Nothing
# This function calculates 10 performance and streamflow indices
# inputs:
# Po = observed precipitation [mm/timestep]
# Qo = observed streamflow [mm/timestep]
# Qs = simulated streamflow [mm/timestep]
# Qb = simulated base flow [mm/timestep]
perfindices <- function(Po,Qo,Qs,Qb){
t <- fdc(Qs,lQ.thr=0.66,hQ.thr=0.33)
theRes <- ccf(Qo,Qs, plot=FALSE)
lagtime <- theRes$lag[min(which(theRes$acf==max(theRes$acf)))] # lagtime (from tiger) - it should tend to zero
meanerr <- mean(Qs - Qo, na.rm = TRUE) # mean error - it should tend to zero
meanaoe <- MAOE(Qo,Qs) # mean absolute ordinal error (from qualV) - it should tend to zero
nsef_hf <- 1-EF(Qo,Qs) # Complement to 1 of Nash-Sutcliffe efficiency for high flows - it should tend to zero (from qualV)
nsef_lf <- 1-EF(log(Qo),log(Qs)) # Complement to 1 of Nash-Sutcliffe efficiency for low flows - it should tend to zero (from qualV)
#prmse <- RMSE(Qo,Qs) # Root mean square error (from qualV) - it should tend to zero
rrcoeff <- sum(Qs)/sum(Po) # Rainfall-Runoff coefficient
bfindex <- sum(Qb)/sum(Qs) # Baseflow Index
slopfdc <- fdc_slope(Qs, 0.33, 0.66) # Slope of flow duration curve
stelast <- sel(Po,Qs) # Streamflow Elasticity
diffhpc <- hpc(Qo)-hpc(Qs) # Difference of High Pulse Count (observed - simulated) - it should tend to zero
return( list("lagtime"=lagtime,
"meanerr"=meanerr,
"meanaoe"=meanaoe,
"nsef_hf"=nsef_hf,
"nsef_lf"=nsef_lf,
"rrcoeff"=rrcoeff,
"bfindex"=bfindex,
"slopfdc"=slopfdc,
"stelast"=stelast,
"diffhpc"=diffhpc) )
}
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