River Loads

paths <- list.files(testthat::test_path("output","rhine/hydrology/loads"), pattern = ".*\\.tif$", full.names = TRUE)
rast_loads <- terra::rast(paths)
terra::plot(log10(rast_loads), col = hcl.colors(50,"Geyser"), plg = list(title= "log10 particels"))

Summary statistics of the log10 river loads

terra::summary(log10(rast_loads))
##       Jan             Feb             Mar             Apr       
##  Min.   :11.04   Min.   :11.04   Min.   :11.05   Min.   :11.05  
##  1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01  
##  Median :12.32   Median :12.32   Median :12.32   Median :12.32  
##  Mean   :12.50   Mean   :12.50   Mean   :12.50   Mean   :12.50  
##  3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96  
##  Max.   :13.99   Max.   :13.99   Max.   :13.99   Max.   :13.99  
##  NA's   :168     NA's   :168     NA's   :168     NA's   :168    
##       May             Jun             Jul             Aug       
##  Min.   :11.05   Min.   :11.05   Min.   :11.05   Min.   :11.05  
##  1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01  
##  Median :12.32   Median :12.32   Median :12.32   Median :12.32  
##  Mean   :12.50   Mean   :12.50   Mean   :12.50   Mean   :12.50  
##  3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96  
##  Max.   :13.99   Max.   :13.99   Max.   :13.99   Max.   :13.99  
##  NA's   :168     NA's   :168     NA's   :168     NA's   :168    
##       Sep             Oct             Nov             Dec       
##  Min.   :11.05   Min.   :11.05   Min.   :11.05   Min.   :11.05  
##  1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01   1st Qu.:12.01  
##  Median :12.32   Median :12.32   Median :12.32   Median :12.32  
##  Mean   :12.50   Mean   :12.50   Mean   :12.50   Mean   :12.50  
##  3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96   3rd Qu.:12.96  
##  Max.   :13.99   Max.   :13.99   Max.   :13.99   Max.   :13.99  
##  NA's   :168     NA's   :168     NA's   :168     NA's   :168

River Concentrations

paths <- list.files(testthat::test_path("output","rhine/hydrology/conc"), pattern = ".*\\.tif$", full.names = TRUE)
rast_conc <- terra::rast(paths)
terra::plot(log10(rast_conc / 1e3), col = hcl.colors(50,"Geyser"), plg = list(title = "log10 part/L"))

Summary statistics of the log10 oocysts/L

terra::summary(log10(rast_conc/1e3))
##       Jan              Feb              Mar              Apr          
##  Min.   :0.1655   Min.   :0.2476   Min.   :0.1164   Min.   :-0.00293  
##  1st Qu.:0.6281   1st Qu.:0.6616   1st Qu.:0.5940   1st Qu.: 0.57577  
##  Median :0.9167   Median :0.9137   Median :0.8470   Median : 0.86899  
##  Mean   :0.8341   Mean   :0.8451   Mean   :0.7799   Mean   : 0.79262  
##  3rd Qu.:1.0114   3rd Qu.:1.0032   3rd Qu.:0.9497   3rd Qu.: 1.00052  
##  Max.   :1.5867   Max.   :1.5914   Max.   :1.5771   Max.   : 1.68198  
##  NA's   :168      NA's   :168      NA's   :168      NA's   :168       
##       May               Jun               Jul               Aug         
##  Min.   :-0.4647   Min.   :-0.7132   Min.   :-0.5697   Min.   :-0.2959  
##  1st Qu.: 0.6436   1st Qu.: 0.6595   1st Qu.: 0.7696   1st Qu.: 0.9339  
##  Median : 0.9519   Median : 1.0475   Median : 1.1682   Median : 1.3118  
##  Mean   : 0.8283   Mean   : 0.9214   Mean   : 1.0385   Mean   : 1.1880  
##  3rd Qu.: 1.1464   3rd Qu.: 1.2960   3rd Qu.: 1.4094   3rd Qu.: 1.5630  
##  Max.   : 1.8144   Max.   : 1.9940   Max.   : 2.0981   Max.   : 2.2134  
##  NA's   :168       NA's   :168       NA's   :168       NA's   :168      
##       Sep               Oct               Nov               Dec         
##  Min.   :-0.2359   Min.   :-0.3048   Min.   :-0.1383   Min.   :0.01022  
##  1st Qu.: 0.9670   1st Qu.: 0.8849   1st Qu.: 0.8412   1st Qu.:0.67811  
##  Median : 1.3515   Median : 1.2506   Median : 1.1686   Median :1.01170  
##  Mean   : 1.2300   Mean   : 1.1349   Mean   : 1.0380   Mean   :0.90122  
##  3rd Qu.: 1.5942   3rd Qu.: 1.4822   3rd Qu.: 1.3270   3rd Qu.:1.12512  
##  Max.   : 2.2281   Max.   : 2.1035   Max.   : 1.9381   Max.   :1.70984  
##  NA's   :168       NA's   :168       NA's   :168       NA's   :168