From 16bc157785ed6e118fe60ec3f8269ac6d2021bb1 Mon Sep 17 00:00:00 2001
From: DirkEilander <15379728+DirkEilander@users.noreply.github.com>
Date: Thu, 14 Mar 2024 13:45:34 +0100
Subject: [PATCH 01/28] simplify ind method (#189)

* simplify ind method

* add unittest for index

* bump version to 1.0.4.dev
---
 envs/hydromt-sfincs-dev.yml   |  2 +-
 hydromt_sfincs/__init__.py    |  2 +-
 hydromt_sfincs/regulargrid.py |  4 +---
 tests/conftest.py             | 24 ++++++++++++++++++++++++
 tests/test_regulargrid.py     |  8 ++++++++
 5 files changed, 35 insertions(+), 5 deletions(-)
 create mode 100644 tests/test_regulargrid.py

diff --git a/envs/hydromt-sfincs-dev.yml b/envs/hydromt-sfincs-dev.yml
index fc949877..4458ad0c 100644
--- a/envs/hydromt-sfincs-dev.yml
+++ b/envs/hydromt-sfincs-dev.yml
@@ -9,7 +9,7 @@ dependencies:
 - descartes
 - ffmpeg
 - geopandas>=0.8
-- hydromt>=0.9.1
+- hydromt>=0.9.1, <0.10
 - jupyterlab
 - matplotlib
 - nbsphinx
diff --git a/hydromt_sfincs/__init__.py b/hydromt_sfincs/__init__.py
index e4d47b46..9c051e8d 100644
--- a/hydromt_sfincs/__init__.py
+++ b/hydromt_sfincs/__init__.py
@@ -3,7 +3,7 @@
 from os.path import dirname, join, abspath
 
 
-__version__ = "1.0.3"
+__version__ = "1.0.4.dev"
 
 DATADIR = join(dirname(abspath(__file__)), "data")
 
diff --git a/hydromt_sfincs/regulargrid.py b/hydromt_sfincs/regulargrid.py
index b8db21df..e4fe71e0 100644
--- a/hydromt_sfincs/regulargrid.py
+++ b/hydromt_sfincs/regulargrid.py
@@ -103,9 +103,7 @@ def empty_mask(self) -> xr.DataArray:
     def ind(self, mask: np.ndarray) -> np.ndarray:
         """Return indices of active cells in mask."""
         assert mask.shape == (self.nmax, self.mmax)
-        iok = np.where(np.transpose(mask) > 0)
-        iok = (iok[1], iok[0])
-        ind = np.ravel_multi_index(iok, (self.nmax, self.mmax), order="F")
+        ind = np.where(mask.ravel(order="F"))[0]
         return ind
 
     def write_ind(
diff --git a/tests/conftest.py b/tests/conftest.py
index 247d693b..9f95fe29 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -3,13 +3,37 @@
 from os.path import abspath, dirname, join
 
 import pytest
+import numpy as np
 
 from hydromt_sfincs.sfincs import SfincsModel
+from hydromt_sfincs.regulargrid import RegularGrid
 
 TESTDATADIR = join(dirname(abspath(__file__)), "data")
 TESTMODELDIR = join(TESTDATADIR, "sfincs_test")
 
 
+@pytest.fixture
+def reggrid():
+    # create a simple regular grid
+    grid = RegularGrid(
+        x0=318650,
+        y0=5040000,
+        dx=150,
+        dy=150,
+        nmax=84,  # height
+        mmax=36,  # width
+    )
+    return grid
+
+
+@pytest.fixture
+def mask(reggrid):
+    # create a simple mask
+    mask = np.zeros((reggrid.nmax, reggrid.mmax), dtype="u1")
+    mask[2:, 3:-1] = 1
+    return mask
+
+
 @pytest.fixture
 def weirs():
     feats = [
diff --git a/tests/test_regulargrid.py b/tests/test_regulargrid.py
new file mode 100644
index 00000000..c64f88b2
--- /dev/null
+++ b/tests/test_regulargrid.py
@@ -0,0 +1,8 @@
+import numpy as np
+
+
+def test_ind(reggrid, mask):
+    ind = reggrid.ind(mask)
+    assert ind[0] == 254
+    assert ind[-1] == 2939
+    assert ind.size == np.sum(mask > 0)

From d7e1d26a58b6f5687ef47da320ea3b95faaba75a Mon Sep 17 00:00:00 2001
From: DirkEilander <15379728+DirkEilander@users.noreply.github.com>
Date: Wed, 10 Apr 2024 17:16:42 +0200
Subject: [PATCH 02/28] Added functionality to add source points at headwater
 locations (#170)

* [WIP] start with including headwater points

* update tests

* remove river based masking of active cells

* run pre-commit

* remove basin_mask functionality since not used

* fix tests

---------

Co-authored-by: roeldegoede <roeldegoede@outlook.com>
---
 docs/api.rst                                  |   2 +-
 hydromt_sfincs/sfincs.py                      |  88 +++++++---
 hydromt_sfincs/workflows/flwdir.py            | 162 +++++++++++-------
 tests/conftest.py                             |  20 +++
 .../sfincs_test/gis/rivers_inflow.geojson     |  17 +-
 tests/data/sfincs_test/gis/src.geojson        |   6 +-
 tests/data/sfincs_test/sfincs.src             |   6 +-
 tests/test_flwdir.py                          |  65 +++++++
 8 files changed, 260 insertions(+), 106 deletions(-)
 create mode 100644 tests/test_flwdir.py

diff --git a/docs/api.rst b/docs/api.rst
index b55cdf88..63f450e9 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -154,7 +154,7 @@ SFINCS workflows
    workflows.merge_dataarrays
    workflows.burn_river_rect
    workflows.snap_discharge
-   workflows.river_boundary_points
+   workflows.river_source_points
    workflows.river_centerline_from_hydrography
    workflows.landuse
    workflows.cn_to_s
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index ca4cbf47..774079d0 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -787,6 +787,7 @@ def setup_river_inflow(
         first_index: int = 1,
         keep_rivers_geom: bool = False,
         reverse_river_geom: bool = False,
+        src_type: str = "inflow",
     ):
         """Setup discharge (src) points where a river enters the model domain.
 
@@ -833,13 +834,18 @@ def setup_river_inflow(
         reverse_river_geom: bool, optional
             If True, assume that segments in 'rivers' are drawn from downstream to upstream.
             Only used if 'rivers' is not None, By default False
+        src_type: {'inflow', 'headwater'}, optional
+            Source type, by default 'inflow'
+            If 'inflow', return points where the river flows into the model domain.
+            If 'headwater', return all headwater (including inflow) points within the model domain.
 
         See Also
         --------
         setup_discharge_forcing
         setup_discharge_forcing_from_grid
         """
-        da_flwdir, da_uparea, gdf_riv = None, None, None
+        # get hydrography data
+        da_uparea = None
         if hydrography is not None:
             ds = self.data_catalog.get_rasterdataset(
                 hydrography,
@@ -847,9 +853,10 @@ def setup_river_inflow(
                 variables=["uparea", "flwdir"],
                 buffer=5,
             )
-            da_flwdir = ds["flwdir"]
-            da_uparea = ds["uparea"]
-        elif (
+            da_uparea = ds["uparea"]  # reused in river_source_points
+
+        # get river centerlines
+        if (
             isinstance(rivers, str)
             and rivers == "rivers_outflow"
             and rivers in self.geoms
@@ -860,24 +867,35 @@ def setup_river_inflow(
             gdf_riv = self.data_catalog.get_geodataframe(
                 rivers, geom=self.region
             ).to_crs(self.crs)
-        else:
+        elif hydrography is not None:
+            gdf_riv = workflows.river_centerline_from_hydrography(
+                da_flwdir=ds["flwdir"],
+                da_uparea=da_uparea,
+                river_upa=river_upa,
+                river_len=river_len,
+                gdf_mask=self.region,
+            )
+        elif hydrography is None:
             raise ValueError("Either hydrography or rivers must be provided.")
 
-        gdf_src, gdf_riv = workflows.river_boundary_points(
-            region=self.region,
-            res=self.reggrid.dx,
+        # estimate buffer based on model resolution
+        buffer = self.reggrid.dx
+        if self.crs.is_geographic:
+            buffer = buffer * 111111.0
+
+        # get river inflow / headwater source points
+        gdf_src = workflows.river_source_points(
             gdf_riv=gdf_riv,
-            da_flwdir=da_flwdir,
-            da_uparea=da_uparea,
-            river_len=river_len,
+            gdf_mask=self.region,
+            src_type=src_type,
+            buffer=buffer,
             river_upa=river_upa,
-            inflow=True,
+            river_len=river_len,
+            da_uparea=da_uparea,
             reverse_river_geom=reverse_river_geom,
             logger=self.logger,
         )
-        n = len(gdf_src.index)
-        self.logger.info(f"Found {n} river inflow points.")
-        if n == 0:
+        if gdf_src.empty:
             return
 
         # set forcing src pnts
@@ -968,7 +986,8 @@ def setup_river_outflow(
         --------
         setup_mask_bounds
         """
-        da_flwdir, da_uparea, gdf_riv = None, None, None
+        # get hydrography data
+        da_uparea = None
         if hydrography is not None:
             ds = self.data_catalog.get_rasterdataset(
                 hydrography,
@@ -976,9 +995,10 @@ def setup_river_outflow(
                 variables=["uparea", "flwdir"],
                 buffer=5,
             )
-            da_flwdir = ds["flwdir"]
-            da_uparea = ds["uparea"]
-        elif (
+            da_uparea = ds["uparea"]  # reused in river_source_points
+
+        # get river centerlines
+        if (
             isinstance(rivers, str)
             and rivers == "rivers_inflow"
             and rivers in self.geoms
@@ -989,22 +1009,36 @@ def setup_river_outflow(
             gdf_riv = self.data_catalog.get_geodataframe(
                 rivers, geom=self.region
             ).to_crs(self.crs)
+        elif hydrography is not None:
+            gdf_riv = workflows.river_centerline_from_hydrography(
+                da_flwdir=ds["flwdir"],
+                da_uparea=da_uparea,
+                river_upa=river_upa,
+                river_len=river_len,
+                gdf_mask=self.region,
+            )
         else:
             raise ValueError("Either hydrography or rivers must be provided.")
 
-        # TODO reproject region and gdf_riv to utm zone if model crs is geographic
-        gdf_out, gdf_riv = workflows.river_boundary_points(
-            region=self.region,
-            res=self.reggrid.dx,
+        # estimate buffer based on model resolution
+        buffer = self.reggrid.dx
+        if self.crs.is_geographic:
+            buffer = buffer * 111111.0
+
+        # get river inflow / headwater source points
+        gdf_out = workflows.river_source_points(
             gdf_riv=gdf_riv,
-            da_flwdir=da_flwdir,
-            da_uparea=da_uparea,
-            river_len=river_len,
+            gdf_mask=self.region,
+            src_type="outflow",
+            buffer=buffer,
             river_upa=river_upa,
-            inflow=False,
+            river_len=river_len,
+            da_uparea=da_uparea,
             reverse_river_geom=reverse_river_geom,
             logger=self.logger,
         )
+        if gdf_out.empty:
+            return
 
         if len(gdf_out) > 0:
             if "rivwth" in gdf_out.columns:
diff --git a/hydromt_sfincs/workflows/flwdir.py b/hydromt_sfincs/workflows/flwdir.py
index 0756d8f2..e13e33fe 100644
--- a/hydromt_sfincs/workflows/flwdir.py
+++ b/hydromt_sfincs/workflows/flwdir.py
@@ -11,7 +11,7 @@
 logger = logging.getLogger(__name__)
 
 __all__ = [
-    "river_boundary_points",
+    "river_source_points",
     "river_centerline_from_hydrography",
 ]
 
@@ -21,7 +21,7 @@ def river_centerline_from_hydrography(
     da_uparea: xr.DataArray,
     river_upa: float = 10,
     river_len: float = 1e3,
-    mask: gpd.GeoDataFrame = None,
+    gdf_mask: gpd.GeoDataFrame = None,
 ) -> gpd.GeoDataFrame:
     """Returns the centerline of rivers based on a flow direction
     raster data (`da_flwdir`).
@@ -37,7 +37,7 @@ def river_centerline_from_hydrography(
     river_len: float, optional
         Mimimum river length [m] within the model domain to define river cells,
         by default 1000 m.
-    mask: geopandas.GeoDataFrame, optional
+    gdf_mask: geopandas.GeoDataFrame, optional
         Polygon to clip river center lines before calculating the river length,
         by default None.
 
@@ -47,108 +47,142 @@ def river_centerline_from_hydrography(
         River line vector data.
     """
     # get river network from hydrography based on upstream area mask
-    flwdir = hydromt.flw.flwdir_from_da(da_flwdir, mask=da_uparea >= river_upa)
-    gdf_riv = gpd.GeoDataFrame.from_features(flwdir.streams(), crs=da_flwdir.raster.crs)
+    riv_mask = da_uparea >= river_upa
+    if not riv_mask.any():
+        return gpd.GeoDataFrame()
+    flwdir = hydromt.flw.flwdir_from_da(da_flwdir, mask=riv_mask)
+    feats = flwdir.streams(uparea=da_uparea.values)
+    gdf_riv = gpd.GeoDataFrame.from_features(feats, crs=da_flwdir.raster.crs)
     # clip to mask and remove empty geometries
-    if mask is not None:
-        gdf_riv = gdf_riv.to_crs(mask.crs).clip(mask.unary_union)
+    if gdf_mask is not None and isinstance(gdf_mask, gpd.GeoDataFrame):
+        gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.unary_union)
     gdf_riv = gdf_riv[~gdf_riv.is_empty]
     # create river network from gdf to get distance from outlet 'rivlen'
-    gdf_riv["rivlen"] = gdf_riv.geometry.length
+    # length of river segments
+    if gdf_riv.crs.is_geographic:
+        gdf_riv["seglen"] = gdf_riv.to_crs("epsg:3857").geometry.length
+    else:
+        gdf_riv["seglen"] = gdf_riv.geometry.length
+    gdf_riv = gdf_riv[gdf_riv["seglen"] > 0]
+    if gdf_riv.empty or river_len == 0:
+        return gdf_riv
+    # accumulate to get river length from outlet
     flwdir = pyflwdir.from_dataframe(gdf_riv.set_index("idx"), ds_col="idx_ds")
-    gdf_riv["rivlen"] = flwdir.accuflux(gdf_riv["rivlen"].values, direction="down")
+    gdf_riv["rivdst"] = flwdir.accuflux(gdf_riv["seglen"].values, direction="down")
+    # get maximum river length from outlet (at headwater segments) for each river segment
+    gdf_riv["rivlen"] = flwdir.fillnodata(
+        np.where(flwdir.n_upstream == 0, gdf_riv["rivdst"], 0), 0
+    )
+    # filter river network based on total length
     gdf_riv = gdf_riv[gdf_riv["rivlen"] >= river_len]
     return gdf_riv
 
 
-def river_boundary_points(
-    region: gpd.GeoDataFrame,
-    res: float,
-    gdf_riv: gpd.GeoDataFrame = None,
-    da_flwdir: xr.DataArray = None,
-    da_uparea: xr.DataArray = None,
+def river_source_points(
+    gdf_riv: gpd.GeoDataFrame,
+    gdf_mask: gpd.GeoDataFrame,
+    src_type: str = "inflow",
+    buffer: float = 100,
     river_upa: float = 10,
     river_len: float = 1e3,
-    inflow: bool = True,
+    da_uparea: xr.DataArray = None,
     reverse_river_geom: bool = False,
     logger: logging.Logger = logger,
 ) -> Tuple[gpd.GeoDataFrame, gpd.GeoDataFrame]:
     """Returns the locations where a river flows in (`inflow=True`)
-    or out (`inflow=False`) of the model region.
+    or out (`inflow=False`) of the model gdf_mask.
 
     Rivers are based on either a river network vector data (`gdf_riv`) or
     a flow direction raster data (`da_flwdir`).
 
     Parameters
     ----------
-    region: geopandas.GeoDataFrame
-        Polygon of model region of interest.
-    res: float
-        Model resolution [m].
-    gdf_riv: geopandas.GeoDataFrame, optional
+    gdf_riv: geopandas.GeoDataFrame
         River network vector data, by default None.
-    da_flwdir: xarray.DataArray, optional
-        D8 flow direction raster data, by default None.
-    da_uparea: xarray.DataArray, optional
-        River upstream area raster data, by default None.
+        Requires 'uparea' and 'rivlen' attributes to
+        check for river length and upstream area thresholds.
+    gdf_mask: geopandas.GeoDataFrame
+        Polygon of model gdf_mask of interest.
+    src_type: ['inflow', 'outflow', 'headwater'], optional
+        Type of river source points to return, by default 'inflow'.
+        If 'inflow', return points where the river flows into the model domain.
+        If 'outflow', return points where the river flows out of the model domain.
+        If 'headwater', return all headwater (including inflow) points within the model domain.
+    buffer: float, optional
+        Buffer around gdf_mask to select river source points, by default 100 m.
     river_upa : float, optional
         Minimum upstream area threshold for rivers [km2], by default 10.0
     river_len: float, optional
         Mimimum river length [m] within the model domain to define river cells, by default 1000 m.
-    inflow: bool, optional
-        If True, return inflow otherwise outflow boundary points, by default True.
+    da_uparea: xarray.DataArray, optional
+        River upstream area raster data, by default None.
     reverse_river_geom: bool, optional
         If True, assume that segments in 'rivers' are drawn from downstream to upstream.
         Only used if 'rivers' is not None, By default False
 
     Returns
     -------
-    gdf_src, gdf_riv: geopandas.GeoDataFrame
-        In-/outflow points and river line vector data.
+    gdf_pnt: geopandas.GeoDataFrame
+        Source points
     """
-    if not isinstance(region, (gpd.GeoDataFrame, gpd.GeoSeries)) and np.all(
-        region.geometry.type == "Polygon"
+    # data checks
+    if not (
+        isinstance(gdf_mask, (gpd.GeoDataFrame, gpd.GeoSeries))
+        and np.all(np.isin(gdf_mask.geometry.type, ["Polygon", "MultiPolygon"]))
+    ):
+        raise TypeError("gdf_mask must be a GeoDataFrame of Polygons.")
+    if not (
+        isinstance(gdf_riv, (gpd.GeoDataFrame, gpd.GeoSeries))
+        and np.all(np.isin(gdf_riv.geometry.type, ["LineString", "MultiLineString"]))
     ):
-        raise ValueError("Boundary must be a GeoDataFrame of LineStrings.")
-    if res > 0.01 and region.crs.is_geographic:
-        # provide warning
+        raise TypeError("gdf_riv must be a GeoDataFrame of LineStrings.")
+    if src_type not in ["inflow", "outflow", "headwater"]:
+        raise ValueError("src_type must be either 'inflow', 'outflow', or 'headwater'.")
+    if gdf_mask.crs.is_geographic:  # to pseudo mercator
+        gdf_mask = gdf_mask.to_crs("epsg:3857")
+
+    # clip river to model gdf_mask
+    gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.unary_union)
+    # filter river network based on uparea and length
+    if "uparea" in gdf_riv.columns:
+        gdf_riv = gdf_riv[gdf_riv["uparea"] >= river_upa]
+    if "rivlen" in gdf_riv.columns:
+        gdf_riv = gdf_riv[gdf_riv["rivlen"] > river_len]
+    if gdf_riv.empty:
         logger.warning(
-            "The region crs is geographic, while the resolution seems to be in meters."
+            "No rivers matching the uparea and rivlen thresholds found in gdf_riv."
         )
+        return gpd.GeoDataFrame()
 
-    if gdf_riv is None and (da_flwdir is None or da_uparea is None):
-        raise ValueError("Either gdf_riv or da_flwdir and da_uparea must be provided.")
-    elif gdf_riv is None:  # get river network from hydrography
-        gdf_riv = river_centerline_from_hydrography(
-            da_flwdir, da_uparea, river_upa, river_len, mask=region
-        )
-    else:
-        # clip river to model region
-        gdf_riv = gdf_riv.to_crs(region.crs).clip(region.unary_union)
-        # filter river network based on uparea and length
-        if "uparea" in gdf_riv.columns:
-            gdf_riv = gdf_riv[gdf_riv["uparea"] >= river_upa]
-        if "rivlen" in gdf_riv.columns:
-            gdf_riv = gdf_riv[gdf_riv["rivlen"] > river_len]
+    # get source points 1m before the start/end of the river
     # a positive dx results in a point near the start of the line (inflow)
     # a negative dx results in a point near the end of the line (outflow)
-    dx = res / 5 if inflow else -res / 5
-    if reverse_river_geom:
-        dx = -dx
-
-    # move point a bit into the model domain
-    gdf_pnt = gdf_riv.interpolate(dx).to_frame("geometry")
-    # keep points on boundary cells
-    bnd = region.boundary.buffer(res).unary_union  # NOTE should be single geom
-    gdf_pnt = gdf_pnt[gdf_pnt.within(bnd)].reset_index(drop=True)
+    dx = -1 if reverse_river_geom else 1
+    gdf_up = gdf_riv.interpolate(dx).to_frame("geometry")
+    gdf_up["riv_idx"] = gdf_riv.index
+    gdf_ds = gdf_riv.interpolate(-dx).to_frame("geometry")
+    gdf_ds["riv_idx"] = gdf_riv.index
+
+    # get points that do not intersect with up/downstream end of other river segments
+    # use a small buffer of 5m around these points to account for dx and avoid issues with inprecise river geometries
+    if src_type in ["inflow", "headwater"]:
+        pnts_ds = gdf_ds.buffer(5).unary_union
+        gdf_pnt = gdf_up[~gdf_up.intersects(pnts_ds)].reset_index(drop=True)
+    elif src_type == "outflow":
+        pnts_up = gdf_up.buffer(5).unary_union
+        gdf_pnt = gdf_ds[~gdf_ds.intersects(pnts_up)].reset_index(drop=True)
+
+    # get buffer around gdf_mask, in- and outflow points should be within this buffer
+    if src_type in ["inflow", "outflow"]:
+        bnd = gdf_mask.boundary.buffer(buffer).unary_union
+        gdf_pnt = gdf_pnt[gdf_pnt.intersects(bnd)].reset_index(drop=True)
+
+    # log numer of source points
+    logger.info(f"Found {gdf_pnt.index.size} {src_type} points.")
 
