Comparison of conventional and intelligent methods in estimating Copula Function Parameters for multivariate frequency analysis of low flows (Case Study: Dez River Basin)

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AHMADI FARSHAD; Radmaneh Fereidun; PARHAM GHOLAM ALI; MIRABBASI NAJAFABADI RASOUL

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Journal: IRANIAN JOURNAL OF ECOHYDROLOGY Year:2017 | Volume:4 | Issue:2 Page(s): 315-329

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Title

Comparison of conventional and intelligent methods in estimating Copula Function Parameters for multivariate frequency analysis of low flows (Case Study: Dez River Basin)

Author(s)

AHMADI FARSHAD | Radmaneh Fereidun | PARHAM GHOLAM ALI | MIRABBASI NAJAFABADI RASOUL | Issue Writer Certificate

Keywords

Frequency analysisQ2

Copula FunctionsQ2

marginal distributionsQ2

joint distributionQ2

Joint return periodQ2

Abstract

Over the recent years, the dependence structure among hydrological variables has been taken into consideration and it resulted in employment of the multivariate analysis as a suitable alternative for univariate methods. In this study, the Copula Functions were employed for multivariate Frequency analysis of low flows of Dez River basin at Tange Panj-Bakhtiari (TPB) and Tange Panj-Sezar (TPS) hydrometric stations. First, 7-d series of low flow was extracted from measured daily flows at the studied stations over the period of 1956-2012. In the next stage, 11 different distribution functions were fitted into the low flow data whereby logistic distribution had the best fit on the TPB station and the GEV distribution had the best fit on the low flow data of TPS station. After specifying the best fitted marginal distributions, the copula parameter should be estimated. In this study, two methods of inference function for margins (IFM) and particle swarm optimization (PSO) were used to estimate copula parameter. The results showed that the PSO method outperformed IFM in estimating the copula parameter. Among the Ali-Mikhail – Haq, Clayton, Frank, Galambos and Gumbel-Hougaard copulas, the Frank copula function had the lowest error and the highest accuracy in constructing the joint distribution of paired 7-d low flows data and was used for calculating the Joint return periods in two states of “ OR” and “ AND” .

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APA: Copy

AHMADI, FARSHAD, Radmaneh, Fereidun, PARHAM, GHOLAM ALI, & MIRABBASI NAJAFABADI, RASOUL. (2017). Comparison of conventional and intelligent methods in estimating Copula Function Parameters for multivariate frequency analysis of low flows (Case Study: Dez River Basin). IRANIAN JOURNAL OF ECOHYDROLOGY, 4(2 ), 315-329. SID. https://sid.ir/paper/254076/en

Vancouver: Copy

AHMADI FARSHAD, Radmaneh Fereidun, PARHAM GHOLAM ALI, MIRABBASI NAJAFABADI RASOUL. Comparison of conventional and intelligent methods in estimating Copula Function Parameters for multivariate frequency analysis of low flows (Case Study: Dez River Basin). IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2017;4(2 ):315-329. Available from: https://sid.ir/paper/254076/en

IEEE: Copy

FARSHAD AHMADI, Fereidun Radmaneh, GHOLAM ALI PARHAM, and RASOUL MIRABBASI NAJAFABADI, “Comparison of conventional and intelligent methods in estimating Copula Function Parameters for multivariate frequency analysis of low flows (Case Study: Dez River Basin),” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 4, no. 2 , pp. 315–329, 2017, [Online]. Available: https://sid.ir/paper/254076/en

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