Manuscript Number : IJSRST151224

Quantitative Assessment on Fitting of Gumbel and Frechet Distributions for Extreme Value Analysis of Rainfall

Authors(1) :-N. Vivekanandan

Rainfall frequency analysis plays an important role in hydrologic and economic evaluation of water resources projects. It helps to estimate the return periods and their corresponding event magnitudes thereby creating reasonable design criteria. Depending on the size, life time and design criteria of the structure, different return periods are generally stipulated for adopting Extreme Value Analysis (EVA) results. This paper illustrates the use of quantitative assessment on fitting of Gumbel (EV1) and Frechet (EV2) probability distributions to the series of annual 1-day maximum rainfall (AMR) data using Goodness-of-Fit (GoF) and diagnostic tests. Order Statistics Approach (OSA) is used for determination of parameters of the distributions. Based on GoF (using Anderson-Darling and Kolmogorov-Smirnov) and diagnostic (using D-index) test results, the study identifies the EV1 distribution is better suited for EVA of rainfall for Fatehabad and Hissar.

Authors and Affiliations

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

Anderson-Darling, D-Index, Frechet, Gumbel, Kolmogorov-Smirnov, Rainfall

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Publication Details

Published in : Volume 1 | Issue 2 | May-June 2015
Date of Publication : 2015-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 68-73
Manuscript Number : IJSRST151224
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

N. Vivekanandan, " Quantitative Assessment on Fitting of Gumbel and Frechet Distributions for Extreme Value Analysis of Rainfall , International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 1, Issue 2, pp.68-73, May-June-2015. Available at doi : 10.32628/IJSRST151224
Journal URL : http://ijsrst.com/IJSRST151224

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