     # add uparea attribute if da_uparea is provided
     if da_uparea is not None:
         gdf_pnt["uparea"] = da_uparea.raster.sample(gdf_pnt).values
         gdf_pnt = gdf_pnt.sort_values("uparea", ascending=False).reset_index(drop=True)
-    if "rivwth" in gdf_riv.columns:
-        gdf_pnt = hydromt.gis_utils.nearest_merge(
-            gdf_pnt, gdf_riv, columns=["rivwth"], max_dist=10
-        )
 
-    return gdf_pnt, gdf_riv
+    return gdf_pnt
diff --git a/tests/conftest.py b/tests/conftest.py
index 9f95fe29..94980b57 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,10 +1,12 @@
 """add global fixtures"""
 
 from os.path import abspath, dirname, join
+import numpy as np
 
 import pytest
 import numpy as np
 
+from hydromt import DataCatalog
 from hydromt_sfincs.sfincs import SfincsModel
 from hydromt_sfincs.regulargrid import RegularGrid
 
@@ -61,3 +63,21 @@ def mod(tmpdir):
     mod.read()
     mod.set_root(str(tmpdir), mode="r+")
     return mod
+
+
+@pytest.fixture
+def data_catalog():
+    return DataCatalog("artifact_data")
+
+
+@pytest.fixture
+def hydrography(data_catalog):
+    bbox = [12.64, 45.48, 12.82, 45.59]
+    ds_hydro = data_catalog.get_rasterdataset(
+        "merit_hydro", variables=["flwdir", "uparea", "basins"], bbox=bbox
+    ).load()
+    da_mask = (ds_hydro["basins"] == 210000039).astype(np.uint8)
+    da_mask.raster.set_crs(ds_hydro.raster.crs)
+    da_mask.raster.set_nodata(0)
+    gdf_mask = da_mask.raster.vectorize()
+    return ds_hydro["flwdir"], ds_hydro["uparea"], gdf_mask
diff --git a/tests/data/sfincs_test/gis/rivers_inflow.geojson b/tests/data/sfincs_test/gis/rivers_inflow.geojson
index 75169010..5221ab44 100644
--- a/tests/data/sfincs_test/gis/rivers_inflow.geojson
+++ b/tests/data/sfincs_test/gis/rivers_inflow.geojson
@@ -2,13 +2,14 @@
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 "crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::32633" } },
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diff --git a/tests/data/sfincs_test/gis/src.geojson b/tests/data/sfincs_test/gis/src.geojson
index 027c2d24..544e09cf 100644
--- a/tests/data/sfincs_test/gis/src.geojson
+++ b/tests/data/sfincs_test/gis/src.geojson
@@ -2,8 +2,8 @@
 "type": "FeatureCollection",
 "crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::32633" } },
 "features": [
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-{ "type": "Feature", "properties": { "index": 2, "uparea": 372.2264404296875 }, "geometry": { "type": "Point", "coordinates": [ 324539.39005017321324, 5049031.24278330616653 ] } },
-{ "type": "Feature", "properties": { "index": 3, "uparea": 10.424988746643066 }, "geometry": { "type": "Point", "coordinates": [ 328191.121168049343396, 5048969.163522810675204 ] } }
+{ "type": "Feature", "properties": { "index": 1, "riv_idx": 0, "uparea": 4039.6552734375 }, "geometry": { "type": "Point", "coordinates": [ 321483.19241256051464, 5047503.030107934959233 ] } },
+{ "type": "Feature", "properties": { "index": 2, "riv_idx": 5, "uparea": 372.2264404296875 }, "geometry": { "type": "Point", "coordinates": [ 324538.312838675745297, 5049059.691759831272066 ] } },
+{ "type": "Feature", "properties": { "index": 3, "riv_idx": 2, "uparea": 10.424988746643066 }, "geometry": { "type": "Point", "coordinates": [ 328208.433359648974147, 5048992.429120215587318 ] } }
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 }
diff --git a/tests/data/sfincs_test/sfincs.src b/tests/data/sfincs_test/sfincs.src
index bfe2e7ea..8c3ff568 100644
--- a/tests/data/sfincs_test/sfincs.src
+++ b/tests/data/sfincs_test/sfincs.src
@@ -1,3 +1,3 @@
-321499.2 5047478.8
-324539.4 5049031.2
-328191.1 5048969.2
+321483.2 5047503.0
+324538.3 5049059.7
+328208.4 5048992.4
diff --git a/tests/test_flwdir.py b/tests/test_flwdir.py
new file mode 100644
index 00000000..b6d55b1b
--- /dev/null
+++ b/tests/test_flwdir.py
@@ -0,0 +1,65 @@
+import pytest
+from hydromt_sfincs.workflows.flwdir import (
+    river_centerline_from_hydrography,
+    river_source_points,
+)
+import geopandas as gpd
+import numpy as np
+
+
+def test_river_centerline_from_hydrography(hydrography):
+    # get data
+    da_flwdir, da_uparea, gdf_mask = hydrography
+    # get river centerlines
+    gdf_riv = river_centerline_from_hydrography(da_flwdir, da_uparea, gdf_mask=gdf_mask)
+    # check
+    assert isinstance(gdf_riv, gpd.GeoDataFrame)
+    assert np.isin(["geometry", "rivlen", "uparea"], gdf_riv.columns).all()
+    assert np.isclose(gdf_riv["rivlen"].max(), 19665.50)
+    assert gdf_riv.index.size == 11
+    # no rivers (uparea threshold too high)
+    gdf_riv = river_centerline_from_hydrography(da_flwdir, da_uparea, river_upa=1e6)
+    assert gdf_riv.empty
+    # no rivers (river length threshold too high)
+    gdf_riv = river_centerline_from_hydrography(da_flwdir, da_uparea, river_len=1e6)
+    assert gdf_riv.empty
+
+
+def test_river_source_points(hydrography, data_catalog):
+    # get data
+    da_flwdir, da_uparea, gdf_mask = hydrography
+    gdf_mask = gdf_mask.to_crs("EPSG:32633")
+
+    # test with derived centerline
+    gdf_riv = river_centerline_from_hydrography(da_flwdir, da_uparea, gdf_mask=gdf_mask)
+    kwargs = dict(gdf_riv=gdf_riv, gdf_mask=gdf_mask)
+    gdf_src = river_source_points(src_type="inflow", **kwargs)
+    assert gdf_src.index.size == 3
+    gdf_src = river_source_points(src_type="headwater", **kwargs)
+    assert gdf_src.index.size == 6
+    gdf_src = river_source_points(src_type="outflow", da_uparea=da_uparea, **kwargs)
+    assert gdf_src.index.size == 1
+    assert np.isin(["geometry", "riv_idx", "uparea"], gdf_src.columns).all()
+
+    # test reverse oriented line
+    gdf_riv = data_catalog.get_geodataframe("rivers_lin2019_v1")
+    kwargs = dict(gdf_riv=gdf_riv, gdf_mask=gdf_mask, reverse_river_geom=True)
+    gdf_src = river_source_points(src_type="inflow", **kwargs)
+    assert gdf_src.index.size == 1  # this data only one river
+    assert gdf_src["riv_idx"].values[0] == 38
+    gdf_src = river_source_points(src_type="outflow", **kwargs)
+    assert gdf_src.index.size == 1  # this data only one river
+    assert gdf_src["riv_idx"].values[0] == 34
+    gdf_src = river_source_points(src_type="headwater", **kwargs)
+    assert gdf_src.index.size == 2
+    assert np.isin(38, gdf_src["riv_idx"].values)
+
+    # test errors
+    with pytest.raises(ValueError, match="src_type must be either"):
+        gdf_src = river_source_points(
+            gdf_riv=gdf_riv, gdf_mask=gdf_mask, src_type="wrong"
+        )
+    with pytest.raises(TypeError, match="gdf_mask must be"):
+        gdf_src = river_source_points(gdf_riv=gdf_riv, gdf_mask=gdf_riv)
+    with pytest.raises(TypeError, match="gdf_riv must be"):
+        gdf_src = river_source_points(gdf_riv=gdf_mask, gdf_mask=gdf_mask)

From 75cd92d4aaa8720b8e53047d537e51fdfcddeca9 Mon Sep 17 00:00:00 2001
From: Tim Leijnse <timleynse94@gmail.com>
Date: Wed, 10 Apr 2024 17:47:44 +0200
Subject: [PATCH 03/28] New subgrid formulations including the wet-fraction
 (#160)

* updated subgridregular and added subgridquadtree

subgrid regular now also computes pwet etc. reads and writes to netcdf. sfincs may still need to be updated to account for this.

subgrid quadtree added. still slow because no numba.

both still need testing.

* - Cherrypick changes by mvo in branch quadtree_subgrid, and remove additions of subgrid netcdf and quadtree, so online subgrid v08 changes for regular grid remain

* - patch 'added correct subgrid_q_table' from 'quadtree-subgrid'

* - to overcome error that np.size is not supported in numba

* black formatting

* bugfixes in subgrid.py

* and now with numba on again

* enable read/write netcdf subgrid file, should be backward compatible

* bugfix in workflows.bathymetry

* write output according to what SFINCS (fortran expects)

* major speed-up in writing the netcdf subgrid tables (now not a bottleneck anymore)

* delete old code

* Changed bins to levels. Update of volume table method to reflect this.

* nlevels now input argument for setup_subgrid

* fix tests subgrid rivers; order of geodataframe provided by hydromt changed somehow

* pre commit formatting

* now really according to black, but my version looked prettier ...

* bugfix in reading binary subgrids

* add version to subgrid to make distinction between binary and netcdf

* Merge main into regular_subgrid

* add proper reading of netcdf subgrid

* update subgrid file and fix last test

* update changelog

* pre-commit

* Update docs/changelog.rst

Co-authored-by: DirkEilander <15379728+DirkEilander@users.noreply.github.com>

* improved readability of new subgrid methods

* removed extrapolate option since that is not supported by xarray

* Revert "removed extrapolate option since that is not supported by xarray"

This reverts commit 9409382f335b2e999c248fc1070e322e90362752.

---------

Co-authored-by: Maarten van Ormondt <maarten.vanormondt@deltares.nl>
Co-authored-by: roeldegoede <roeldegoede@outlook.com>
Co-authored-by: roeldegoede <83765910+roeldegoede@users.noreply.github.com>
Co-authored-by: DirkEilander <15379728+DirkEilander@users.noreply.github.com>
Co-authored-by: Kees Nederhoff <kees.nederhoff@deltares.nl>
---
 docs/changelog.rst                       |  17 +
 hydromt_sfincs/sfincs.py                 |  44 +-
 hydromt_sfincs/subgrid.py                | 602 +++++++++++++++++------
 hydromt_sfincs/utils.py                  | 101 ++++
 tests/data/sfincs_test/sfincs.inp        |   2 +-
 tests/data/sfincs_test/sfincs.sbg        | Bin 451792 -> 451792 bytes
 tests/data/sfincs_test/sfincs_subgrid.nc | Bin 0 -> 1121609 bytes
 tests/test_1model_class.py               |  51 ++
 8 files changed, 668 insertions(+), 149 deletions(-)
 create mode 100644 tests/data/sfincs_test/sfincs_subgrid.nc

diff --git a/docs/changelog.rst b/docs/changelog.rst
index cb8b1682..f2d17a17 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -6,6 +6,23 @@ Distinction is made between new methods (Added), changes to existing methods (Ch
 The format is based on `Keep a Changelog`_, and this project adheres to
 `Semantic Versioning`_.
 
+v1.0.4 (Unreleased)
+===================
+
+Added
+-----
+- improved subgrid tables that account for the wet fraction of the cell (#160)
+
+Changed
+-------
+- improved subgrid tables are saved as NetCDF (#160)
+
+Fixed
+-----
+- rounding errors in `workflows.tile_window` which resulted in erronuous slippy-tiles (#178)
+- "active geometry column to use has not been set" error for GeoDataFrame (#180)
+
+
 v1.0.3 (3 January 2024)
 =======================
 This release contains several changes and fixes. Most notably, models with a geographical CRS can now be build.
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 774079d0..5a22a067 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -23,6 +23,7 @@
 
 from . import DATADIR, plots, utils, workflows
 from .regulargrid import RegularGrid
+from .subgrid import SubgridTableRegular
 from .sfincs_input import SfincsInput
 
 __all__ = ["SfincsModel"]
@@ -614,7 +615,8 @@ def setup_subgrid(
         datasets_rgh: List[dict] = [],
         datasets_riv: List[dict] = [],
         buffer_cells: int = 0,
-        nbins: int = 10,
+        nlevels: int = 10,
+        nbins: int = None,
         nr_subgrid_pixels: int = 20,
         nrmax: int = 2000,  # blocksize
         max_gradient: float = 5.0,
@@ -695,6 +697,9 @@ def setup_subgrid(
             by default 0
         nbins : int, optional
             Number of bins in which hypsometry is subdivided, by default 10
+            Note that this keyword is deprecated and will be removed in future versions.
+        nlevels: int, optional
+            Number of levels to describe hypsometry, by default 10
         nr_subgrid_pixels : int, optional
             Number of subgrid pixels per computational cell, by default 20
         nrmax : int, optional
@@ -742,6 +747,12 @@ def setup_subgrid(
         else:
             highres_dir = None
 
+        if nbins is not None:
+            logger.warning(
+                "Keyword nbins is deprecated and will be removed in future versions. Please use nlevels instead."
+            )
+            nlevels = nbins
+
         if self.grid_type == "regular":
             self.reggrid.subgrid.build(
                 da_mask=self.mask,
@@ -749,7 +760,7 @@ def setup_subgrid(
                 datasets_rgh=datasets_rgh,
                 datasets_riv=datasets_riv,
                 buffer_cells=buffer_cells,
-                nbins=nbins,
+                nlevels=nlevels,
                 nr_subgrid_pixels=nr_subgrid_pixels,
                 nrmax=nrmax,
                 max_gradient=max_gradient,
@@ -768,8 +779,11 @@ def setup_subgrid(
         elif self.grid_type == "quadtree":
             pass
 
-        if "sbgfile" not in self.config:  # only add sbgfile if not already present
-            self.config.update({"sbgfile": "sfincs.sbg"})
+        # when building a new subgrid table, always update config
+        # NOTE from now onwards, netcdf subgrid tables are used
+        self.config.update({"sbgfile": "sfincs_subgrid.nc"})
+        # if "sbgfile" not in self.config:  # only add sbgfile if not already present
+        #     self.config.update({"sbgfile": "sfincs.sbg"})
         # subgrid is used so no depfile or manningfile needed
         if "depfile" in self.config:
             self.config.pop("depfile")  # remove depfile from config
@@ -2886,7 +2900,16 @@ def read_subgrid(self):
                 self.logger.warning(f"sbgfile not found at {fn}")
                 return
 
-            self.reggrid.subgrid.load(file_name=fn, mask=self.mask)
+            # re-initialize subgrid (different variables for old/new version)
+            # TODO: come up with a better way to handle this
+            self.reggrid.subgrid = SubgridTableRegular()
+            self.subgrid = xr.Dataset()
+
+            # read subgrid file
+            if fn.parts[-1].endswith(".sbg"):  # read binary file
+                self.reggrid.subgrid.read_binary(file_name=fn, mask=self.mask)
+            else:  # read netcdf file
+                self.reggrid.subgrid.read(file_name=fn, mask=self.mask)
             self.subgrid = self.reggrid.subgrid.to_xarray(
                 dims=self.mask.raster.dims, coords=self.mask.raster.coords
             )
@@ -2897,9 +2920,16 @@ def write_subgrid(self):
 
         if self.subgrid:
             if "sbgfile" not in self.config:
-                self.set_config("sbgfile", "sfincs.sbg")
+                # apparently no subgrid was read, so set default filename
+                self.set_config("sbgfile", "sfincs_subgrid.nc")
+
             fn = self.get_config("sbgfile", abs_path=True)
-            self.reggrid.subgrid.save(file_name=fn, mask=self.mask)
+            if fn.parts[-1].endswith(".sbg"):
+                # write binary file
+                self.reggrid.subgrid.write_binary(file_name=fn, mask=self.mask)
+            else:
+                # write netcdf file
+                self.reggrid.subgrid.write(file_name=fn, mask=self.mask)
 
     def read_geoms(self):
         """Read geometry files and save to `geoms` attribute.
diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index 22130548..3fda9464 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -18,13 +18,188 @@
 
 
 class SubgridTableRegular:
-    def __init__(self, version=0):
+    def __init__(self, version=1):
         # A regular subgrid table contains only for cells with msk>0
         self.version = version
 
