_license: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/210_prtl/tou.html;jsessionid=A56D50D4A36D3D8707CBF00CBD71F106.live11291?nn=2862854 source_url: https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/StationCatalogue path: grdc.csv + grip_roads: crs: 4326 data_type: GeoDataFrame @@ -435,8 +463,9 @@ grip_roads: paper_ref: Meijer et al, 2018 source_license: CC0-1.0 source_url: https://www.globio.info/download-grip-dataset - source_version: v4 + version: v4 path: grip_roads.gpkg + grwl: data_type: GeoDataFrame driver: vector @@ -446,8 +475,9 @@ grwl: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 path: grwl.gpkg + grwl_mask: data_type: RasterDataset driver: raster_tindex @@ -463,9 +493,10 @@ grwl_mask: paper_ref: Allen and Pavelsky (2018) source_license: CC BY 4.0 source_url: https://doi.org/10.5281/zenodo.1297434 - source_version: 1.01 + version: 1.01 nodata: 0 path: grwl_tindex.gpkg + gswo: data_type: RasterDataset driver: raster @@ -474,9 +505,10 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) source_url: https://global-surface-water.appspot.com/download - source_version: v1_1_2019 + version: v1_1_2019 nodata: 255 path: gswo.tif + gtsmv3_eu_era5: crs: 4326 data_type: GeoDataset @@ -487,8 +519,9 @@ gtsmv3_eu_era5: paper_ref: Copernicus Climate Change Service 2019 source_license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview - source_version: GTSM v3.0 + version: 3.0 path: gtsmv3_eu_era5.nc + guf_bld_2012: crs: 4326 data_type: RasterDataset @@ -500,6 +533,7 @@ guf_bld_2012: source_license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf source_url: http://www.dlr.de/guf path: guf_bld_2012.tif + hydro_lakes: crs: 4326 data_type: GeoDataFrame @@ -508,10 +542,11 @@ hydro_lakes: category: surface water source_author: Arjen Haag source_info: HydroLAKES.v10_extract - source_version: 1.0 + version: 1.0 path: hydro_lakes.gpkg unit_mult: Area_avg: 1000000.0 + hydro_reservoirs: crs: 4326 data_type: GeoDataFrame @@ -520,8 +555,8 @@ hydro_reservoirs: category: surface water source_author: Alessia Matano source_info: GRanD.v1.1_HydroLAKES.v10_JRC.2016 - source_version: 1.0 nodata: -99 + version: 1.0 path: hydro_reservoirs.gpkg unit_mult: Area_avg: 1000000.0 @@ -529,6 +564,7 @@ hydro_reservoirs: Capacity_min: 1000000.0 Capacity_norm: 1000000.0 Vol_avg: 1000000.0 + koppen_geiger: crs: 4326 data_type: RasterDataset @@ -538,9 +574,10 @@ koppen_geiger: paper_doi: 10.1127/0941-2948/2006/0130 paper_ref: Kottek et al. (2006) source_url: http://koeppen-geiger.vu-wien.ac.at/present.htm - source_version: 2017 nodata: 0 + version: 2017 path: koppen_geiger.tif + mdt_cnes_cls18: crs: 4326 data_type: RasterDataset @@ -550,9 +587,10 @@ mdt_cnes_cls18: paper_doi: 10.5194/os-17-789-2021 paper_ref: Mulet et al (2021) source_url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html - source_version: 18 unit: m+GOCO05S + version: 18 path: mdt_cnes_cls18.tif + merit_hydro: crs: 4326 data_type: RasterDataset @@ -563,8 +601,9 @@ merit_hydro: paper_ref: Yamazaki et al. (2019) source_license: CC-BY-NC 4.0 or ODbL 1.0 source_url: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro - source_version: 1.0 + version: 1.0 path: merit_hydro/{variable}.tif + merit_hydro_1k: crs: 4326 data_type: RasterDataset @@ -575,8 +614,9 @@ merit_hydro_1k: paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 source_url: https://doi.org/10.5281/zenodo.4138776 - source_version: 0.1 + version: 0.1 path: merit_hydro_1k/{variable}.tif + merit_hydro_index: crs: 4326 data_type: GeoDataFrame @@ -587,6 +627,7 @@ merit_hydro_index: paper_ref: Eilander et al. (in review) source_license: CC-BY-NC 4.0 path: merit_hydro_index.gpkg + modis_lai: crs: 4326 data_type: RasterDataset @@ -600,10 +641,11 @@ modis_lai: paper_ref: Myneni et al (2015) source_license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ source_url: https://lpdaac.usgs.gov/products/mcd15a3hv006/ - source_version: MCD15A3H V006 + version: 6 path: modis_lai.nc unit_mult: LAI: 0.1 + osm_coastlines: crs: 4326 data_type: GeoDataFrame @@ -614,8 +656,9 @@ osm_coastlines: source_info: OpenStreetMap coastlines water polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_coastlines.gpkg + osm_landareas: crs: 4326 data_type: GeoDataFrame @@ -626,8 +669,9 @@ osm_landareas: source_info: OpenStreetMap coastlines land polygons, last updated 2020-01-09T05:29 source_license: ODbL source_url: https://osmdata.openstreetmap.de/data/coastlines.html - source_version: 1.0 + version: 1.0 path: osm_landareas.gpkg + rgi: crs: 4326 data_type: GeoDataFrame @@ -639,9 +683,10 @@ rgi: source_info: Randolph Glacier Inventory source_license: CC BY 4.0 source_url: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-glaciers-extent?tab=overview - source_version: 6.0 + version: 6.0 path: rgi.gpkg -rivers_lin2019_v1: + +rivers_lin2019: data_type: GeoDataFrame driver: vector meta: @@ -650,8 +695,9 @@ rivers_lin2019_v1: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk - source_version: 1 + version: 1 path: rivers_lin2019_v1.gpkg + simard: crs: 4326 data_type: RasterDataset @@ -662,6 +708,7 @@ simard: paper_ref: Simard et al (2011) source_url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 path: simard.tif + soilgrids: crs: 4326 data_type: RasterDataset @@ -680,7 +727,7 @@ soilgrids: paper_ref: Hengl et al. (2017) source_license: ODbL source_url: https://www.isric.org/explore/soilgrids/faq-soilgrids-2017 - source_version: 2017 + version: 2017 path: soilgrids/{variable}.tif unit_mult: bd_sl1: 0.001 @@ -704,6 +751,7 @@ soilgrids: ph_sl5: 0.1 ph_sl6: 0.1 ph_sl7: 0.1 + vito: crs: 4326 data_type: RasterDataset @@ -713,8 +761,9 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) source_url: https://land.copernicus.eu/global/products/lc - source_version: v2.0.2 + version: 2.0.2 path: vito.tif + wb_countries: crs: 4326 data_type: GeoDataFrame @@ -726,6 +775,7 @@ wb_countries: source_url: https://datacatalog.worldbank.org/dataset/world-bank-official-boundaries timestamp: February 2020 path: wb_countries.gpkg + worldclim: crs: 4326 data_type: RasterDataset @@ -735,5 +785,5 @@ worldclim: paper_doi: 10.1002/joc.5086 paper_ref: Fick and Hijmans (2017) source_url: https://www.worldclim.org/data/worldclim21.html - source_version: 2 + version: 2 path: worldclim.nc diff --git a/data/catalogs/changelog.md b/data/catalogs/changelog.md deleted file mode 100644 index 4d8a39aea..000000000 --- a/data/catalogs/changelog.md +++ /dev/null @@ -1,148 +0,0 @@ -# Change log predefined datasets - -## deltares_data - -### version 2024.2 - -#### added -- version argument to data source where applicable -- variants argument for data sources that are of the same dataset but different versions -- processing_script / processing_notes arguments to data sources that have been (pre-) processed -- temporal extent of datasets that have a temporal dimension. -- spatial extents to datasets - -#### changed -- removed source_version from data source meta -- kwargs to driver_kwargs -- updated source_url if url was not working anymore -- sorted datasets by alphabetical order -- Removed version from dataset names -- prefixed 'hydro' where for all HydroSHEDS datasets -- added the epoch of the dataset to the name of the dataset - -See table below for mapping of old and new names: - -| Old name | New name | -|--------------------------------|---------------------------| -| basin_atlas_level12_v10 | hydro_basin_atlas_level12 | -| eobs_v.. | eobs | -| eobs_orography_v.. | eobs_orography | -| lake_atlas_pol_v10 | hydro_lake_atlas_pol | -| river_atlas_v10 | hydro_river_atlas | -| ghs_pop_2015_54009_v2019a | ghs_pop_2015 | -| ghs_smod_2015_54009_v2019a | ghs_smod_2015 | -| glofas_era5_v31 | glofas_era5 | -| guf_bld_2012 | guf_bld_2012 | -| rivers_lin2019_v1 | hydro_rivers_lin2019 | -| SM2RAIN_ASCAT_monthly_025_v1.4 | SM2RAIN_ASCAT_monthly_025 | -| SM2RAIN_ASCAT_monthly_05_v1.4 | SM2RAIN_ASCAT_monthly_05 | -| vito | vito_2015 | -| vito_2015_v2.0.2 | vito_2015 | -| vito_2016_v3.0.1 | vito_2016 | -| vito_2017_v3.0.1 | vito_2017 | -| vito_2018_v3.0.1 | vito_2018 | -| vito_2019_v3.0.1 | vito_2019 | -| esa_worldcover | esa_worldcover_2020 | -| corine | corine_2018 | -| globcover | globcover_2009 | - -- Some datasets have multiple versions, for these datasets the default can be changed if -you do not supply a version in your config file. See the table below for which dataset -the default version has changed. - -| Dataset name | Default version | Previous default version | -|----------------|-----------------|--------------------------| -| eobs | 25.0e | 22.0e | -| eobs_orography | 25.0e | 22.0e | - - -### version 2024.1.30 - -#### added -- HydroMT version to catalog -- GRDC dataset - - -### version: 2023.12 - -#### changed -- updated GADM dataset and converted the GeoPackage layers to FlatGeoBuf files -- removed gtsm_codec_reanalysis dataset - -#### added -- Added waterdemand pcr_globwb dataset -- Added GADM 4.1 as FlatGeoBuff files to deltares_data catalog (#686) - - -### version: 2023.2 - -#### changed -- convert GeoPackage files to FlatGeoBuf for cloud compatibility -- fix ERA5 nc files to read from archive of combined yearly and monthly files - -#### added -- Additional variables to era5 daily and hourly with name and unit conventions - - temp_dew: dewpoint temperature (degree C) - - wind10_u: 10m wind U-component (m s-1) - - wind10_v: 10m wind V-component (m s-1) - - ssr: surface net solar radiation (W m-2) - - tcc: total cloud cover (-) - - -### version: 2022.7 - -#### added - -- README with conventions regarding data (download, storage, .yml) -- change log file of deltares_data.yml -- new data sets - - basin_atlas_level12_v10 - - river_atlas_v10 - - lake_atlas_pol_v10 - - eobs_v24.0e - - eobs_v25.0e - - eobs_orography_v24.0e - - eobs_orography_v25.0e - - SM2RAIN_ASCAT_monthly_025_v1.4 - - SM2RAIN_ASCAT_monthly_05_v1.4 - -#### changed -- Apply convention specified in the README - - check reasonable alphabetical order in data sets and components - - implement right versioning convention _v where possible - - apply consistent meta information - -#### fixed -- enable versioning of yml.files - -## aws_data - -### version 0.0.9 - -#### changed -- updated source naming to match deltares_data version 2024.2 - -## cmip6_data - -### version: 2024.1.30 - -#### added -- hydromt_version to data catalog meta - - -### version: 2023.2 - -#### added -- CMIP6 data from Google Cloud Storage. Only models and scenarios for which regular grids are available are listed - -## aws_data - -### version: 2024.1.30 - -#### added -- HydroMT version to catalog - -### version: 2023.2 - -#### added -- ESA Worldcover v100 2020. diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index 88a1abcb9..a36601fab 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -42,7 +42,7 @@ changed - updated source_url if url was not working anymore - sorted datasets by alphabetical order - Removed version from dataset names -- prefixed 'hydro' where for all HydroSHEDS datasets +- prefixed 'hydro' for all HydroSHEDS datasets - added the epoch of the dataset to the name of the dataset See table below for mapping of old and new names: From 2ac6e7d60dcefbe5483d4d3980a06175772f5089 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Thu, 16 May 2024 11:02:44 +0200 Subject: [PATCH 087/110] updated registry for artifact_data --- data/catalogs/artifact_data/registry.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index 3ee7980c4..0001045bb 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,4 +1,4 @@ v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 v0.0.8/data_catalog.yml f332438ef26ede5a863674a4cd1e7fe0380a17a3f6ef57956cd7ba15a2fd5b04 -v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 +v0.0.9/data_catalog.yml c184cc98d63ff273b8ece4e9571c8dd5b15ee3bb8a8a12ebeacc4db186513c0a v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee From 7cfa04a21644d61df150266d251b3c8746392200 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Tue, 21 May 2024 11:58:10 +0200 Subject: [PATCH 088/110] Updated .gitattributes for working with yaml files on Windows (#930) --- .gitattributes | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitattributes b/.gitattributes index c6702ae45..756d5f840 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,4 +1,4 @@ -* text eol=lf +*.yaml text eol=lf # GitHub syntax highlighting pixi.lock linguist-language=YAML From ef8766a50b7f0f5b283854fa90951930f71e86bd Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:54:02 +0200 Subject: [PATCH 089/110] Update data/catalogs/artifact_data/v0.0.8/data_catalog.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/artifact_data/v0.0.8/data_catalog.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml index c0d27104e..a3f29c8c8 100644 --- a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml +++ b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml @@ -32,7 +32,7 @@ chirps_global: unit_add: time: 86400 -corine_2018: +corine: data_type: RasterDataset driver: raster meta: From 95d76b29ab0b8d3fe3e471f167e9ad4ebb8fdf46 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:54:25 +0200 Subject: [PATCH 090/110] Update data/catalogs/artifact_data/v0.0.8/data_catalog.