Evaluation of Estimators of Probability Distributions for Frequency Analysis of Rainfall and River Flow Data

Abstract

Assessment of extreme rainfall and peak flood for a given return period is of utmost importance for planning and design of hydraulic structures. This can be achieved through Extreme Value Analysis (EVA) of rainfall and Flood Frequency Analysis (FFA) of river flow data by fitting 2-parameter Log Normal, Extreme Value Type-1, Generalized Extreme Value and Log Pearson Type-3 (LP3) distributions to the annual maximum series of observed data. Based on the intended applications and the variate under consideration, method of moments and Maximum Likelihood Method (MLM) are used for determination of parameters of the distributions. The adequacy of fitting probability distributions applied in frequency analysis of rainfall and river flow data was evaluated by quantitative assessment using Goodness-of-Fit (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic (viz., Correlation Coefficient and Root Mean Squared Error) tests, and qualitative assessment by the fitted curves of the estimated values. Based on quantitative and qualitative assessments, the study shows the LP3 (MLM) is better suited for estimation of extreme rainfall and peak flood amongst four distributions adopted in EVA and FFA.