On selection of probability distributions of annual maximum daily rainfalls using TL-moments
Knowledge related to distributions of rainfall amounts are of great impor- tant for designs of water related structures. The greater problem facing hydrologists and engineering is the identification the best distribution form for regional data. The main goal of the study is to perform regional frequ...
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my.utm.369842014-03-13T01:03:07Z http://eprints.utm.my/id/eprint/36984/ On selection of probability distributions of annual maximum daily rainfalls using TL-moments Shabri, Ani Mohd. Ariff, Noratiqah QA Mathematics Knowledge related to distributions of rainfall amounts are of great impor- tant for designs of water related structures. The greater problem facing hydrologists and engineering is the identification 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 by using the method of TL-moment. Several distributions were taken into account in this study which include two-parameter normal (NOM), log- normal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and general- ized Pareto (GPA) distribution. The most suitable distribution among the selected distributions 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. 2010-12 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/36984/1/AniShabri2010_OnSelectionofProbabilityDistributionsofAnnualMaximum.pdf text/html en http://eprints.utm.my/id/eprint/36984/2/20102623.pdf Shabri, Ani and Mohd. Ariff, Noratiqah (2010) On selection of probability distributions of annual maximum daily rainfalls using TL-moments. Matematika, 26 (2). pp. 137-151. ISSN 1812-5662 |
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Knowledge related to distributions of rainfall amounts are of great impor- tant for designs of water related structures. The greater problem facing hydrologists and engineering is the identification 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 by using the method of TL-moment. Several distributions were taken into account in this study which include two-parameter normal (NOM), log- normal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and general- ized Pareto (GPA) distribution. The most suitable distribution among the selected distributions 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. |
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Article |
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Shabri, Ani Mohd. Ariff, Noratiqah |
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Shabri, Ani Mohd. Ariff, Noratiqah |
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Shabri, Ani |
title |
On selection of probability distributions of annual maximum daily rainfalls using TL-moments |
title_short |
On selection of probability distributions of annual maximum daily rainfalls using TL-moments |
title_full |
On selection of probability distributions of annual maximum daily rainfalls using TL-moments |
title_fullStr |
On selection of probability distributions of annual maximum daily rainfalls using TL-moments |
title_full_unstemmed |
On selection of probability distributions of annual maximum daily rainfalls using TL-moments |
title_sort |
on selection of probability distributions of annual maximum daily rainfalls using tl-moments |
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2010 |
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http://eprints.utm.my/id/eprint/36984/1/AniShabri2010_OnSelectionofProbabilityDistributionsofAnnualMaximum.pdf http://eprints.utm.my/id/eprint/36984/2/20102623.pdf http://eprints.utm.my/id/eprint/36984/ |
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