Frequency Analysis of Stream Flow Data Using L-moments of Probability Distributions for Estimation of Peak Flood Discharge

Authors(1) :-N. Vivekanandan

Estimation of Peak Flood Discharge (PFD) at a desired location on a river is important for planning, design and management of hydraulic structures. This can be achieved through Flood Frequency Analysis (FFA) by fitting of probability distributions to the series of annual maximum discharge data. In the present study, Exponential, Extreme Value Type-1, Extreme Value Type-2, Generalized Pareto and Generalized Extreme Value (GEV) and Normal distributions are adopted in FFA for river Ganga at Allahabad and Varanasi sites. Method of L-Moments (LMO) is used for determination of parameters of the distributions. The adequacy of fitting of probability distributions to the recorded data is quantitatively assessed by applying Goodness-of-Fit (GoF) tests viz., Chi-square and Kolmogorov-Smirnov and diagnostic test using D-index. However, the diverging results based on GoF tests lead to adopt qualitative test to aid the selection of most suitable distribution for estimation of PFD. The study presents the GEV is found to be better suited probability distribution for estimation of PFD for river Ganga at Allahabad and Varanasi.

Authors and Affiliations

N. Vivekanandan
Central Water and Power Research Station, Pune, Maharashtra, India

Chi-square, D-index, Generalized Extreme Value, Kolmogorov-Smirnov, L-Moments, Peak Flood

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Publication Details

Published in : Volume 1 | Issue 6 | November-December 2015
Date of Publication : 2015-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 358-363
Manuscript Number : IJSRSET151677
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

N. Vivekanandan, " Frequency Analysis of Stream Flow Data Using L-moments of Probability Distributions for Estimation of Peak Flood Discharge, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.358-363, November-December-2015.
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