Modelling of extreme streamflow using copula

This study explores applying various copula models to estimate the dependencies between streamflow and stage data for the Kahang River in Kluang, Johor. Using daily streamflow and stage data, we compared the performance of several copula parameter estimation methods: Maximum Pseudo-Likelihood Estima...

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Main Authors: Buliah, Nur Amirah, Ling, Wendy Shin Yie
Format: Article
Language:English
Published: Universiti Putra Malaysia 2024
Online Access:http://psasir.upm.edu.my/id/eprint/120285/
http://psasir.upm.edu.my/id/eprint/120285/1/120285.pdf
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author Buliah, Nur Amirah
Ling, Wendy Shin Yie
author_facet Buliah, Nur Amirah
Ling, Wendy Shin Yie
author_sort Buliah, Nur Amirah
building UPM Institutional Repository
collection Online Access
description This study explores applying various copula models to estimate the dependencies between streamflow and stage data for the Kahang River in Kluang, Johor. Using daily streamflow and stage data, we compared the performance of several copula parameter estimation methods: Maximum Pseudo-Likelihood Estimator (MPLE), Inference Functions for Margins Estimator (IFME), Method-of-Moments Estimator (MoM), Empirical Copula Estimation, and Robust Estimation by Maximum Mean Discrepancy Minimization (MMD). Our findings indicate that different copula performed best for different estimation methods. Specifically, the Student t-copula best fits IFME, the Frank copula for Kendall’s tau, Spearman’s rho, and the most recent method, MMD. Also, the Joe copula is best for the MPLE and the empirical copula estimation method. The Jackknife interval method produced narrower and more precise confidence intervals across multiple methods, making it the best interval estimator. This comprehensive analysis improves hydrological modelling, facilitating effective water resource management and flood risk assessment.
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spelling upm-1202852025-09-29T07:10:34Z http://psasir.upm.edu.my/id/eprint/120285/ Modelling of extreme streamflow using copula Buliah, Nur Amirah Ling, Wendy Shin Yie This study explores applying various copula models to estimate the dependencies between streamflow and stage data for the Kahang River in Kluang, Johor. Using daily streamflow and stage data, we compared the performance of several copula parameter estimation methods: Maximum Pseudo-Likelihood Estimator (MPLE), Inference Functions for Margins Estimator (IFME), Method-of-Moments Estimator (MoM), Empirical Copula Estimation, and Robust Estimation by Maximum Mean Discrepancy Minimization (MMD). Our findings indicate that different copula performed best for different estimation methods. Specifically, the Student t-copula best fits IFME, the Frank copula for Kendall’s tau, Spearman’s rho, and the most recent method, MMD. Also, the Joe copula is best for the MPLE and the empirical copula estimation method. The Jackknife interval method produced narrower and more precise confidence intervals across multiple methods, making it the best interval estimator. This comprehensive analysis improves hydrological modelling, facilitating effective water resource management and flood risk assessment. Universiti Putra Malaysia 2024 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/120285/1/120285.pdf Buliah, Nur Amirah and Ling, Wendy Shin Yie (2024) Modelling of extreme streamflow using copula. Menemui Matematik, 46 (2). pp. 44-62. ISSN 2231-7023 https://myjms.mohe.gov.my/index.php/dismath/issue/archive
spellingShingle Buliah, Nur Amirah
Ling, Wendy Shin Yie
Modelling of extreme streamflow using copula
title Modelling of extreme streamflow using copula
title_full Modelling of extreme streamflow using copula
title_fullStr Modelling of extreme streamflow using copula
title_full_unstemmed Modelling of extreme streamflow using copula
title_short Modelling of extreme streamflow using copula
title_sort modelling of extreme streamflow using copula
url http://psasir.upm.edu.my/id/eprint/120285/
http://psasir.upm.edu.my/id/eprint/120285/
http://psasir.upm.edu.my/id/eprint/120285/1/120285.pdf