-    def load(self, file_name, mask):
+    # new way of reading netcdf subgrid tables
+    def read(self, file_name, mask):
+        """Load subgrid table from netcdf file."""
+
+        self.version = 1
+
+        # Read data from netcdf file with xarray
+        ds = xr.open_dataset(file_name)
+
+        # transpose to have level as first dimension
+        ds = ds.transpose("levels", "npuv", "np")
+
+        # grid dimensions
+        grid_dim = mask.shape
+
+        # get number of levels, point and uv points
+        self.nlevels, self.nr_cells, self.nr_uv_points = (
+            ds.dims["levels"],
+            ds.dims["np"],
+            ds.dims["npuv"],
+        )
+
+        # find indices of active cells
+        index_nm, index_mu1, index_nu1 = utils.find_uv_indices(mask)
+        active_indices = np.where(index_nm > -1)[0]
+        active_indices_u = np.where(index_mu1 > -1)[0]
+        active_indices_v = np.where(index_nu1 > -1)[0]
+
+        # convert 1D indices to 2D indices
+        active_z = np.unravel_index(active_indices, grid_dim, order="F")
+        active_u = np.unravel_index(active_indices_u, grid_dim, order="F")
+        active_v = np.unravel_index(active_indices_v, grid_dim, order="F")
+
+        # Initialize the data-arrays
+        # Z points
+        self.z_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.z_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.z_volmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.z_level = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+
+        # U points
+        self.u_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.u_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.u_havg = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.u_nrep = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.u_pwet = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.u_ffit = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_navg = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+
+        # V points
+        self.v_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.v_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+        self.v_havg = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.v_nrep = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.v_pwet = np.full(
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
+        self.v_ffit = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_navg = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+
+        # Now read the data and add it to the data-arrays
+        # use index_nm of the active cells in the new dataset
+        self.z_zmin[active_z] = ds["z_zmin"].values.flatten()
+        self.z_zmax[active_z] = ds["z_zmax"].values.flatten()
+        self.z_volmax[active_z] = ds["z_volmax"].values.flatten()
+        for ilevel in range(self.nlevels):
+            self.z_level[ilevel, active_z[0], active_z[1]] = ds["z_level"][
+                ilevel
+            ].values.flatten()
+
+        # now use index_mu1 and index_nu1 to put the values of the active cells in the new dataset
+        var_list = ["zmin", "zmax", "ffit", "navg"]
+        for var in var_list:
+            uv_var = ds["uv_" + var].values.flatten()
+            self.u_zmin[active_u] = uv_var[index_mu1[active_indices_u]]
+            self.v_zmin[active_v] = uv_var[index_nu1[active_indices_v]]
+
+        var_list_levels = ["havg", "nrep", "pwet"]
+        for var in var_list_levels:
+            for ilevel in range(self.nlevels):
+                uv_var = ds["uv_" + var][ilevel].values.flatten()
+                self.u_havg[ilevel, active_u[0], active_u[1]] = uv_var[
+                    index_mu1[active_indices_u]
+                ]
+                self.v_havg[ilevel, active_v[0], active_v[1]] = uv_var[
+                    index_nu1[active_indices_v]
+                ]
+
+        # close the dataset
+        ds.close()
+
+    # new way of writing netcdf subgrid tables
+    def write(self, file_name, mask):
+        """Write subgrid table to netcdf file for a regular grid with given mask.
+        Values are only written for active cells (mask > 0)."""
+
+        ds = self.to_xarray(dims=mask.raster.dims, coords=mask.raster.coords)
+
+        # Need to transpose to match the FORTRAN convention in SFINCS
+        ds = ds.transpose("levels", "x", "y")
+
+        # find indices of active cells
+        index_nm, index_mu1, index_nu1 = utils.find_uv_indices(mask)
+
+        # get number of levels
+        nlevels = self.nlevels
+
+        active_cells = index_nm > -1
+        active_indices = np.where(active_cells)[0]
+
+        # get nr of active points (where index_nm > -1)
+        nr_z_points = index_nm.max() + 1
+        nr_uv_points = max(index_mu1.max(), index_nu1.max()) + 1
+
+        # Make a new xarray dataset where we only keep the values of the active cells (index_nm > -1)
+        # use index_nm to put the values of the active cells in the new dataset
+        ds_new = xr.Dataset(attrs={"_FillValue": np.nan})
+
+        # Z points
+        variables = ["z_zmin", "z_zmax", "z_volmax"]
+        for var in variables:
+            ds_new[var] = xr.DataArray(
+                ds[var].values.flatten()[active_cells], dims=("np")
+            )
+
+        z_level = np.zeros((nlevels, nr_z_points))
+        for ilevel in range(nlevels):
+            z_level[ilevel] = ds["z_level"][ilevel].values.flatten()[active_cells]
+        ds_new["z_level"] = xr.DataArray(z_level, dims=("levels", "np"))
+
+        # u and v points
+        var_list = ["zmin", "zmax", "ffit", "navg"]
+        for var in var_list:
+            uv_var = np.zeros(nr_uv_points)
+            uv_var[index_mu1[active_indices]] = ds["u_" + var].values.flatten()[
+                active_cells
+            ]
+            uv_var[index_nu1[active_indices]] = ds["v_" + var].values.flatten()[
+                active_cells
+            ]
+            ds_new[f"uv_{var}"] = xr.DataArray(uv_var, dims=("npuv"))
+
+        var_list_levels = ["havg", "nrep", "pwet"]
+        for var in var_list_levels:
+            uv_var = np.zeros((nlevels, nr_uv_points))
+            for ilevel in range(nlevels):
+                uv_var[ilevel, index_mu1[active_indices]] = ds["u_" + var][
+                    ilevel
+                ].values.flatten()[active_cells]
+                uv_var[ilevel, index_nu1[active_indices]] = ds["v_" + var][
+                    ilevel
+                ].values.flatten()[active_cells]
+            ds_new[f"uv_{var}"] = xr.DataArray(uv_var, dims=("levels", "npuv"))
+
+        # ensure levels is last dimension
+        ds_new = ds_new.transpose("npuv", "np", "levels")
+
+        # Write to netcdf file
+        ds_new.to_netcdf(file_name)
+
+    # Following remains for backward compatibility, but should soon not be used anymore
+    def read_binary(self, file_name, mask):
         """Load subgrid table from file for a regular grid with given mask."""
 
+        self.version = 0
+
         if isinstance(mask, xr.DataArray):
             mask = mask.values
 
@@ -40,9 +215,11 @@ def load(self, file_name, mask):
 
         # File version
         # self.version = np.fromfile(file, dtype=np.int32, count=1)[0]
+
+        # Initialize the data-arrays
         self.nr_cells = np.fromfile(file, dtype=np.int32, count=1)[0]
         self.nr_uv_points = np.fromfile(file, dtype=np.int32, count=1)[0]
-        self.nbins = np.fromfile(file, dtype=np.int32, count=1)[0]
+        self.nlevels = np.fromfile(file, dtype=np.int32, count=1)[0]
 
         # Z points
         self.z_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
@@ -50,43 +227,41 @@ def load(self, file_name, mask):
         # self.z_zmean = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.z_volmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.z_depth = np.full(
-            (self.nbins, *grid_dim), fill_value=np.nan, dtype=np.float32
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
         )
 
         # U points
         self.u_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.u_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.u_hrep = np.full(
-            (self.nbins, *grid_dim), fill_value=np.nan, dtype=np.float32
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
         )
         self.u_navg = np.full(
-            (self.nbins, *grid_dim), fill_value=np.nan, dtype=np.float32
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
         )
 
         # V points
         self.v_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.v_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.v_hrep = np.full(
-            (self.nbins, *grid_dim), fill_value=np.nan, dtype=np.float32
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
         )
         self.v_navg = np.full(
-            (self.nbins, *grid_dim), fill_value=np.nan, dtype=np.float32
+            (self.nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
         )
 
+        # Now read the data
         self.z_zmin[iok[0], iok[1]] = np.fromfile(
             file, dtype=np.float32, count=self.nr_cells
         )
         self.z_zmax[iok[0], iok[1]] = np.fromfile(
             file, dtype=np.float32, count=self.nr_cells
         )
-        # self.z_zmean[iok[0], iok[1]] = np.fromfile(
-        #     file, dtype=np.float32, count=self.nr_cells
-        # )
         self.z_volmax[iok[0], iok[1]] = np.fromfile(
             file, dtype=np.float32, count=self.nr_cells
         )
-        for ibin in range(self.nbins):
-            self.z_depth[ibin, iok[0], iok[1]] = np.fromfile(
+        for ilevel in range(self.nlevels):
+            self.z_depth[ilevel, iok[0], iok[1]] = np.fromfile(
                 file, dtype=np.float32, count=self.nr_cells
             )
 
@@ -97,12 +272,12 @@ def load(self, file_name, mask):
             file, dtype=np.float32, count=self.nr_cells
         )
         _ = np.fromfile(file, dtype=np.float32, count=self.nr_cells)  # not used
-        for ibin in range(self.nbins):
-            self.u_hrep[ibin, iok[0], iok[1]] = np.fromfile(
+        for ilevel in range(self.nlevels):
+            self.u_hrep[ilevel, iok[0], iok[1]] = np.fromfile(
                 file, dtype=np.float32, count=self.nr_cells
             )
-        for ibin in range(self.nbins):
-            self.u_navg[ibin, iok[0], iok[1]] = np.fromfile(
+        for ilevel in range(self.nlevels):
+            self.u_navg[ilevel, iok[0], iok[1]] = np.fromfile(
                 file, dtype=np.float32, count=self.nr_cells
             )
 
@@ -113,19 +288,21 @@ def load(self, file_name, mask):
             file, dtype=np.float32, count=self.nr_cells
         )
         _ = np.fromfile(file, dtype=np.float32, count=self.nr_cells)  # not used
-        for ibin in range(self.nbins):
-            self.v_hrep[ibin, iok[0], iok[1]] = np.fromfile(
+        for ilevel in range(self.nlevels):
+            self.v_hrep[ilevel, iok[0], iok[1]] = np.fromfile(
                 file, dtype=np.float32, count=self.nr_cells
             )
-        for ibin in range(self.nbins):
-            self.v_navg[ibin, iok[0], iok[1]] = np.fromfile(
+        for ilevel in range(self.nlevels):
+            self.v_navg[ilevel, iok[0], iok[1]] = np.fromfile(
                 file, dtype=np.float32, count=self.nr_cells
             )
 
         file.close()
 
-    def save(self, file_name, mask):
+    # Following remains for backward compatibility, but should soon not be used anymore
+    def write_binary(self, file_name, mask):
         """Save the subgrid data to a binary file."""
+
         if isinstance(mask, xr.DataArray):
             mask = mask.values
 
@@ -142,7 +319,7 @@ def save(self, file_name, mask):
         # file.write(np.int32(self.version))  # version
         file.write(np.int32(np.size(ind)))  # Nr of active points
         file.write(np.int32(1))  # min
-        file.write(np.int32(self.nbins))
+        file.write(np.int32(self.nlevels))
 
         # Z
         v = self.z_zmin[iok]
@@ -151,8 +328,8 @@ def save(self, file_name, mask):
         file.write(np.float32(v))
         v = self.z_volmax[iok]
         file.write(np.float32(v))
-        for ibin in range(self.nbins):
-            v = np.squeeze(self.z_depth[ibin, :, :])[iok]
+        for ilevel in range(self.nlevels):
+            v = np.squeeze(self.z_depth[ilevel, :, :])[iok]
             file.write(np.float32(v))
 
         # U
@@ -162,11 +339,11 @@ def save(self, file_name, mask):
         file.write(np.float32(v))
         dhdz = np.full(np.shape(v), 1.0)
         file.write(np.float32(dhdz))  # Not used in SFINCS anymore
-        for ibin in range(self.nbins):
-            v = np.squeeze(self.u_hrep[ibin, :, :])[iok]
+        for ilevel in range(self.nlevels):
+            v = np.squeeze(self.u_hrep[ilevel, :, :])[iok]
             file.write(np.float32(v))
-        for ibin in range(self.nbins):
-            v = np.squeeze(self.u_navg[ibin, :, :])[iok]
+        for ilevel in range(self.nlevels):
+            v = np.squeeze(self.u_navg[ilevel, :, :])[iok]
             file.write(np.float32(v))
 
         # V
@@ -175,26 +352,28 @@ def save(self, file_name, mask):
         v = self.v_zmax[iok]
         file.write(np.float32(v))
         file.write(np.float32(dhdz))  # Not used in SFINCS anymore
-        for ibin in range(self.nbins):
-            v = np.squeeze(self.v_hrep[ibin, :, :])[iok]
+        for ilevel in range(self.nlevels):
+            v = np.squeeze(self.v_hrep[ilevel, :, :])[iok]
             file.write(np.float32(v))
-        for ibin in range(self.nbins):
-            v = np.squeeze(self.v_navg[ibin, :, :])[iok]
+        for ilevel in range(self.nlevels):
+            v = np.squeeze(self.v_navg[ilevel, :, :])[iok]
             file.write(np.float32(v))
 
         file.close()
 
+    # This is the new way of building subgrid tables, that will end up in netcdf files
     def build(
         self,
         da_mask: xr.DataArray,
         datasets_dep: list[dict],
         datasets_rgh: list[dict] = [],
         datasets_riv: list[dict] = [],
-        nbins=10,
-        nr_subgrid_pixels=20,
-        nrmax=2000,
-        max_gradient=5.0,
-        z_minimum=-99999.0,
+        nlevels: int = 10,
+        nr_subgrid_pixels: int = 20,
+        nrmax: int = 2000,
+        max_gradient: float = 5.0,
+        z_minimum: float = -99999.0,
+        huthresh: float = 0.01,
         manning_land: float = 0.04,
         manning_sea: float = 0.02,
         rgh_lev_land: float = 0.0,
@@ -235,8 +414,8 @@ def build(
               "rivwth" in river is not used and can be omitted.
             * arguments for :py:function:~hydromt.workflows.bathymetry.burn_river_rect
             e.g.: [{'gdf_riv': <gpd.GeoDataFrame>, 'gdf_riv_mask': <gpd.GeoDataFrame>}]
-        nbins : int, optional
-            Number of bins in which hypsometry is subdivided, by default 10
+        nlevels : int, optional
+            Number of levels in which hypsometry is subdivided, by default 10
         nr_subgrid_pixels : int, optional
             Number of subgrid pixels per computational cell, by default 20
         nrmax : int, optional
@@ -247,6 +426,8 @@ def build(
             prevent numerical stability problems, by default 5.0
         z_minimum : float, optional
             Minimum depth in the subgrid tables, by default -99999.0
+        huthresh : float, optional
+            Threshold depth in SFINCS model, by default 0.01 m
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea,
             by default 0.04 and 0.02 s.m-1/3
@@ -269,16 +450,18 @@ def build(
             are stored, by default None
         """
 
+        self.version = 1
+
         if write_dep_tif or write_man_tif:
             assert highres_dir is not None, "highres_dir must be specified"
 
         refi = nr_subgrid_pixels
-        self.nbins = nbins
+        self.nlevels = nlevels
         grid_dim = da_mask.raster.shape
         x_dim, y_dim = da_mask.raster.x_dim, da_mask.raster.y_dim
 
         # determine the output dimensions and transform to match da_mask grid
-        # NOTE: this is only usef for writing the cloud optimized geotiffs
+        # NOTE: this is only used for writing the cloud optimized geotiffs
         output_width = da_mask.sizes[x_dim] * nr_subgrid_pixels
         output_height = da_mask.sizes[y_dim] * nr_subgrid_pixels
         output_transform = da_mask.raster.transform * da_mask.raster.transform.scale(
@@ -320,19 +503,27 @@ def build(
         self.z_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         # self.z_zmean = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.z_volmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-        self.z_depth = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.z_level = np.full(
+            (nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32
+        )
 
         # U points
         self.u_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.u_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-        self.u_hrep = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
-        self.u_navg = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_havg = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_nrep = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_pwet = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_ffit = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.u_navg = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
 
         # V points
         self.v_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
         self.v_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-        self.v_hrep = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
-        self.v_navg = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_havg = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_nrep = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_pwet = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_ffit = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
+        self.v_navg = np.full((grid_dim), fill_value=np.nan, dtype=np.float32)
 
         dx, dy = da_mask.raster.res
         dxp = dx / refi  # size of subgrid pixel
@@ -499,25 +690,32 @@ def build(
                     self.z_zmin[sn, sm],
                     self.z_zmax[sn, sm],
                     self.z_volmax[sn, sm],
-                    self.z_depth[:, sn, sm],
+                    self.z_level[:, sn, sm],
                     self.u_zmin[sn, sm],
                     self.u_zmax[sn, sm],
-                    self.u_hrep[:, sn, sm],
-                    self.u_navg[:, sn, sm],
+                    self.u_havg[:, sn, sm],
+                    self.u_nrep[:, sn, sm],
+                    self.u_pwet[:, sn, sm],
+                    self.u_ffit[sn, sm],
+                    self.u_navg[sn, sm],
                     self.v_zmin[sn, sm],
                     self.v_zmax[sn, sm],
-                    self.v_hrep[:, sn, sm],
-                    self.v_navg[:, sn, sm],
-                ) = process_tile(
+                    self.v_havg[:, sn, sm],
+                    self.v_nrep[:, sn, sm],
+                    self.v_pwet[:, sn, sm],
+                    self.v_ffit[sn, sm],
+                    self.v_navg[sn, sm],
+                ) = process_tile_regular(
                     da_mask_block.values,
                     da_dep.values,
                     da_man.values,
                     dxp,
                     dyp,
                     refi,
-                    nbins,
+                    nlevels,
                     yg,
                     max_gradient,
+                    huthresh,
                     da_mask.raster.crs.is_geographic,
                 )
 
@@ -541,13 +739,36 @@ def build(
             )
 
     def to_xarray(self, dims, coords):
-        """Convert subgrid class to xarray dataset."""
-        ds_sbg = xr.Dataset(coords={"bins": np.arange(self.nbins), **coords})
+        """Convert old binary subgrid class to xarray dataset."""
+        ds_sbg = xr.Dataset(coords={"levels": np.arange(self.nlevels), **coords})
         ds_sbg.attrs.update({"_FillValue": np.nan})
 
-        zlst2 = ["z_zmin", "z_zmax", "z_zmin", "z_volmax"]  # "z_zmean",
-        uvlst2 = ["u_zmin", "u_zmax", "v_zmin", "v_zmax"]
-        lst3 = ["z_depth", "u_hrep", "u_navg", "v_hrep", "v_navg"]
+        zlst2 = ["z_zmin", "z_zmax", "z_volmax"]
+        if self.version == 0:
+            uvlst2 = ["u_zmin", "u_zmax", "v_zmin", "v_zmax"]
+            lst3 = ["z_depth", "u_hrep", "u_navg", "v_hrep", "v_navg"]
+
+        elif self.version == 1:
+            uvlst2 = [
+                "u_zmin",
+                "u_zmax",
+                "u_ffit",
+                "u_navg",
+                "v_zmin",
+                "v_zmax",
+                "v_ffit",
+                "v_navg",
+            ]
+            lst3 = [
+                "z_level",
+                "u_havg",
+                "u_nrep",
+                "u_pwet",
+                "v_havg",
+                "v_nrep",
+                "v_pwet",
+            ]
+
         # 2D arrays
         for name in zlst2 + uvlst2:
             if hasattr(self, name):
@@ -555,7 +776,7 @@ def to_xarray(self, dims, coords):
         # 3D arrays
         for name in lst3:
             if hasattr(self, name):
-                ds_sbg[name] = xr.Variable(("bins", *dims), getattr(self, name))
+                ds_sbg[name] = xr.Variable(("levels", *dims), getattr(self, name))
         return ds_sbg
 
     def from_xarray(self, ds_sbg):
@@ -565,29 +786,44 @@ def from_xarray(self, ds_sbg):
 
 
 @njit
-def process_tile(
-    mask, zg, manning_grid, dxp, dyp, refi, nbins, yg, max_gradient, is_geographic=False
+def process_tile_regular(
+    mask,
+    zg,
+    manning_grid,
+    dxp,
+    dyp,
+    refi,
+    nlevels,
+    yg,
+    max_gradient,
+    huthresh,
+    is_geographic=False,
 ):
     """calculate subgrid properties for a single tile"""
     # Z points
     grid_dim = mask.shape
     z_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
     z_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-    # z_zmean = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
     z_volmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-    z_depth = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    z_level = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
 
