Frequency analysis of maximum daily rainfalls via L-moment approach
Knowledge related to distributions of rainfall amounts are of great importance for the design of water related structures. The greater problem faced by the hydrologists and engineers is identifying the best distribution form for regional data. The main goal of the study is to perform regional freque...
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Universiti Kebangsaan Malaysia
2009
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ukm-732016-12-14T06:26:19Z http://journalarticle.ukm.my/73/ Frequency analysis of maximum daily rainfalls via L-moment approach Ani Shabri, Noratiqah Mohd Ariff, Knowledge related to distributions of rainfall amounts are of great importance for the design of water related structures. The greater problem faced by the hydrologists and engineers is identifying the best distribution form for regional data. The main goal of the study is to perform regional frequency analysis of maximum daily rainfalls selected each year among daily rainfalls measured over stations in Selangor and Kuala Lumpur using the L-moment method. Several distributions were taken into account in this study which include two-parameter normal (NOM), lognormal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and generalized Pareto (GPA) distribution. The most suitable distribution was determined according to the mean absolute deviation index (MADI), mean square deviation index (MSDI) and the L-moment ratio diagram. The result of this study showed that the GLO distribution is the most suitable distribution to fit the data of maximum daily rainfalls for stations in Selangor and Kuala Lumpur. Universiti Kebangsaan Malaysia 2009-04 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/73/1/ Ani Shabri, and Noratiqah Mohd Ariff, (2009) Frequency analysis of maximum daily rainfalls via L-moment approach. Sains Malaysiana, 38 (2). pp. 149-158. ISSN 0126-6039 |
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Universiti Kebangasaan Malaysia |
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Online Access |
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English |
description |
Knowledge related to distributions of rainfall amounts are of great importance for the design of water related structures. The greater problem faced by the hydrologists and engineers is identifying the best distribution form for regional data. The main goal of the study is to perform regional frequency analysis of maximum daily rainfalls selected each year among daily rainfalls measured over stations in Selangor and Kuala Lumpur using the L-moment method. Several distributions were taken into account in this study which include two-parameter normal (NOM), lognormal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and generalized Pareto (GPA) distribution. The most suitable distribution was determined according to the mean absolute deviation index (MADI), mean square deviation index (MSDI) and the L-moment ratio diagram. The result of this study showed that the GLO distribution is the most suitable distribution to fit the data of maximum daily rainfalls for stations
in Selangor and Kuala Lumpur. |
format |
Article |
author |
Ani Shabri, Noratiqah Mohd Ariff, |
spellingShingle |
Ani Shabri, Noratiqah Mohd Ariff, Frequency analysis of maximum daily rainfalls via L-moment approach |
author_facet |
Ani Shabri, Noratiqah Mohd Ariff, |
author_sort |
Ani Shabri, |
title |
Frequency analysis of maximum daily rainfalls via L-moment approach |
title_short |
Frequency analysis of maximum daily rainfalls via L-moment approach |
title_full |
Frequency analysis of maximum daily rainfalls via L-moment approach |
title_fullStr |
Frequency analysis of maximum daily rainfalls via L-moment approach |
title_full_unstemmed |
Frequency analysis of maximum daily rainfalls via L-moment approach |
title_sort |
frequency analysis of maximum daily rainfalls via l-moment approach |
publisher |
Universiti Kebangsaan Malaysia |
publishDate |
2009 |
url |
http://journalarticle.ukm.my/73/ http://journalarticle.ukm.my/73/1/ |
first_indexed |
2023-09-18T19:01:10Z |
last_indexed |
2023-09-18T19:01:10Z |
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1777403083883544576 |