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王颖, 白莹莹, 邓承之, 刘川. 2024. 重庆区域性暴雨过程的重现期评估模型构建方法研究[J]. 暴雨灾害, 43(2): 204-213. DOI: 10.12406/byzh.2023-091
引用本文: 王颖, 白莹莹, 邓承之, 刘川. 2024. 重庆区域性暴雨过程的重现期评估模型构建方法研究[J]. 暴雨灾害, 43(2): 204-213. DOI: 10.12406/byzh.2023-091
WANG Ying, BAI Yingying, DENG Chengzhi, LIU Chuan. 2024. Research on the Construction Method of Return Period Assessment Model for Regional Rainstorm Process in Chongqing[J]. Torrential Rain and Disasters, 43(2): 204-213. DOI: 10.12406/byzh.2023-091
Citation: WANG Ying, BAI Yingying, DENG Chengzhi, LIU Chuan. 2024. Research on the Construction Method of Return Period Assessment Model for Regional Rainstorm Process in Chongqing[J]. Torrential Rain and Disasters, 43(2): 204-213. DOI: 10.12406/byzh.2023-091

重庆区域性暴雨过程的重现期评估模型构建方法研究

Research on the Construction Method of Return Period Assessment Model for Regional Rainstorm Process in Chongqing

  • 摘要: 提出一种利用重现期方法构建区域性暴雨过程的评估模型,用于全面评估暴雨过程发生的频率和强度。基于2011—2021年重庆市114次区域性暴雨过程的小时雨量数据及暴雨灾情数据,利用概率分布函数拟合、重现期计算、相关分析等方法,构建区域性暴雨过程的重现期评估模型,并开展业务检验。结果表明:(1)利用自建的重现期计算公式,得到暴雨过程特征量的重现值与原始值的误差小于10%,重现期计算结果准确性较高。(2)构建的重现期评估模型与直接经济损失的正相关系数可通过0.001显著性水平检验,较现行业务指标提高16%。(3)历史回算和独立样本检验结果显示,重现期评估模型与业务指标评估等级一致率达70%,模型稳定性强且能反映事件发生频率和强度,可为区域性暴雨过程评估提供新思路。

     

    Abstract: This paper proposes an assessment model of the regional rainstorm process based on the return period method, which is used to comprehensively assess the frequency and intensity of rainstorm processes. Based on the hourly rainfall data and rainstorm disaster data of 114 regional rainstorm processes in Chongqing from 2011 to 2021, the probabilistic fitting, return period calculation, correlation analysis and other methods are used to construct the return period assessment model of regional rainstorm processes, and the business verification is carried out. The results are as follows: (1) Using the return period calculation formula built in this study, the error between the return value and the original value of the rainstorm process characteristic quantity is less than 10%, suggesting a higher accuracy of the return period calculation. (2) The correlation coefficient between the constructed return period assessment model and direct economic loss is significant at the significance level of 0.001, which shows a 16% improvement compared to the current business index. (3) Historical backtracking and independent sample tests show that the grade consistency rate between the return period evaluation model and business index is 70%. The return period assessment model is stable and can reflect the frequency and intensity of events, which can provide a new idea for regional rainstorm process assessment.

     

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