     # U points
     u_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
     u_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-    u_hrep = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
-    u_navg = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    u_havg = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    u_nrep = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    u_pwet = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    u_ffit = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+    u_navg = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
 
     # V points
     v_zmin = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
     v_zmax = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
-    v_hrep = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
-    v_navg = np.full((nbins, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    v_havg = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    v_nrep = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    v_pwet = np.full((nlevels, *grid_dim), fill_value=np.nan, dtype=np.float32)
+    v_ffit = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
+    v_navg = np.full(grid_dim, fill_value=np.nan, dtype=np.float32)
 
     # Loop through all active cells in this block
     for n in range(mask.shape[0]):  # row
@@ -612,12 +848,12 @@ def process_tile(
             zgc = zg[nn : nn + refi, mm : mm + refi]
             zvmin = -20.0
             z, v, zmin, zmax = subgrid_v_table(
-                zgc.flatten(), dxpm, dypm, nbins, zvmin, max_gradient
+                zgc.flatten(), dxpm, dypm, nlevels, zvmin, max_gradient
             )
             z_zmin[n, m] = zmin
             z_zmax[n, m] = zmax
             z_volmax[n, m] = v[-1]
-            z_depth[:, n, m] = z[1:]
+            z_level[:, n, m] = z
 
             # Now the U/V points
             # U
@@ -627,40 +863,51 @@ def process_tile(
             zgu = np.transpose(zgu)
             manning = manning_grid[nn : nn + refi, mm : mm + refi]
             manning = np.transpose(manning)
-            zmin, zmax, hrep, navg, zz = subgrid_q_table(
-                zgu.flatten(), manning.flatten(), nbins
+            zmin, zmax, havg, nrep, pwet, ffit, navg, zz = subgrid_q_table(
+                zgu.flatten(), manning.flatten(), nlevels, huthresh
             )
             u_zmin[n, m] = zmin
             u_zmax[n, m] = zmax
-            u_hrep[:, n, m] = hrep
-            u_navg[:, n, m] = navg
+            u_havg[:, n, m] = havg
+            u_nrep[:, n, m] = nrep
+            u_pwet[:, n, m] = pwet
+            u_ffit[n, m] = ffit
+            u_navg[n, m] = navg
 
             # V
             nn = n * refi + int(0.5 * refi)
             mm = m * refi
             zgu = zg[nn : nn + refi, mm : mm + refi]
             manning = manning_grid[nn : nn + refi, mm : mm + refi]
-            zmin, zmax, hrep, navg, zz = subgrid_q_table(
-                zgu.flatten(), manning.flatten(), nbins
+            zmin, zmax, havg, nrep, pwet, ffit, navg, zz = subgrid_q_table(
+                zgu.flatten(), manning.flatten(), nlevels, huthresh
             )
             v_zmin[n, m] = zmin
             v_zmax[n, m] = zmax
-            v_hrep[:, n, m] = hrep
-            v_navg[:, n, m] = navg
+            v_havg[:, n, m] = havg
+            v_nrep[:, n, m] = nrep
+            v_pwet[:, n, m] = pwet
+            v_ffit[n, m] = ffit
+            v_navg[n, m] = navg
 
     return (
         z_zmin,
         z_zmax,
-        # z_zmean,
         z_volmax,
-        z_depth,
+        z_level,
         u_zmin,
         u_zmax,
-        u_hrep,
+        u_havg,
+        u_nrep,
+        u_pwet,
+        u_ffit,
         u_navg,
         v_zmin,
         v_zmax,
-        v_hrep,
+        v_havg,
+        v_nrep,
+        v_pwet,
+        v_ffit,
         v_navg,
     )
 
@@ -684,7 +931,7 @@ def subgrid_v_table(
     elevation: np.ndarray,
     dx: float,
     dy: float,
-    nbins: int,
+    nlevels: int,
     zvolmin: float,
     max_gradient: float,
 ):
@@ -700,8 +947,8 @@ def subgrid_v_table(
         x-directional cell size (typically not known at this level) [m]
     dy: float
         y-directional cell size (typically not known at this level) [m]
-    nbins: int
-        number of bins to use for the hypsometric curve
+    nlevels: int
+        number of levels to use for the hypsometric curve
     zvolmin: float
         minimum elevation value to use for volume calculation (typically -20 m)
     max_gradient: float
@@ -731,10 +978,10 @@ def subgrid_v_table(
     volume = np.zeros_like(depth)
     volume[1:] = np.cumsum((np.diff(depth) * dx * dy) * np.arange(1, depth.size))
 
-    # Resample volumes to discrete bins
-    steps = np.arange(nbins + 1) / nbins
+    # Resample volumes to discrete levels
+    steps = np.arange(nlevels) / (nlevels - 1)
     V = steps * volume.max()
-    dvol = volume.max() / nbins
+    dvol = volume.max() / (nlevels - 1)
     # scipy not supported in numba jit
     # z = interpolate.interp1d(volume, ele_sort)(V)
     z = np.interp(V, volume, ele_sort)
@@ -742,7 +989,7 @@ def subgrid_v_table(
     n = 0
     while (
         dzdh.max() > max_gradient and not (isclose(dzdh.max(), max_gradient))
-    ) and n < nbins:
+    ) and n < nlevels:
         # reshape until gradient is satisfactory
         idx = np.where(dzdh == dzdh.max())[0]
         z[idx + 1] = z[idx] + max_gradient * (dvol / a)
@@ -752,63 +999,136 @@ def subgrid_v_table(
 
 
 @njit
-def subgrid_q_table(elevation: np.ndarray, manning: np.ndarray, nbins: int):
+def subgrid_q_table(
+    elevation: np.ndarray, manning: np.ndarray, nlevels: int, huthresh: float
+):
     """
-    map elevation values into a hypsometric hydraulic radius - depth relationship
-
+    map vector of elevation values into a hypsometric hydraulic radius - depth relationship for one u/v point
     Parameters
     ----------
-    elevation: np.ndarray
-        subgrid elevation values for one grid cell [m]
-    manning: np.ndarray
-        subgrid manning roughness values for one grid cell [s m^(-1/3)]
-    nbins: int
-        number of bins to use for the hypsometric curve
-
+    elevation : np.ndarray (nr of pixels in one cell) containing subgrid elevation values for one grid cell [m]
+    manning : np.ndarray (nr of pixels in one cell) containing subgrid manning roughness values for one grid cell [s m^(-1/3)]
+    nlevels : int, number of vertical levels [-]
+    huthresh : float, threshold depth [m]
     Returns
     -------
-    zmin, zmax: float
-        minimum and maximum elevation values used for hypsometric curve
-    hrep, navg, zz: np.ndarray
-        conveyance depth, average manning roughness, and elevation values
-        for each bin
+    zmin : float, minimum elevation [m]
+    zmax : float, maximum elevation [m]
+    havg : np.ndarray (nlevels) grid-average depth for vertical levels [m]
+    nrep : np.ndarray (nlevels) representative roughness for vertical levels [m1/3/s] ?
+    pwet : np.ndarray (nlevels) wet fraction for vertical levels [-] ?
+    navg : float, grid-average Manning's n [m 1/3 / s]
+    ffit : float, fitting coefficient [-]
+    zz   : np.ndarray (nlevels) elevation of vertical levels [m]
     """
-    hrep = np.zeros(nbins, dtype=np.float32)
-    navg = np.zeros(nbins, dtype=np.float32)
-    zz = np.zeros(nbins, dtype=np.float32)
+    # Initialize output arrays
+    havg = np.zeros(nlevels)
+    nrep = np.zeros(nlevels)
+    pwet = np.zeros(nlevels)
+    zz = np.zeros(nlevels)
 
     n = int(elevation.size)  # Nr of pixels in grid cell
-    n05 = int(n / 2)
-
-    zmin_a = np.min(elevation[0:n05])
-    zmax_a = np.max(elevation[0:n05])
-
-    zmin_b = np.min(elevation[n05:])
-    zmax_b = np.max(elevation[n05:])
-
-    zmin = max(zmin_a, zmin_b)
-    zmax = max(zmax_a, zmax_b)
-
-    # Make sure zmax is a bit higher than zmin
-    if zmax < zmin + 0.01:
-        zmax += 0.01
-
-    # Determine bin size
-    dbin = (zmax - zmin) / nbins
-
-    # Loop through bins
-    for ibin in range(nbins):
-        # Top of bin
-        zbin = zmin + (ibin + 1) * dbin
-        zz[ibin] = zbin
-
-        ibelow = np.where(elevation <= zbin)  # index of pixels below bin level
-        # water depth in each pixel
-        h = np.maximum(zbin - np.maximum(elevation, zmin), 0.0)
-        qi = h ** (5.0 / 3.0) / manning  # unit discharge in each pixel
-        q = np.sum(qi) / n  # combined unit discharge for cell
-
-        navg[ibin] = manning[ibelow].mean()  # mean manning's n
-        hrep[ibin] = (q * navg[ibin]) ** (3.0 / 5.0)  # conveyance depth
-
-    return zmin, zmax, hrep, navg, zz
+    # n   = int(np.size(elevation)) # Nr of pixels in grid cell
+
+    n05 = int(n / 2)  # Index of middle pixel
+
+    dd_a = elevation[0:n05]  # Pixel elevations side A
+    dd_b = elevation[n05:]  # Pixel elevations side B
+    manning_a = manning[0:n05]  # Pixel manning side A
+    manning_b = manning[n05:]  # Pixel manning side B
+
+    zmin_a = np.min(dd_a)  # Minimum elevation side A
+    zmax_a = np.max(dd_a)  # Maximum elevation side A
+
+    zmin_b = np.min(dd_b)  # Minimum elevation side B
+    zmax_b = np.max(dd_b)  # Maximum elevation side B
+
+    zmin = max(zmin_a, zmin_b) + huthresh  # Minimum elevation of uv point
+    zmax = max(zmax_a, zmax_b)  # Maximum elevation of uv point
+
+    # Make sure zmax is always a bit higher than zmin
+    if zmax < zmin + 0.001:
+        zmax = max(zmax, zmin + 0.001)
+
+    # Determine level size (metres)
+    dlevel = (zmax - zmin) / (nlevels - 1)
+
+    # Grid mean roughness
+    navg = np.mean(manning)
+
+    # Loop through levels
+    for ilevel in range(nlevels):
+        # Top of level
+        zlevel = zmin + ilevel * dlevel
+        zz[ilevel] = zlevel
+
+        # ibelow = np.where(elevation<=zlevel)                           # index of pixels below level level
+        h = np.maximum(zlevel - elevation, 0.0)  # water depth in each pixel
+        iwet = np.where(zlevel - elevation > -1.0e-6)[0]  # indices of wet pixels
+        hmean = np.mean(h)
+        havg[ilevel] = hmean  # conveyance depth
+        pwet[ilevel] = len(iwet) / n  # wet fraction
+
+        # Side A
+        h_a = np.maximum(
+            zlevel - dd_a, 0.0
+        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_a = h_a ** (5.0 / 3.0) / manning_a  # Determine 'flux' for each pixel
+        q_a = np.mean(q_a)  # Wet-average flux through all the pixels
+
+        # Side B
+        h_b = np.maximum(
+            zlevel - dd_b, 0.0
+        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_b = h_b ** (5.0 / 3.0) / manning_b  # Determine 'flux' for each pixel
+        q_b = np.mean(q_b)  # Wet-average flux through all the pixels
+
+        q_ab = np.minimum(q_a, q_b)
+
+        q_all = h ** (5.0 / 3.0) / manning  # Determine 'flux' for each pixel
+        q_all = np.mean(q_all)  # Wet-average flux through all the pixels
+
+        # Weighted average of q_ab and q_all
+        w = (ilevel) / (nlevels - 1)
+        q = (1.0 - w) * q_ab + w * q_all
+
+        nrep[ilevel] = hmean ** (5.0 / 3.0) / q  # Representative n for qmean and hmean
+
+    nrep_top = nrep[-1]
+    havg_top = havg[-1]
+
+    ### Fitting for nrep above zmax
+
+    # Determine nfit at zfit
+    zfit = zmax + zmax - zmin
+    h = np.maximum(zfit - elevation, 0.0)  # water depth in each pixel
+    hfit = (
+        havg_top + zmax - zmin
+    )  # mean water depth in cell as computed in SFINCS (assuming linear relation between water level and water depth above zmax)
+    q = h ** (5.0 / 3.0) / manning  # unit discharge in each pixel
+    qmean = np.mean(q)  # combined unit discharge for cell
+
+    nfit = hfit ** (5.0 / 3.0) / qmean
+
+    # Actually apply fit on gn2 (this is what is used in sfincs)
+    gnavg2 = 9.81 * navg**2
+    gnavg_top2 = 9.81 * nrep_top**2
+
+    if gnavg2 / gnavg_top2 > 0.99 and gnavg2 / gnavg_top2 < 1.01:
+        # gnavg2 and gnavg_top2 are almost identical
+        ffit = 0.0
+    else:
+        if navg > nrep_top:
+            if nfit > navg:
+                nfit = nrep_top + 0.9 * (navg - nrep_top)
+            if nfit < nrep_top:
+                nfit = nrep_top + 0.1 * (navg - nrep_top)
+        else:
+            if nfit < navg:
+                nfit = nrep_top + 0.9 * (navg - nrep_top)
+            if nfit > nrep_top:
+                nfit = nrep_top + 0.1 * (navg - nrep_top)
+        gnfit2 = 9.81 * nfit**2
+        ffit = (((gnavg2 - gnavg_top2) / (gnavg2 - gnfit2)) - 1) / (zfit - zmax)
+
+    return zmin, zmax, havg, nrep, pwet, ffit, navg, zz
diff --git a/hydromt_sfincs/utils.py b/hydromt_sfincs/utils.py
index 5c56ad22..48a1324c 100644
--- a/hydromt_sfincs/utils.py
+++ b/hydromt_sfincs/utils.py
@@ -52,6 +52,7 @@
     "downscale_floodmap",
     "rotated_grid",
     "build_overviews",
+    "find_uv_indices",
 ]
 
 logger = logging.getLogger(__name__)
@@ -1184,3 +1185,103 @@ def _downscale_floodmap_da(
         hmax = hmax.where(mask)
 
     return hmax
+
+
+def find_uv_indices(mask: xr.DataArray):
+    """The subgrid tables for a regular SFINCS grid are organized as flattened arrays, meaning
+    2D arrays (y,x) are transformed into 1D arrays, only containing values for active cells.
+
+    For the cell centers, this is straightforward, we just find the indices of the active cells.
+    However, the u and v points are saved in combined arrays. Since u and v points are absent
+    at the boundaries of the domain, the index arrays are used to determine the location of the
+    u and v points in the combined flattened arrays.
+
+
+
+    Parameters
+    ----------
+    mask: xr.DataArray
+        Mask with integer values specifying the active cells of the SFINCS domain.
+
+    Returns
+    -------
+    index_nm: np.ndarray
+        Index array for the active cell centers.
+    index_mu1: np.ndarray
+        Index of upstream u-point in combined uv-array.
+    index_nu1: np.ndarray
+        Index of upstream v-point in combined uv-array.
+
+    """
+
+    mask = mask.values
+
+    # nr of cells
+    nr_cells = mask.shape[0] * mask.shape[1]
+
+    # get the index of the u and v points in a combined array
+    mu1 = np.zeros(nr_cells, dtype=int) - 1
+    nu1 = np.zeros(nr_cells, dtype=int) - 1
+
+    ms = np.linspace(0, mask.shape[1] - 1, mask.shape[1], dtype=int)
+    ns = np.linspace(0, mask.shape[0] - 1, mask.shape[0], dtype=int)
+
+    m, n = np.meshgrid(ms, ns)
+
+    m = np.transpose(m).flatten()
+    n = np.transpose(n).flatten()
+
+    mask = mask.transpose().flatten()
+
+    nmax = n.max() + 1
+    nms = m * nmax + n
+
+    for ic in range(nr_cells):
+        # nu1
+        nn = n[ic] + 1
+        if nn < nmax:
+            mm = m[ic]
+            nm = mm * nmax + nn
+            j = binary_search(nms, nm)
+            if j is not None:
+                nu1[ic] = j
+        # mu1
+        nn = n[ic]
+        mm = m[ic] + 1
+        nm = mm * nmax + nn
+        j = binary_search(nms, nm)
+        if j is not None:
+            mu1[ic] = j
+
+    # For regular grids, only the points with mask > 0 are stored
+    # The index arrays determine the location in the flattened arrays (with values for all active points)
+    # Initialize index arrays with -1, inactive cells will remain -1
+    index_nm = np.zeros(nr_cells, dtype=int) - 1
+    index_mu1 = np.zeros(nr_cells, dtype=int) - 1
+    index_nu1 = np.zeros(nr_cells, dtype=int) - 1
+    npuv = 0
+    npc = 0
+    # Loop through all cells
+    for ip in range(nr_cells):
+        # Check if this cell is active
+        if mask[ip] > 0:
+            index_nm[ip] = npc
+            npc += 1
+            if mu1[ip] >= 0:
+                if mask[mu1[ip]] > 0:
+                    index_mu1[ip] = npuv
+                    npuv += 1
+            if nu1[ip] >= 0:
+                if mask[nu1[ip]] > 0:
+                    index_nu1[ip] = npuv
+                    npuv += 1
+
+    return index_nm, index_mu1, index_nu1
+
+
+def binary_search(vals, val):
+    indx = np.searchsorted(vals, val)
+    if indx < np.size(vals):
+        if vals[indx] == val:
+            return indx
+    return None
diff --git a/tests/data/sfincs_test/sfincs.inp b/tests/data/sfincs_test/sfincs.inp
index 5b0c70fd..2ccebd03 100644
--- a/tests/data/sfincs_test/sfincs.inp
+++ b/tests/data/sfincs_test/sfincs.inp
@@ -44,7 +44,7 @@ bndfile              = sfincs.bnd
 bzsfile              = sfincs.bzs
 srcfile              = sfincs.src
 disfile              = sfincs.dis
-sbgfile              = sfincs.sbg
+sbgfile              = sfincs_subgrid.nc
 obsfile              = sfincs.obs
 crsfile              = sfincs.crs
 thdfile              = sfincs.thd
diff --git a/tests/data/sfincs_test/sfincs.sbg b/tests/data/sfincs_test/sfincs.sbg
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z`JD5>Py5p!WN}XY>3?=q`^Wb}^otWc=6z!G_W@7*j6ZqN&wl$Xe)?&W<u(3YG~QLD
zxBR{J?+s)>e13ta-{Zbraa!)x_)l?L*3slg{H|Wxr#r;Yd8K@ppW~6~@9ftu-xBe&
zJ>~Q}8K0iS9H(3V#=DC2U*+kKpLTb0<|Y2sb)!FimmgF6ck$KJt4M$Ph0M<#;%A<u
zoOwgWpZqlGpXP17CDNbv?#lS~<*SI#A02k{!|$F??f5^9WBi+cUya?BA0N+Y-E;iA
zc-Q_e?o<0+yT6NH_3+mF1NHPOvcKZ%y!IA5KjJ&LT*Z?g_m8LZ@bX<J^W=$toZpLg
zpnRSDil67CT=!Y`$oN_B)c+|S_%+`0{?~XlkLA3VGJejp`Yq?~Zan<*+wuL1-x6y+
z$GOrt5dTg8<Nuw=c%_V=_ILS~?fC3T%>Ee<e0fvPmwyMQ+L!zzn+HDsB(f*%AfNoW
zUm3srx)uMaU-z8;dcNe#u8iNE7js>iH^k3=<cwF!__=<_ryqy?ud{!bPhW@XK_dHW
zULWg!jr;a~iC^)0yMO1rG7s=GZ(rod&x{{AG2@kW^-2Ho|J0<PI{CZ!Y1ghy|I0j^
ze}^sm;mh~L-TdqPGquy7aU*Bmr9BhhI341bUzWO?^29H{Ex+GLdE%F!miHzpXWYo_
zpX#N3AQ69xQ}-PIE@s~C%6IkR^XFB3;(yGa8u#sU{M&f*`^Rnl-}D{tt9E3a*p=z)
z_OG*j*uT5=p*{CK@{|6L=bvsqPyA#5b^qDTWBjsnsXxw{?C&u7rS~{T)ck(Wr}3LQ
zj_;hHPNx0(C*nIlm!Fn<OpcQ>zBseP{MF0J|JDEaewF%-lXjEo@5Z0n@##M?{%%EH
zK<A4m{&LSqKXo$x8E<h9<ky@JerI==ciLb0k2siLVy8dtmxmM5&z=*T^J<QVFV8$L
zdp_Q~Jjbv2Ea!LQ!JIc4U!FpCbeQ_Z7bY*`K&GEPiS%@cf96lT$2sE>-?6mg*Z6Pm
zFE92)J;Ud>t9bH<^=jQF;{P<NXIJsGJI*iiw!_Syis!O_O>*+(ZDOZiJNq-=M?XB)
z_sMVaQ=WE+pLww><5&Lw8NZ*{lJV1T+wxz3zq;%{yX)xN^xs^6StoYo)Bc<1=PBR2
z=k#a(?#lR6{&e|>U-3TPn<r)-rC;%@{W$mKI_dTe?fCBNsV~nxo&K_W`TbJo@3Z}J
zKA>N_ynm@5&3OPn{dUTc*EueJ&2zb*@+ah%^e=w4@5=b<@l`zeasJ^)*yS_6`6cE&
z<PF5{@;mb-W&FF?&2MTy^~V02e#pEb<ENiSIr3kgLH?bP{#>WKGQR!1!;BmG;Qt>-
Co<jiu

literal 0
HcmV?d00001

diff --git a/tests/test_1model_class.py b/tests/test_1model_class.py
index c987e02e..98850e63 100644
--- a/tests/test_1model_class.py
+++ b/tests/test_1model_class.py
@@ -103,6 +103,57 @@ def test_infiltration(mod):
     assert np.isclose(mod1.grid["ks"].where(mod.mask > 0).sum(), 351.10803)
 
