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Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China
Yurui Fan, Guohe Huang, Yin Zhang, Yongping Li
Engineering ›› 2018, Vol. 4 ›› Issue (5) : 617-626.
PDF(2810 KB)
PDF(2810 KB)
Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China
This study develops a multivariate eco-hydrological risk-assessment framework based on the multivariate copula method in order to evaluate the occurrence of extreme eco-hydrological events for the Xiangxi River within the Three Gorges Reservoir (TGR) area in China. Parameter uncertainties in marginal distributions and dependence structure are quantified by a Markov chain Monte Carlo (MCMC) algorithm. Uncertainties in the joint return periods are evaluated based on the posterior distributions. The probabilistic features of bivariate and multivariate hydrological risk are also characterized. The results show that the obtained predictive intervals bracketed the observations well, especially for flood duration. The uncertainty for the joint return period in “AND” case increases with an increase in the return period for univariate flood variables. Furthermore, a low design discharge and high service time may lead to high bivariate hydrological risk with great uncertainty.
Flood risk / Copula / Multivariate flood frequency analysis / Distribution / Markov chain Monte Carlo
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This work was jointly funded by the National Natural Science Foundation of China (51520105013 and 51679087) and the National Key Research and Development Plan of China (2016YFC0502800).
Yurui Fan, Guohe Huang, Yin Zhang, and Yongping Li declare that they have no conflict of interest or financial conflicts to disclose.
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