The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment

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Abstract

The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution.

Original languageEnglish
Pages (from-to)337-344
Number of pages8
JournalTheoretical and Applied Climatology
Volume96
Issue number3-4
DOIs
Publication statusPublished - 2009

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rainfall
logistics
method
distribution
gauge
parameter
station

ASJC Scopus subject areas

  • Atmospheric Science

Cite this

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title = "The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment",
abstract = "The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution.",
author = "{Wan Zin @ Wan Ibrahim}, {Wan Zawiah} and Jemain, {Abdul Aziz} and Kamarulzaman Ibrahim",
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AB - The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution.

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