 
+def test_subgrid_io(tmpdir):
+    # test the backward compatibility of reading/writing subgrid
+    root = TESTMODELDIR
+    datadir = TESTDATADIR
+
+    mod0 = SfincsModel(root=root, mode="r")
+    # read-in the current subgrid (netcdf format)
+    mod0.read()
+    # check version and new parameter
+    assert mod0.reggrid.subgrid.version == 1
+    # u and v paramters should be separated internally
+    assert "u_pwet" in mod0.subgrid
+    assert "uv_pwet" not in mod0.subgrid
+    sbg_net = mod0.subgrid.copy()
+
+    # write the subgrid (new format)
+    tmp_root = str(tmpdir.join("subgrid_io_test"))
+    mod0.set_root(tmp_root, mode="w")
+    mod0.write()
+    assert isfile(join(mod0.root, "sfincs_subgrid.nc"))
+
+    # read back-in
+    mod1 = SfincsModel(root=tmp_root, mode="r")
+    mod1.read()
+    # Check if variables are the same
+    assert mod0.subgrid.variables.keys() == mod1.subgrid.variables.keys()
+
+    # Check if values are almost equal
+    for var_name in mod0.subgrid.variables:
+        assert np.isclose(np.sum(mod0.subgrid[var_name] - mod1.subgrid[var_name]), 0.0)
+
+    # copy old sbgfile to new location
+    sbgfile = join(datadir, "sfincs_test", "sfincs.sbg")
+
+    # change the subgrid to the old format (binary format)
+    mod1.set_config("sbgfile", sbgfile)
+    mod1.read_subgrid()
+
+    # check version and new parameter
+    assert mod1.reggrid.subgrid.version == 0
+    assert "u_pwet" not in mod1.subgrid
+    assert "uv_pwet" not in mod1.subgrid
+    sbg_bin = mod1.subgrid.copy()
+
+    # compare z_zmin and z_zmax
+    assert np.isclose(np.sum(sbg_net["z_zmin"] - sbg_bin["z_zmin"]), 0.0)
+    # TODO: check with Maarten whether this is meant to be different
+    # difference comes from different discretization of volume bins
+    assert np.isclose(np.sum(sbg_net["z_zmax"] - sbg_bin["z_zmax"]), 1.0714283)
+
+
 def test_subgrid_rivers(mod):
     gdf_riv = mod.data_catalog.get_geodataframe(
         "rivers_lin2019_v1", geom=mod.region, buffer=1e3

From 7d64e7a6f7fadb7cf38b489949bc73c23256e129 Mon Sep 17 00:00:00 2001
From: roeldegoede <83765910+roeldegoede@users.noreply.github.com>
Date: Wed, 24 Apr 2024 12:05:30 +0200
Subject: [PATCH 04/28] update changelog (#193)

---
 docs/changelog.rst | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index f2d17a17..29b356c4 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -12,6 +12,7 @@ v1.0.4 (Unreleased)
 Added
 -----
 - improved subgrid tables that account for the wet fraction of the cell (#160)
+- add source points at headwater locations with `SfincsModel.setup_river_inflow` (#170)
 
 Changed
 -------

From 2d32528502c23bc51705b6a3d15e304798c1956b Mon Sep 17 00:00:00 2001
From: maartenvanormondt <maarten.vanormondt@deltares.nl>
Date: Wed, 15 May 2024 10:47:09 -0400
Subject: [PATCH 05/28] update weigths between zmin and zmax in uv points

---
 hydromt_sfincs/subgrid.py | 100 +++++++++++++++++++++-----------------
 1 file changed, 55 insertions(+), 45 deletions(-)

diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index 3fda9464..113dbeed 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -1053,62 +1053,72 @@ def subgrid_q_table(
     # Determine level size (metres)
     dlevel = (zmax - zmin) / (nlevels - 1)
 
-    # Grid mean roughness
-    navg = np.mean(manning)
+    # Option can be either 1 ("old") or 2 ("new")
+    option = 2
 
     # Loop through levels
-    for ilevel in range(nlevels):
-        # Top of level
-        zlevel = zmin + ilevel * dlevel
-        zz[ilevel] = zlevel
-
-        # ibelow = np.where(elevation<=zlevel)                           # index of pixels below level level
-        h = np.maximum(zlevel - elevation, 0.0)  # water depth in each pixel
-        iwet = np.where(zlevel - elevation > -1.0e-6)[0]  # indices of wet pixels
-        hmean = np.mean(h)
-        havg[ilevel] = hmean  # conveyance depth
-        pwet[ilevel] = len(iwet) / n  # wet fraction
+    for ibin in range(nlevels):
 
-        # Side A
-        h_a = np.maximum(
-            zlevel - dd_a, 0.0
-        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
-        q_a = h_a ** (5.0 / 3.0) / manning_a  # Determine 'flux' for each pixel
-        q_a = np.mean(q_a)  # Wet-average flux through all the pixels
-
-        # Side B
-        h_b = np.maximum(
-            zlevel - dd_b, 0.0
-        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
-        q_b = h_b ** (5.0 / 3.0) / manning_b  # Determine 'flux' for each pixel
-        q_b = np.mean(q_b)  # Wet-average flux through all the pixels
-
-        q_ab = np.minimum(q_a, q_b)
+        # Top of bin
+        zbin = zmin + ibin * dlevel
+        zz[ibin] = zbin
 
-        q_all = h ** (5.0 / 3.0) / manning  # Determine 'flux' for each pixel
-        q_all = np.mean(q_all)  # Wet-average flux through all the pixels
+        h = np.maximum(zbin - elevation, 0.0)  # water depth in each pixel
 
-        # Weighted average of q_ab and q_all
-        w = (ilevel) / (nlevels - 1)
-        q = (1.0 - w) * q_ab + w * q_all
 
-        nrep[ilevel] = hmean ** (5.0 / 3.0) / q  # Representative n for qmean and hmean
+        pwet[ibin] = (zbin - elevation > -1.0e-6).sum() / n
 
-    nrep_top = nrep[-1]
+        # Side A
+        h_a   = np.maximum(zbin - dd_a, 0.0)  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_a   = h_a**(5.0 / 3.0) / manning_a  # Determine 'flux' for each pixel
+        q_a   = np.mean(q_a)                  # Grid-average flux through all the pixels
+        h_a   = np.mean(h_a)                  # Grid-average depth through all the pixels
+        
+        # Side B
+        h_b   = np.maximum(zbin - dd_b, 0.0)  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_b   = h_b**(5.0 / 3.0) / manning_b  # Determine 'flux' for each pixel
+        q_b   = np.mean(q_b)                  # Grid-average flux through all the pixels
+        h_b   = np.mean(h_b)                  # Grid-average depth through all the pixels
+
+        # Compute q and h
+        q_all = np.mean(h**(5.0 / 3.0) / manning)   # Determine grid average 'flux' for each pixel
+        h_all = np.mean(h)                          # grid averaged depth of A and B combined
+        q_min = np.minimum(q_a, q_b)
+        h_min = np.minimum(h_a, h_b)
+
+        if option == 1:
+            # Use old 1 option (weighted average of q_ab and q_all) option (min at bottom bin, mean at top bin) 
+            w     = (ibin) / (nlevels - 1)              # Weight (increase from 0 to 1 from bottom to top bin)
+            q     = (1.0 - w) * q_min + w * q_all        # Weighted average of q_min and q_all
+            hmean = h_all
+
+        elif option == 2:
+            # Use newer 2 option (minimum of q_a an q_b, minimum of h_a and h_b increasing to h_all, using pwet for weighting) option
+            pwet_a = (zbin - dd_a > -1.0e-6).sum() / (n / 2) 
+            pwet_b = (zbin - dd_b > -1.0e-6).sum() / (n / 2) 
+            # Weight increases linearly from 0 to 1 from bottom to top bin use percentage wet in sides A and B
+            w = 2 * np.minimum(pwet_a, pwet_b) / (pwet_a + pwet_b)
+            q     = (1.0 - w) * q_min + w * q_all        # Weighted average of q_min and q_all
+            hmean = (1.0 - w) * h_min + w * h_all        # Weighted average of h_min and h_all
+
+        havg[ibin] = hmean                          # conveyance depth
+        nrep[ibin] = hmean**(5.0 / 3.0) / q           # Representative n for qmean and hmean
+
+    nrep_top = nrep[-1]    
     havg_top = havg[-1]
 
     ### Fitting for nrep above zmax
 
     # Determine nfit at zfit
-    zfit = zmax + zmax - zmin
-    h = np.maximum(zfit - elevation, 0.0)  # water depth in each pixel
-    hfit = (
-        havg_top + zmax - zmin
-    )  # mean water depth in cell as computed in SFINCS (assuming linear relation between water level and water depth above zmax)
-    q = h ** (5.0 / 3.0) / manning  # unit discharge in each pixel
-    qmean = np.mean(q)  # combined unit discharge for cell
+    zfit  = zmax + zmax - zmin
+    hfit  = havg_top + zmax - zmin                 # mean water depth in cell as computed in SFINCS (assuming linear relation between water level and water depth above zmax)
 
-    nfit = hfit ** (5.0 / 3.0) / qmean
+    # Compute q and navg
+    h     = np.maximum(zfit - elevation, 0.0)      # water depth in each pixel
+    q     = np.mean(h**(5.0 / 3.0) / manning)          # combined unit discharge for cell
+    navg  = np.mean(manning)
+
+    nfit = hfit**(5.0 / 3.0) / q
 
     # Actually apply fit on gn2 (this is what is used in sfincs)
     gnavg2 = 9.81 * navg**2
@@ -1130,5 +1140,5 @@ def subgrid_q_table(
                 nfit = nrep_top + 0.1 * (navg - nrep_top)
         gnfit2 = 9.81 * nfit**2
         ffit = (((gnavg2 - gnavg_top2) / (gnavg2 - gnfit2)) - 1) / (zfit - zmax)
-
-    return zmin, zmax, havg, nrep, pwet, ffit, navg, zz
+         
+    return zmin, zmax, havg, nrep, pwet, ffit, navg, zz       

From 89a1e7687cee46bbf04493f87e91ca986b1a81ef Mon Sep 17 00:00:00 2001
From: dalmijn <92092029+dalmijn@users.noreply.github.com>
Date: Fri, 24 May 2024 11:00:09 +0200
Subject: [PATCH 06/28] Update plots.py (#196)

When shaded and no rotation, `kwargs` is still used instead of `kwargs0`
---
 hydromt_sfincs/plots.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/hydromt_sfincs/plots.py b/hydromt_sfincs/plots.py
index 7cbe43e4..17e4b888 100644
--- a/hydromt_sfincs/plots.py
+++ b/hydromt_sfincs/plots.py
@@ -258,8 +258,8 @@ def plot_basemap(
             dx, dy = da.raster.res
             _rgb = ls.shade(
                 da.fillna(0).values,
-                norm=kwargs["norm"],
-                cmap=kwargs["cmap"],
+                norm=kwargs0["norm"],
+                cmap=kwargs0["cmap"],
                 blend_mode="soft",
                 dx=dx,
                 dy=dy,

From c84c590067b32ebb5e7ba7053488c655905ceb8f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?David=20Guti=C3=A9rrez-Barcel=C3=B3?=
 <38423310+gutierrad@users.noreply.github.com>
Date: Mon, 3 Jun 2024 01:31:29 -0700
Subject: [PATCH 07/28] Added nodata value to raster before writing (#199)

* Added nodata value to raster before writing

* checked variable type to set nodata

* removed trailing whitespace

* removed trailing whitespace
---
 hydromt_sfincs/sfincs.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 5a22a067..dafde8bf 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -3398,6 +3398,9 @@ def write_raster(
                             f"Variable {attr}.{layer} has more than 2 dimensions: skipping."
                         )
                         continue
+                # If the raster type is float, set nodata to np.nan
+                if da.dtype == "float32" or da.dtype == "float64":
+                    da.raster.set_nodata(np.nan)
                 # only write active cells to gis files
                 da = da.where(self.mask > 0, da.raster.nodata).raster.mask_nodata()
                 if da.raster.res[1] > 0:  # make sure orientation is N->S

From 0893a8e0be2907d192a0ce2db766883445d9fd67 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 17 Jun 2024 07:55:39 +0200
Subject: [PATCH 08/28] Update hydromt requirement from <0.10,>=0.9.1 to
 >=0.9.1,<0.11 (#201)

* Update hydromt requirement from <0.10,>=0.9.1 to >=0.9.1,<0.11

Updates the requirements on [hydromt](https://github.com/Deltares/hydromt) to permit the latest version.
- [Release notes](https://github.com/Deltares/hydromt/releases)
- [Changelog](https://github.com/Deltares/hydromt/blob/main/docs/changelog.rst)
- [Commits](https://github.com/Deltares/hydromt/compare/v0.9.1...v0.10.0)

---
updated-dependencies:
- dependency-name: hydromt
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>

* temp pin numpy

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: DirkEilander <15379728+DirkEilander@users.noreply.github.com>
---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index dd6d25c5..03c9f952 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,9 +13,9 @@ authors = [
 dependencies = [
     "affine",
     "geopandas>=0.8",
-    "hydromt>=0.9.1, <0.10",
+    "hydromt>=0.9.1, <0.11",
     "numba",
-    "numpy",
+    "numpy<2.0", # temp pin until bottleneck release v1.4
     "pandas",
     "pillow",
     "pyflwdir>=0.5.5",

From 33be56ec7d6cc1559ea293e971ead17a05933ac8 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Mon, 26 Aug 2024 13:55:10 +0200
Subject: [PATCH 09/28] run pre-commit

---
 hydromt_sfincs/subgrid.py | 70 ++++++++++++++++++++++-----------------
 1 file changed, 39 insertions(+), 31 deletions(-)

diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index 113dbeed..fd5c1780 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -1058,67 +1058,75 @@ def subgrid_q_table(
 
     # Loop through levels
     for ibin in range(nlevels):
-
         # Top of bin
         zbin = zmin + ibin * dlevel
         zz[ibin] = zbin
 
         h = np.maximum(zbin - elevation, 0.0)  # water depth in each pixel
 
-
         pwet[ibin] = (zbin - elevation > -1.0e-6).sum() / n
 
         # Side A
-        h_a   = np.maximum(zbin - dd_a, 0.0)  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
-        q_a   = h_a**(5.0 / 3.0) / manning_a  # Determine 'flux' for each pixel
-        q_a   = np.mean(q_a)                  # Grid-average flux through all the pixels
-        h_a   = np.mean(h_a)                  # Grid-average depth through all the pixels
-        
+        h_a = np.maximum(
+            zbin - dd_a, 0.0
+        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_a = h_a ** (5.0 / 3.0) / manning_a  # Determine 'flux' for each pixel
+        q_a = np.mean(q_a)  # Grid-average flux through all the pixels
+        h_a = np.mean(h_a)  # Grid-average depth through all the pixels
+
         # Side B
-        h_b   = np.maximum(zbin - dd_b, 0.0)  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
-        q_b   = h_b**(5.0 / 3.0) / manning_b  # Determine 'flux' for each pixel
-        q_b   = np.mean(q_b)                  # Grid-average flux through all the pixels
-        h_b   = np.mean(h_b)                  # Grid-average depth through all the pixels
+        h_b = np.maximum(
+            zbin - dd_b, 0.0
+        )  # Depth of all pixels (but set min pixel height to zbot). Can be negative, but not zero (because zmin = zbot + huthresh, so there must be pixels below zb).
+        q_b = h_b ** (5.0 / 3.0) / manning_b  # Determine 'flux' for each pixel
+        q_b = np.mean(q_b)  # Grid-average flux through all the pixels
+        h_b = np.mean(h_b)  # Grid-average depth through all the pixels
 
         # Compute q and h
-        q_all = np.mean(h**(5.0 / 3.0) / manning)   # Determine grid average 'flux' for each pixel
-        h_all = np.mean(h)                          # grid averaged depth of A and B combined
+        q_all = np.mean(
+            h ** (5.0 / 3.0) / manning
+        )  # Determine grid average 'flux' for each pixel
+        h_all = np.mean(h)  # grid averaged depth of A and B combined
         q_min = np.minimum(q_a, q_b)
         h_min = np.minimum(h_a, h_b)
 
         if option == 1:
-            # Use old 1 option (weighted average of q_ab and q_all) option (min at bottom bin, mean at top bin) 
-            w     = (ibin) / (nlevels - 1)              # Weight (increase from 0 to 1 from bottom to top bin)
-            q     = (1.0 - w) * q_min + w * q_all        # Weighted average of q_min and q_all
+            # Use old 1 option (weighted average of q_ab and q_all) option (min at bottom bin, mean at top bin)
+            w = (ibin) / (
+                nlevels - 1
+            )  # Weight (increase from 0 to 1 from bottom to top bin)
+            q = (1.0 - w) * q_min + w * q_all  # Weighted average of q_min and q_all
             hmean = h_all
 
         elif option == 2:
             # Use newer 2 option (minimum of q_a an q_b, minimum of h_a and h_b increasing to h_all, using pwet for weighting) option
-            pwet_a = (zbin - dd_a > -1.0e-6).sum() / (n / 2) 
-            pwet_b = (zbin - dd_b > -1.0e-6).sum() / (n / 2) 
+            pwet_a = (zbin - dd_a > -1.0e-6).sum() / (n / 2)
+            pwet_b = (zbin - dd_b > -1.0e-6).sum() / (n / 2)
             # Weight increases linearly from 0 to 1 from bottom to top bin use percentage wet in sides A and B
             w = 2 * np.minimum(pwet_a, pwet_b) / (pwet_a + pwet_b)
-            q     = (1.0 - w) * q_min + w * q_all        # Weighted average of q_min and q_all
-            hmean = (1.0 - w) * h_min + w * h_all        # Weighted average of h_min and h_all
+            q = (1.0 - w) * q_min + w * q_all  # Weighted average of q_min and q_all
+            hmean = (1.0 - w) * h_min + w * h_all  # Weighted average of h_min and h_all
 
