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Incorporation of Cost-Benefit Analysis Considering Epistemic Uncertainty for Calculating the Optimal Design Flood
Water Resources Management ( IF 4.3 ) Pub Date : 2021-01-18 , DOI: 10.1007/s11269-021-02764-z
Sang Ug Kim , Cheol-Eung Lee

Design flood via flood frequency analysis provides basic information for designing hydraulic structures. Quantification of uncertainty in flood frequency analysis has become an important issue during the past three decades. However, few studies have considered practical procedures for selecting a single design flood in the uncertainty range. Cost-benefit analysis can be incorporated to select a single design flood by calculating the optimal value in the total expected cost function. In particular, in this study, the relationship between conventional flood frequency analysis and cost-benefit analysis is addressed. Additionally, the parameter uncertainty is quantified by the Metropolis-Hastings algorithm to find the optimal design floods considering parameter uncertainty. The annual maximum (AM) series and partial duration (PD) series were used to identify the effect of various types of data. The optimal design floods obtained by the cost-benefit analysis considering parameter uncertainty were systematically larger than the design flood obtained by the conventional flood frequency analysis. Regarding the types of data, the generalized Pareto distribution (GPD) had the largest values in all return periods, while the Gumbel distribution had the smallest values in all cases.



中文翻译:

结合认识不确定性的成本效益分析计算最优设计洪水

通过洪水频率分析进行设计洪水可为设计水工结构提供基本信息。在过去的三十年中,洪水频率分析中不确定性的量化已经成为一个重要的问题。但是,很少有研究考虑在不确定性范围内选择单个设计洪水的实用程序。通过计算总预期成本函数中的最优值,可以结合成本效益分析来选择单个设计洪水。特别是,在这项研究中,解决了常规洪水频率分析和成本效益分析之间的关系。另外,通过Metropolis-Hastings算法对参数不确定性进行量化,以找到考虑参数不确定性的最佳设计洪水。Ť他优化设计考虑参数不确定性的成本效益分析得到洪水进行了系统比以往的洪水频率分析得到的设计洪水较大。关于数据类型,广义帕累托分布(GPD)在所有返回期间均具有最大值,而Gumbel分布在所有情况下均具有最小值。

更新日期:2021-01-18
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