基于多重精度降雨数据的北京市极端降雨事件研究  

Research on extreme precipitation events in Beijing based on multi-resolution rainfall data

作　　者：张伟[1,2,3] 王璇 孙慧超 李俊奇[1,2,3] ZHANG Wei;WANG Xuan;SUN Huichao;LI Junqi(Beijing Engineering Research Center of Sustainable Urban Sewage System Construction and Risk Control,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Key Laboratory of Urban Stormwater System and Water Environment,Ministry of Education,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Energy Conservation&Sustainable Urban and Rural Development Provincial and Ministry Co-construction Collaboration Innovation Center,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)

机构地区：[1]北京建筑大学北京市可持续城市排水系统构建与风险控制工程技术研究中心,北京100044 [2]北京建筑大学城市雨水系统与水环境教育部重点实验室,北京100044 [3]北京建筑大学北京节能减排与城乡可持续发展省部共建协同创新中心,北京100044

出　　处：《水资源保护》2025年第2期123-132,157,共11页Water Resources Protection

基　　金：国家重点研发计划项目(2022YFC3800500);泸州市海绵城市科研课题项目(N5105012022000106);北京市属高等学校高水平科研创新团队建设支持计划项目(BPHR20220108);北京建筑大学培育项目专项资金项目(X23047)。

摘　　要：基于北京基本站1987—2016年逐分钟精度降雨数据,利用Kruskal-Wallis检验对1 min、1 h、3 h、6 h等不同精度数据获取的极端降雨事件样本进行统计分析,比较短历时极端降雨(SEP)、长历时极端降雨(LEP)、持续性极端降雨(PEP)3类极端降雨事件降雨特征指标的差异,并利用Sen’s斜率、Mann-Kendall检验、有序聚类等方法探究了极端降雨事件的时间变化规律。结果表明:北京市极端降雨以LEP事件为主,降雨数据精度会显著影响降水量和降雨历时的统计结果,1 h精度降雨数据可基本反映极端降雨事件的主要时间特征;数据精度差异会造成极端降雨事件的降雨集中度和降雨集中期识别出现偏差,北京市极端降雨多分布于6—10月,并主要集中在7—8月,但9—10月仍存在PEP事件出现的可能;SEP和LEP事件多出现在夜间,而PEP事件在7—12时更易形成降雨峰值,对居民紧急避险和内涝应急响应造成更高潜在风险;在统计年限内,数据精度差异对降水量和降雨频率趋势预测结果的影响并不显著,但会使得降雨历时预测不确定性增加,降雨特征指标突变年份产生“跳跃”;PEP事件的降水量、降雨频率、降雨历时和降雨集中度受数据精度影响较小。Based on the minute resolution rainfall data of Beijing basic station from 1987 to 2016,Kruskal-Wallis test was used to statistically analyze extreme precipitation event samples obtained from multi-resolution data such as 1 min,1 h,3 h,and 6 h.The differences in rainfall characteristic indicators of three types of extreme precipitation events,including short extreme precipitation(SEP),long extreme precipitation(LEP),and persistent extreme precipitation(PEP)were compared,and the temporal variation patterns of extreme precipitation events using methods such as Sen’s slope,Mann-Kendall test,and ordered clustering were explored.The results show that extreme precipitation in Beijing is mainly caused by LEP events,and the resolution of rainfall data significantly affects the statistical results of precipitation amount and duration.The rainfall data of 1 h resolution can basically reflect the main time characteristics of extreme precipitation events.Differences in data resolution can cause deviations in the identification of rainfall concentration and rainfall concentration periods for extreme precipitation events.Extreme precipitation in Beijing is mostly distributed from June to October,and mainly concentrated in July and August,but there is still a possibility of PEP events occurring in September and October.SEP and LEP events often occur at night,while PEP events are more likely to form rainfall peaks from 7:00 to 12:00,posing higher potential risks to residents’emergency shelter and waterlogging emergency response.Within the statistical period,the difference in data resolution does not have a significant impact on the prediction results of precipitation amount and frequency trends,but it will increase the uncertainty of rainfall duration prediction and cause a“jump”in the year of sudden changes in rainfall characteristic indicators.The precipitation amount,frequency,duration,and concentration of PEP events are less affected by data resolution.

关 键 词：极端降雨事件 多重精度降雨数据 Kruskal-Wallis检验 Sen’s斜率法 MANN-KENDALL检验 有序聚类法 北京市 

分 类 号：TV213.4[水利工程—水文学及水资源]