Comparison of Estimators of Five Probability Distributions for Estimation of Peak Flood

N. Vivekanandan¹

Section:Research Paper, Product Type: Journal-Paper
Vol.7 , Issue.5 , pp.53-59, Oct-2020

Online published on Oct 31, 2020

Copyright © N. Vivekanandan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Estimation of Peak Flood (PF) for a given return period is of utmost importance for planning, design and management of civil and hydraulic structures. Depending on the design-life of the structure, the estimated PF with a desired return period is used. This can be achieved through Flood Frequency Analysis (FFA) that involves fitting probability distribution to the series of observed Annual Peak Flood (APF) data. In this paper, a study on comparison of estimators of 2-parameter Log Normal, Log Pearson Type-3 (LP3), Generalized Extreme Value (GEV), Extreme Value Type-1 and Extreme Value Type-2 distributions adopted in FFA for river Tapi at Bhusawal and Savkheda sites is carried out. Based on the intended applications and the variate under consideration, standard parameter estimation procedures such as Method of Moments (MoM), Maximum Likelihood Method (MLM) and L-Moments (LMO) are used for determination of parameters of the probability distributions. The adequacy of probability distributions applied in FFA is quantitatively assessed by Goodness-of-Fit (GoF) tests viz., Chi-square and Kolmogorov-Smirnov, and diagnostic test using D-index. The paper presents the GEV (LMO) distribution is better suited for estimation of PF at Bhusawal whereas LP3 (MLM) for Savkheda.

Key-Words / Index Term :
Chi-Square, D-index, Generalized Extreme Value, Kolmogorov-Smirnov, L-Moments, Log Pearson Type-3, Maximum Likelihood Method, Peak Flood

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