Flood frequency analysis using method of moments and L-moments of probability distributions

Estimation of maximum flood discharge (MFD) at a desired location on a river is important for planning, design and management of hydraulic structures. This can be achieved using deterministic models with extreme storm events or through frequency analysis by fitting of probability distributions to th...

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Main Author: N. Vivekanandan
Format: Article
Language:English
Published: Taylor & Francis Group 2015-12-01
Series:Cogent Engineering
Subjects:
Online Access:http://dx.doi.org/10.1080/23311916.2015.1018704
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spelling doaj-752a19dff0994264bd440e3f4132f0f52020-11-24T23:08:23ZengTaylor & Francis GroupCogent Engineering2331-19162015-12-012110.1080/23311916.2015.10187041018704Flood frequency analysis using method of moments and L-moments of probability distributionsN. Vivekanandan0Central Water and Power Research StationEstimation of maximum flood discharge (MFD) at a desired location on a river is important for planning, design and management of hydraulic structures. This can be achieved using deterministic models with extreme storm events or through frequency analysis by fitting of probability distributions to the recorded annual maximum discharge data. In the latter approach, suitable probability distributions and associated parameter estimation methods are applied. In the present study, method of moments and L-moments (LMO) are used for determination of parameters of six probability distributions. Goodness-of-Fit tests such as Chi-square and Kolmogorov–Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data. Diagnostic test of D-index is used for the selection of a suitable distribution for estimation of MFD. The study reveals that the Extreme Value Type-1 distribution (using LMO) is better suited amongst six distributions used in the estimation of MFD at Malakkara and Neeleswaram gauging stations in Pampa and Periyar river basins, respectively.http://dx.doi.org/10.1080/23311916.2015.1018704chi-squareD-indexKolmogorov–SmirnovL-momentsmethod of momentsmaximum floodprobability distribution
collection DOAJ
language English
format Article
sources DOAJ
author N. Vivekanandan
spellingShingle N. Vivekanandan
Flood frequency analysis using method of moments and L-moments of probability distributions
Cogent Engineering
chi-square
D-index
Kolmogorov–Smirnov
L-moments
method of moments
maximum flood
probability distribution
author_facet N. Vivekanandan
author_sort N. Vivekanandan
title Flood frequency analysis using method of moments and L-moments of probability distributions
title_short Flood frequency analysis using method of moments and L-moments of probability distributions
title_full Flood frequency analysis using method of moments and L-moments of probability distributions
title_fullStr Flood frequency analysis using method of moments and L-moments of probability distributions
title_full_unstemmed Flood frequency analysis using method of moments and L-moments of probability distributions
title_sort flood frequency analysis using method of moments and l-moments of probability distributions
publisher Taylor & Francis Group
series Cogent Engineering
issn 2331-1916
publishDate 2015-12-01
description Estimation of maximum flood discharge (MFD) at a desired location on a river is important for planning, design and management of hydraulic structures. This can be achieved using deterministic models with extreme storm events or through frequency analysis by fitting of probability distributions to the recorded annual maximum discharge data. In the latter approach, suitable probability distributions and associated parameter estimation methods are applied. In the present study, method of moments and L-moments (LMO) are used for determination of parameters of six probability distributions. Goodness-of-Fit tests such as Chi-square and Kolmogorov–Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data. Diagnostic test of D-index is used for the selection of a suitable distribution for estimation of MFD. The study reveals that the Extreme Value Type-1 distribution (using LMO) is better suited amongst six distributions used in the estimation of MFD at Malakkara and Neeleswaram gauging stations in Pampa and Periyar river basins, respectively.
topic chi-square
D-index
Kolmogorov–Smirnov
L-moments
method of moments
maximum flood
probability distribution
url http://dx.doi.org/10.1080/23311916.2015.1018704
work_keys_str_mv AT nvivekanandan floodfrequencyanalysisusingmethodofmomentsandlmomentsofprobabilitydistributions
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