Extreme precipitation-related hazards like flash floods pose a widespread risk to humans and infrastructure around the world. In the current study, the Fisher information was applied to understand the nonstationarity of the extreme precipitation regimes, whereas copula was used to quantify the likelihood of joint occurrence of two extreme precipitation indices and associated risk assessment in the upper Midwestern United States (UMUS). The trend analysis revealed an increasing trend in 37% of the stations in heavy precipitation amount in the UMUS. The regime shift analysis showed the non-stationary nature of extreme precipitation in about half of the total stations in UMUS. Further, the bivariate analysis using copula demonstrated the risk of the joint occurrence of extreme precipitation indices potentially causing flash floods. The risk index analysis indicated about 28.8% of stations under moderate, 10.6% of stations under high and 0.4% of stations under very high risk of flash flooding. The results from the study can provide important insights for the (re)design of resilient and sustainable water infrastructure in the changing climate condition and can also inform managers and planners for better response and preparedness toward extreme precipitation-related hazards in this region. The results from this study can also help in a more accurate risk assessment, especially in the socio-economically vulnerable community.

中文翻译：

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描述美国中西部上部两个极端降水指数联合发生的概率方法

山洪等与极端降水相关的灾害对世界各地的人类和基础设施构成了广泛的风险。在本研究中，Fisher信息用于了解极端降水状况的非平稳性，而copula用于量化美国中西部上游地区（UMUS）两个极端降水指数联合发生的可能性和相关风险评估。趋势分析显示，UMUS中有37%的站点强降水量呈增加趋势。动态变化分析表明，UMUS 约一半的总站极端降水具有非平稳性质。此外，使用联结函数的双变量分析证明了极端降水指数联合发生可能导致山洪爆发的风险。风险指数分析表明，约 28.8% 的站点处于中等风险，10.6% 的站点处于高风险，0.4% 的站点处于极高风险。研究结果可以为在不断变化的气候条件下（重新）设计有弹性和可持续的水基础设施提供重要见解，还可以为管理者和规划者提供信息，以便更好地应对和准备该地区与极端降水相关的灾害。这项研究的结果还可以帮助进行更准确的风险评估，特别是在社会经济脆弱的社区。