Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China

本研究基于copula函数开发了一种多变量生态水文风险评估框架,用于分析三峡库区香溪河流域极端生态水文事件的发生频率。通过马尔可夫链蒙特卡罗(MCMC)方法量化边缘分布及copula函数中参数的不确定性,并基于后验概率揭示联合重现期的内在不确定性,同时可进一步得到双变量及多变量风险的概率特征。研究结果显示所得概率模型的预测区间可很好地匹配观测值,尤其对洪水持续时间而言。同时,"AND"联合重现期的不确定性随着单个洪水变量重现期的增加而增加。此外,低设计流量及高服务年限可能导致高洪水风险且伴随大量不确定性。

This study develops a multivariate eco-hydrological risk-assessment framework based on the multivari-ate 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 distri-butions 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 proba- bilistic 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.