SJVI WYT classification.Rmd

```{r}
library(readr)
library(dplyr)

path <- "C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/pywr_models/data/common/hydrology/"

#Historical SJVI
SJVI_Livneh <- read_csv(paste(path,"historical/Livneh/SJVI.csv", sep="")) %>%
  mutate(WYT = ifelse(`SJVI (maf)` >= 3.8, "Wet", ifelse(`SJVI (maf)` < 3.8 & `SJVI (maf)` > 3.1, "Above Normal", ifelse(`SJVI (maf)` <= 3.1 & `SJVI (maf)` > 2.5, "Below Normal", ifelse(`SJVI (maf)` <= 2.5 & `SJVI (maf)` > 2.1, "Dry", "Critical")))),
         Scenario = "Livneh (Historical)")

SJVI_Livneh

write_csv(SJVI_Livneh, paste("C:/Users/gusta/Desktop/PhD/Classes/ES207/SJVI_Historical_Livneh_March.csv",sep=""))

#GCMs SJVI

GCMs <- c("ACCESS1-0", "CanESM2", "CCSM4", "GFDL-CM3", "HadGEM2-ES", "HadGEM2-CC", "MIROC5", "CNRM-CM5", "CMCC-CMS", "CESM1-BGC")
rcps <- c("rcp45", "rcp85")

for(GCM in GCMs){
  for(rcp in rcps){
  
SJVI_GCMs <- read_csv(paste(path,"gcms/",GCM,"_",rcp,"/SJVI.csv", sep="")) %>%
  mutate(WYT = ifelse(`SJVI (maf)` >= 3.8, "Wet", ifelse(`SJVI (maf)` < 3.8 & `SJVI (maf)` > 3.1, "Above Normal", ifelse(`SJVI (maf)` <= 3.1 & `SJVI (maf)` > 2.5, "Below Normal", ifelse(`SJVI (maf)` <= 2.5 & `SJVI (maf)` > 2.1, "Dry", "Critical")))),
         Scenario = GCM,
         RCP = rcp)
SJVI_GCMs

write_csv(SJVI_GCMs, paste("C:/Users/gusta/Desktop/PhD/Classes/ES207/SJVI_",GCM,"_",rcp,"_March.csv",sep=""))
  }
}






```