-        havg[ibin] = hmean                          # conveyance depth
-        nrep[ibin] = hmean**(5.0 / 3.0) / q           # Representative n for qmean and hmean
+        havg[ibin] = hmean  # conveyance depth
+        nrep[ibin] = hmean ** (5.0 / 3.0) / q  # Representative n for qmean and hmean
 
-    nrep_top = nrep[-1]    
+    nrep_top = nrep[-1]
     havg_top = havg[-1]
 
     ### Fitting for nrep above zmax
 
     # Determine nfit at zfit
-    zfit  = zmax + zmax - zmin
-    hfit  = havg_top + zmax - zmin                 # mean water depth in cell as computed in SFINCS (assuming linear relation between water level and water depth above zmax)
+    zfit = zmax + zmax - zmin
+    hfit = (
+        havg_top + zmax - zmin
+    )  # mean water depth in cell as computed in SFINCS (assuming linear relation between water level and water depth above zmax)
 
     # Compute q and navg
-    h     = np.maximum(zfit - elevation, 0.0)      # water depth in each pixel
-    q     = np.mean(h**(5.0 / 3.0) / manning)          # combined unit discharge for cell
-    navg  = np.mean(manning)
+    h = np.maximum(zfit - elevation, 0.0)  # water depth in each pixel
+    q = np.mean(h ** (5.0 / 3.0) / manning)  # combined unit discharge for cell
+    navg = np.mean(manning)
 
-    nfit = hfit**(5.0 / 3.0) / q
+    nfit = hfit ** (5.0 / 3.0) / q
 
     # Actually apply fit on gn2 (this is what is used in sfincs)
     gnavg2 = 9.81 * navg**2
@@ -1140,5 +1148,5 @@ def subgrid_q_table(
                 nfit = nrep_top + 0.1 * (navg - nrep_top)
         gnfit2 = 9.81 * nfit**2
         ffit = (((gnavg2 - gnavg_top2) / (gnavg2 - gnfit2)) - 1) / (zfit - zmax)
-         
-    return zmin, zmax, havg, nrep, pwet, ffit, navg, zz       
+
+    return zmin, zmax, havg, nrep, pwet, ffit, navg, zz

From 0c2eb7d9131c10b5b9f3d152b63c079f54367a26 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Wed, 28 Aug 2024 13:42:19 +0200
Subject: [PATCH 10/28] added q_table_option for backward compatability and
 changed max_gradient accordingly

---
 hydromt_sfincs/sfincs.py  | 12 +++++++++++-
 hydromt_sfincs/subgrid.py | 25 +++++++++++++++++++------
 2 files changed, 30 insertions(+), 7 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index dafde8bf..1a2b8d81 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -619,8 +619,10 @@ def setup_subgrid(
         nbins: int = None,
         nr_subgrid_pixels: int = 20,
         nrmax: int = 2000,  # blocksize
-        max_gradient: float = 5.0,
+        max_gradient: float = 999.0,
         z_minimum: float = -99999.0,
+        huthresh: float = 0.01,
+        q_table_option: int = 2,
         manning_land: float = 0.04,
         manning_sea: float = 0.02,
         rgh_lev_land: float = 0.0,
@@ -710,6 +712,12 @@ def setup_subgrid(
             to prevent numerical stability problems, by default 5.0
         z_minimum : float, optional
             Minimum depth in the subgrid tables, by default -99999.0
+        huthresh : float, optional
+            Threshold depth in SFINCS model, by default 0.01 m
+        q_table_option : int, optional
+            Option for the computation of the conveyance depth at u/v points, by default 2.
+            1: "old" method, compliant with SFINCS < v2.1.0
+            2: "new" method, recommended for SFINCS >= v2.1.0
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea, by default 0.04 and 0.02 s.m-1/3
             Note that these values are only used when no Manning's n datasets are provided,
@@ -765,6 +773,8 @@ def setup_subgrid(
                 nrmax=nrmax,
                 max_gradient=max_gradient,
                 z_minimum=z_minimum,
+                huthresh=huthresh,
+                q_table_option=q_table_option,
                 manning_land=manning_land,
                 manning_sea=manning_sea,
                 rgh_lev_land=rgh_lev_land,
diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index fd5c1780..1f0c7026 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -371,9 +371,10 @@ def build(
         nlevels: int = 10,
         nr_subgrid_pixels: int = 20,
         nrmax: int = 2000,
-        max_gradient: float = 5.0,
+        max_gradient: float = 999.0,
         z_minimum: float = -99999.0,
         huthresh: float = 0.01,
+        q_table_option: int = 2,
         manning_land: float = 0.04,
         manning_sea: float = 0.02,
         rgh_lev_land: float = 0.0,
@@ -428,6 +429,10 @@ def build(
             Minimum depth in the subgrid tables, by default -99999.0
         huthresh : float, optional
             Threshold depth in SFINCS model, by default 0.01 m
+        q_table_option : int, optional
+            Option for the computation of the conveyance depth at u/v points, by default 2.
+            1: "old" method, compliant with SFINCS < v2.1.0
+            2: "new" method, recommended for SFINCS >= v2.1.0
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea,
             by default 0.04 and 0.02 s.m-1/3
@@ -716,6 +721,7 @@ def build(
                     yg,
                     max_gradient,
                     huthresh,
+                    q_table_option,
                     da_mask.raster.crs.is_geographic,
                 )
 
@@ -797,6 +803,7 @@ def process_tile_regular(
     yg,
     max_gradient,
     huthresh,
+    q_table_option,
     is_geographic=False,
 ):
     """calculate subgrid properties for a single tile"""
@@ -864,7 +871,7 @@ def process_tile_regular(
             manning = manning_grid[nn : nn + refi, mm : mm + refi]
             manning = np.transpose(manning)
             zmin, zmax, havg, nrep, pwet, ffit, navg, zz = subgrid_q_table(
-                zgu.flatten(), manning.flatten(), nlevels, huthresh
+                zgu.flatten(), manning.flatten(), nlevels, huthresh, q_table_option
             )
             u_zmin[n, m] = zmin
             u_zmax[n, m] = zmax
@@ -880,7 +887,7 @@ def process_tile_regular(
             zgu = zg[nn : nn + refi, mm : mm + refi]
             manning = manning_grid[nn : nn + refi, mm : mm + refi]
             zmin, zmax, havg, nrep, pwet, ffit, navg, zz = subgrid_q_table(
-                zgu.flatten(), manning.flatten(), nlevels, huthresh
+                zgu.flatten(), manning.flatten(), nlevels, huthresh, q_table_option
             )
             v_zmin[n, m] = zmin
             v_zmax[n, m] = zmax
@@ -1000,7 +1007,11 @@ def subgrid_v_table(
 
 @njit
 def subgrid_q_table(
-    elevation: np.ndarray, manning: np.ndarray, nlevels: int, huthresh: float
+    elevation: np.ndarray,
+    manning: np.ndarray,
+    nlevels: int,
+    huthresh: float,
+    option: int,
 ):
     """
     map vector of elevation values into a hypsometric hydraulic radius - depth relationship for one u/v point
@@ -1010,6 +1021,8 @@ def subgrid_q_table(
     manning : np.ndarray (nr of pixels in one cell) containing subgrid manning roughness values for one grid cell [s m^(-1/3)]
     nlevels : int, number of vertical levels [-]
     huthresh : float, threshold depth [m]
+    option : int, option to use "old" or "new" method for computing conveyance depth at u/v points
+
     Returns
     -------
     zmin : float, minimum elevation [m]
@@ -1053,8 +1066,8 @@ def subgrid_q_table(
     # Determine level size (metres)
     dlevel = (zmax - zmin) / (nlevels - 1)
 
-    # Option can be either 1 ("old") or 2 ("new")
-    option = 2
+    # Option can be either 1 ("old, compliant with SFINCS < v2.1.0") or 2 ("new", recommended SFINCS >= v2.1.0)
+    option = option
 
     # Loop through levels
     for ibin in range(nlevels):

From e7d0e37383c8e0a88c68dea179878d5145106cad Mon Sep 17 00:00:00 2001
From: Tim Leijnse <timleynse94@gmail.com>
Date: Wed, 28 Aug 2024 16:47:18 +0200
Subject: [PATCH 11/28] =?UTF-8?q?Default=20for=20baro=20should=20be=20set?=
 =?UTF-8?q?=20to=201!=20As=20is=20default=20in=20SFINCS=20itself,=20?=
 =?UTF-8?q?=E2=80=A6=20(#208)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* Default for baro should be set to 1! As is default in SFINCS itself, otherwise any pressure input is ignored....

* cahnge default value also in test-inputs

---------

Co-authored-by: roeldegoede <roeldegoede@outlook.com>
---
 hydromt_sfincs/sfincs_input.py    | 2 +-
 tests/data/sfincs_test/sfincs.inp | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/hydromt_sfincs/sfincs_input.py b/hydromt_sfincs/sfincs_input.py
index a5faa9d2..a504f6fa 100644
--- a/hydromt_sfincs/sfincs_input.py
+++ b/hydromt_sfincs/sfincs_input.py
@@ -45,7 +45,7 @@ def __init__(self):
         self.rhow = 1024.0
         self.dtmax = 60.0
         self.advection = 1
-        self.baro = 0
+        self.baro = 1
         self.pavbnd = 0
         self.gapres = 101200.0
         self.stopdepth = 100.0
diff --git a/tests/data/sfincs_test/sfincs.inp b/tests/data/sfincs_test/sfincs.inp
index 2ccebd03..6e210f7f 100644
--- a/tests/data/sfincs_test/sfincs.inp
+++ b/tests/data/sfincs_test/sfincs.inp
@@ -30,7 +30,7 @@ rhoa                 = 1.25
 rhow                 = 1024.0
 dtmax                = 60.0
 advection            = 1
-baro                 = 0
+baro                 = 1
 pavbnd               = 0
 gapres               = 101200.0
 stopdepth            = 100.0

From ca7f23c6e3ef5c154eca0c17a0b57e105f453cf2 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 29 Aug 2024 09:28:10 +0200
Subject: [PATCH 12/28] fix dependencies and deprecation warnings

---
 hydromt_sfincs/sfincs.py               |  6 +++---
 hydromt_sfincs/subgrid.py              |  6 +++---
 hydromt_sfincs/utils.py                |  6 +++---
 hydromt_sfincs/workflows/bathymetry.py |  4 ++--
 hydromt_sfincs/workflows/flwdir.py     | 10 +++++-----
 pyproject.toml                         |  4 ++--
 6 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 1a2b8d81..635e0647 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -292,7 +292,7 @@ def setup_grid_from_region(
         # create grid from region
         # NOTE keyword rotated is added to still have the possibility to create unrotated grids if needed (e.g. for FEWS?)
         if rotated:
-            geom = self.geoms["region"].unary_union
+            geom = self.geoms["region"].union_all()
             x0, y0, mmax, nmax, rot = utils.rotated_grid(
                 geom, res, dec_origin=dec_origin, dec_rotation=dec_rotation
             )
@@ -1072,11 +1072,11 @@ def setup_river_outflow(
             if np.any(self.mask == 2) and btype == "outflow":
                 gdf_msk2 = utils.get_bounds_vector(self.mask)
                 # NOTE: this should be a single geom
-                geom = gdf_msk2[gdf_msk2["value"] == 2].unary_union
+                geom = gdf_msk2[gdf_msk2["value"] == 2].union_all()
                 gdf_out = gdf_out[~gdf_out.intersects(geom)]
             # remove outflow points near source points
             if "dis" in self.forcing and len(gdf_out) > 0:
-                geom = self.forcing["dis"].vector.to_gdf().unary_union
+                geom = self.forcing["dis"].vector.to_gdf().union_all()
                 gdf_out = gdf_out[~gdf_out.intersects(geom)]
 
         # update mask
diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index 1f0c7026..add6ea3d 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -39,9 +39,9 @@ def read(self, file_name, mask):
 
         # get number of levels, point and uv points
         self.nlevels, self.nr_cells, self.nr_uv_points = (
-            ds.dims["levels"],
-            ds.dims["np"],
-            ds.dims["npuv"],
+            ds.sizes["levels"],
+            ds.sizes["np"],
+            ds.sizes["npuv"],
         )
 
         # find indices of active cells
diff --git a/hydromt_sfincs/utils.py b/hydromt_sfincs/utils.py
index 48a1324c..b4060ab9 100644
--- a/hydromt_sfincs/utils.py
+++ b/hydromt_sfincs/utils.py
@@ -221,7 +221,7 @@ def read_xy(fn: Union[str, Path], crs: Union[int, CRS] = None) -> gpd.GeoDataFra
 
 
 def read_xyn(fn: str, crs: int = None):
-    df = pd.read_csv(fn, index_col=False, header=None, delim_whitespace=True).rename(
+    df = pd.read_csv(fn, index_col=False, header=None, sep="\s+").rename(
         columns={0: "x", 1: "y"}
     )
     if len(df.columns) > 2:
@@ -280,7 +280,7 @@ def read_timeseries(fn: Union[str, Path], tref: Union[str, datetime]) -> pd.Data
         Dataframe of timeseries with parsed time index.
     """
     tref = parse_datetime(tref)
-    df = pd.read_csv(fn, delim_whitespace=True, index_col=0, header=None)
+    df = pd.read_csv(fn, index_col=0, header=None, sep="\s+")
     df.index = pd.to_datetime(df.index.values, unit="s", origin=tref)
     df.columns = df.columns.values.astype(int)
     df.index.name = "time"
@@ -800,7 +800,7 @@ def read_sfincs_map_results(
             continue
         if "x" in ds_map[var].dims and "y" in ds_map[var].dims:
             # drop to overwrite with ds_like.raster.coords
-            ds_face[var] = ds_map[var].drop(["xc", "yc"])
+            ds_face[var] = ds_map[var].drop_vars(["xc", "yc"])
         elif ds_map[var].ndim == 0:
             ds_face[var] = ds_map[var]
         else:
diff --git a/hydromt_sfincs/workflows/bathymetry.py b/hydromt_sfincs/workflows/bathymetry.py
index f4e3e010..e7969a8d 100644
--- a/hydromt_sfincs/workflows/bathymetry.py
+++ b/hydromt_sfincs/workflows/bathymetry.py
@@ -257,7 +257,7 @@ def burn_river_rect(
         # get gdf_riv outside of mask and buffer these lines
         # then merge with gdf_riv_mask to get the full river mask
         gdf_mask = gpd.GeoDataFrame(
-            geometry=[gdf_riv_mask.buffer(0).unary_union],
+            geometry=[gdf_riv_mask.buffer(0).union_all()],
             crs=gdf_riv_mask.crs,
         )  # create single polygon to clip
         gdf_riv_clip = gdf_riv.overlay(gdf_mask, how="difference")
@@ -318,7 +318,7 @@ def burn_river_rect(
     # merge river lines > z points are interpolated along merged line
     if gdf_riv.index.size > 1:
         gdf_riv_merged = gpd.GeoDataFrame(
-            geometry=[linemerge(gdf_riv.unary_union)], crs=gdf_riv.crs
+            geometry=[linemerge(gdf_riv.union_all())], crs=gdf_riv.crs
         )
         gdf_riv_merged = gdf_riv_merged.explode(index_parts=True).reset_index(drop=True)
     else:
diff --git a/hydromt_sfincs/workflows/flwdir.py b/hydromt_sfincs/workflows/flwdir.py
index e13e33fe..18d5a7ea 100644
--- a/hydromt_sfincs/workflows/flwdir.py
+++ b/hydromt_sfincs/workflows/flwdir.py
@@ -55,7 +55,7 @@ def river_centerline_from_hydrography(
     gdf_riv = gpd.GeoDataFrame.from_features(feats, crs=da_flwdir.raster.crs)
     # clip to mask and remove empty geometries
     if gdf_mask is not None and isinstance(gdf_mask, gpd.GeoDataFrame):
-        gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.unary_union)
+        gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.union_all())
     gdf_riv = gdf_riv[~gdf_riv.is_empty]
     # create river network from gdf to get distance from outlet 'rivlen'
     # length of river segments
@@ -142,7 +142,7 @@ def river_source_points(
         gdf_mask = gdf_mask.to_crs("epsg:3857")
 
     # clip river to model gdf_mask
-    gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.unary_union)
+    gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.union_all())
     # filter river network based on uparea and length
     if "uparea" in gdf_riv.columns:
         gdf_riv = gdf_riv[gdf_riv["uparea"] >= river_upa]
@@ -166,15 +166,15 @@ def river_source_points(
     # get points that do not intersect with up/downstream end of other river segments
     # use a small buffer of 5m around these points to account for dx and avoid issues with inprecise river geometries
     if src_type in ["inflow", "headwater"]:
-        pnts_ds = gdf_ds.buffer(5).unary_union
+        pnts_ds = gdf_ds.buffer(5).union_all()
         gdf_pnt = gdf_up[~gdf_up.intersects(pnts_ds)].reset_index(drop=True)
     elif src_type == "outflow":
-        pnts_up = gdf_up.buffer(5).unary_union
+        pnts_up = gdf_up.buffer(5).union_all()
         gdf_pnt = gdf_ds[~gdf_ds.intersects(pnts_up)].reset_index(drop=True)
 
     # get buffer around gdf_mask, in- and outflow points should be within this buffer
     if src_type in ["inflow", "outflow"]:
-        bnd = gdf_mask.boundary.buffer(buffer).unary_union
+        bnd = gdf_mask.boundary.buffer(buffer).union_all()
         gdf_pnt = gdf_pnt[gdf_pnt.intersects(bnd)].reset_index(drop=True)
 
     # log numer of source points
diff --git a/pyproject.toml b/pyproject.toml
index 03c9f952..b7e0d34d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,8 +12,8 @@ authors = [
 ]
 dependencies = [
     "affine",
-    "geopandas>=0.8",
-    "hydromt>=0.9.1, <0.11",
+    "geopandas>=1.0",
+    "hydromt>=0.10, <0.11",
     "numba",
     "numpy<2.0", # temp pin until bottleneck release v1.4
     "pandas",

From 562da59bcc75861e46412596404946250467a0cc Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 29 Aug 2024 09:29:56 +0200
Subject: [PATCH 13/28] version bump

---
 hydromt_sfincs/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/hydromt_sfincs/__init__.py b/hydromt_sfincs/__init__.py
index 9c051e8d..41d287be 100644
--- a/hydromt_sfincs/__init__.py
+++ b/hydromt_sfincs/__init__.py
@@ -3,7 +3,7 @@
 from os.path import dirname, join, abspath
 
 
-__version__ = "1.0.4.dev"
+__version__ = "1.1.0"
 
 DATADIR = join(dirname(abspath(__file__)), "data")
 

From 213bfcfa1946a774f1ac72bc670ae9b36b877971 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 29 Aug 2024 09:53:39 +0200
Subject: [PATCH 14/28] update changelog

---
 docs/changelog.rst | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index 29b356c4..5acc7b7e 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -6,22 +6,28 @@ Distinction is made between new methods (Added), changes to existing methods (Ch
 The format is based on `Keep a Changelog`_, and this project adheres to
 `Semantic Versioning`_.
 
