In aemon-j/LakeEnsemblR: Run Ensemble of Lake Models

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Once you have your hypsograph, water temperature observations and meteorological files prepared, running LakeEnsemblR is relatively straightforward.

Example model run

# Load LakeEnsemblR
library(LakeEnsemblR)

# Copy template folder
template_folder <- system.file("extdata/feeagh", package= "LakeEnsemblR")
dir.create("example") # Create example folder
file.copy(from = template_folder, to = "example", recursive = TRUE)
setwd("example/feeagh") # Change working directory to example folder

knitr::opts_knit$set(root.dir = "example/feeagh")

# Set config file & models
config_file <- "LakeEnsemblR.yaml"
model <- c("FLake", "GLM", "GOTM", "Simstrat", "MyLake")

# Example run
# 1. Export settings - creates directories with all model setups and exports settings from the LER configuration file
export_config(config_file = config_file, model = model)

# 2. Run ensemble lake models
run_ensemble(config_file = config_file, model = model)

Post-processing

# Load libraries for post-processing
library(gotmtools)
library(ggplot2)

## Plot model output using gotmtools/ggplot2
# Extract names of all the variables in netCDF
ncdf <- "output/ensemble_output.nc"
vars <- gotmtools::list_vars(ncdf)
vars # Print variables

p1 <- plot_heatmap(ncdf)
p1
# Change the theme and increase text size for saving
p1 <- p1 +
  theme_classic(base_size = 14) + 
  scale_colour_gradientn(limits = c(0, 21),
                         colours = rev(RColorBrewer::brewer.pal(11, "Spectral")))

p1