JDSI {drought}

Compute Joint Drought Severity Index with joint distribution

Description

The JDSI can be computed based on joint distribution or kendall distribution

Usage

JDSI(X, Y, ts = 6, type = 1)

Arguments

X

is the vector of a monthly hydro-climatic variable of n years.

Y

is the vector of a monthly hydro-climatic variable of n years.

ts

is the accumulated time scale.

type

is the method used to compute the JDSI (1 is Joint distribution and 2 is the Kendall function).

Value

The multivariate drought index based on the joint distribution or Kendall distribution

References

Hao, Z. et al. (2017) An integrated package for drought monitoring, prediction and analysis to aid drought modeling and assessment, Environ Modell Softw, 91, 199-209.

Examples

X=runif(120, min = 0, max = 100) # 10-year monthly data
Y=runif(120, min = 0, max = 100) # 10-year monthly data
fit<-JDSI(X,Y,ts=6)  
z=matrix(t(fit$JDSI),ncol=1)
plot(z, type="l", col=1, lwd=2, lty=1, xlim=c(0,120),xlab="Time",ylab="JDSI")