-v1.0.4 (Unreleased)
+v1.1.0 (Unreleased)
 ===================
 
 Added
 -----
 - improved subgrid tables that account for the wet fraction of the cell (#160)
 - add source points at headwater locations with `SfincsModel.setup_river_inflow` (#170)
+- it's now possible to provide a format/precision in `SfincsModel.write_forcing` (#197)
+- river bed levels for burn-in can now be provided at point locations in `SfincsModel.setup_subgrid` (#209)
 
 Changed
 -------
 - improved subgrid tables are saved as NetCDF (#160)
+- improved weighting of adjacent cells in u/v points for determining representative Manning roughness and conveyance depth (#200)
+- turned on "baro", the atmospheric pressure term in the momentum equation, in sfincs.inp by default (#208)
+- the expected variable names for wind and pressure forcing have been changed to "wind10_u", "wind10_v" and "press_msl" to match hydromt-core conventions (#211)
 
 Fixed
 -----
 - rounding errors in `workflows.tile_window` which resulted in erronuous slippy-tiles (#178)
 - "active geometry column to use has not been set" error for GeoDataFrame (#180)
+- added nodata value to raster before writing (#199)
 
 
 v1.0.3 (3 January 2024)

From 4200bcddec5ebc0676ee8be2f0c2f0e3692c7f2f Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 29 Aug 2024 10:16:32 +0200
Subject: [PATCH 15/28] add valueerror for max_gradient when using old
 q_table_option

---
 hydromt_sfincs/sfincs.py  | 13 +++++++++----
 hydromt_sfincs/subgrid.py | 10 +++++-----
 2 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 1a2b8d81..da09adb4 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -619,7 +619,7 @@ def setup_subgrid(
         nbins: int = None,
         nr_subgrid_pixels: int = 20,
         nrmax: int = 2000,  # blocksize
-        max_gradient: float = 999.0,
+        max_gradient: float = 99999.0,
         z_minimum: float = -99999.0,
         huthresh: float = 0.01,
         q_table_option: int = 2,
@@ -715,9 +715,9 @@ def setup_subgrid(
         huthresh : float, optional
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
-            Option for the computation of the conveyance depth at u/v points, by default 2.
-            1: "old" method, compliant with SFINCS < v2.1.0
-            2: "new" method, recommended for SFINCS >= v2.1.0
+            Option for the computation of the representative roughness and conveyance depth at u/v points, by default 2.
+            1: "old" weighting method, compliant with SFINCS < v2.1.0, taking the avarage of the adjecent cells
+            2: "improved" weighting method, recommended for SFINCS >= v2.1.0, that takes into account the wet fractions of the adjacent cells
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea, by default 0.04 and 0.02 s.m-1/3
             Note that these values are only used when no Manning's n datasets are provided,
@@ -761,6 +761,11 @@ def setup_subgrid(
             )
             nlevels = nbins
 
+        if q_table_option == 1 and max_gradient > 20.0:
+            raise ValueError(
+                "For the old q_table_option, a max_gradient of 5.0 is recommended to improve numerical stability"
+            )
+
         if self.grid_type == "regular":
             self.reggrid.subgrid.build(
                 da_mask=self.mask,
diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index 1f0c7026..1a741864 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -371,7 +371,7 @@ def build(
         nlevels: int = 10,
         nr_subgrid_pixels: int = 20,
         nrmax: int = 2000,
-        max_gradient: float = 999.0,
+        max_gradient: float = 99999.0,
         z_minimum: float = -99999.0,
         huthresh: float = 0.01,
         q_table_option: int = 2,
@@ -430,9 +430,9 @@ def build(
         huthresh : float, optional
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
-            Option for the computation of the conveyance depth at u/v points, by default 2.
-            1: "old" method, compliant with SFINCS < v2.1.0
-            2: "new" method, recommended for SFINCS >= v2.1.0
+            Option for the computation of the representative roughness and conveyance depth at u/v points, by default 2.
+            1: "old" weighting method, compliant with SFINCS < v2.1.0, taking the avarage of the adjecent cells
+            2: "improved" weighting method, recommended for SFINCS >= v2.1.0, that takes into account the wet fractions of the adjacent cells
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea,
             by default 0.04 and 0.02 s.m-1/3
@@ -959,7 +959,7 @@ def subgrid_v_table(
     zvolmin: float
         minimum elevation value to use for volume calculation (typically -20 m)
     max_gradient: float
-        maximum gradient to use for volume calculation (typically 0.1)
+        maximum gradient to use for volume calculation
 
     Return
     ------

From e5245a90c59ee9534773d4ddde900716a2a7352c Mon Sep 17 00:00:00 2001
From: DirkEilander <15379728+DirkEilander@users.noreply.github.com>
Date: Thu, 29 Aug 2024 10:17:09 +0200
Subject: [PATCH 16/28] move inflow points to confluence if within buffer from
 model boundary (#202)

* move inflow points to confluence

* fix of test_river_source_points

* force river_inflow buffer to be 100 to match old default value (and fix the test)

* update test and changelog

---------

Co-authored-by: roeldegoede <roeldegoede@outlook.com>
---
 docs/changelog.rst                 |  2 ++
 hydromt_sfincs/sfincs.py           | 13 +++++++------
 hydromt_sfincs/workflows/flwdir.py | 20 ++++++++++++++------
 tests/data/sfincs_test.yml         |  1 +
 tests/test_flwdir.py               |  8 ++++----
 5 files changed, 28 insertions(+), 16 deletions(-)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index 29b356c4..aed8bcb5 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -17,6 +17,8 @@ Added
 Changed
 -------
 - improved subgrid tables are saved as NetCDF (#160)
+- In `SfincsModel.setup_river_inflow`, in case of a confluence within a user-defined buffer of the
+  model boundary the confluence rather than both tributaries is selected as inflow point. (#202)
 
 Fixed
 -----
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index dafde8bf..65327bcb 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -794,6 +794,7 @@ def setup_river_inflow(
         self,
         rivers: Union[str, Path, gpd.GeoDataFrame] = None,
         hydrography: Union[str, Path, xr.Dataset] = None,
+        buffer: float = 200,
         river_upa: float = 10.0,
         river_len: float = 1e3,
         river_width: float = 500,
@@ -814,7 +815,8 @@ def setup_river_inflow(
         Discharge is set to zero at these points, but can be updated
         using the `setup_discharge_forcing` or `setup_discharge_forcing_from_grid` methods.
 
-        Note: this method assumes the rivers are directed from up- to downstream.
+        Note: this method assumes the rivers are directed from up- to downstream. Use
+        `reverse_river_geom=True` if the rivers are directed from downstream to upstream.
 
         Adds model layers:
 
@@ -831,6 +833,10 @@ def setup_river_inflow(
             Path, data source name, or a xarray raster object for hydrography data.
 
             * Required layers: ['uparea', 'flwdir'].
+        buffer: float, optional
+            Buffer around the model region boundary to define in/outflow points [m],
+            by default 200 m. We suggest to use a buffer of at least twice the hydrography
+            resolution. Inflow points are moved to a downstreawm confluence if within the buffer.
         river_upa : float, optional
             Minimum upstream area threshold for rivers [km2], by default 10.0
         river_len: float, optional
@@ -892,11 +898,6 @@ def setup_river_inflow(
         elif hydrography is None:
             raise ValueError("Either hydrography or rivers must be provided.")
 
-        # estimate buffer based on model resolution
-        buffer = self.reggrid.dx
-        if self.crs.is_geographic:
-            buffer = buffer * 111111.0
-
         # get river inflow / headwater source points
         gdf_src = workflows.river_source_points(
             gdf_riv=gdf_riv,
diff --git a/hydromt_sfincs/workflows/flwdir.py b/hydromt_sfincs/workflows/flwdir.py
index e13e33fe..f59ff334 100644
--- a/hydromt_sfincs/workflows/flwdir.py
+++ b/hydromt_sfincs/workflows/flwdir.py
@@ -1,4 +1,5 @@
 """Flow direction and river network workflows for SFINCS models."""
+
 import logging
 from typing import Tuple
 
@@ -82,7 +83,7 @@ def river_source_points(
     gdf_riv: gpd.GeoDataFrame,
     gdf_mask: gpd.GeoDataFrame,
     src_type: str = "inflow",
-    buffer: float = 100,
+    buffer: float = 200,
     river_upa: float = 10,
     river_len: float = 1e3,
     da_uparea: xr.DataArray = None,
@@ -109,7 +110,8 @@ def river_source_points(
         If 'outflow', return points where the river flows out of the model domain.
         If 'headwater', return all headwater (including inflow) points within the model domain.
     buffer: float, optional
-        Buffer around gdf_mask to select river source points, by default 100 m.
+        Buffer around gdf_mask to select river source points, by default 200 m.
+        Inflow points are moved to a downstream confluence if within the buffer.
     river_upa : float, optional
         Minimum upstream area threshold for rivers [km2], by default 10.0
     river_len: float, optional
@@ -143,6 +145,11 @@ def river_source_points(
 
     # clip river to model gdf_mask
     gdf_riv = gdf_riv.to_crs(gdf_mask.crs).clip(gdf_mask.unary_union)
+    # keep only lines
+    gdf_riv = gdf_riv[
+        [t.endswith("LineString") for t in gdf_riv.geom_type]
+    ].reset_index(drop=True)
+
     # filter river network based on uparea and length
     if "uparea" in gdf_riv.columns:
         gdf_riv = gdf_riv[gdf_riv["uparea"] >= river_upa]
@@ -154,17 +161,19 @@ def river_source_points(
         )
         return gpd.GeoDataFrame()
 
+    # remove lines that fully are within the buffer of the mask boundary
+    bnd = gdf_mask.boundary.buffer(buffer).unary_union
+    gdf_riv = gdf_riv[~gdf_riv.within(bnd)]
+
     # get source points 1m before the start/end of the river
     # a positive dx results in a point near the start of the line (inflow)
     # a negative dx results in a point near the end of the line (outflow)
     dx = -1 if reverse_river_geom else 1
     gdf_up = gdf_riv.interpolate(dx).to_frame("geometry")
-    gdf_up["riv_idx"] = gdf_riv.index
     gdf_ds = gdf_riv.interpolate(-dx).to_frame("geometry")
-    gdf_ds["riv_idx"] = gdf_riv.index
 
     # get points that do not intersect with up/downstream end of other river segments
-    # use a small buffer of 5m around these points to account for dx and avoid issues with inprecise river geometries
+    # use a small buffer of 5m around these points to account for dx and avoid issues with imprecise river geometries
     if src_type in ["inflow", "headwater"]:
         pnts_ds = gdf_ds.buffer(5).unary_union
         gdf_pnt = gdf_up[~gdf_up.intersects(pnts_ds)].reset_index(drop=True)
@@ -174,7 +183,6 @@ def river_source_points(
 
     # get buffer around gdf_mask, in- and outflow points should be within this buffer
     if src_type in ["inflow", "outflow"]:
-        bnd = gdf_mask.boundary.buffer(buffer).unary_union
         gdf_pnt = gdf_pnt[gdf_pnt.intersects(bnd)].reset_index(drop=True)
 
     # log numer of source points
diff --git a/tests/data/sfincs_test.yml b/tests/data/sfincs_test.yml
index e0f37222..a5089958 100644
--- a/tests/data/sfincs_test.yml
+++ b/tests/data/sfincs_test.yml
@@ -56,6 +56,7 @@ setup_drainage_structures:
 
 setup_river_inflow:
   hydrography: merit_hydro
+  buffer: 100
   river_upa: 10
   river_len: 1000
   keep_rivers_geom: True
diff --git a/tests/test_flwdir.py b/tests/test_flwdir.py
index b6d55b1b..9e416661 100644
--- a/tests/test_flwdir.py
+++ b/tests/test_flwdir.py
@@ -39,20 +39,20 @@ def test_river_source_points(hydrography, data_catalog):
     assert gdf_src.index.size == 6
     gdf_src = river_source_points(src_type="outflow", da_uparea=da_uparea, **kwargs)
     assert gdf_src.index.size == 1
-    assert np.isin(["geometry", "riv_idx", "uparea"], gdf_src.columns).all()
+    assert np.isin(["geometry", "uparea"], gdf_src.columns).all()
+    np.allclose(gdf_src.geometry[0].coords[:], [(322650.3, 5044385.7)])
 
     # test reverse oriented line
     gdf_riv = data_catalog.get_geodataframe("rivers_lin2019_v1")
     kwargs = dict(gdf_riv=gdf_riv, gdf_mask=gdf_mask, reverse_river_geom=True)
     gdf_src = river_source_points(src_type="inflow", **kwargs)
     assert gdf_src.index.size == 1  # this data only one river
-    assert gdf_src["riv_idx"].values[0] == 38
+    np.allclose(gdf_src.geometry[0].coords[:], [(322650.3, 5044385.7)])
     gdf_src = river_source_points(src_type="outflow", **kwargs)
+    np.allclose(gdf_src.geometry[0].coords[:], [(322554.0, 5044434.7)])
     assert gdf_src.index.size == 1  # this data only one river
-    assert gdf_src["riv_idx"].values[0] == 34
     gdf_src = river_source_points(src_type="headwater", **kwargs)
     assert gdf_src.index.size == 2
-    assert np.isin(38, gdf_src["riv_idx"].values)
 
     # test errors
     with pytest.raises(ValueError, match="src_type must be either"):

From 74039aff1be81690e9ce45034b0e7c3d7c66571b Mon Sep 17 00:00:00 2001
From: roeldegoede <83765910+roeldegoede@users.noreply.github.com>
Date: Thu, 29 Aug 2024 10:35:49 +0200
Subject: [PATCH 17/28] update variable names for wind and pressure according
 to hydromt-core (#211)

---
 hydromt_sfincs/sfincs.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 65327bcb..4691bfb2 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -2326,7 +2326,7 @@ def setup_pressure_forcing_from_grid(
         press, str, Path, xr.Dataset, xr.DataArray
             Path to pressure rasterdataset netcdf file or xarray dataset.
 
-            * Required variables: ['press' (Pa)]
+            * Required variables: ['press_msl' (Pa)]
             * Required coordinates: ['time', 'y', 'x']
 
         dst_res: float
@@ -2342,7 +2342,7 @@ def setup_pressure_forcing_from_grid(
             geom=self.region,
             buffer=2,
             time_tuple=self.get_model_time(),
-            variables=["press"],
+            variables=["press_msl"],
         )
 
         # reproject to model utm crs
@@ -2384,7 +2384,7 @@ def setup_wind_forcing_from_grid(self, wind, dst_res=None, **kwargs):
         wind, str, Path, xr.Dataset
             Path to wind rasterdataset (including eastward and northward components) netcdf file or xarray dataset.
 
-            * Required variables: ['wind_u' (m/s), 'wind_v' (m/s)]
+            * Required variables: ['wind10_u' (m/s), 'wind10_v' (m/s)]
             * Required coordinates: ['time', 'y', 'x']
 
         dst_res: float
@@ -2396,7 +2396,7 @@ def setup_wind_forcing_from_grid(self, wind, dst_res=None, **kwargs):
             geom=self.region,
             buffer=2,
             time_tuple=self.get_model_time(),
-            variables=["wind_u", "wind_v"],
+            variables=["wind10_u", "wind10_v"],
         )
 
         # reproject to model utm crs

From 84262d03e9d76d14bd2c49708e33e8987563c0d5 Mon Sep 17 00:00:00 2001
From: roeldegoede <83765910+roeldegoede@users.noreply.github.com>
Date: Thu, 29 Aug 2024 10:40:39 +0200
Subject: [PATCH 18/28] Parse forcing precision (#210)

* Default for baro should be set to 1! As is default in SFINCS itself, otherwise any pressure input is ignored....

* cahnge default value also in test-inputs

* added option to parse precision of forcing timeseries

* remove "auto" derivation of timeseries format because it's prone to errors

* fix tests

---------

Co-authored-by: Tim Leijnse <timleynse94@gmail.com>
---
 hydromt_sfincs/sfincs.py   | 12 +++++++-----
 tests/test_1model_class.py | 31 +++++++++++++++++++++++++++++++
 2 files changed, 38 insertions(+), 5 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 4691bfb2..5ea70510 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -3113,7 +3113,7 @@ def read_forcing(self, data_vars: List = None):
             else:
                 logger.warning(f"No forcing variables found in {fname}file")
 
-    def write_forcing(self, data_vars: Union[List, str] = None):
+    def write_forcing(self, data_vars: Union[List, str] = None, fmt: str = "%7.2f"):
         """Write forcing to ascii or netcdf (netampr) files.
         Filenames are based on the `config` attribute.
 
@@ -3121,14 +3121,16 @@ def write_forcing(self, data_vars: Union[List, str] = None):
         ----------
         data_vars : list of str, optional
             List of data variables to write, by default None (all)
+        fmt : str, optional
+            Format string for timeseries data, by default "%7.2f".
         """
         self._assert_write_mode
 
         # change precision of coordinates according to crs
         if self.crs.is_geographic:
-            fmt = "%.6f"
+            fmt_xy = "%.6f"
         else:
-            fmt = "%.1f"
+            fmt_xy = "%.1f"
 
         if self.forcing:
             self.logger.info("Write forcing files")
@@ -3166,7 +3168,7 @@ def write_forcing(self, data_vars: Union[List, str] = None):
                         self.set_config(f"{ts_name}file", f"sfincs.{ts_name}")
                     fn = self.get_config(f"{ts_name}file", abs_path=True)
                     # write timeseries
-                    utils.write_timeseries(fn, df, tref)
+                    utils.write_timeseries(fn, df, tref, fmt=fmt)
                 # write xy
                 if xy_name and da is not None:
                     # parse data to geodataframe
@@ -3179,7 +3181,7 @@ def write_forcing(self, data_vars: Union[List, str] = None):
                         self.set_config(f"{xy_name}file", f"sfincs.{xy_name}")
                     fn_xy = self.get_config(f"{xy_name}file", abs_path=True)
                     # write xy
-                    hydromt.io.write_xy(fn_xy, gdf, fmt=fmt)
+                    hydromt.io.write_xy(fn_xy, gdf, fmt=fmt_xy)
                     if self._write_gis:  # write geojson file to gis folder
                         self.write_vector(variables=f"forcing.{ts_names[0]}")
 
diff --git a/tests/test_1model_class.py b/tests/test_1model_class.py
index 98850e63..785af152 100644
--- a/tests/test_1model_class.py
+++ b/tests/test_1model_class.py
@@ -359,6 +359,37 @@ def test_observations(tmpdir):
     assert len(mod.geoms["crs"].index) == nr_observation_lines * 2
 
 
+def test_forcing_io(tmpdir):
+    root = TESTMODELDIR
+    mod = SfincsModel(root=root, mode="r")
+    # read
+    mod.read_forcing()
+
+    # write forcing
+    tmp_root = str(tmpdir.join("forcing_test"))
+    mod.set_root(tmp_root, mode="w")
+    mod.write_forcing()
+    mod.write_config()
+
+    # read and check if identical
+    mod1 = SfincsModel(root=tmp_root, mode="r")
+    mod1.read_forcing()
+    assert np.allclose(mod1.forcing["bzs"], mod.forcing["bzs"])
+
+    # now change the timeseries-format and write again
+    tmp_root = str(tmpdir.join("forcing_test2"))
+    mod1.set_root(tmp_root, mode="w+")
+    mod1.write_forcing(fmt="%7.1f")
+    mod1.write_config()
+
+    # read and check if identical
+    mod2 = SfincsModel(root=tmp_root, mode="r")
+    mod2.read_forcing()
+    assert np.isclose(
+        np.sum(mod2.forcing["bzs"].values - mod1.forcing["bzs"].values), 0.73
+    )
+
+
 def test_read_results():
     root = TESTMODELDIR
     mod = SfincsModel(root=root, mode="r")

From aef72a3bd72a5fd693da193344f0d32567c99c0b Mon Sep 17 00:00:00 2001
From: vanasseltk <167875592+vanasseltk@users.noreply.github.com>
Date: Thu, 29 Aug 2024 11:01:23 +0200
Subject: [PATCH 19/28] Dca rivers (#209)

* key_zb

* compatible with burnign in rivers through elevation dataset

* changes_review (to be cotinued)