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/artifact_data/v0.0.8/data_catalog.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml index a3f29c8c8..2a4bcc9af 100644 --- a/data/catalogs/artifact_data/v0.0.8/data_catalog.yml +++ b/data/catalogs/artifact_data/v0.0.8/data_catalog.yml @@ -329,7 +329,7 @@ ghs_pop_2015_54009: version: R2019A_v1.0 path: ghs_pop_2015_54009.tif -globcover_2009: +globcover: crs: 4326 data_type: RasterDataset driver: raster From fcce98027679e4ac4e87d40d54bcb6e3d4a719e2 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:55:06 +0200 Subject: [PATCH 091/110] Update data/catalogs/deltares_data/v0.7.0/data_catalog.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data/v0.7.0/data_catalog.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index 1799a7856..6715f3717 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -1615,7 +1615,7 @@ pcr_globwb: crs: 4326 data_type: RasterDataset driver: zarr - kwargs: + driver_kwargs: chunks: auto meta: category: water demand From 5ceb03daa21efb667523f00fd6e9215955e3f47c Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:55:48 +0200 Subject: [PATCH 092/110] Update data/catalogs/deltares_data/v0.7.0/data_catalog.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data/v0.7.0/data_catalog.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index 6715f3717..491daf205 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -1285,6 +1285,7 @@ hydro_reservoirs: meta: category: surface water notes: GRanD.v1.1_HydroLAKES.v10_JRC.2016 + processing_notes: combined not natural lakes from HydroLAKES v10 (Lake_type != 1) with reservoirs attributes from GRanD v1.1 source_author: Alessia Matano source_spatial_extent: West: -153.059 From b381e6794fba964d2f6a0a54ab8c13147cac9876 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:56:01 +0200 Subject: [PATCH 093/110] Update data/catalogs/deltares_data/v0.7.0/data_catalog.yml Co-authored-by: hboisgon <45457510+hboisgon@users.noreply.github.com> --- data/catalogs/deltares_data/v0.7.0/data_catalog.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index 491daf205..b1d3aa8a6 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -1700,7 +1700,7 @@ hydro_river_atlas: rename: dis_m3_pyr: Dis_avg -hydro_rivers_lin2019: +hydro_rivers_lin: data_type: GeoDataFrame driver: vector meta: From 9123922c16c1087b81ca8ea3c2f79f48c8669ae8 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong <93266159+Tjalling-dejong@users.noreply.github.com> Date: Wed, 22 May 2024 09:59:43 +0200 Subject: [PATCH 094/110] Update docs/user_guide/data_existing_cat.rst Co-authored-by: Sam Vente --- docs/user_guide/data_existing_cat.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/user_guide/data_existing_cat.rst b/docs/user_guide/data_existing_cat.rst index 73e6ac4f5..976beb8fc 100644 --- a/docs/user_guide/data_existing_cat.rst +++ b/docs/user_guide/data_existing_cat.rst @@ -66,7 +66,7 @@ catalog name. You can then get data from the catalog using the # specify a data catalog version data_catalog = DataCatalog(data_libs=["deltares_data=v2024.2"]) # get data from the catalog - ds = data_catalog.get_rasterdataset("eobs") # get the latest + ds = data_catalog.get_rasterdataset("eobs") # get the most recently added ds = data_catalog.get_rasterdataset("eobs", version="22.0e") # get a specific version From bc24b95cc89b38f0e774be0384c7c9fe7d036572 Mon Sep 17 00:00:00 2001 From: Tjalling de Jong Date: Wed, 22 May 2024 10:27:46 +0200 Subject: [PATCH 095/110] updated data catalogs with requested changes --- .../artifact_data/v0.0.9/data_catalog.yml | 43 ++++++++----------- data/catalogs/changelog.rst | 6 --- .../deltares_data/v0.7.0/data_catalog.yml | 6 +-- 3 files changed, 22 insertions(+), 33 deletions(-) diff --git a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml index d3879a9ac..f1e1a46f4 100644 --- a/data/catalogs/artifact_data/v0.0.9/data_catalog.yml +++ b/data/catalogs/artifact_data/v0.0.9/data_catalog.yml @@ -264,19 +264,27 @@ gebco: unit: m+MSL version: 2020 path: gebco.tif -ghs-smod_2015_v2: + +ghs_smod_2015: crs: ESRI:54009 data_type: RasterDataset driver: raster meta: category: socio economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - version: R2019A_v2.0 - path: ghs-smod_2015_v2.tif + variants: + - version: R2016A_v1.0 + path: ghs_smod_2015.tif + meta: + paper_ref: Pesaresi and Freire (2016) + source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + path: ghs-smod_2015_v2.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 ghs_pop_2015: crs: 4326 @@ -289,7 +297,6 @@ ghs_pop_2015: source_author: JRC-ISPRA EC source_license: https://data.jrc.ec.europa.eu/licence/com_reuse source_url: https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f - path: ghs_pop_2015.tif ghs_pop_2015_54009: @@ -305,20 +312,7 @@ ghs_pop_2015_54009: version: R2019A_v1.0 path: ghs_pop_2015_54009.tif -ghs_smod_2015: - crs: ESRI:54009 - data_type: RasterDataset - driver: raster - meta: - category: socio economic - paper_ref: Pesaresi and Freire (2016) - source_author: JRC-ISPRA EC - source_license: https://data.jrc.ec.europa.eu/licence/com_reuse - source_url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - version: R2016A_v1.0 - path: ghs_smod_2015.tif - -globcover: +globcover_2009: crs: 4326 data_type: RasterDataset driver: raster @@ -604,7 +598,7 @@ merit_hydro: version: 1.0 path: merit_hydro/{variable}.tif -merit_hydro_1k: +merit_hydro_ihu: crs: 4326 data_type: RasterDataset driver: raster @@ -686,7 +680,7 @@ rgi: version: 6.0 path: rgi.gpkg -rivers_lin2019: +hydro_rivers_lin: data_type: GeoDataFrame driver: vector meta: @@ -695,6 +689,7 @@ rivers_lin2019: paper_ref: Lin et al. (2019) source_license: CC-BY-NC 4.0 source_url: https://zenodo.org/record/3552776#.YVbOrppByUk + processing_notes: hydrography/rivers_lin2019/README version: 1 path: rivers_lin2019_v1.gpkg @@ -752,7 +747,7 @@ soilgrids: ph_sl6: 0.1 ph_sl7: 0.1 -vito: +vito_2015: crs: 4326 data_type: RasterDataset driver: raster diff --git a/data/catalogs/changelog.rst b/data/catalogs/changelog.rst index a36601fab..1e45b50cf 100644 --- a/data/catalogs/changelog.rst +++ b/data/catalogs/changelog.rst @@ -86,12 +86,6 @@ See table below for mapping of old and new names: +--------------------------------+---------------------------+ | vito_2019_v3.0.1 | vito_2019 | +--------------------------------+---------------------------+ -| esa_worldcover | esa_worldcover_2020 | -+--------------------------------+---------------------------+ -| corine | corine_2018 | -+--------------------------------+---------------------------+ -| globcover | globcover_2009 | -+--------------------------------+---------------------------+ - Some datasets have multiple versions, for these datasets the default can be changed if diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index b1d3aa8a6..bc2d973b8 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -179,7 +179,7 @@ copdem30_masked: rename: copdem_masked: elevtn -corine_2018: +corine: data_type: RasterDataset driver: raster driver_kwargs: @@ -596,7 +596,7 @@ era5_orography: unit_mult: elevtn: 0.10197162129779283 -esa_worldcover_2020: +esa_worldcover: crs: 4326 data_type: RasterDataset driver: raster @@ -869,7 +869,7 @@ ghs_smod_2015: paper_ref: Pesaresi et al (2019) source_url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 -globcover_2009: +globcover: crs: 4326 data_type: RasterDataset driver: raster From a2e31d1c7528627f44ecd14862bf21a1f0fddd54 Mon Sep 17 00:00:00 2001 From: Tjalling de Jong Date: Wed, 22 May 2024 10:30:08 +0200 Subject: [PATCH 096/110] updated data catalog registry files --- data/catalogs/artifact_data/registry.txt | 4 ++-- data/catalogs/deltares_data/registry.txt | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index 0001045bb..f1297045d 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,4 +1,4 @@ v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v0.0.8/data_catalog.yml f332438ef26ede5a863674a4cd1e7fe0380a17a3f6ef57956cd7ba15a2fd5b04 -v0.0.9/data_catalog.yml c184cc98d63ff273b8ece4e9571c8dd5b15ee3bb8a8a12ebeacc4db186513c0a v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee +v0.0.8/data_catalog.yml 0c1b3187cc51896232baebc63f6e1da0e07ffe81bf85aaf370fb0c7508c15ca5 +v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index bd416abad..dd9d1d5c8 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,3 +1,3 @@ -v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef -v0.7.0/data_catalog.yml 16f281de2cf269483bba60e8463ca4bcc9a90fdd20cef7a9ae35e7e453252dbf +v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 +v0.7.0/data_catalog.yml b80df56abcd56e697528664a379f3fe5e4419fbd81f756bb2489ebfaa62c9048 From 4b5029ed8d8714793001900fcccaeefd4ed78522 Mon Sep 17 00:00:00 2001 From: Tjalling de Jong Date: Wed, 22 May 2024 11:16:03 +0200 Subject: [PATCH 097/110] updated tests --- tests/test_model.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/tests/test_model.py b/tests/test_model.py index 975de27fc..4229da55b 100644 --- a/tests/test_model.py +++ b/tests/test_model.py @@ -142,7 +142,7 @@ def test_run_log_method(): def test_write_data_catalog(tmpdir): - model = Model(root=join(tmpdir, "model"), data_libs=["artifact_data"]) + model = Model(root=join(tmpdir, "model"), data_libs=["artifact_data=v0.0.7"]) sources = list(model.data_catalog.sources.keys()) data_lib_fn = join(model.root, "hydromt_data.yml") # used_only=True -> no file written @@ -157,7 +157,7 @@ def test_write_data_catalog(tmpdir): model.write_data_catalog(data_lib_fn=data_lib_fn1) assert isfile(data_lib_fn1) # append source - model1 = Model(root=model.root, data_libs=["artifact_data"], mode="r+") + model1 = Model(root=model.root, data_libs=["artifact_data=v0.0.7"], mode="r+") model1.data_catalog.get_source(sources[1]).mark_as_used() model1.write_data_catalog(append=False) assert list(DataCatalog(data_lib_fn).sources.keys()) == [sources[1]] @@ -425,9 +425,9 @@ def test_maps_setup(tmpdir): variables=["elevtn", "flwdir"], split_dataset=False, ) - mod.setup_maps_from_rasterdataset(raster_fn="vito", fill_method="nearest") + mod.setup_maps_from_rasterdataset(raster_fn="vito_2015", fill_method="nearest") mod.setup_maps_from_raster_reclass( - raster_fn="vito", + raster_fn="vito_2015", reclass_table_fn="vito_mapping", reclass_variables=["roughness_manning"], split_dataset=True, @@ -595,13 +595,13 @@ def test_gridmodel_setup(tmpdir): mask_name="mask", ) mod.setup_grid_from_rasterdataset( - raster_fn="vito", + raster_fn="vito_2015", fill_method="nearest", reproject_method="mode", rename={"vito": "landuse"}, ) mod.setup_grid_from_raster_reclass( - raster_fn="vito", + raster_fn="vito_2015", fill_method="nearest", reclass_table_fn="vito_mapping", reclass_variables=["roughness_manning"], @@ -830,11 +830,11 @@ def test_meshmodel_setup(griduda, world): mod1 = MeshModel(data_libs=["artifact_data", dc_param_fn]) mod1.setup_mesh2d(region, grid_name="mesh2d") mod1.setup_mesh2d_from_rasterdataset( - "vito", grid_name="mesh2d", resampling_method="mode" + "vito_2015", grid_name="mesh2d", resampling_method="mode" ) assert "vito" in mod1.mesh.data_vars mod1.setup_mesh2d_from_raster_reclass( - raster_fn="vito", + raster_fn="vito_2015", reclass_table_fn="vito_mapping", reclass_variables=["landuse", "roughness_manning"], resampling_method=["mode", "centroid"], From c6682fcd9b0d9793f7be7833003e4481c64d9754 Mon Sep 17 00:00:00 2001 From: Tjalling de Jong Date: Wed, 22 May 2024 11:26:30 +0200 Subject: [PATCH 098/110] updated docs --- docs/user_guide/data_existing_cat.rst | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/docs/user_guide/data_existing_cat.rst b/docs/user_guide/data_existing_cat.rst index 976beb8fc..80dc4f889 100644 --- a/docs/user_guide/data_existing_cat.rst +++ b/docs/user_guide/data_existing_cat.rst @@ -21,20 +21,27 @@ Using a predefined catalog From CLI ~~~~~~~~ -To use a predefined catalog, you can specify the catalog name with the ``--dd`` or ``--data_catalog`` option when running a HydroMT command. +To use a predefined catalog, you can specify the catalog name with the ``-d`` or ``--data`` option when running a HydroMT command. For example, to use the ``deltares_data`` catalog with the `hydromt build` command, you can run the following: .. code-block:: bash - hydromt build MODEL --dd deltares_data ... + hydromt build MODEL -d deltares_data ... + +Alternatively, deltares_data can also be accessed with the ``--dd`` option: + +.. code-block:: bash + + hydromt build MODEL --dd ... + You can specify a version of the catalog by adding the version number after the catalog name, e.g. ``deltares_data=2024.2``. .. code-block:: bash - hydromt build MODEL --dd deltares_data=2024.2 ... + hydromt build MODEL -d deltares_data=2024.2 ... -Once you have set the data catalog you can specify the datat source(s) for each method in the HydroMT +Once you have set the data catalog you can specify the data source(s) for each method in the HydroMT :ref:`model configuration file ` as shown in the example below with the `setup_precip_forcing` method. .. code-block:: yaml From 658013cc37b367974bcc3174d143a67f7d18c50c Mon Sep 17 00:00:00 2001 From: Tjalling de Jong Date: Thu, 23 May 2024 11:07:20 +0200 Subject: [PATCH 099/110] changed .yaml to .yml --- .gitattributes | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitattributes b/.gitattributes index 756d5f840..7ca1aab87 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,4 +1,4 @@ -*.yaml text eol=lf +*.yml text eol=lf # GitHub syntax highlighting pixi.lock linguist-language=YAML From 3ac134c21c2855d1abb5da25f0ce9f0d86be97a1 Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 13:31:59 +0200 Subject: [PATCH 100/110] restored plugins.py --- hydromt/plugins.py | 249 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 249 insertions(+) create mode 100644 hydromt/plugins.py diff --git a/hydromt/plugins.py b/hydromt/plugins.py new file mode 100644 index 000000000..36ac4bc36 --- /dev/null +++ b/hydromt/plugins.py @@ -0,0 +1,249 @@ +"""Implementation of the mechanism to access the plugin entrypoints.""" + +import inspect +from abc import abstractmethod +from importlib import import_module +from typing import TYPE_CHECKING, ClassVar, Dict, Optional, Type, TypedDict, cast + +from importlib_metadata import entry_points + +if TYPE_CHECKING: + from hydromt.data_catalog.drivers import BaseDriver + from hydromt.data_catalog.predefined_catalog import PredefinedCatalog + from hydromt.model import Model + from hydromt.model.components import ModelComponent + +__all__ = ["PLUGINS"] + +Plugin = TypedDict( + "Plugin", {"type": Type, "name": str, "plugin_name": str, "version": str} +) + + +def _format_metadata(metadata: Dict[str, str]) -> str: + return "{name} ({plugin_name} {version})".format( + name=metadata["name"], + plugin_name=metadata["plugin_name"], + version=metadata["version"], + ) + + +class PluginGroup: + group: ClassVar[str] = None + base_module: ClassVar[str] = None + base_class: ClassVar[str] = None + + def __init__(self) -> None: + self._plugins: Optional[Dict[str, Plugin]] = None + + def _initialize_plugins(self) -> None: + # load the base class to check for subclasses + # not pretty, but we import dynamically to avoid circular imports + mod = import_module(self.base_module) + base_class = getattr(mod, self.base_class) + + plugins: Dict[str, Plugin] = {} + eps = entry_points(group=self.group) + for ep in eps: + module = ep.load() + hydromt_eps = getattr(module, "__hydromt_eps__", None) + ep_name = getattr(ep, "name", None) # this cannot be mocked? + if hydromt_eps is None or not isinstance(hydromt_eps, list): + raise ValueError( + f"{self.group} plugin {ep_name} ({ep.dist.name}) does not define __hydromt_eps__ list attribute" + ) + for attr_name in hydromt_eps: + attr = getattr(module, attr_name, None) + # check if the attribute is a subclass of the expected type and not an ABCs from core + if ( + not inspect.isclass(attr) + or inspect.isabstract(attr) + or not issubclass(attr, base_class) + ): + raise ValueError( + f"{self.group} plugin {ep_name} {attr_name} ({ep.dist.name}) is not a valid {self.base_class}" + ) + name = getattr(attr, "name", attr_name) + if name not in plugins: + # other than type, this is for display only, hence string + plugins[name] = { + "type": attr, + "name": name, + "plugin_name": str(ep.dist.name), + "version": str(ep.dist.version), + } + else: + raise ValueError(f"Conflicting definitions for {self.group} {name}") + + # we should have at least one plugin from core + if not plugins: + raise RuntimeError(f"Could not load any {self.group} plugins") + + self._plugins = plugins + + @property + @abstractmethod + def plugins(self) -> dict[str, Type]: + pass + + @property + def metadata(self) -> Dict[str, Dict[str, str]]: + if self._plugins is None: + self._initialize_plugins() + + return cast( + Dict[str, Dict[str, str]], + {k: v for k, v in self._plugins.items() if isinstance(k, str)}, + ) + + def summary(self) -> str: + name = self.group.split(".")[-1][:-1].capitalize() + s = "" + for metadata in self.metadata.values(): + s += f"\n\t- {_format_metadata(metadata)}" + plugins = "\n\t- ".join(map(_format_metadata, self.metadata.values())) + return f"{name} plugins:\n\t- {plugins}" + + +class ComponentPlugins(PluginGroup): + group = "hydromt.components" + base_module = "hydromt.model.components" + base_class = "ModelComponent" + + @property + def plugins(self) -> dict[str, Type["ModelComponent"]]: + if self._plugins is None: + self._initialize_plugins() + + return cast( + Dict[str, Type["ModelComponent"]], + {name: value["type"] for name, value in self._plugins.items()}, + ) + + +class DriverPlugins(PluginGroup): + group = "hydromt.drivers" + base_module = "hydromt.data_catalog.drivers" + base_class = "BaseDriver" + + @property + def plugins(self) -> dict[str, Type["BaseDriver"]]: + if self._plugins is None: + self._initialize_plugins() + + return cast( + Dict[str, Type["BaseDriver"]], + {name: value["type"] for name, value in self._plugins.items()}, + ) + + +class ModelPlugins(PluginGroup): + group = "hydromt.models" + base_module = "hydromt.model.model" + base_class = "Model" + + @property + def plugins(self) -> dict[str, Type["Model"]]: + if self._plugins is None: + self._initialize_plugins() + + return cast( + Dict[str, Type["Model"]], + {name: value["type"] for name, value in self._plugins.items()}, + ) + + +class CatalogPlugins(PluginGroup): + group = "hydromt.catalogs" + base_module = "hydromt.data_catalog.predefined_catalog" + base_class = "PredefinedCatalog" + + @property + def plugins(self) -> dict[str, Type["PredefinedCatalog"]]: + if self._plugins is None: + self._initialize_plugins() + + return cast( + Dict[str, Type["PredefinedCatalog"]], + {name: value["type"] for name, value in self._plugins.items()}, + ) + + +class Plugins: + """The model catalogue provides access to plugins.""" + + def __init__(self) -> None: + """Initiate the catalog object.""" + self._component_plugins: ComponentPlugins = ComponentPlugins() + self._driver_plugins: DriverPlugins = DriverPlugins() + self._model_plugins: ModelPlugins = ModelPlugins() + self._catalog_plugins: CatalogPlugins = CatalogPlugins() + + @property + def component_plugins(self) -> dict[str, type["ModelComponent"]]: + """Load and provide access to all known model component plugins.""" + return self._component_plugins.plugins + + @property + def driver_plugins(self) -> dict[str, Type["BaseDriver"]]: + """Load and provide access to all known driver plugins.""" + return self._driver_plugins.plugins + + @property + def model_plugins(self) -> dict[str, type["Model"]]: + """Load and provide access to all known model plugins.""" + return self._model_plugins.plugins + + @property + def catalog_plugins(self) -> dict[str, Type["PredefinedCatalog"]]: + """Load and provide access to all known catalog plugins.""" + return self._catalog_plugins.plugins + + @property + def model_metadata(self) -> Dict[str, Dict[str, str]]: + """Load and provide access to all known model plugins.""" + return self._model_plugins.metadata + + @property + def component_metadata(self) -> Dict[str, Dict[str, str]]: + """Load and provide access to all known model component plugins.""" + return self._component_plugins.metadata + + @property + def driver_metadata(self) -> Dict[str, Dict[str, str]]: + """Load and provide access to all known driver plugin metadata.""" + return self._driver_plugins.metadata + + @property + def catalog_metadata(self) -> Dict[str, Dict[str, str]]: + """Load and provide access to all known catalog plugin metadata.""" + return self._catalog_plugins.metadata + + def model_summary(self) -> str: + """Generate string representation containing the registered model entrypoints.""" + return self._model_plugins.summary() + + def driver_summary(self) -> str: + """Generate string representation container the registered driver entrypoints.""" + return self._driver_plugins.summary() + + def component_summary(self) -> str: + """Generate string representation containing the registered model component entrypoints.""" + return self._component_plugins.summary() + + def catalog_summary(self) -> str: + """Generate string representation containing the registered catalog entrypoints.""" + return self._catalog_plugins.summary() + + def plugin_summary(self) -> str: + return "\n".join( + [ + self.model_summary(), + self.component_summary(), + self.driver_summary(), + self.catalog_summary(), + ] + ) + + +PLUGINS = Plugins() From e454b820ca867f38d978090ac698a27c042743fc Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 13:43:45 +0200 Subject: [PATCH 101/110] updated registry.txt for data catalogs --- data/catalogs/artifact_data/registry.txt | 6 +++--- data/catalogs/deltares_data/registry.txt | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index 35d26228f..0eb2d586a 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,5 +1,5 @@ +v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v0.0.7/data_catalog.yml 8c4aa8e5bc28fd9a6d25b93d73dc091dd9aa6beec3de48dc2a56b57aafe415ee -v0.0.8/data_catalog.yml c1cf2229eeb93607ea881fdbced45ebf43471271f0b7d878db8183734274cd88 -v0.0.9/data_catalog.yml a074379f3ef244f3a860ec40165163538b6d690d8a3cbc8c6e883e02a8936258 v1.0.0/data_catalog.yml e422a0f4a32998d96186f2197068a2d9daf7409192a6db63a2211142c9b0b4ad +v0.0.8/data_catalog.yml 3092305249af479061938ca484fe0245731174f072325740e9a85d1e986f8efc +v0.0.7/data_catalog.yml 8daccd1b551b3bafdb95b5ddc4b8dddafd6f25070ad9c543e3c0027bb55bc16e diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index a607c8243..09d98b151 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,4 +1,4 @@ -v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 -v0.7.0/data_catalog.yml e3acaf4634a0302045d8b7249c27ba560b48050b13d268603bd1b3fe6006ce05 +v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef v1.0.0/data_catalog.yml aa6426be88c16e5dd88f032bcec1cb69b59a3e3eaae4a2afacaf5d9d7cfd0f02 +v0.7.0/data_catalog.yml fbcb24b3e994e20430c30e8246b17a1bb7fd06a2b3a4e756e75afa4275d94ea5 From ccadb919f513bffb86f0c525e3d6f7572ab2a6be Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 15:52:16 +0200 Subject: [PATCH 102/110] updated deltares_data --- .../deltares_data/v0.7.0/data_catalog.yml | 8 +- .../deltares_data/v1.0.0/data_catalog.yml | 1049 +++++++++++------ 2 files changed, 683 insertions(+), 374 deletions(-) diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index 2605a8154..4e38c27d6 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -1751,10 +1751,10 @@ soilgrids: processing_notes: "soilthickness is based on 1) soilgrids (global, depth to bedrock - BDRICM variable) and 2) dataset for Eurasia" processing_script: p:/wflow_global/static_data/wflow_sbm_parameters/ source_spatial_extent: - West: -19949000.0 - South: -6147500.0 - East: 19861750.0 - North: 8361000.0 + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 version: 1.0 path: soil/soilgrids_v1.0/*_250m_ll.tif rename: diff --git a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml index 472f9b369..487965c63 100644 --- a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml @@ -3,58 +3,8 @@ meta: version: v1.0.0 name: deltares_data hydromt_version: '>1.0a,<2' -basin_atlas_level12_v10: - data_type: GeoDataFrame - uri: hydrography/hydro_atlas/basin_atlas_v10.gpkg - driver: - name: pyogrio - options: - layer: BasinATLAS_v10_lev12 - metadata: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - url: https://www.hydrosheds.org/hydroatlas - version: 10 - license: CC BY 4.0 - crs: 4326 -river_atlas_v10: - data_type: GeoDataFrame - uri: hydrography/hydro_atlas/river_atlas_v10.gpkg - driver: - name: pyogrio - metadata: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-019-0300-6 - paper_ref: Linke et al. (2019) - url: https://www.hydrosheds.org/hydroatlas - version: 10 - license: CC BY 4.0 - crs: 4326 - data_adapter: - rename: - dis_m3_pyr: Dis_avg -lake_atlas_pol_v10: - data_type: GeoDataFrame - uri: hydrography/hydro_atlas/lake_atlas_v10.gpkg - driver: - name: pyogrio - options: - layer: LakeATLAS_v10_pol - metadata: - category: hydrography - notes: renaming and units might require some revision - paper_doi: 10.1038/s41597-022-01425-z - paper_ref: Lehner et al. (2022) - url: https://www.hydrosheds.org/hydroatlas - version: 10 - license: CC BY 4.0 - crs: 4326 - data_adapter: - rename: - dis_m3_pyr: Dis_avg + + chelsa: data_type: RasterDataset uri: meteo/chelsa_clim_v1.2/CHELSA_bio10_12.tif @@ -67,11 +17,17 @@ chelsa: metadata: category: meteo paper_doi: 10.1038/sdata.2017.122 + crs: 4326 + version: 1.2 paper_ref: Karger et al. (2017) url: http://chelsa-climate.org/downloads/ - version: 1.2 license: CC BY 4.0 - crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 84.0 + chirps: data_type: RasterDataset uri: meteo/chirps_africa_daily_v2.0/CHIRPS_rainfall_{year}.nc @@ -87,17 +43,26 @@ chirps: parallel: true metadata: category: meteo + crs: 4326 + version: v2.0 paper_doi: 10.1038/sdata.2015.66 paper_ref: Funk et al (2015) url: https://www.chc.ucsb.edu/data/chirps - version: v2.0 license: CC - crs: 4326 + temporal_extent: + start: '1981-01-02' + end: '2022-04-01' + spatial_extent: + West: -20.0 + South: -40.0 + East: 55.0 + North: 40.0 data_adapter: unit_add: time: 86400 rename: precipitation: precip + chirps_global: data_type: RasterDataset uri: meteo/chirps_global_daily_v2.0/chirps-v2.0.