Yield change scenarios based on theoretical models

Load packages, read data and source custom scripts

rm(list = ls())
library(stars)

#> Loading required package: abind

#> Loading required package: sf

#> Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1

path_proj <- day2day::git_path()
path_data <- file.path(path_proj, "data")
path_cleaned <- file.path(path_data, "cleaned")
path_modelled <- file.path(path_data, "modelled")

source(file.path(path_proj, "src", "34-read-sce-var.R"))
source(file.path(path_proj, "src", "61-vis-stars.R"))

yields <- readRDS(file.path(path_cleaned, "yield-params-and-season.rds"))
uk <- st_read(file.path(path_cleaned, "uk_simple.gpkg"), "union")

#> Reading layer `union' from data source `/home/rstudio/Documents/Projects/land-suitability/data/cleaned/uk_simple.gpkg' using driver `GPKG'
#> Simple feature collection with 1 feature and 0 fields
#> geometry type:  MULTIPOLYGON
#> dimension:      XY
#> bbox:           xmin: -116.1923 ymin: 7054.099 xmax: 655644.8 ymax: 1218625
#> projected CRS:  OSGB 1936 / British National Grid

products <- names(yields$season)

Visualize

read_yield_change <- function(path_read, var = "wheat") {
    pattern <- paste("uk_1km_yield_change", var, "20yr", sep = "_")
    regex <- "^.+_20yr-[a-z]+-[a-z]+_([[:digit:]]{4}).+(-[[:digit:]]{4}).+$"
    out <- read_sce_var(path_read, pattern, regex)
    return(out)
}

for (product in products) {
    cat(paste0("\n### Yield change scenarios (", product, ")\n" ))
    out <- read_yield_change(path_modelled, product)
    plot_stars(out, uk, nbreaks = 20, breaks = "quantile")
    cat("\n")
}

Time to execute the task

Only useful when executed with Rscript.

proc.time()

#>    user  system elapsed 
#>  76.523   4.855  81.449