Determining probability distribution for streamflow regions using partial-moments

An attempt has been made to model the annual maximum streamflow, utilizing the guidelines in the regional flood frequency analysis. The Partial L-moments (PL-moments) at several censoring levels are employed to estimate the regional parameters of three extreme value distributions, namely; generalize...

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Main Authors: Zakaria, Zahrahtul Amani, Shabri, Ani, Awang, Mohd. Khalid
Format: Article
Published: International Journal of Advances in Science, Engineering and Technology 2017
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Online Access:http://eprints.utm.my/id/eprint/81522/
http://www.worldresearchlibrary.org/up_proc/pdf/527-14797292679-12.pdf
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spelling my.utm.815222019-08-23T05:21:18Z http://eprints.utm.my/id/eprint/81522/ Determining probability distribution for streamflow regions using partial-moments Zakaria, Zahrahtul Amani Shabri, Ani Awang, Mohd. Khalid Q Science (General) An attempt has been made to model the annual maximum streamflow, utilizing the guidelines in the regional flood frequency analysis. The Partial L-moments (PL-moments) at several censoring levels are employed to estimate the regional parameters of three extreme value distributions, namely; generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA) distributions. A total number of 18 streamflow stations located throughout the eastern region of Peninsular Malaysia were used as a case study. Firstly, the data is screening out for data verification and quality control. Next, identification of homogeneous regions is made using homogeneity test based on PL-moments. The PL - diagram is then constructed and GEV and GLO distributions appeared to be the acceptable distributions for representing the regional data. However, it is relatively difficult to identify a particular distribution that most fitted the regional data.Thus, goodness-of-fit test (Z-test) is used and the result showed that the most appropriate distribution for modeling maximum streamflow in the East Coast of Peninsular Malaysia, based on PL-moments is the GLO distribution. International Journal of Advances in Science, Engineering and Technology 2017 Article PeerReviewed Zakaria, Zahrahtul Amani and Shabri, Ani and Awang, Mohd. Khalid (2017) Determining probability distribution for streamflow regions using partial-moments. International Journal of Advances in Science, Engineering and Technology(IJASEAT), 5 (1). pp. 41-44. ISSN 2321-9009 http://www.worldresearchlibrary.org/up_proc/pdf/527-14797292679-12.pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science (General)
spellingShingle Q Science (General)
Zakaria, Zahrahtul Amani
Shabri, Ani
Awang, Mohd. Khalid
Determining probability distribution for streamflow regions using partial-moments
description An attempt has been made to model the annual maximum streamflow, utilizing the guidelines in the regional flood frequency analysis. The Partial L-moments (PL-moments) at several censoring levels are employed to estimate the regional parameters of three extreme value distributions, namely; generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA) distributions. A total number of 18 streamflow stations located throughout the eastern region of Peninsular Malaysia were used as a case study. Firstly, the data is screening out for data verification and quality control. Next, identification of homogeneous regions is made using homogeneity test based on PL-moments. The PL - diagram is then constructed and GEV and GLO distributions appeared to be the acceptable distributions for representing the regional data. However, it is relatively difficult to identify a particular distribution that most fitted the regional data.Thus, goodness-of-fit test (Z-test) is used and the result showed that the most appropriate distribution for modeling maximum streamflow in the East Coast of Peninsular Malaysia, based on PL-moments is the GLO distribution.
format Article
author Zakaria, Zahrahtul Amani
Shabri, Ani
Awang, Mohd. Khalid
author_facet Zakaria, Zahrahtul Amani
Shabri, Ani
Awang, Mohd. Khalid
author_sort Zakaria, Zahrahtul Amani
title Determining probability distribution for streamflow regions using partial-moments
title_short Determining probability distribution for streamflow regions using partial-moments
title_full Determining probability distribution for streamflow regions using partial-moments
title_fullStr Determining probability distribution for streamflow regions using partial-moments
title_full_unstemmed Determining probability distribution for streamflow regions using partial-moments
title_sort determining probability distribution for streamflow regions using partial-moments
publisher International Journal of Advances in Science, Engineering and Technology
publishDate 2017
url http://eprints.utm.my/id/eprint/81522/
http://www.worldresearchlibrary.org/up_proc/pdf/527-14797292679-12.pdf
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score 13.211869