* commnets_roel (continued)

* new adjustment for parsing

* last edit

* pre_commit

* small update; point zb could be combined with gdf_riv so it should be outside the if centerlines statement

---------

Co-authored-by: roeldegoede <roeldegoede@outlook.com>
---
 hydromt_sfincs/sfincs.py               | 21 ++++++++++++++++++---
 hydromt_sfincs/workflows/bathymetry.py |  1 +
 2 files changed, 19 insertions(+), 3 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 5ea70510..683e9d5d 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -680,6 +680,7 @@ def setup_subgrid(
               rivdph or rivbed (river depth [m]; river bedlevel [m+REF]),
               manning (Manning's n [s/m^(1/3)]; optional)
             * mask (optional): filename (or Path) of river mask
+            * point_zb (optional): filename (or Path) of river points with bed (z) values
             * river attributes (optional): "rivdph", "rivbed", "rivwth", "manning"
               to fill missing values
             * arguments to the river burn method (optional):
@@ -3720,6 +3721,8 @@ def _parse_datasets_riv(self, datasets_riv):
             "mask",
             "gdf_riv",
             "gdf_riv_mask",
+            "gdf_zb",
+            "point_zb",
         ]
         copy_keys = []
         attrs = ["rivwth", "rivdph", "rivbed", "manning"]
@@ -3747,11 +3750,24 @@ def _parse_datasets_riv(self, datasets_riv):
                             gdf_riv[key] = value
                         elif np.any(np.isnan(gdf_riv[key])):  # fill na
                             gdf_riv[key] = gdf_riv[key].fillna(value)
-                if not gdf_riv.columns.isin(["rivbed", "rivdph"]).any():
+                dd.update({"gdf_riv": gdf_riv})
+
+            # parse bed_level on points
+            if "point_zb" in dataset:
+                gdf_zb = self.data_catalog.get_geodataframe(
+                    dataset.get("point_zb"),
+                    geom=self.mask.raster.box,
+                )
+                dd.update({"gdf_zb": gdf_zb})
+
+            if "gdf_riv" in dd:
+                if (
+                    not gdf_riv.columns.isin(["rivbed", "rivdph"]).any()
+                    and "gdf_zb" not in dd
+                ):
                     raise ValueError("No 'rivbed' or 'rivdph' attribute found.")
             else:
                 raise ValueError("No 'centerlines' dataset provided.")
-            dd.update({"gdf_riv": gdf_riv})
 
             # parse mask
             if "mask" in dataset:
@@ -3765,7 +3781,6 @@ def _parse_datasets_riv(self, datasets_riv):
                     "Either mask must be provided or centerlines "
                     "should contain a 'rivwth' attribute."
                 )
-
             # copy remaining keys
             for key, value in dataset.items():
                 if key in copy_keys and key not in dd:
diff --git a/hydromt_sfincs/workflows/bathymetry.py b/hydromt_sfincs/workflows/bathymetry.py
index f4e3e010..adb68d60 100644
--- a/hydromt_sfincs/workflows/bathymetry.py
+++ b/hydromt_sfincs/workflows/bathymetry.py
@@ -311,6 +311,7 @@ def burn_river_rect(
         if np.any(np.isnan(gdf_zb[manning_name])):
             gdf_zb["idx0"], _ = nearest(gdf_zb, gdf_riv)
             man_nearest = gdf_riv.loc[gdf_zb["idx0"], manning_name]
+            man_nearest.index = gdf_zb.index
             gdf_zb[manning_name] = gdf_zb[manning_name].fillna(man_nearest)
     elif rivbed_name not in gdf_zb.columns:
         raise ValueError(f"Missing {rivbed_name} or {rivdph_name} attributes")

From 97c803c4fcfda410a9cc7ba06a62d5204022749a Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 29 Aug 2024 11:07:43 +0200
Subject: [PATCH 20/28] don't show working_with_data_example anymore on the
 docs

---
 docs/user_guide/sfincs_build_update.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/user_guide/sfincs_build_update.rst b/docs/user_guide/sfincs_build_update.rst
index e3f95145..e75ccdf5 100644
--- a/docs/user_guide/sfincs_build_update.rst
+++ b/docs/user_guide/sfincs_build_update.rst
@@ -147,4 +147,4 @@ See `Example: Build from Script <../_examples/build_from_script.ipynb>`_ for a m
     Example: Build from CLI <../_examples/build_from_cli.ipynb>
     Example: Build from script <../_examples/build_from_script.ipynb>
     Example: Setup model forcing <../_examples/example_forcing.ipynb>
-    Example: Working with data <../_examples/example_datasources.ipynb>
+    .. Example: Working with data <../_examples/example_datasources.ipynb>

From 36c11ffd4bc2575f1e7808da921f6afc1bcfe844 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Tue, 3 Sep 2024 15:20:19 +0200
Subject: [PATCH 21/28] solve deprecation warning

---
 hydromt_sfincs/workflows/flwdir.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/hydromt_sfincs/workflows/flwdir.py b/hydromt_sfincs/workflows/flwdir.py
index 4f1188e2..00a5b370 100644
--- a/hydromt_sfincs/workflows/flwdir.py
+++ b/hydromt_sfincs/workflows/flwdir.py
@@ -162,7 +162,7 @@ def river_source_points(
         return gpd.GeoDataFrame()
 
     # remove lines that fully are within the buffer of the mask boundary
-    bnd = gdf_mask.boundary.buffer(buffer).unary_union
+    bnd = gdf_mask.boundary.buffer(buffer).union_all()
     gdf_riv = gdf_riv[~gdf_riv.within(bnd)]
 
     # get source points 1m before the start/end of the river

From 7c3330ab44bd1f839cabe2c8bfd725c687ebc67a Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Wed, 4 Sep 2024 14:19:24 +0200
Subject: [PATCH 22/28] update environment and sfincs release name

---
 envs/hydromt-sfincs-dev.yml | 4 ++--
 hydromt_sfincs/sfincs.py    | 4 ++--
 hydromt_sfincs/subgrid.py   | 6 +++---
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/envs/hydromt-sfincs-dev.yml b/envs/hydromt-sfincs-dev.yml
index 4458ad0c..ebb3ce98 100644
--- a/envs/hydromt-sfincs-dev.yml
+++ b/envs/hydromt-sfincs-dev.yml
@@ -8,8 +8,8 @@ dependencies:
 - cartopy
 - descartes
 - ffmpeg
-- geopandas>=0.8
-- hydromt>=0.9.1, <0.10
+- geopandas>=1.0
+- hydromt>=0.10, <0.11
 - jupyterlab
 - matplotlib
 - nbsphinx
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 7fca5fde..2c534769 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -717,8 +717,8 @@ def setup_subgrid(
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
             Option for the computation of the conveyance depth at u/v points, by default 2.
-            1: "old" method, compliant with SFINCS < v2.1.0
-            2: "new" method, recommended for SFINCS >= v2.1.0
+            1: "old" method, compliant with SFINCS < v2.1.
+            2: "new" method, recommended for SFINCS >= v2.1.
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea, by default 0.04 and 0.02 s.m-1/3
             Note that these values are only used when no Manning's n datasets are provided,
diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index add6ea3d..32d0b7b6 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -431,8 +431,8 @@ def build(
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
             Option for the computation of the conveyance depth at u/v points, by default 2.
-            1: "old" method, compliant with SFINCS < v2.1.0
-            2: "new" method, recommended for SFINCS >= v2.1.0
+            1: "old" method, compliant with SFINCS < v2.1.
+            2: "new" method, recommended for SFINCS >= v2.1.
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea,
             by default 0.04 and 0.02 s.m-1/3
@@ -1066,7 +1066,7 @@ def subgrid_q_table(
     # Determine level size (metres)
     dlevel = (zmax - zmin) / (nlevels - 1)
 
-    # Option can be either 1 ("old, compliant with SFINCS < v2.1.0") or 2 ("new", recommended SFINCS >= v2.1.0)
+    # Option can be either 1 ("old, compliant with SFINCS < v2.1.") or 2 ("new", recommended SFINCS >= v2.1.)
     option = option
 
     # Loop through levels

From cbc59232be1690d4d4370d0220e2d851ca4683e4 Mon Sep 17 00:00:00 2001
From: Tim Leijnse <timleynse94@gmail.com>
Date: Wed, 4 Sep 2024 14:25:55 +0200
Subject: [PATCH 23/28] Update sfincs.py

---
 hydromt_sfincs/sfincs.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index da09adb4..f0920980 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -716,7 +716,7 @@ def setup_subgrid(
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
             Option for the computation of the representative roughness and conveyance depth at u/v points, by default 2.
-            1: "old" weighting method, compliant with SFINCS < v2.1.0, taking the avarage of the adjecent cells
+            1: "old" weighting method, compliant with SFINCS < v2.1.0, taking the avarage of the adjacent cells
             2: "improved" weighting method, recommended for SFINCS >= v2.1.0, that takes into account the wet fractions of the adjacent cells
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea, by default 0.04 and 0.02 s.m-1/3

From 9c422abeb6c5ab172db3cfc06de2385c5f1dbf00 Mon Sep 17 00:00:00 2001
From: Tim Leijnse <timleynse94@gmail.com>
Date: Wed, 4 Sep 2024 14:26:37 +0200
Subject: [PATCH 24/28] Update sfincs.py

---
 hydromt_sfincs/sfincs.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index f0920980..e82c633f 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -716,8 +716,8 @@ def setup_subgrid(
             Threshold depth in SFINCS model, by default 0.01 m
         q_table_option : int, optional
             Option for the computation of the representative roughness and conveyance depth at u/v points, by default 2.
-            1: "old" weighting method, compliant with SFINCS < v2.1.0, taking the avarage of the adjacent cells
-            2: "improved" weighting method, recommended for SFINCS >= v2.1.0, that takes into account the wet fractions of the adjacent cells
+            1: "old" weighting method, compliant with SFINCS < v2.1.1, taking the avarage of the adjacent cells
+            2: "improved" weighting method, recommended for SFINCS >= v2.1.1, that takes into account the wet fractions of the adjacent cells
         manning_land, manning_sea : float, optional
             Constant manning roughness values for land and sea, by default 0.04 and 0.02 s.m-1/3
             Note that these values are only used when no Manning's n datasets are provided,

From 12f1081d65e40bac81d5b934b4cb5ae48eefa7e7 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Wed, 4 Sep 2024 16:01:08 +0200
Subject: [PATCH 25/28] bugfixes related to renaming wind and pressure
 variables in #211

---
 hydromt_sfincs/plots.py  | 4 ++--
 hydromt_sfincs/sfincs.py | 6 +++---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/hydromt_sfincs/plots.py b/hydromt_sfincs/plots.py
index 17e4b888..350ae31a 100644
--- a/hydromt_sfincs/plots.py
+++ b/hydromt_sfincs/plots.py
@@ -73,8 +73,8 @@ def plot_forcing(forcing: Dict, **kwargs):
             df.plot(drawstyle="steps", ax=axes[i])
         elif (
             name.startswith("press")
-            or name.startswith("wind_u")
-            or name.startswith("wind_v")
+            or name.startswith("wind10_u")
+            or name.startswith("wind10_v")
         ):
             df.plot.line(ax=axes[i])
         elif name.startswith("wnd"):
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index b3bf6d59..ab8a86e7 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -61,7 +61,7 @@ class SfincsModel(GridModel):
         "press_2d": ("netamp", {"barometric_pressure": "press_2d"}),
         "wind_2d": (
             "netamuamv",
-            {"eastward_wind": "wind_u", "northward_wind": "wind_v"},
+            {"eastward_wind": "wind10_u", "northward_wind": "wind10_v"},
         ),
     }
     _FORCING_SPW = {"spiderweb": "spw"}  # TODO add read and write functions
@@ -87,8 +87,8 @@ class SfincsModel(GridModel):
         "precip": {"standard_name": "precipitation", "unit": "mm.hr-1"},
         "precip_2d": {"standard_name": "precipitation", "unit": "mm.hr-1"},
         "press_2d": {"standard_name": "barometric pressure", "unit": "Pa"},
-        "wind_u": {"standard_name": "eastward wind", "unit": "m/s"},
-        "wind_v": {"standard_name": "northward wind", "unit": "m/s"},
+        "wind10_u": {"standard_name": "eastward wind", "unit": "m/s"},
+        "wind10_v": {"standard_name": "northward wind", "unit": "m/s"},
         "wnd": {"standard_name": "wind", "unit": "m/s"},
     }
 

From cdfb0b4ff2d0bf059cc8f0dc2b19b1ca982dc9aa Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Wed, 4 Sep 2024 23:23:48 +0200
Subject: [PATCH 26/28] bugfix in reading of subgrid netcdf file

---
 hydromt_sfincs/subgrid.py | 54 ++++++++++++++++++++++++++++-----------
 1 file changed, 39 insertions(+), 15 deletions(-)

diff --git a/hydromt_sfincs/subgrid.py b/hydromt_sfincs/subgrid.py
index c76a8a1f..b40446b5 100644
--- a/hydromt_sfincs/subgrid.py
+++ b/hydromt_sfincs/subgrid.py
@@ -47,13 +47,9 @@ def read(self, file_name, mask):
         # find indices of active cells
         index_nm, index_mu1, index_nu1 = utils.find_uv_indices(mask)
         active_indices = np.where(index_nm > -1)[0]
-        active_indices_u = np.where(index_mu1 > -1)[0]
-        active_indices_v = np.where(index_nu1 > -1)[0]
 
         # convert 1D indices to 2D indices
-        active_z = np.unravel_index(active_indices, grid_dim, order="F")
-        active_u = np.unravel_index(active_indices_u, grid_dim, order="F")
-        active_v = np.unravel_index(active_indices_v, grid_dim, order="F")
+        active_cells = np.unravel_index(active_indices, grid_dim, order="F")
 
         # Initialize the data-arrays
         # Z points
@@ -96,11 +92,11 @@ def read(self, file_name, mask):
 
         # Now read the data and add it to the data-arrays
         # use index_nm of the active cells in the new dataset
-        self.z_zmin[active_z] = ds["z_zmin"].values.flatten()
-        self.z_zmax[active_z] = ds["z_zmax"].values.flatten()
-        self.z_volmax[active_z] = ds["z_volmax"].values.flatten()
+        self.z_zmin[active_cells] = ds["z_zmin"].values.flatten()
+        self.z_zmax[active_cells] = ds["z_zmax"].values.flatten()
+        self.z_volmax[active_cells] = ds["z_volmax"].values.flatten()
         for ilevel in range(self.nlevels):
-            self.z_level[ilevel, active_z[0], active_z[1]] = ds["z_level"][
+            self.z_level[ilevel, active_cells[0], active_cells[1]] = ds["z_level"][
                 ilevel
             ].values.flatten()
 
@@ -108,20 +104,48 @@ def read(self, file_name, mask):
         var_list = ["zmin", "zmax", "ffit", "navg"]
         for var in var_list:
             uv_var = ds["uv_" + var].values.flatten()
-            self.u_zmin[active_u] = uv_var[index_mu1[active_indices_u]]
-            self.v_zmin[active_v] = uv_var[index_nu1[active_indices_v]]
+
+            # Dynamically set the attribute for self.u_var and self.v_var
+            u_attr_name = f"u_{var}"
+            v_attr_name = f"v_{var}"
+
+            # Retrieve the current attribute values
+            u_array = getattr(self, u_attr_name)
+            v_array = getattr(self, v_attr_name)
+
+            # Update only the active indices
+            u_array[active_cells] = uv_var[index_mu1[active_indices]]
+            v_array[active_cells] = uv_var[index_nu1[active_indices]]
+
+            # Set the modified arrays back to the attributes
+            setattr(self, u_attr_name, u_array)
+            setattr(self, v_attr_name, v_array)
 
         var_list_levels = ["havg", "nrep", "pwet"]
         for var in var_list_levels:
             for ilevel in range(self.nlevels):
                 uv_var = ds["uv_" + var][ilevel].values.flatten()
-                self.u_havg[ilevel, active_u[0], active_u[1]] = uv_var[
-                    index_mu1[active_indices_u]
+
+                # Dynamically set the attribute for self.u_var and self.v_var
+                u_attr_name = f"u_{var}"
+                v_attr_name = f"v_{var}"
+
+                # Retrieve the current attribute values
+                u_array = getattr(self, u_attr_name)
+                v_array = getattr(self, v_attr_name)
+
+                # Update only the active indices
+                u_array[ilevel, active_cells[0], active_cells[1]] = uv_var[
+                    index_mu1[active_indices]
                 ]
-                self.v_havg[ilevel, active_v[0], active_v[1]] = uv_var[
-                    index_nu1[active_indices_v]
+                v_array[ilevel, active_cells[0], active_cells[1]] = uv_var[
+                    index_nu1[active_indices]
                 ]
 
+                # Set the modified arrays back to the attributes
+                setattr(self, u_attr_name, u_array)
+                setattr(self, v_attr_name, v_array)
+
         # close the dataset
         ds.close()
 

From 3f648d8d126887cb9dfb60f804b3f981e58ef436 Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 5 Sep 2024 09:33:01 +0200
Subject: [PATCH 27/28] update changelog and environment.yml

---
 docs/changelog.rst | 9 ++++++++-
 environment.yml    | 4 ++--
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index 7966c706..6a2a9878 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -6,8 +6,15 @@ Distinction is made between new methods (Added), changes to existing methods (Ch
 The format is based on `Keep a Changelog`_, and this project adheres to
 `Semantic Versioning`_.
 
-v1.1.0 (Unreleased)
+v1.1.0 (05-09-2024)
 ===================
+**This release contains some breaking changes and can only be used in combination with SFINCS versions ≥ 2.1.1
+`SFINCS model <https://github.com/Deltares/SFINCS/releases/tag/v2.1.1_Dollerup_release>`_.**
+
+The most important change is the implementation of a new subgrid methodology including wet fraction as in Van Ormondt et al. (2024, in review),
+which is now written as a NetCDF file! The old implementation is still available when providing the original binary file, but then all wet fractions are assumed to be 1.
+
+Next to this, some minor additions and bugfixes are made that improve the overall functionality of the package.
 
 Added
 -----
diff --git a/environment.yml b/environment.yml
index 98ea9cec..af93b103 100644
--- a/environment.yml
+++ b/environment.yml
@@ -10,8 +10,8 @@ dependencies:
   - descartes # to run examples
   - ffmpeg  # to run examples (animation)
   # - git
-  - hydromt>=0.8.0
-  - hydromt_sfincs>=1.0
+  - hydromt>=0.10.0, <0.11
+  - hydromt_sfincs>=1.1.0
   - jupyterlab # to run examples
   - matplotlib # to run examples
   - pip

From 872bde61edc750cb8da4585cd31ca31f7476395c Mon Sep 17 00:00:00 2001
From: roeldegoede <roeldegoede@outlook.com>
Date: Thu, 5 Sep 2024 10:08:56 +0200
Subject: [PATCH 28/28] update lay-out changelog

---
 docs/changelog.rst | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index 6a2a9878..10553a24 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -8,8 +8,8 @@ The format is based on `Keep a Changelog`_, and this project adheres to
 
 v1.1.0 (05-09-2024)
 ===================
-**This release contains some breaking changes and can only be used in combination with SFINCS versions ≥ 2.1.1
-`SFINCS model <https://github.com/Deltares/SFINCS/releases/tag/v2.1.1_Dollerup_release>`_.**
+**This release contains some breaking changes and can only be used in combination with
+`SFINCS versions ≥ 2.1.1  <https://github.com/Deltares/SFINCS/releases/tag/v2.1.1_Dollerup_release>`_.**
 
 The most important change is the implementation of a new subgrid methodology including wet fraction as in Van Ormondt et al. (2024, in review),
 which is now written as a NetCDF file! The old implementation is still available when providing the original binary file, but then all wet fractions are assumed to be 1.