A review of bivariate gamma distributions for hydrological application

A univariate gamma distribution is one of the most commonly adopted statist ical distributions in hydrological frequency analysis. A bivariate gamma di stribution constructed from specified gamma marginals may be useful for rep resenting joint probabilistic properties of multivariate hydrological event s such as floods and storms. This article presents a review of various biva riate gamma distribution models that are constructed from gamma marginals. Advantages and limitations of each of these models are pointed out. Applica bility of a few bigamma distributions whose gamma marginal distributions ha ve different scale and shape parameters is investigated. The dependence of these models is directly or indirectly measured via the Pearson's product-m oment correlation coefficient. The scale and shape parameters of the models are estimated from their marginal distributions by the method of moments. Results indicate that these bigamma distribution models will be useful for describing the joint probability distribution of two correlated random vari ables with gamma marginals. (C) 2001 Elsevier Science Ltd All rights reserv ed.