{year}.days_p05.nc @@ -112,18 +77,27 @@ chirps_global: decode_times: true parallel: true metadata: + crs: 4326 + version: v2.0 category: meteo paper_doi: 10.3133/ds832 paper_ref: Funk et al (2014) url: https://www.chc.ucsb.edu/data/chirps - version: v2.0 license: CC - crs: 4326 + temporal_extent: + start: '1981-01-02' + end: '2023-02-01' + spatial_extent: + West: -180.0 + South: -50.0 + East: 180.0 + North: 50.0 data_adapter: unit_add: time: 86400 rename: precipitation: precip + copdem30: data_type: RasterDataset uri: topography/copdem/copdem.vrt @@ -136,12 +110,18 @@ copdem30: metadata: category: topography url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - version: '2021_1' license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + version: 2021.1 nodata: -9999 + spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 data_adapter: rename: copdem: elevtn + copdem30_mask: data_type: RasterDataset uri: topography/copdem/copdem_mask.vrt @@ -154,12 +134,18 @@ copdem30_mask: metadata: category: topography url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - version: '2021_1' + version: 2021.1 license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 nodata: -1 + spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 data_adapter: rename: copdem_mask: mask + copdem30_masked: data_type: RasterDataset uri: topography/copdem/copdem_masked.vrt @@ -172,11 +158,17 @@ copdem30_masked: metadata: category: topography url: https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198#D4 - version: '2021_1' + version: 2021.1 license: https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex+%281%29.pdf/83b44c0a-244a-7ba3-b00c-b578a34e88a7?t=1604070311399 + spatial_extent: + West: -180.001 + South: -90.0 + East: 180.0 + North: 84.0 data_adapter: rename: copdem_masked: elevtn + corine: data_type: RasterDataset uri: landuse/corine/CLC2018_CLC2018_V2018_20.tif @@ -192,6 +184,12 @@ corine: author: European Environment Agency version: v.2020_20u1 license: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=metadata + spatial_extent: + West: 900000.0 + South: 900000.0 + East: 7400000.0 + North: 5500000.0 + dtu10mdt: data_type: RasterDataset uri: topography/dtu10mdt/DTU10MDT_1min_float32.tif @@ -209,6 +207,12 @@ dtu10mdt: url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography version: 2010 crs: 4326 + spatial_extent: + West: -179.992 + South: -89.992 + East: 179.992 + North: 89.992 + dtu10mdt_egm96: data_type: RasterDataset uri: topography/dtu10mdt/DTU10MDT_1min_egm96.tif @@ -226,6 +230,12 @@ dtu10mdt_egm96: url: https://www.space.dtu.dk/english/research/scientific_data_and_models/global_mean_dynamic_topography version: 2010 crs: 4326 + spatial_extent: + West: -179.992 + South: -89.985 + East: 179.995 + North: 89.992 + eobs: data_type: RasterDataset uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc @@ -247,6 +257,14 @@ eobs: version: 22.0e license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles crs: 4326 + temporal_extent: + start: '1950-01-02' + end: '2022-01-01' + spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 data_adapter: unit_add: time: 86400 @@ -255,123 +273,44 @@ eobs: qq: kin rr: precip tg: temp -eobs_v23.1e: - data_type: RasterDataset - uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 23.1e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - unit_add: - time: 86400 - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp -eobs_v24.0e: - data_type: RasterDataset - uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 24.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - unit_add: - time: 86400 - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp -eobs_v25.0e: - data_type: RasterDataset - uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 25.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - unit_add: - time: 86400 - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp -eobs_v29.0e: - data_type: RasterDataset - uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - time: 100 - combine: by_coords - parallel: true - preprocess: round_latlon - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 29.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - unit_add: - time: 86400 - rename: - pp: press_msl - qq: kin - rr: precip - tg: temp -eobs_orography_v20.0e: + variants: + - version: 22.0e + uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc + meta: + temporal_extent: + start: '1950-01-02' + end: '2020-07-01' + - version: 23.1e + uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc + meta: + temporal_extent: + start: '1950-01-02' + end: '2021-01-01' + - version: 24.0e + uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc + meta: + processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + temporal_extent: + start: '1950-01-02' + end: '2021-07-01' + - version: 25.0e + uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc + meta: + processing_script: v25.0e_fix_qq_dims_and_match_extent.py + processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables + temporal_extent: + start: '1950-01-02' + end: '2022-01-01' + - version: 29.0e + uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc + meta: + processing_script: meteo/eobs/scripts/v29.0e_fix_qq_dims_and_match_extent.py + temporal_extent: + start: '1950-01-01' + end: '2024-02-01' + +eobs_orography: data_type: RasterDataset uri: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc driver: @@ -388,109 +327,30 @@ eobs_orography_v20.0e: version: 20.0e license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles crs: 4326 + spatial_extent: + West: -25.0 + South: 25.0 + East: 45.5 + North: 71.5 data_adapter: rename: elevation: elevtn -eobs_orography: - data_type: RasterDataset - uri: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 22.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - rename: - elevation: elevtn -eobs_orography_v23.1e: - data_type: RasterDataset - uri: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 23.1e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - rename: - elevation: elevtn -eobs_orography_v24.0e: - data_type: RasterDataset - uri: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 24.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - rename: - elevation: elevtn -eobs_orography_v25.0e: - data_type: RasterDataset - uri: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 25.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - rename: - elevation: elevtn -eobs_orography_v29.0e: - data_type: RasterDataset - uri: meteo/eobs/elev_ens_0.1deg_reg_v29.0e.nc - driver: - name: raster_xarray - options: - chunks: - latitude: 100 - longitude: 100 - metadata: - category: meteo - paper_doi: 10.1029/2017JD028200 - paper_ref: Cornes et al (2018) - url: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - version: 29.0e - license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles - crs: 4326 - data_adapter: - rename: - elevation: elevtn + variants: + - version: 20.0e + uri: meteo/eobs/elev_ens_0.1deg_reg_v20.0e.nc + - version: 22.0e + uri: meteo/eobs/elev_ens_0.1deg_reg_v22.0e.nc + - version: 23.1e + uri: meteo/eobs/elev_ens_0.1deg_reg_v23.1e.nc + - version: 24.0e + uri: meteo/eobs/elev_ens_0.1deg_reg_v24.0e.nc + - version: 25.0e + uri: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc + - version: 29.0e + uri: meteo/eobs/elev_ens_0.1deg_reg_v29.0e.nc + rename: + elevation: elevtn + era5: data_type: RasterDataset variants: @@ -522,6 +382,14 @@ era5: version: ERA5 daily data on pressure levels license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products crs: 4326 + temporal_extent: + start: '1950-01-02' + end: '2023-11-30' + spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 data_adapter: unit_add: temp: -273.15 @@ -544,6 +412,7 @@ era5: tp: precip u10: wind10_u v10: wind10_v + era5_hourly: data_type: RasterDataset variants: @@ -574,6 +443,14 @@ era5_hourly: version: ERA5 hourly data on single levels from 1940 to present license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products crs: 4326 + temporal_extent: + start: '1950-01-01' + end: '2023-03-01' + spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 data_adapter: unit_add: temp: -273.15 @@ -593,6 +470,7 @@ era5_hourly: tp: precip u10: wind10_u v10: wind10_v + era5_ocean: data_type: RasterDataset uri: ocean/era5/{variable}/era5_{variable}_{year}_hourly.nc @@ -614,6 +492,15 @@ era5_ocean: url: https://doi.org/10.24381/cds.bd0915c6 license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products crs: 4326 + temporal_extent: + start: '1979-01-01' + end: '2022-04-08' + spatial_extent: + West: -0.25 + South: -90.25 + East: 359.75 + North: 90.25 + era5_orography: data_type: RasterDataset uri: meteo/era5/meta/era5_orography_2018.nc @@ -631,11 +518,20 @@ era5_orography: url: https://apps.ecmwf.int/codes/grib/param-db?id=129 license: https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products crs: 4326 + temporal_extent: + start: '2018-01-01' + end: '2018-01-01' + spatial_extent: + West: -0.125 + South: -90.125 + East: 359.875 + North: 90.125 data_adapter: unit_mult: elevtn: 0.10197162129779283 rename: z: elevtn + esa_worldcover: data_type: RasterDataset uri: landuse/esa_worldcover/esa-worldcover.vrt @@ -647,10 +543,20 @@ esa_worldcover: y: 36000 metadata: category: landuse + processing_notes: prepare vrt file with gdalbuildvrt url: https://doi.org/10.5281/zenodo.5571936 version: v100 license: CC BY 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 84.0 + temporal_extent: + start: '2020-01-01' + end: '2020-12-31' + fabdem: data_type: RasterDataset uri: topography/fabdem/fabdem.vrt @@ -668,6 +574,11 @@ fabdem: version: 1.0 license: CC BY-NC-SA 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 data_adapter: rename: fabdem: elevtn @@ -685,6 +596,12 @@ gadm: version: 4.1 license: https://gadm.org/license.html crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + gadm_level1: data_type: GeoDataFrame uri: geography/gadm/version4_1/gadm_level1.fgb @@ -699,6 +616,12 @@ gadm_level1: version: 4.1 license: https://gadm.org/license.html crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + gadm_level2: data_type: GeoDataFrame uri: geography/gadm/version4_1/gadm_level2.fgb @@ -713,6 +636,12 @@ gadm_level2: version: 4.1 license: https://gadm.org/license.html crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + gadm_level3: data_type: GeoDataFrame uri: geography/gadm/version4_1/gadm_level3.fgb @@ -727,6 +656,12 @@ gadm_level3: version: 4.1 license: https://gadm.org/license.html crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.658 + gcn250: data_type: RasterDataset uri: landuse/gcn250/GCN250_*.tif @@ -744,11 +679,17 @@ gcn250: version: v1 license: CC BY 4.0 nodata: 255 + spatial_extent: + West: -180.0 + South: -56.0 + East: 180.0 + North: 84.0 data_adapter: rename: GCN250_ARCI: cn_dry GCN250_ARCII: cn_avg GCN250_ARCIII: cn_wet + gdp_world: data_type: GeoDataFrame uri: socio_economic/gdp_world/World_countries_GDPpcPPP.fgb @@ -756,17 +697,23 @@ gdp_world: name: pyogrio metadata: category: socio-economic - notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) + processing_notes: data combined from World Bank (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD) and CIA World Factbook (https://www.cia.gov/the-world-factbook/field/real-gdp-per-capita/country-comparison) author: Wilfred Altena version: 1.0 license: CC BY-4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.665 data_adapter: unit_mult: gdp: 0.001 rename: GDP: gdp + gebco: data_type: RasterDataset uri: bathymetry/gebco/gebco.vrt @@ -785,10 +732,17 @@ gebco: version: 2020 license: https://www.gebco.net/data_and_products/gridded_bathymetry_data/#a1 crs: 4326 + processing_script: bathymetry/gebco/gebco_tiles.ipynb + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 data_adapter: rename: gebco: elevtn -ghs_pop: + +ghs_pop_2015: data_type: RasterDataset uri: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_4326_9ss_V1_0.tif driver: @@ -806,7 +760,13 @@ ghs_pop: version: R2019A_v1.0 license: https://data.jrc.ec.europa.eu/licence/com_reuse crs: 4326 -ghs_pop_2015_54009_v2019a: + spatial_extent: + West: -180.0 + South: -59.485 + East: 180.0 + North: 83.628 + +ghs_pop_2015_54009: data_type: RasterDataset uri: socio_economic/ghs/GHS_POP_E2015_GLOBE_R2019A_54009_250_V1_0.tif driver: @@ -822,7 +782,13 @@ ghs_pop_2015_54009_v2019a: url: https://ghsl.jrc.ec.europa.eu/download.php?ds=pop license: CC BY 4.0 crs: ESRI:54009 -ghs_smod: + spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 + +ghs_smod_2015: data_type: RasterDataset uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif driver: @@ -839,24 +805,24 @@ ghs_smod: version: R2016A_v1.0 license: https://data.jrc.ec.europa.eu/licence/com_reuse crs: ESRI:54009 -ghs_smod_2015_54009_v2019a: - data_type: RasterDataset - uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif - driver: - name: rasterio - options: - chunks: - x: 3600 - y: 3600 - metadata: - category: socio-economic - paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 - paper_ref: Pesaresi et al (2019) - url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 - author: JRC-ISPRA EC - version: R2019A_v2.0 - license: