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1860797097442279424
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INTELEK Repository
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Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2017-02-21 15:49:33
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| format |
Restricted Document
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| id |
11361
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UniSZA
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5592-01-FH02-FIK-18-12300.pdf
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Personal
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11361
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| spelling |
11361 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11361 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal application/pdf 4 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Personal 2017-02-21 15:49:33 5592-01-FH02-FIK-18-12300.pdf UniSZA Private Access Determining probability distribution for streamflow region using partial L-moments International Journal of Advances in Science Engineering and Technology 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. 5 1 41-44
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| spellingShingle |
Determining probability distribution for streamflow region using partial L-moments
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| summary |
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.
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| title |
Determining probability distribution for streamflow region using partial L-moments
|
| title_full |
Determining probability distribution for streamflow region using partial L-moments
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| title_fullStr |
Determining probability distribution for streamflow region using partial L-moments
|
| title_full_unstemmed |
Determining probability distribution for streamflow region using partial L-moments
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| title_short |
Determining probability distribution for streamflow region using partial L-moments
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| title_sort |
determining probability distribution for streamflow region using partial l-moments
|