Modelling annual maximum river flows with generalized extreme value distribution
A good understanding of probability distribution of annual maximum river flow is believed to improve water resources planning and design. Based on the annual maximum river flow record over 20-48 years at 9 individual river sites in Sabah, the data set are fitted into generalized extreme value (GEV)...
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| Format: | Article |
| Language: | English English |
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SANDKRS sdn bhd.
2019
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| Online Access: | https://eprints.ums.edu.my/id/eprint/30040/1/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution.pdf https://eprints.ums.edu.my/id/eprint/30040/2/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution1.pdf |
| _version_ | 1825714285881327616 |
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| author | R Y Cheong Darmesah Gabda |
| author_facet | R Y Cheong Darmesah Gabda |
| author_sort | R Y Cheong |
| collection | UMS |
| description | A good understanding of probability distribution of annual maximum river flow is believed to improve water resources planning and design. Based on the annual maximum river flow record over 20-48 years at 9 individual river sites in Sabah, the data set are fitted into generalized extreme value (GEV) distribution with maximum likelihood estimator. Both stationary and non-stationary models are considered. Likelihood ratio test shows that most of the river flows are stationary. Over a homogeneous region, a parent distribution with common shape parameter is found well describing the behavior of selected annual maximum river flow. Hence, 10- and 100-year return levels are estimated using the single model. |
| first_indexed | 2024-03-06T03:09:32Z |
| format | Article |
| id | ums.eprints-30040 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:09:32Z |
| publishDate | 2019 |
| publisher | SANDKRS sdn bhd. |
| record_format | dspace |
| spelling | ums.eprints-300402021-07-22T06:09:49Z https://eprints.ums.edu.my/id/eprint/30040/ Modelling annual maximum river flows with generalized extreme value distribution R Y Cheong Darmesah Gabda QE Geology T Technology (General) A good understanding of probability distribution of annual maximum river flow is believed to improve water resources planning and design. Based on the annual maximum river flow record over 20-48 years at 9 individual river sites in Sabah, the data set are fitted into generalized extreme value (GEV) distribution with maximum likelihood estimator. Both stationary and non-stationary models are considered. Likelihood ratio test shows that most of the river flows are stationary. Over a homogeneous region, a parent distribution with common shape parameter is found well describing the behavior of selected annual maximum river flow. Hence, 10- and 100-year return levels are estimated using the single model. SANDKRS sdn bhd. 2019 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/30040/1/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution.pdf text en https://eprints.ums.edu.my/id/eprint/30040/2/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution1.pdf R Y Cheong and Darmesah Gabda (2019) Modelling annual maximum river flows with generalized extreme value distribution. Journal of Computer Science & Computational Mathematics, 9. pp. 7-10. ISSN 2231-8879 https://www.jcscm.net/fp/149.pdf http://doi.org/10.20967/jcscm.2019.01.002 http://doi.org/10.20967/jcscm.2019.01.002 |
| spellingShingle | QE Geology T Technology (General) R Y Cheong Darmesah Gabda Modelling annual maximum river flows with generalized extreme value distribution |
| title | Modelling annual maximum river flows with generalized extreme value distribution |
| title_full | Modelling annual maximum river flows with generalized extreme value distribution |
| title_fullStr | Modelling annual maximum river flows with generalized extreme value distribution |
| title_full_unstemmed | Modelling annual maximum river flows with generalized extreme value distribution |
| title_short | Modelling annual maximum river flows with generalized extreme value distribution |
| title_sort | modelling annual maximum river flows with generalized extreme value distribution |
| topic | QE Geology T Technology (General) |
| url | https://eprints.ums.edu.my/id/eprint/30040/1/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution.pdf https://eprints.ums.edu.my/id/eprint/30040/2/Modelling%20annual%20maximum%20river%20flows%20with%20generalized%20extreme%20value%20distribution1.pdf |
| work_keys_str_mv | AT rycheong modellingannualmaximumriverflowswithgeneralizedextremevaluedistribution AT darmesahgabda modellingannualmaximumriverflowswithgeneralizedextremevaluedistribution |