https://data.jrc.ec.europa.eu/licence/com_reuse - crs: ESRI:54009 + spatial_extent: + West: -18041000.0 + South: -9000000.0 + East: 18041000.0 + North: 9000000.0 + variants: + - version: R2016A_v1.0 + uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif + meta: + paper_ref: Pesaresi and Freire (2016) + url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a + - version: R2019A_v2.0 + uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif + meta: + paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 + paper_ref: Pesaresi et al (2019) + url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 + globcover: data_type: RasterDataset uri: landuse/globcover/GLOBCOVER_L4_200901_200912_V2.3.tif @@ -874,7 +840,13 @@ globcover: version: v2.3 license: CC-BY-3.0 crs: 4326 -glofas_era5_v31: + spatial_extent: + West: -180.001 + South: -64.999 + East: 179.999 + North: 90.001 + +glofas_era5: data_type: RasterDataset variants: - provider: normal @@ -914,6 +886,16 @@ glofas_era5_v31: version: v31 license: https://cds.climate.copernicus.eu/api/v2/terms/static/cems-floods.pdf crs: 4326 + processing_script: hydro/glofas_era5/glofas_cds_get.py + temporal_extent: + start: '1980-01-01' + end: '2021-05-31' + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 90.0 + glw_buffaloes: data_type: RasterDataset uri: socio_economic/glw/5_Bf_2010_Da.tif @@ -929,9 +911,16 @@ glw_buffaloes: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_cattle: data_type: RasterDataset uri: socio_economic/glw/5_Ct_2010_Da.tif @@ -947,9 +936,16 @@ glw_cattle: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes : last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_chicken: data_type: RasterDataset uri: socio_economic/glw/5_Ch_2010_Da.tif @@ -965,9 +961,16 @@ glw_chicken: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_ducks: data_type: RasterDataset uri: socio_economic/glw/5_Dk_2010_Da.tif @@ -983,9 +986,16 @@ glw_ducks: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_goats: data_type: RasterDataset uri: socio_economic/glw/5_Gt_2010_Da.tif @@ -1001,9 +1011,16 @@ glw_goats: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_horses: data_type: RasterDataset uri: socio_economic/glw/5_Ho_2010_Da.tif @@ -1019,9 +1036,16 @@ glw_horses: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_pigs: data_type: RasterDataset uri: socio_economic/glw/5_Pg_2010_Da.tif @@ -1037,9 +1061,16 @@ glw_pigs: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + glw_sheeps: data_type: RasterDataset uri: socio_economic/glw/5_Sh_2010_Da.tif @@ -1055,9 +1086,16 @@ glw_sheeps: paper_ref: Gilbert at al (2018) url: https://dataverse.harvard.edu/dataverse/glw_3 author: glw (Gridded Livestock of World 3 Dataverse) - version: GLW 3, last downloaded 2020-06-11 + notes: last downloaded 2020-06-11 + version: 3 license: CC 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + grdc: data_type: GeoDataFrame uri: hydro/grdc/GRDC_Stations.csv @@ -1074,6 +1112,7 @@ grdc: data_adapter: rename: area: uparea + grip_roads: data_type: GeoDataFrame uri: infrastructure/grip/GRIP4_world.fgb @@ -1087,10 +1126,17 @@ grip_roads: version: v4 license: CC0-1.0 crs: 4326 + processing_script: infrastructure/grip/merge.ipynb + spatial_extent: + West: -179.999 + South: -55.055 + East: 180.0 + North: 73.836 data_adapter: rename: GP_RTP: road_type GP_RCY: country_code + grwl: data_type: GeoDataFrame uri: hydrography/grwl/GRWL_vector_V01.01/grwl.fgb @@ -1103,6 +1149,12 @@ grwl: url: https://doi.org/10.5281/zenodo.1297434 version: 1.01 license: CC BY 4.0 + spatial_extent: + West: -180.0 + South: -54.31 + East: 180.0 + North: 82.311 + grwl_mask: data_type: RasterDataset uri: hydrography/grwl/tindex.gpkg @@ -1137,35 +1189,14 @@ gswo: paper_doi: 10.1038/nature20584 paper_ref: Pekel et al. (2016) url: https://global-surface-water.appspot.com/download - version: v1_1_2019 + version: 1.1 nodata: 255 -gtsm_codec_reanalysis_{freq}_v1: - data_type: GeoDataset - placeholders: - freq: - - 10min - - hourly - - dailymax - uri: p:/11205028-c3s_435/01_data/01_Timeseries/timeseries2/{variable}/reanalysis_{variable}_{freq}_{year}_{month:02d}_v1.nc - driver: - name: geodataset_xarray - options: - chunks: - stations: 10 - time: -1 - metadata: - category: ocean - paper_doi: 10.3389/fmars.2020.00263 - paper_ref: Muis at al (2020) - url: https://doi.org/10.24381/cds.8c59054f - version: v1 - license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf - crs: 4326 - data_adapter: - rename: - station_x_coordinate: lon - station_y_coordinate: lat - stations: index + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + guf_bld_2012: data_type: RasterDataset uri: infrastructure/guf/GUF04_DLR_v02.vrt @@ -1182,6 +1213,12 @@ guf_bld_2012: url: http://www.dlr.de/guf license: https://www.dlr.de/eoc/en/PortalData/60/Resources/dokumente/guf/DLR-GUF_LicenseAgreement-and-OrderForm.pdf crs: 4326 + spatial_extent: + West: -180.0 + South: -65.0 + East: 180.0 + North: 85.0 + hydro_lakes: data_type: GeoDataFrame uri: hydrography/lakes/lake-db.fgb @@ -1193,6 +1230,11 @@ hydro_lakes: author: Arjen Haag version: 1.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 data_adapter: unit_mult: Area_avg: 1000000.0 @@ -1204,6 +1246,54 @@ hydro_lakes: Pour_lat: yout Pour_long: xout Vol_total: Vol_avg + +hydro_basin_atlas_level12: + data_type: GeoDataFrame + uri: hydrography/hydro_atlas/basin_atlas_v10.gpkg + driver: + name: pyogrio + options: + layer: BasinATLAS_v10_lev12 + metadata: + category: hydrography + crs: 4326 + version: 10 + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + url: https://www.hydrosheds.org/hydroatlas + license: CC BY 4.0 + spatial_extent: + West: -180.0 + South: -55.988 + East: 180.001 + North: 83.626 + +hydro_lake_atlas_pol: + crs: 4326 + data_type: GeoDataFrame + version: 10 + uri: hydrography/hydro_atlas/lake_atlas_v10.gpkg + driver: + name: pyogrio + options: + layer: LakeATLAS_v10_pol + metadata: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-022-01425-z + paper_ref: Lehner et al. (2022) + url: https://www.hydrosheds.org/hydroatlas + license: CC BY 4.0 + spatial_extent: + West: -180.0 + South: -55.865 + East: 180.0 + North: 83.576 + data_adapter: + rename: + dis_m3_pyr: Dis_avg + hydro_reservoirs: data_type: GeoDataFrame uri: hydrography/reservoirs/reservoir-db.fgb @@ -1216,6 +1306,11 @@ hydro_reservoirs: version: 1.0 nodata: -99 crs: 4326 + spatial_extent: + West: -153.059 + South: -45.881 + East: 176.825 + North: 70.396 data_adapter: unit_mult: Area_avg: 1000000.0 @@ -1236,6 +1331,54 @@ hydro_reservoirs: Pour_lat: yout Pour_long: xout Vol_total: Vol_avg + +hydro_river_atlas: + data_type: GeoDataFrame + uri: hydrography/hydro_atlas/river_atlas_v10.gpkg + driver: + name: pyogrio + metadata: + category: hydrography + crs: 4326 + version: 10 + notes: renaming and units might require some revision + paper_doi: 10.1038/s41597-019-0300-6 + paper_ref: Linke et al. (2019) + url: https://www.hydrosheds.org/hydroatlas + license: CC BY 4.0 + spatial_extent: + West: -179.998 + South: -55.877 + East: 179.998 + North: 83.59 + data_adapter: + rename: + dis_m3_pyr: Dis_avg + +hydro_rivers_lin2019: + data_type: GeoDataFrame + uri: hydrography/rivers_lin2019/rivers_ge30m.fgb + driver: + name: pyogrio + metadata: + category: hydrography + notes: renaming and units might require some revision + paper_doi: 10.5281/zenodo.3552776 + paper_ref: Lin et al. (2019) + url: https://zenodo.org/record/3552776#.YVbOrppByUk + version: 1 + license: CC-BY-NC 4.0 + crs: 4326 + spatial_extent: + West: -179.998 + South: -55.877 + East: 179.998 + North: 83.59 + data_adapter: + rename: + width_m: rivwth + Q2: qbankfull + koppen_geiger: data_type: RasterDataset uri: meteo/climate_classification_v2017/Map_KG-Global.tif @@ -1252,6 +1395,12 @@ koppen_geiger: url: http://koeppen-geiger.vu-wien.ac.at/present.htm version: 2017 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + mdt_cnes_cls18: data_type: RasterDataset uri: topography/mdt_cnes_cls18/MDT_CNES_CLS18_global_filled.tif @@ -1269,6 +1418,13 @@ mdt_cnes_cls18: url: https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html version: 18 crs: 4326 + processing_script: topography/mdt_cnes_cls18/convert_lon_fill_mdt.ipynb + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + merit: data_type: RasterDataset uri: topography/merit/merit.nc @@ -1287,9 +1443,15 @@ merit: version: 1.0.3 license: CC-BY-NC 4.0 or ODbL 1.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 data_adapter: rename: elevation: elevtn + merit_hydro: data_type: RasterDataset uri: topography/merit_hydro/*.vrt @@ -1307,6 +1469,11 @@ merit_hydro: version: 1.0 license: CC-BY-NC 4.0 or ODbL 1.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 data_adapter: rename: bas: basins @@ -1317,6 +1484,7 @@ merit_hydro: upa: uparea upg: upgrid wth: rivwth + merit_hydro_ihu: data_type: RasterDataset uri: topography/merit_hydro_ihu/30sec/*.tif @@ -1330,11 +1498,17 @@ merit_hydro_ihu: category: topography paper_doi: 10.5194/hess-2020-582 paper_ref: Eilander et al. (2021) - source_doi: 10.5281/zenodo.5166932 + doi: 10.5281/zenodo.5166932 url: https://zenodo.org/record/5166932#.YVbxJ5pByUk version: 1.0 license: ODC-By 1.0 + processing_notes: topography/merit_hydro_ihu/README crs: 4326 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 data_adapter: rename: 30sec_basids: basins @@ -1344,6 +1518,7 @@ merit_hydro_ihu: 30sec_uparea: uparea 30sec_rivlen: rivlen 30sec_rivslp: rivslp + merit_hydro_ihu_index: data_type: GeoDataFrame uri: topography/merit_hydro_ihu/30sec/basins.gpkg @@ -1355,7 +1530,14 @@ merit_hydro_ihu_index: paper_ref: Eilander et al. (2021) url: https://zenodo.org/record/5166932#.YVbxJ5pByUk license: CC-BY-NC 4.0 - crs: 4326 + processing_notes: topography/merit_hydro_ihu/README + crs: 4326 + spatial_extent: + West: -180.025 + South: -59.467 + East: 190.35 + North: 83.683 + merit_hydro_index: data_type: GeoDataFrame uri: topography/merit_hydro/basin_index.fgb @@ -1367,6 +1549,12 @@ merit_hydro_index: paper_ref: Eilander et al. (2021) license: CC-BY-NC 4.0 crs: 4326 + spatial_extent: + West: -180.028 + South: -59.46 + East: 190.338 + North: 83.661 + merit_hydro_patch: data_type: RasterDataset uri: topography/merit_hydro/patches/*.vrt @@ -1384,6 +1572,13 @@ merit_hydro_patch: version: 1.0 Deltares patch license: CC-BY-NC 4.0 or ODbL 1.0 crs: 4326 + processing_script: topography/merit_hydro/patches/scripts + processing_notes: local corrections of flow direction raster and re-derive the related maps (basins, uparea, strord) + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 85.0 data_adapter: rename: bas: basins @@ -1394,6 +1589,7 @@ merit_hydro_patch: upa: uparea upg: upgrid wth: rivwth + modis_lai: data_type: RasterDataset uri: landuse/modis/MODIS_MCD15A3H_LAI/*.tif @@ -1414,9 +1610,20 @@ modis_lai: version: MCD15A3H V006 license: https://lpdaac.usgs.gov/data/data-citation-and-policies/ crs: 4326 + processing_notes: this dataset has been extracted from GEE ('MODIS/006/MCD15A3H') + for the period '2003-01-01', '2017-12-31' + processing_script: + GEE_script: landuse/modis/MODIS_MCD15A3H_LAI/GEE_MODIS_LAI.js + merge_script: landuse/modis/MODIS_MCD15A3H_LAI/merge_rasters_GEE_LAI.py + spatial_extent: + West: -180.004 + South: -90.002 + East: 180.004 + North: 90.002 data_adapter: unit_mult: LAI: 0.1 + osm_coastlines: data_type: GeoDataFrame uri: geography/osm/osm_coastlines-db.fgb @@ -1430,9 +1637,15 @@ osm_coastlines: version: 1.0 license: ODbL crs: 4326 + spatial_extent: + West: -180.0 + South: -78.733 + East: 180.0 + North: 90.0 data_adapter: rename: fid: coastline_id + osm_landareas: data_type: GeoDataFrame uri: geography/osm/osm_landareas-db.fgb @@ -1446,9 +1659,15 @@ osm_landareas: version: 1.0 license: ODbL crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 83.666 data_adapter: rename: fid: land_id + pcr_globwb: data_type: RasterDataset variants: @@ -1471,7 +1690,11 @@ pcr_globwb: paper_ref: Sutanudjaja, E. H., et al (2017) processing_script: hydro/pcr_globwb/prep_glob.py url: https://zenodo.org/records/1045339#.XWUr7E2P5aR - version: 2017.11b1 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 nodata: -9999 crs: 4326 data_adapter: @@ -1489,6 +1712,7 @@ pcr_globwb: industryGrossDemand: ind_gross livestockNettoDemand: lsk_net livestockGrossDemand: lsk_gross + rgi: data_type: GeoDataFrame uri: hydrography/rgi/rgi.fgb @@ -1503,28 +1727,18 @@ rgi: version: 6.0 license: CC BY 4.0 crs: 4326 + spatial_extent: + West: -179.921 + South: -78.309 + East: 179.751 + North: 83.608 data_adapter: rename: C3S_ID: C3S_id GLIMSID: GLIMS_id ID: simple_id RGIID: RGI_id -rivers_lin2019_v1: - data_type: GeoDataFrame - uri: hydrography/rivers_lin2019/rivers_ge30m.fgb - driver: - name: pyogrio - metadata: - category: hydrography - paper_doi: 10.5281/zenodo.3552776 - paper_ref: Lin et al. (2019) - url: https://zenodo.org/record/3552776#.YVbOrppByUk - version: 1 - license: CC-BY-NC 4.0 - data_adapter: - rename: - width_m: rivwth - Q2: qbankfull + simard: data_type: RasterDataset uri: landuse/simard/sdat_10023_canopy_height_simard.tif @@ -1540,7 +1754,13 @@ simard: paper_ref: Simard et al (2011) url: https://webmap.ornl.gov/ogc/dataset.jsp?ds_id=10023 crs: 4326 -SM2RAIN_ASCAT_monthly_025_v1.4: + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 + +SM2RAIN_ASCAT_monthly_025: data_type: RasterDataset uri: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_025_2007_2020.nc driver: @@ -1559,10 +1779,20 @@ SM2RAIN_ASCAT_monthly_025_v1.4: url: https://zenodo.org/record/4570192#.YueKJWNByUl license: https://creativecommons.org/licenses/by/4.0/legalcode crs: 4326 + version: 1.4 + temporal_extent: + start: '2007-01-01' + end: '2020-12-01' + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 data_adapter: rename: rainfall: precip -SM2RAIN_ASCAT_monthly_05_v1.4: + +SM2RAIN_ASCAT_monthly_05: data_type: RasterDataset uri: meteo/sm2rain_ascat/SM2RAIN_ASCAT_monthly_05_2007_2020.nc driver: @@ -1580,10 +1810,20 @@ SM2RAIN_ASCAT_monthly_05_v1.4: paper_ref: Brocca et al. (2019) url: https://zenodo.org/record/4570192#.YueKJWNByUl license: https://creativecommons.org/licenses/by/4.0/legalcode - crs: 4326 + version: 1.4 + crs: 4326 + temporal_extent: + start: '2007-01-01' + end: '2020-12-01' + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 data_adapter: rename: rainfall: precip + soilgrids: data_type: RasterDataset uri: soil/soilgrids_v1.0/*_250m_ll.tif @@ -1608,6 +1848,13 @@ soilgrids: version: 2017 license: ODbL crs: 4326 + processing_notes: "soilthickness is based on 1) soilgrids (global, depth to bedrock - BDRICM variable) and 2) dataset for Eurasia" + processing_script: p:/wflow_global/static_data/wflow_sbm_parameters/ + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90 data_adapter: unit_mult: bd_sl1: 0.001 @@ -1676,6 +1923,7 @@ soilgrids: SNDPPT_M_sl7_250m_ll: sndppt_sl7 SoilThickness_250m_ll: soilthickness TAXOUSDA_250m_ll: tax_usda + soilgrids_2020: data_type: RasterDataset uri: soil/soilgrids_v2.0/*/*_mean.vrt @@ -1699,6 +1947,11 @@ soilgrids_2020: url: https://www.isric.org/explore/soilgrids/faq-soilgrids version: 2020 license: CC BY 4.0 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90 data_adapter: unit_mult: bd_sl1: 0.01 @@ -1782,7 +2035,8 @@ soilgrids_2020: sand_100-200cm_mean: sndppt_sl6 SoilThickness_250_mean: soilthickness TAXOUSDA_250_mean: tax_usda -vito: + +vito_2015: data_type: RasterDataset uri: landuse/vito/ProbaV_LC100_epoch2015_global_v2.0.2_discrete-classification_EPSG-4326.tif driver: @@ -1796,9 +2050,15 @@ vito: paper_doi: 10.5281/zenodo.3939038 paper_ref: Buchhorn et al (2020) url: https://land.copernicus.eu/global/products/lc - version: v2.0.2 + version: 2.0.2 crs: 4326 -vito_2016_v3.0.1: + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + +vito_2016: data_type: RasterDataset uri: landuse/vito/PROBAV_LC100_global_v3.0.1_2016-conso_Discrete-Classification-map_EPSG-4326.tif driver: @@ -1812,9 +2072,15 @@ vito_2016_v3.0.1: paper_doi: 10.5281/zenodo.3518026 paper_ref: Buchhorn et al (2020) url: https://land.copernicus.eu/global/products/lc - version: v3.0.1 + version: 3.0.1 crs: 4326 -vito_2017_v3.0.1: + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + +vito_2017: data_type: RasterDataset uri: landuse/vito/PROBAV_LC100_global_v3.0.1_2017-conso_Discrete-Classification-map_EPSG-4326.tif driver: @@ -1828,9 +2094,15 @@ vito_2017_v3.0.1: paper_doi: 10.5281/zenodo.3518036 paper_ref: Buchhorn et al (2020) url: https://land.copernicus.eu/global/products/lc - version: v3.0.1 + version: 3.0.1 crs: 4326 -vito_2018_v3.0.1: + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + +vito_2018: data_type: RasterDataset uri: landuse/vito/PROBAV_LC100_global_v3.0.1_2018-conso_Discrete-Classification-map_EPSG-4326.tif driver: @@ -1844,9 +2116,15 @@ vito_2018_v3.0.1: paper_doi: 10.5281/zenodo.3518038 paper_ref: Buchhorn et al (2020) url: https://land.copernicus.eu/global/products/lc - version: v3.0.1 + version: 3.0.1 crs: 4326 -vito_2019_v3.0.1: + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + +vito_2019: data_type: RasterDataset uri: landuse/vito/ProbaV_LC100_global_v3.0.1_2019-nrt_discrete-classification-map_EPSG-4326.tif driver: @@ -1860,8 +2138,14 @@ vito_2019_v3.0.1: paper_doi: 10.5281/zenodo.3939050 paper_ref: Buchhorn et al (2020) url: https://land.copernicus.eu/global/products/lc - version: v3.0.1 - crs: 4326 + version: 3.0.1 + crs: 4326 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 + wb_countries: data_type: GeoDataFrame uri: geography/wb/WB_countries_Admin0.fgb @@ -1874,6 +2158,11 @@ wb_countries: author: World Bank license: CC-BY 4.0 crs: 4326 + spatial_extent: + West: -180.0 + South: -59.473 + East: 180.0 + North: 83.634 data_adapter: unit_mult: gdp_pc: 1000 @@ -1883,6 +2172,7 @@ wb_countries: POP_EST: population GDP_MD_EST: gdp_pc GDP_kD_PPP: gdp + worldclim: data_type: RasterDataset uri: meteo/worldclim_v2.0/wc2.0_30s_prec.nc @@ -1900,9 +2190,15 @@ worldclim: url: https://www.worldclim.org/data/worldclim21.html version: 2 crs: 4326 + spatial_extent: + West: -180.0 + South: -90.0 + East: 180.0 + North: 90.0 data_adapter: rename: prec: precip + worldpop_2020_constrained: data_type: RasterDataset variants: @@ -1925,8 +2221,15 @@ worldpop_2020_constrained: paper_doi: 10.1371/journal.pone.0107042 paper_ref: Stevens et al. (2015) url: https://www.worldpop.org/doi/10.5258/SOTON/WP00684 + processing_script: socio_economic/worldpop/src/ license: CC BY 4.0 nodata: -99999 + spatial_extent: + West: -180.0 + South: -55.985 + East: 180.0 + North: 83.628 + wsf_bld_2015: data_type: RasterDataset uri: infrastructure/wsf/WSF2015_v1_EPSG4326.vrt @@ -1943,3 +2246,9 @@ wsf_bld_2015: url: https://un-spider.org/links-and-resources/data-sources/world-settlement-footprint-2015-wsf-dlr-eoc license: CC0 1.0 crs: 4326 + version: 1 + spatial_extent: + West: -180.0 + South: -60.0 + East: 180.0 + North: 80.0 From 033f85278833bf32b808ce24cd04a140ac06fb31 Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 15:53:23 +0200 Subject: [PATCH 103/110] updated registry.txt files --- data/catalogs/deltares_data/registry.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index 09d98b151..abf25921f 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,4 +1,4 @@ v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef -v1.0.0/data_catalog.yml aa6426be88c16e5dd88f032bcec1cb69b59a3e3eaae4a2afacaf5d9d7cfd0f02 -v0.7.0/data_catalog.yml fbcb24b3e994e20430c30e8246b17a1bb7fd06a2b3a4e756e75afa4275d94ea5 +v1.0.0/data_catalog.yml 5fafe1e057ad1cbf486a323d9f3f3035e6b80e51928af52547e86cccb41424c6 +v0.7.0/data_catalog.yml 7fe2d7c978baa1f6957ecb08fddbeae277b7466621de49f73960085a0a56875f From d9b7938f6e8b8325974d937f0bacc5cbeabef58c Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 16:49:17 +0200 Subject: [PATCH 104/110] updated test_data_catalog.py --- data/catalogs/test_data_catalog.py | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/data/catalogs/test_data_catalog.py b/data/catalogs/test_data_catalog.py index c3a876362..c9f5df2fc 100644 --- a/data/catalogs/test_data_catalog.py +++ b/data/catalogs/test_data_catalog.py @@ -19,15 +19,17 @@ In addition the passed data catalog yaml is checked if it is a valid data catalog yaml. """ + import argparse import json +from os.path import exists from dask.distributed import Client from pydantic_core import ValidationError from hydromt import DataCatalog +from hydromt._validators.data_catalog import DataCatalogValidator from hydromt.utils import setuplog -from hydromt.validators.data_catalog import DataCatalogValidator def test_dataset(args, datacatalog): @@ -68,17 +70,18 @@ def test_data_catalog(args, datacatalog): """Tests the paths of the given data catalog.""" error_count = 0 logger.info("Checking paths of data catalog sources") - for source in datacatalog.get_source_names(): + for source_name in datacatalog.get_source_names(): try: - logger.info(f"Checking paths of {source}") - datacatalog.get_source(source)._resolve_paths() + logger.info(f"Checking paths of {source_name}") + if not exists(datacatalog.get_source(source_name).uri): + raise FileNotFoundError except FileNotFoundError as e: - logger.error(f"File not found for dataset source {source}: {e}") + logger.error(f"File not found for dataset source {source_name}: {e}") error_count += 1 except ValueError as e: logger.error( - f"Something went wrong with creating path string for dataset source {source}: {e}" + f"Something went wrong with creating path string for dataset source {source_name}: {e}" ) error_count += 1 if error_count > 0: From 171749105f6f8318b33f33b52d9fc2f6dc807650 Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 20 Jun 2024 16:49:42 +0200 Subject: [PATCH 105/110] fixed minor issues deltares_data --- .../deltares_data/v1.0.0/data_catalog.yml | 21 +++++++------------ hydromt/_validators/data_catalog.py | 2 ++ 2 files changed, 10 insertions(+), 13 deletions(-) diff --git a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml index 487965c63..ae144a37d 100644 --- a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml @@ -257,9 +257,6 @@ eobs: version: 22.0e license: https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles crs: 4326 - temporal_extent: - start: '1950-01-02' - end: '2022-01-01' spatial_extent: West: -25.0 South: 25.0 @@ -276,19 +273,19 @@ eobs: variants: - version: 22.0e uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v22.0e.nc - meta: + metadata: temporal_extent: start: '1950-01-02' end: '2020-07-01' - version: 23.1e uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v23.1e.nc - meta: + metadata: temporal_extent: start: '1950-01-02' end: '2021-01-01' - version: 24.0e uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v24.0e.nc - meta: + metadata: processing_script: meteo/eobs/scripts/v24.0e_fix_qq_dims_and_match_extent.py processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables temporal_extent: @@ -296,7 +293,7 @@ eobs: end: '2021-07-01' - version: 25.0e uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v25.0e.nc - meta: + metadata: processing_script: v25.0e_fix_qq_dims_and_match_extent.py processing_notes: correct lat/lon dimension for variable qq to match the grid of the other variables temporal_extent: @@ -304,7 +301,7 @@ eobs: end: '2022-01-01' - version: 29.0e uri: meteo/eobs/*/{variable}_ens_mean_0.1deg_reg_v29.0e.nc - meta: + metadata: processing_script: meteo/eobs/scripts/v29.0e_fix_qq_dims_and_match_extent.py temporal_extent: start: '1950-01-01' @@ -348,8 +345,6 @@ eobs_orography: uri: meteo/eobs/elev_ens_0.1deg_reg_v25.0e.nc - version: 29.0e uri: meteo/eobs/elev_ens_0.1deg_reg_v29.0e.nc - rename: - elevation: elevtn era5: data_type: RasterDataset @@ -813,12 +808,12 @@ ghs_smod_2015: variants: - version: R2016A_v1.0 uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2016A_54009_1k_v1_0.tif - meta: + metadata: paper_ref: Pesaresi and Freire (2016) url: https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_smod_pop_globe_r2016a - version: R2019A_v2.0 uri: socio_economic/ghs/GHS_SMOD_POP2015_GLOBE_R2019A_54009_1K_V2_0.tif - meta: + metadata: paper_doi: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 paper_ref: Pesaresi et al (2019) url: https://data.jrc.ec.europa.eu/dataset/42e8be89-54ff-464e-be7b-bf9e64da5218 @@ -1270,7 +1265,6 @@ hydro_basin_atlas_level12: North: 83.626 hydro_lake_atlas_pol: - crs: 4326 data_type: GeoDataFrame version: 10 uri: hydrography/hydro_atlas/lake_atlas_v10.gpkg @@ -1285,6 +1279,7 @@ hydro_lake_atlas_pol: paper_ref: Lehner et al. (2022) url: https://www.hydrosheds.org/hydroatlas license: CC BY 4.0 + crs: 4326 spatial_extent: West: -180.0 South: -55.865 diff --git a/hydromt/_validators/data_catalog.py b/hydromt/_validators/data_catalog.py index ac2f79f4b..105618c96 100644 --- a/hydromt/_validators/data_catalog.py +++ b/hydromt/_validators/data_catalog.py @@ -93,6 +93,8 @@ class DataCatalogItemMetadata(BaseModel): source_url: Optional[AnyUrl] = None source_version: Optional[str] = None notes: Optional[str] = None + temporal_extent: Optional[dict] = None + spatial_extent: Optional[dict] = None model_config: ConfigDict = ConfigDict( str_strip_whitespace=True, coerce_numbers_to_str=True From fab44288afb4741c3fb4753699e9e1382610c2b7 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 21 Jun 2024 12:55:01 +0200 Subject: [PATCH 106/110] fixed bug with using era5 daily and hourly netcdf files --- data/catalogs/deltares_data/v0.7.0/data_catalog.yml | 4 ++-- data/catalogs/deltares_data/v1.0.0/data_catalog.yml | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml index 4e38c27d6..0111169f6 100644 --- a/data/catalogs/deltares_data/v0.7.