杨子昕,王佳,刘家宏,王浩,梅超,李峰平

• 1:地下水资源与环境教育部重点实验室
• 2:吉林省水资源与水环境重点实验室
• 3:吉林大学新能源与环境学院
• 4:中国水利水电科学研究院流域水循环模拟与调控国家重点实验室

摘要(Abstract)：

【目的】城市降雨具有高度的不确定性和时空变异性，现阶段洪涝风险预测、应急响应预案的时效性和有效性有待加强。为提高“预报降雨—灾害风险识别—应急响应预案”的时效性和有效性【方法】提出了一种基于自组织特征映射网络的数据密集型城市场次降雨情景库构建方法和基于动态时间弯曲法的预报降雨与情景库场次降雨匹配技术。以北京城市副中心通县站1980—2015年(36年)的小时降雨监测数据作为情景库数据基础，并以同地区2023年降雨数据作为“预报降雨”进行匹配方法验证。【结果】结果显示：构建的城市场次降雨情景库可全面、有效的反映研究区域降雨特征。“预报降雨”匹配效果良好，平均纳什系数达到0.73,降雨总量平均相对误差为0.17,降雨量峰值平均相对误差为0.09。【结论】该方法可快速实现实时预报降雨与情景库中场次降雨的匹配，通过情景库中预置洪涝风险及应急预案知识库，实现城市洪涝风险的有效识别和及时响应。

关键词(KeyWords)： 雨型;动态时间弯曲;城市洪涝;预报降雨;风险评估;洪水;降水;气候变化

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目(2022YFC3090600);; 国家自然科学基金项目(52192671);; 重点实验室项目(SKL2022TS11)

作者(Author): 杨子昕,王佳,刘家宏,王浩,梅超,李峰平

DOI: 10.13928/j.cnki.wrahe.2024.10.002

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