drought (version 1.2)

JDSI: 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)

Value

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

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).

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")