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v0.7.0/data_catalog.yml @@ -403,7 +403,7 @@ era5: combine: by_coords decode_times: true parallel: true - path: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + path: meteo/era5_daily/nc_merged/era5_{year}_daily.nc - provider: zarr driver: zarr driver_kwargs: @@ -458,7 +458,7 @@ era5_hourly: combine: by_coords decode_times: true parallel: true - path: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + path: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc - provider: zarr driver: zarr kwargs: diff --git a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml index ae144a37d..970c270be 100644 --- a/data/catalogs/deltares_data/v1.0.0/data_catalog.yml +++ b/data/catalogs/deltares_data/v1.0.0/data_catalog.yml @@ -2,7 +2,7 @@ meta: root: p:/wflow_global/hydromt version: v1.0.0 name: deltares_data - hydromt_version: '>1.0a,<2' + hydromt_version: '>1.0.0-alpha,<2' chelsa: @@ -350,7 +350,7 @@ era5: data_type: RasterDataset variants: - provider: netcdf - uri: meteo/era5_daily/nc_merged/era5_{year}*_daily.nc + uri: meteo/era5_daily/nc_merged/era5_{year}_daily.nc driver: name: raster_xarray options: @@ -412,7 +412,7 @@ era5_hourly: data_type: RasterDataset variants: - provider: netcdf - uri: meteo/era5/{variable}/era5_{variable}_{year}*_hourly.nc + uri: meteo/era5/{variable}/era5_{variable}_{year}_hourly.nc driver: name: raster_xarray options: From 2125b959b1ecf5a223e887e1923e749e237eafb3 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 21 Jun 2024 12:55:29 +0200 Subject: [PATCH 107/110] updated test_data_catalog.py --- data/catalogs/test_data_catalog.py | 36 +++++++++++++++++++----------- 1 file changed, 23 insertions(+), 13 deletions(-) diff --git a/data/catalogs/test_data_catalog.py b/data/catalogs/test_data_catalog.py index c9f5df2fc..79b0c6db3 100644 --- a/data/catalogs/test_data_catalog.py +++ b/data/catalogs/test_data_catalog.py @@ -29,6 +29,9 @@ from hydromt import DataCatalog from hydromt._validators.data_catalog import DataCatalogValidator +from hydromt.data_catalog.uri_resolvers.raster_tindex_resolver import ( + RasterTindexResolver, +) from hydromt.utils import setuplog @@ -70,20 +73,27 @@ def test_data_catalog(args, datacatalog): """Tests the paths of the given data catalog.""" error_count = 0 logger.info("Checking paths of data catalog sources") - for source_name in datacatalog.get_source_names(): - try: - logger.info(f"Checking paths of {source_name}") - if not exists(datacatalog.get_source(source_name).uri): - raise FileNotFoundError - except FileNotFoundError as e: - logger.error(f"File not found for dataset source {source_name}: {e}") - - error_count += 1 - except ValueError as e: - logger.error( - f"Something went wrong with creating path string for dataset source {source_name}: {e}" + for source_name, source in datacatalog.__iter__(): + logger.info(f"Checking paths of {source_name}") + if isinstance(source.driver.metadata_resolver, RasterTindexResolver): + if not exists(source.full_uri): + error_count += 1 + logger.error( + f"File {source.full_uri} not found for dataset source {source_name}" + ) + continue + + else: + paths = source.driver.metadata_resolver.resolve( + source.full_uri, source.driver.filesystem ) - error_count += 1 + for path in paths: + if not exists(path): + logger.error( + f"File {path} not found for dataset source {source_name}" + ) + error_count += 1 + if error_count > 0: logger.error(f"Encountered {error_count} errors") From c305bb8ac19791d8cd7bffa3f957f7505a10e1c5 Mon Sep 17 00:00:00 2001 From: Tjalling-dejong Date: Fri, 21 Jun 2024 13:04:36 +0200 Subject: [PATCH 108/110] updated registry.txt files --- data/catalogs/artifact_data/registry.txt | 6 +++--- data/catalogs/deltares_data/registry.txt | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index 0eb2d586a..5fce61e41 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,5 +1,5 @@ -v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v1.0.0/data_catalog.yml e422a0f4a32998d96186f2197068a2d9daf7409192a6db63a2211142c9b0b4ad -v0.0.8/data_catalog.yml 3092305249af479061938ca484fe0245731174f072325740e9a85d1e986f8efc v0.0.7/data_catalog.yml 8daccd1b551b3bafdb95b5ddc4b8dddafd6f25070ad9c543e3c0027bb55bc16e +v0.0.8/data_catalog.yml 3092305249af479061938ca484fe0245731174f072325740e9a85d1e986f8efc +v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 +v1.0.0/data_catalog.yml e422a0f4a32998d96186f2197068a2d9daf7409192a6db63a2211142c9b0b4ad diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index abf25921f..aa22a9efc 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,4 +1,4 @@ -v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef -v1.0.0/data_catalog.yml 5fafe1e057ad1cbf486a323d9f3f3035e6b80e51928af52547e86cccb41424c6 -v0.7.0/data_catalog.yml 7fe2d7c978baa1f6957ecb08fddbeae277b7466621de49f73960085a0a56875f +v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 +v0.7.0/data_catalog.yml 24c77c0c5429353eeedb75d4c0f2dbfa305d81454b2fbf32239ab23166b3b1a6 +v1.0.0/data_catalog.yml 7c637c967faa8547483f7076c99b8b0058e40e26adae525cc838ba9ea472cdc6 From b5b08a0d51469bd2646cc183d5fed1194ad4f418 Mon Sep 17 00:00:00 2001 From: Tjalling Date: Wed, 26 Jun 2024 16:03:26 +0200 Subject: [PATCH 109/110] implemented requested changes --- docs/api.rst | 966 ------------------------------ docs/changelog.rst | 4 +- docs/parse_predefined_catalogs.py | 3 +- 3 files changed, 3 insertions(+), 970 deletions(-) delete mode 100644 docs/api.rst diff --git a/docs/api.rst b/docs/api.rst deleted file mode 100644 index ecb7382d8..000000000 --- a/docs/api.rst +++ /dev/null @@ -1,966 +0,0 @@ -.. currentmodule:: hydromt - -.. _api_reference: - -############# -API reference -############# - -====================== -Command Line Interface -====================== - -.. toctree:: - :maxdepth: 2 - :hidden: - - api_cli/hydromt_cli.rst - api_cli/hydromt_build.rst - api_cli/hydromt_update.rst - api_cli/hydromt_clip.rst - api_cli/hydromt_export.rst - api_cli/hydromt_check.rst - - -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt `_ | Main command line interface of HydroMT. | -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt build `_ | Build a model. | -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt update `_ | Update an existing model. | -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt clip `_ | Clip/Extract a submodel from an existing model. | -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt export `_ | Export data extract from a data catalog. | -+------------------------------------------------+--------------------------------------------------------+ -| `hydromt check `_ | Check if data catalog or configuration file are valid. | -+------------------------------------------------+--------------------------------------------------------+ - -==== -Data -==== - -.. _api_data_catalog: - -Data catalog -============ - -General -------- - -.. autosummary:: - :toctree: _generated - - data_catalog.DataCatalog - data_catalog.DataCatalog.get_source - data_catalog.DataCatalog.iter_sources - data_catalog.DataCatalog.sources - data_catalog.DataCatalog.keys - data_catalog.DataCatalog.predefined_catalogs - data_catalog.DataCatalog.to_dict - data_catalog.DataCatalog.to_dataframe - data_catalog.DataCatalog.to_yml - data_catalog.DataCatalog.export_data - data_catalog.DataCatalog.get_source_bbox - data_catalog.DataCatalog.get_source_time_range - -Add data sources ----------------- - -.. autosummary:: - :toctree: _generated - - data_catalog.DataCatalog.add_source - data_catalog.DataCatalog.update - data_catalog.DataCatalog.from_predefined_catalogs - data_catalog.DataCatalog.from_yml - data_catalog.DataCatalog.from_dict - -.. _api_data_catalog_get: - -Get data --------- - -.. autosummary:: - :toctree: _generated - - data_catalog.DataCatalog.get_rasterdataset - data_catalog.DataCatalog.get_geodataset - data_catalog.DataCatalog.get_geodataframe - data_catalog.DataCatalog.get_dataframe - data_catalog.DataCatalog.get_dataset - - -Predefined data catalog -======================= - -.. autosummary:: - :toctree: _generated - - predefined_catalog.PredefinedCatalog - predefined_catalog.PredefinedCatalog.get_catalog_file - predefined_catalog.create_registry_file - - - -DataAdapter -=========== - -General -------- - -.. autosummary:: - :toctree: _generated - - data_adapter.DataAdapter - data_adapter.DataAdapter.summary - data_adapter.DataAdapter.to_dict - -RasterDataset -------------- - -.. autosummary:: - :toctree: _generated - - data_adapter.RasterDatasetAdapter - data_adapter.RasterDatasetAdapter.summary - data_adapter.RasterDatasetAdapter.get_data - data_adapter.RasterDatasetAdapter.to_dict - data_adapter.RasterDatasetAdapter.to_file - data_adapter.RasterDatasetAdapter.get_bbox - data_adapter.RasterDatasetAdapter.get_time_range - data_adapter.RasterDatasetAdapter.detect_bbox - data_adapter.RasterDatasetAdapter.detect_time_range - data_adapter.RasterDatasetAdapter.to_stac_catalog - -GeoDataset ----------- - -.. autosummary:: - :toctree: _generated - - data_adapter.GeoDatasetAdapter - data_adapter.GeoDatasetAdapter.summary - data_adapter.GeoDatasetAdapter.get_data - data_adapter.GeoDatasetAdapter.to_dict - data_adapter.GeoDatasetAdapter.to_file - data_adapter.GeoDatasetAdapter.get_bbox - data_adapter.GeoDatasetAdapter.get_time_range - data_adapter.GeoDatasetAdapter.detect_bbox - data_adapter.GeoDatasetAdapter.detect_time_range - data_adapter.GeoDatasetAdapter.to_stac_catalog - -GeoDataFrame ------------- - -.. autosummary:: - :toctree: _generated - - data_adapter.GeoDataFrameAdapter - data_adapter.GeoDataFrameAdapter.summary - data_adapter.GeoDataFrameAdapter.get_data - data_adapter.GeoDataFrameAdapter.to_dict - data_adapter.GeoDataFrameAdapter.to_file - data_adapter.GeoDataFrameAdapter.get_bbox - data_adapter.GeoDataFrameAdapter.detect_bbox - data_adapter.GeoDataFrameAdapter.to_stac_catalog - -DataFrame ---------- - -.. autosummary:: - :toctree: _generated - - data_adapter.DataFrameAdapter - data_adapter.DataFrameAdapter.summary - data_adapter.DataFrameAdapter.get_data - data_adapter.DataFrameAdapter.to_dict - data_adapter.DataFrameAdapter.to_file - data_adapter.DataFrameAdapter.to_stac_catalog - -Dataset -------- - -.. autosummary:: - :toctree: _generated - - data_adapter.DatasetAdapter - data_adapter.DatasetAdapter.summary - data_adapter.DatasetAdapter.get_data - data_adapter.DatasetAdapter.to_dict - data_adapter.DatasetAdapter.to_file - data_adapter.DatasetAdapter.to_stac_catalog - - -====== -Models -====== - -Discovery -========= - -.. autosummary:: - :toctree: _generated - - ModelCatalog - - -.. _model_api: - -Model -===== - -Note that the base Model attributes and methods are available to all models. - -.. autosummary:: - :toctree: _generated - - Model - -High level methods ------------------- - -.. autosummary:: - :toctree: _generated - - Model.read - Model.write - Model.build - Model.update - Model.set_root - Model.write_data_catalog - -Model attributes ----------------- - -.. autosummary:: - :toctree: _generated - - Model.crs - Model.region - Model.root - Model.api - -Model components and attributes -------------------------------- - -.. autosummary:: - :toctree: _generated - - Model.config - Model.maps - Model.geoms - Model.forcing - Model.states - Model.results - -General methods ---------------- - -.. autosummary:: - :toctree: _generated - - Model.get_config - Model.set_config - Model.read_config - Model.write_config - - Model.set_maps - Model.read_maps - Model.write_maps - - Model.set_geoms - Model.read_geoms - Model.write_geoms - - Model.set_forcing - Model.read_forcing - Model.write_forcing - - Model.set_states - Model.read_states - Model.write_states - - Model.set_results - Model.read_results - - Model.read_nc - Model.write_nc - -.. _setup_methods: - -Setup methods -------------- - -.. autosummary:: - :toctree: _generated - - Model.setup_config - Model.setup_region - Model.setup_maps_from_rasterdataset - Model.setup_maps_from_raster_reclass - - -.. _grid_model_api: - -GridModel -========= - -.. autosummary:: - :toctree: _generated - - GridModel - - -Components and attributes -------------------------- - -.. autosummary:: - :toctree: _generated - - GridModel.grid - GridModel.crs - GridModel.region - - -General methods ---------------- - -.. autosummary:: - :toctree: _generated - - GridModel.set_grid - GridModel.read_grid - GridModel.write_grid - -Setup methods -------------- - -.. autosummary:: - :toctree: _generated - - GridModel.setup_config - GridModel.setup_region - GridModel.setup_maps_from_rasterdataset - GridModel.setup_maps_from_raster_reclass - GridModel.setup_grid - GridModel.setup_grid_from_constant - GridModel.setup_grid_from_rasterdataset - GridModel.setup_grid_from_raster_reclass - GridModel.setup_grid_from_geodataframe - - -.. _vector_model_api: - -VectorModel -=========== - -.. autosummary:: - :toctree: _generated - - VectorModel - - -Components and attributes -------------------------- - -.. autosummary:: - :toctree: _generated - - VectorModel.vector - VectorModel.crs - VectorModel.region - -General methods ---------------- - -.. autosummary:: - :toctree: _generated - - VectorModel.set_vector - VectorModel.read_vector - VectorModel.write_vector - -Setup methods -------------- - -.. autosummary:: - :toctree: _generated - - VectorModel.setup_config - VectorModel.setup_region - VectorModel.setup_maps_from_rasterdataset - VectorModel.setup_maps_from_raster_reclass - - -.. _mesh_model_api: - -MeshModel -========= - -.. autosummary:: - :toctree: _generated - - MeshModel - - -Components and attributes -------------------------- - -.. autosummary:: - :toctree: _generated - - MeshModel.mesh - MeshModel.mesh_names - MeshModel.mesh_grids - MeshModel.mesh_datasets - MeshModel.mesh_gdf - MeshModel.crs - MeshModel.region - MeshModel.bounds - -General methods ---------------- - -.. autosummary:: - :toctree: _generated - - MeshModel.set_mesh - MeshModel.get_mesh - MeshModel.read_mesh - MeshModel.write_mesh - - -Setup methods -------------- - -.. autosummary:: - :toctree: _generated - - MeshModel.setup_config - MeshModel.setup_region - MeshModel.setup_mesh2d - MeshModel.setup_mesh2d_from_rasterdataset - MeshModel.setup_mesh2d_from_raster_reclass - MeshModel.setup_maps_from_rasterdataset - MeshModel.setup_maps_from_raster_reclass - -.. _workflows_api: - -========= -Workflows -========= - -.. _workflows_grid_api: - -Grid -==== - -.. autosummary:: - :toctree: _generated - - workflows.grid.grid_from_constant - workflows.grid.grid_from_rasterdataset - workflows.grid.grid_from_raster_reclass - workflows.grid.grid_from_geodataframe - -.. _workflows_mesh_api: - -Mesh -==== - -.. autosummary:: - :toctree: _generated - - workflows.mesh.create_mesh2d - workflows.mesh.mesh2d_from_rasterdataset - workflows.mesh.mesh2d_from_raster_reclass - -.. _workflows_basin_api: - -Basin mask -========== - -.. autosummary:: - :toctree: _generated - - workflows.basin_mask.get_basin_geometry - workflows.basin_mask.parse_region - -.. _workflows_rivers_api: - -River bathymetry -================ - -.. autosummary:: - :toctree: _generated - - workflows.rivers.river_width - workflows.rivers.river_depth - -.. _workflows_forcing_api: - -Forcing -======= - -Data handling -------------- - -.. autosummary:: - :toctree: _generated - - workflows.forcing.precip - workflows.forcing.temp - workflows.forcing.press - workflows.forcing.pet - workflows.forcing.wind - - -Correction methods ------------------- - -.. autosummary:: - :toctree: _generated - - workflows.forcing.press_correction - workflows.forcing.temp_correction - -Time resampling methods ------------------------ - -.. autosummary:: - :toctree: _generated - - workflows.forcing.resample_time - workflows.forcing.delta_freq - -Computation methods -------------------- - -**PET** - -.. autosummary:: - :toctree: _generated - - workflows.forcing.pet_debruin - workflows.forcing.pet_makkink - workflows.forcing.pm_fao56 - -======================= -Reading/writing methods -======================= - -.. _open_methods: - -Reading methods -=============== - -.. autosummary:: - :toctree: _generated - - io.open_raster - io.open_mfraster - io.open_raster_from_tindex - io.open_vector - io.open_vector_from_table - io.open_geodataset - io.open_timeseries_from_table - -Raster writing methods -====================== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.to_xyz_tiles - DataArray.raster.to_slippy_tiles - DataArray.raster.to_raster - Dataset.raster.to_mapstack - -.. _raster_api: - -============== -Raster methods -============== - -High level methods -================== - -.. autosummary:: - :toctree: _generated - - merge.merge - raster.full - raster.full_like - raster.full_from_transform - -.. autosummary:: - :toctree: _generated - :template: autosummary/accessor_method.rst - - DataArray.raster.from_numpy - Dataset.raster.from_numpy - -Attributes -========== - -.. autosummary:: - :toctree: _generated - :template: autosummary/accessor_attribute.rst - - DataArray.raster.attrs - DataArray.raster.crs - DataArray.raster.bounds - DataArray.raster.transform - DataArray.raster.res - DataArray.raster.rotation - DataArray.raster.origin - DataArray.raster.nodata - DataArray.raster.dims - DataArray.raster.coords - DataArray.raster.dim0 - DataArray.raster.y_dim - DataArray.raster.x_dim - DataArray.raster.xcoords - DataArray.raster.ycoords - DataArray.raster.shape - DataArray.raster.size - DataArray.raster.width - DataArray.raster.height - DataArray.raster.internal_bounds - DataArray.raster.box - - -General methods -=============== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.set_crs - DataArray.raster.set_spatial_dims - DataArray.raster.reset_spatial_dims_attrs - DataArray.raster.identical_grid - DataArray.raster.aligned_grid - DataArray.raster.gdal_compliant - DataArray.raster.idx_to_xy - DataArray.raster.xy_to_idx - DataArray.raster.rowcol - DataArray.raster.xy - DataArray.raster.flipud - DataArray.raster.area_grid - DataArray.raster.density_grid - DataArray.raster.reclassify - - -Nodata handling and interpolation -================================= - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.set_nodata - DataArray.raster.mask_nodata - DataArray.raster.interpolate_na - - -Clip -==== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.clip - DataArray.raster.clip_bbox - DataArray.raster.clip_mask - DataArray.raster.clip_geom - -Reproject -========= - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.reproject - DataArray.raster.reindex2d - DataArray.raster.reproject_like - DataArray.raster.transform_bounds - DataArray.raster.nearest_index - -Transform -========= - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.rasterize - DataArray.raster.rasterize_geometry - DataArray.raster.geometry_mask - DataArray.raster.vectorize - DataArray.raster.vector_grid - -Sampling and zonal stats -======================== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.raster.sample - DataArray.raster.zonal_stats - - -Low level methods -================= - -.. autosummary:: - :toctree: _generated - - gis_utils.axes_attrs - gis_utils.meridian_offset - -.. _geodataset_api: - -================== -GeoDataset methods -================== - -High level methods -================== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.vector.from_gdf - DataArray.vector.to_gdf - DataArray.vector.from_netcdf - DataArray.vector.to_netcdf - Dataset.vector.from_gdf - Dataset.vector.to_gdf - Dataset.vector.from_netcdf - Dataset.vector.to_netcdf - -Attributes -========== - -.. autosummary:: - :template: autosummary/accessor_attribute.rst - :toctree: _generated - - DataArray.vector.attrs - DataArray.vector.crs - DataArray.vector.index_dim - DataArray.vector.time_dim - DataArray.vector.x_name - DataArray.vector.y_name - DataArray.vector.geom_name - DataArray.vector.geom_type - DataArray.vector.geom_format - DataArray.vector.index - DataArray.vector.bounds - DataArray.vector.size - DataArray.vector.sindex - DataArray.vector.geometry - Dataset.vector.attrs - Dataset.vector.crs - Dataset.vector.index_dim - Dataset.vector.time_dim - Dataset.vector.x_name - Dataset.vector.y_name - Dataset.vector.geom_name - Dataset.vector.geom_type - Dataset.vector.geom_format - Dataset.vector.index - Dataset.vector.bounds - Dataset.vector.size - Dataset.vector.sindex - Dataset.vector.geometry - -Conversion -========== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.vector.ogr_compliant - DataArray.vector.update_geometry - DataArray.vector.to_geom - DataArray.vector.to_xy - DataArray.vector.to_wkt - Dataset.vector.ogr_compliant - Dataset.vector.update_geometry - Dataset.vector.to_geom - Dataset.vector.to_xy - Dataset.vector.to_wkt - -General methods -=============== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.vector.set_crs - DataArray.vector.set_spatial_dims - Dataset.vector.set_crs - Dataset.vector.set_spatial_dims - -Clip -==== - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.vector.clip_bbox - DataArray.vector.clip_geom - Dataset.vector.clip_bbox - Dataset.vector.clip_geom - -Reproject -========= - -.. autosummary:: - :template: autosummary/accessor_method.rst - :toctree: _generated - - DataArray.vector.to_crs - Dataset.vector.to_crs - -.. _flw_api: - -====================== -Flow direction methods -====================== - -These methods are based on the pyflwdir library. For more flow direction based methods -visit the `pyflwdir docs. `_ - -.. autosummary:: - :toctree: _generated - - flw.flwdir_from_da - flw.d8_from_dem - flw.reproject_hydrography_like - flw.upscale_flwdir - flw.stream_map - flw.basin_map - flw.gauge_map - flw.outlet_map - flw.clip_basins - flw.dem_adjust - -.. _gis_utils_api: - -=================== -General GIS methods -=================== - -Raster -========= - -.. autosummary:: - :toctree: _generated - - gis_utils.create_vrt - gis_utils.spread2d - gis_utils.reggrid_area - gis_utils.cellarea - gis_utils.cellres - -CRS and transform -================= - -.. autosummary:: - :toctree: _generated - - gis_utils.parse_crs - gis_utils.utm_crs - gis_utils.affine_to_coords - -Vector -====== - -.. autosummary:: - :toctree: _generated - - gis_utils.filter_gdf - gis_utils.nearest - gis_utils.nearest_merge - - -.. _statistics: - -===================================== -Statistics and Extreme Value Analysis -===================================== - -Statistics and performance metrics -================================== - -.. autosummary:: - :toctree: _generated - - stats.skills.bias - stats.skills.percentual_bias - stats.skills.volumetric_error - stats.skills.nashsutcliffe - stats.skills.lognashsutcliffe - stats.skills.pearson_correlation - stats.skills.spearman_rank_correlation - stats.skills.kge - stats.skills.kge_2012 - stats.skills.kge_non_parametric - stats.skills.kge_non_parametric_flood - stats.skills.rsquared - stats.skills.mse - stats.skills.rmse - stats.skills.rsr - -Extreme Value Analysis -======================= -.. autosummary:: - :toctree: _generated - - stats.extremes.get_peaks - stats.extremes.fit_extremes - stats.extremes.get_return_value - stats.extremes.eva - -============= -Design Events -============= -.. autosummary:: - :toctree: _generated - - stats.design_events.get_peak_hydrographs - - -========= -Utilities -========= - -Configuration files -=================== - -.. autosummary:: - :toctree: _generated - - config.configread - config.configwrite - -Logging -======= - -.. autosummary:: - :toctree: _generated - - log.setuplog diff --git a/docs/changelog.rst b/docs/changelog.rst index a31fa5da8..1c7c4e3dd 100644 --- a/docs/changelog.rst +++ b/docs/changelog.rst @@ -33,7 +33,7 @@ Changed - The model region is no longer a subset of the `geoms` but rather it's own component class. See the migration guide for more info (#810) - The model class has been moved to a component architecture. See the migration guide for more info (#845) - Changed the `GeoDatasetAdapter` to transform vector data from tabular formats. (#912) - +- Updated deltares_data data catalog to incorporate the newest data catalog features (#667) Removed ------- @@ -132,7 +132,7 @@ Added Changed ------- - Export CLI now uses '-s' for source, '-t' for time and '-i' for config. (#660) -- Updated deltares_data data catalog to incorporate the newest data catalog features (#667) + Fixed ----- diff --git a/docs/parse_predefined_catalogs.py b/docs/parse_predefined_catalogs.py index cb0ae9c85..323e5e695 100644 --- a/docs/parse_predefined_catalogs.py +++ b/docs/parse_predefined_catalogs.py @@ -53,7 +53,7 @@ def write_nested_dropdown(name, df_dict: dict, note: str=""): with open(path, mode="w") as f: write_panel(f, name, note, level=0) for i, version in enumerate(df_dict): - df = df_dict[version]#.reset_index().set_index(["name", "provider", "version"]) + df = df_dict[version] df = df.sort_index() name_str = f"{version}" if i == len(df_dict)-1: @@ -73,7 +73,6 @@ def write_nested_dropdown(name, df_dict: dict, note: str=""): write_panel(f, "all", level=3, item="tab-item") write_sources_panel(f, df, level=4) - # return relative path return path.relative_to(FILE_ROOT) def write_sources_panel(f, df, level, sources=None): From 014b216ab1e8927082cc20825d5dc145b5929150 Mon Sep 17 00:00:00 2001 From: Tjalling Date: Thu, 27 Jun 2024 14:46:26 +0200 Subject: [PATCH 110/110] updated registry files --- data/catalogs/artifact_data/registry.txt | 6 +++--- data/catalogs/deltares_data/registry.txt | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/data/catalogs/artifact_data/registry.txt b/data/catalogs/artifact_data/registry.txt index 5fce61e41..5e32969ff 100644 --- a/data/catalogs/artifact_data/registry.txt +++ b/data/catalogs/artifact_data/registry.txt @@ -1,5 +1,5 @@ +v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 v0.0.6/data_catalog.yml 5d9e47158185f1afbf793db68c887f6e6b119d7ffd3edfbc198e5ae3a9d760f3 -v0.0.7/data_catalog.yml 8daccd1b551b3bafdb95b5ddc4b8dddafd6f25070ad9c543e3c0027bb55bc16e +v1.0.0/data_catalog.yml e871875c4d4919eb2f3f0975db2ee4fa6967489ccb6a1f2c231aacb4ca510365 v0.0.8/data_catalog.yml 3092305249af479061938ca484fe0245731174f072325740e9a85d1e986f8efc -v0.0.9/data_catalog.yml 6592ad6028b01012ed6bf1a7511238c3e02844f696ff2065c404ddbbab55bdc8 -v1.0.0/data_catalog.yml e422a0f4a32998d96186f2197068a2d9daf7409192a6db63a2211142c9b0b4ad +v0.0.7/data_catalog.yml 8daccd1b551b3bafdb95b5ddc4b8dddafd6f25070ad9c543e3c0027bb55bc16e diff --git a/data/catalogs/deltares_data/registry.txt b/data/catalogs/deltares_data/registry.txt index aa22a9efc..87fef0706 100644 --- a/data/catalogs/deltares_data/registry.txt +++ b/data/catalogs/deltares_data/registry.txt @@ -1,4 +1,4 @@ -v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef v0.6.0/data_catalog.yml b002767a1cdd24ec8708caa0b658bdeed1cfb93d985efd78f6e9343e00da0f21 +v0.5.0/data_catalog.yml 418f93cebb57c8d165556c874a3cd4077afca1d38e76640273c86b740d18c0ef +v1.0.0/data_catalog.yml 79ab491af13cbe83e1f7680ab502d52276f3257d40479b70d8b4f34cdbeec2d9 v0.7.0/data_catalog.yml 24c77c0c5429353eeedb75d4c0f2dbfa305d81454b2fbf32239ab23166b3b1a6 -v1.0.0/data_catalog.yml 7c637c967faa8547483f7076c99b8b0058e40e26adae525cc838ba9ea472cdc6