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Selection of Best Fit Probability Distribution for Estimation of Peak Flood using Qualitative and Quantitative Assessments
Abstract
Estimation of Peak Flood (PF) for a given return period is of utmost importance for planning and design of hydraulic structures. This can be achieved through Flood Frequency Analysis (FFA) of stream flow data by fitting normal, gamma and extreme value families of distributions to the series of observed annual peak flood data. In this paper, a study on estimation of PF for river Beas at Dhaulasidh site adopting 2-parameter Log Normal, Log Pearson Type-3, Generalized Extreme Value, Extreme Value Type-1, Extreme Value Type-2 and Generalized Pareto distributions is carried out. The parameters of the distributions are determined by method of moments, maximum likelihood method and L-moments, and are used for estimation of PF. The adequacy of fitting probability distributions applied in FFA is evaluated by quantitative assessment using Goodness-of-Fit (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic (viz., correlation coefficient and D-index) tests, and qualitative assessment by the fitted curves of the estimated PF. The paper presents the GEV (MLM) is better suited distribution for estimation of PF at Dhaulasidh site.
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