Abstract

Assessment of extreme rainfall is needed to be carried out to prevent floods and droughts and applied to the studies on water resources projects. This can be done by extreme value analysis (EVA) that consists of fitting probability distributions to the annual 1-day maximum rainfall (AMR) series. This paper presents a study on EVA of rainfall for Pune and Vadgaon Maval sites using method of moments, maximum likelihood method and L-moments (LMO) estimators of log normal, extreme value type-1 (EV1), generalized extreme value (GEV) and generalized Pareto distributions. The evaluation of probability distributions adopted in EVA is made by goodness-of-fit (viz., Chi-square and Kolmogorov–Smirnov) tests, D-index and fitted curves of the estimated rainfall. On the basis of the results obtained from the study, it is found that EV1 (LMO) is better suited for rainfall estimation for Pune whereas GEV (LMO) for Vadgaon Maval.

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