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AEME AEME website

Lifecycle: experimental R-CMD-check pkgdown Codecov test coverage

The Aquatic Ecosystem Model Ensemble (AEME) package allows you to setup and run an ensemble of aquatic ecosystem models. The models are DYRESM-CAEDYM, GLM-AED and GOTM-WET.

Development

This package was developed by LimnoTrack as part of the Lake Ecosystem Restoration New Zealand Modelling Platform (LERNZmp) project. LimnoTrack website

Installation

You can install the development version of AEME from GitHub with:

# install.packages("devtools")
devtools::install_github("limnotrack/AEME")

Example

This is a basic example which shows you how to build and run one of the models in the ensemble:

library(AEME)
#> 
#> Attaching package: 'AEME'
#> The following object is masked from 'package:stats':
#> 
#>     time
## basic example code
tmpdir <- tempdir()
aeme_dir <- system.file("extdata/lake/", package = "AEME")
# Copy files from package into tempdir
file.copy(aeme_dir, tmpdir, recursive = TRUE)
#> [1] TRUE
path <- file.path(tmpdir, "lake")
aeme <- yaml_to_aeme(path = path, "aeme.yaml")
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is FALSE
#> Warning in aeme_constructor(lake = yaml$lake, time = yaml$time, configuration = yaml$configuration, : Lake area [152343 m2] is different to the area calculated from the lake
#> shape [152433.09 m2].
model_controls <- get_model_controls(use_bgc = TRUE)
model <- c("dy_cd", "glm_aed", "gotm_wet")
aeme <- build_aeme(path = path, aeme = aeme, model = model,
                            model_controls = model_controls,
                            ext_elev = 5, use_bgc = TRUE)
#> Building simulation for Wainamu [2024-09-18 03:18:48]
#> Missing state variables in inflows: PHY_crypt
#> Added default values for missing variables.
#> Using observed water level
#> Missing values in observed water level
#> Using constant water level
#> Correcting water balance using estimated outflows (method = 2).
#> Calculating lake level using lake depth and a sinisoidal function.
#> Building DYRESM-CAEDYM for lake wainamu
#> Copied in DYRESM par file
#> Writing DYRESM configuration
#> [1] "TEMPTURE SALINITY DO PO4 DOPL POPL PIP TP NH4 NO3 DONL PONL TN DOCL POCL SiO2 CYANO CHLOR CRYPT FDIAT TCHLA SSOL1"
#> Writing DYRESM control file
#> Building GLM3-AED2 model for lake wainamu
#> Copied in GLM nml file
#> Copied in AED nml file
#>    oxy_initial   = 625 replaced with 312.5
#>    frp_initial = 0.3229 replaced with 0.3229
#>      dop_initial  = 0.3229 replaced with 0.3229
#>      pop_initial  = 0.3229 replaced with 0.3229
#>    amm_initial = 1.4279 replaced with 1.4279
#>    nit_initial = 1.0709 replaced with 1.0709
#>      don_initial  = 21.4183 replaced with 21.4183
#>      pon_initial  = 7.1394 replaced with 7.1394
#>      doc_initial  = 41.6285 replaced with 41.6285
#>      poc_initial  = 16.6514 replaced with 16.6514
#>    rsi_initial = 1 replaced with 1
#> PHY_cyano 0.24022 replaced with 0.24022
#> PHY_green 0.300275 replaced with 0.300275
#> PHY_crypt  replaced with
#> PHY_diatom 0.300275 replaced with 0.300275
#>     ss_initial   = 3,3 replaced with 3,
#> Building GOTM-WET for lake wainamu
#> Copied all GOTM configuration files
#> instances/abiotic_water/initialization/sO2W 13 replaced with 10
#> instances/abiotic_water/initialization/sPO4W 0.1 replaced with 0.01
#> instances/abiotic_water/initialization/sPDOMW 0.001 replaced with 0.01
#> instances/abiotic_water/initialization/sPPOMW 0.001 replaced with 0.01
#> instances/abiotic_water/initialization/sNH4W 0.05 replaced with 0.02
#> instances/abiotic_water/initialization/sNO3W 0.5 replaced with 0.015
#> instances/abiotic_water/initialization/sNDOMW 0.01 replaced with 0.3
#> instances/abiotic_water/initialization/sNPOMW 0.01 replaced with 0.1
#> instances/abiotic_water/initialization/sDDOMW 2.5 replaced with 0.5
#> instances/abiotic_water/initialization/sDPOMW 0.1 replaced with 0.2
#> instances/abiotic_water/initialization/sSiO2W 3.5 replaced with 1
#> instances/cyanobacteria/initialization/sDW 0.1 replaced with 0.2
#> instances/cyanobacteria/initialization/sNW 0.03 replaced with 0.03
#> instances/cyanobacteria/initialization/sPW 0.003 replaced with 0.0019
#> instances/greens/initialization/sDW 0.1 replaced with 0.1
#> instances/greens/initialization/sNW 0.05 replaced with 0.015
#> instances/greens/initialization/sPW 0.001 replaced with 0.00094
#> instances/diatoms/initialization/sDW 0.2 replaced with 0.25
#> instances/diatoms/initialization/sNW 0.05 replaced with 0.038
#> instances/diatoms/initialization/sPW 0.005 replaced with 0.0024
#> instances/abiotic_water/initialization/sDIMW 4 replaced with 3
aeme <- run_aeme(aeme = aeme, model = model, verbose = FALSE, 
                      path = path, parallel = TRUE)
#> Running models in parallel... [2024-09-18 15:18:52]
#> Model run complete![2024-09-18 15:21:12]
#> Reading models in parallel... [2024-09-18 15:21:13]
#> Model reading complete![2024-09-18 15:21:16]

