Likelihood and Empirical Bayes Modeling for Drought Via Copula

One of the fundamental steps in management of drought involves identification and frequency analysis of its properties, e.g. duration and severity of drought. Regarding the high correlation among these factors, one must use a method that shows the relation and effects of these factors on drought analysis. Copula functions can be used to represent the dependency structure of several variables through a model. In this paper, we introduce the appropriate copula families for modeling drought phenomenon modeling. Then, their parameters would be estimated by maximum likelihood and Empirical Bayes methods and the most appropriate copula function for determining bivariate distribution of duration and severity of drought in Tehran stations is determined. Next, this copula function is used to model the drought phenomenon of Tehran for the period of 37 years from 1348 until 1384, Finaly the application of this model is represented in water supply management.