Aiming at the limitations of conventional deduction method of design flood hydrograph, the bivariate joint distribu-tion of flood peak and volume is established by Copula function. The design values of flood peak and volume are jointly simulated by the established joint distribution. Meanwhile, the typical flood hydrographs are chosen based on the similarity between simula-ted and observed flood values. A bivariate flood risk analysis model is proposed according to the multivariate joint return period. Geheyan Reservoir, on Qingjiang River, is selected as a case and the overtopping risk and ultimate risk corresponding to different flood limited water levels (FLWLs) are estimated. The results show that the FLWL of Geheyan Reservoir can be raised to 193. 6m, which will not increase the flood risk if the FLWL drops to 192. 2m before the forecasted flood coming;however the overtop-ping risk will multiply increase if the FLWL rise to 194. 0m, though the ultimate risk remains unchanged. The proposed bivariate risk analysis model can fully consider the randomness and uncertainty of flood process and provide reference information for reser-voir operation.%针对传统设计洪水过程线推求方法所存在的局限性,采用Copula函数建立洪峰和洪量的两变量联合分布,对洪峰和洪量设计值进行联合随机模拟,同时根据随机模拟值与实测洪水过程特征量的相似性来选择典型洪水过程,并基于多变量重现期,建立了两变量防洪风险分析模型. 以清江流域隔河岩水库为例,分析不同汛限水位对应的极限风险率和漫坝风险率. 研究结果表明:① 隔河岩水库汛期运行水位可确定为193. 6m,在预报长江将发生大洪水时,可将水位提前降低至192. 2m,不会增加水库的防洪风险;② 当汛限水位继续抬高至194. 0m时,尽管极限风险率变化不大,但漫坝风险率成倍增加. 所提出的模型可以充分考虑洪水过程的随机性和不确定性,可为流域水库的防洪设计和安全运行提供参考.
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