The model input and output is handled as it’s own S4 object of class aeme. This allows for the standardisation and generalisation of functions for this class alongside ensuring integrity and validity to it’s structure.

class(aeme)
#> [1] "Aeme"
#> attr(,"package")
#> [1] "AEME"

This allows for easier handling of the model output data within our structure and allows for condensed output to be printed to the console:

aeme
#>             AEME 
#> -------------------------------------------------------------------
#>   Lake
#> Wainamu (ID: 45819); Lat: -36.89; Lon: 174.47; Elev: 23.64m; Depth: 13.07m;
#> Area: 152343 m2; Shape file: Present
#> -------------------------------------------------------------------
#>   Time
#> Start: 2020-08-01; Stop: 2021-06-30; Time step: 3600
#>  Spin up (days): GLM: 2; GOTM: 1; DYRESM: 1
#> -------------------------------------------------------------------
#>   Configuration
#>     Model controls: Present
#>           Physical   |   Biogeochemical
#> DY-CD    : Present    |   Present
#> GLM-AED  : Present    |   Present
#> GOTM-WET : Present    |   Present
#> -------------------------------------------------------------------
#>   Observations
#> Lake: Present; Level: Present
#> -------------------------------------------------------------------
#>   Input
#> Inital profile: Present; Inital depth: 13.07m; Hypsograph: Present (n=44);
#> Meteo: Present; Use longwave: TRUE; Kw: 1.31
#> -------------------------------------------------------------------
#>   Inflows
#> Data: Present; Scaling factors: DY-CD: 1; GLM-AED: 1; GOTM-WET: 1
#> -------------------------------------------------------------------
#>   Outflows
#> Data: Present; Scaling factors: DY-CD: 1; GLM-AED: 1; GOTM-WET: 1
#> -------------------------------------------------------------------
#>   Water balance
#> Method: 2; Use: obs; Modelled: Absent; Water balance: Present
#> -------------------------------------------------------------------
#>   Parameters: 
#> Number of parameters: 0
#> -------------------------------------------------------------------
#>   Output: 
#> Number of ensembles: 1
#> DY-CD:    1
#> GLM-AED:  1
#> GOTM-WET: 1

Model data can be visualised easily using the plot_output() function:

p1 <- plot_output(aeme = aeme, model = model, var_sim = "HYD_temp")
p1
#> Warning: Removed 246 rows containing missing values or values outside the scale range
#> (`geom_col()`).

Also, visualising lake level plots.

p2 <- plot_output(aeme = aeme, model = model, var_sim = "LKE_lvlwtr",
                  facet = FALSE)
p2