基于随机暴雨移置方法的城市设计暴雨分析

Analysis of urban design storm based on stochastic storm transposition

  • 摘要: 城市地区暴雨洪灾发生频繁,合理计算设计暴雨是解决城市洪涝的重要前提。采用随机暴雨移置方法(Stochastic Storm Transposition,SST),设定暴雨移置区并提取出暴雨目录,通过区域性概率重采样与暴雨空间变换相结合的方式进行降雨频率分析,估计本地化的极端暴雨频率。以上海地区为例,研究发现暴雨移置区内暴雨分布具有空间异质性,暴雨随机移置概率不均,计算得到的设计暴雨方案包含了降雨时空分布信息,在不同重现期下设计暴雨的时空结构存在变异性,说明传统方法中采用的简化雨型和均一化空间分布假设会增加设计暴雨的不确定性。

     

    Abstract: Urban flooding is becoming more severe due to increases in extreme rainfall amounts and impervious land cover. Design storms are critical for developing infrastructure and land use solutions to these flood challenges. In this study, we examine urban design storms using Stochastic Storm Transposition (SST). SST is a technique that uses probabilistic resampling from a "storm catalog" of observed rainfall events selected from a pre-defined regional "transposition domain". Resampled storms are then spatially transposed to estimate distributions of extreme rainfall intensity, duration, and frequency (IDF). This study presents an SST-based rainfall analysis for Shanghai, China. Results show that there is spatial heterogeneity in rainfall across study's transposition domain which must be accounted for during the transposition step of SST. SST can reproduce reasonable IDF estimates and provide design storms with realistic spatiotemporal rainfall structures. Large variations in spatio-temporal structure of these SST-based design storms under different return periods call into question the conventional hydrologic engineering assumption of design storm rainfall that is spatially-uniform and temporally idealized.

     

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