Article(id=1311351198637191661, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2026.20250478, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742140800000, receivedDateStr=2025-03-17, revisedDate=1743868800000, revisedDateStr=2025-04-06, acceptedDate=1744300800000, acceptedDateStr=2025-04-11, onlineDate=1790580089482, onlineDateStr=2026-09-28, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790580089482, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790580089482, creator=13701087609, updateTime=1790580089482, updator=13701087609, issue=Issue{id=1311351152067830064, tenantId=1146029695717560320, journalId=1205116964453384197, year='2026', volume='44', issue='1', pageStart='1', pageEnd='246', issueExtLink='null', onlineDate='null', pubDate='1769270400000', pubDateStr='2026-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790580078378, creator='13701087609', updateTime=1790588459421, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311386304772927717, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311386304772927718, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=6, endPage=10, ext={EN=ArticleExt(id=1311351198804963822, articleId=1311351198637191661, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Analysis of Multi-scale Spatio-temporal Distribution Characteristics and Driving Forces of Urban Waterlogging in Zhengzhou City, columnId=null, journalTitle=Water Resources and Power, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In recent years, frequent heavy rains have made Zhengzhou city suffer from the hazards of urban waterlogging. Identifying the spatiotemporal distribution characteristics and driving forces of waterlogging can help improve the current flood-prone situation in Zhengzhou city. Based on the waterlogging data of Zhengzhou from 2020 to 2024, the standard deviation ellipse method, autocorrelation method, kernel density estimation method, and optimal parameter geographic detector were used to systematically analyze the spatiotemporal distribution characteristics of waterlogging points and their driving forces from multiple scales. The results show that the annual distribution of waterlogging points in Zhengzhou is uneven; Spatially, the the focus of waterlogging is located in the old urban area, with significant clustering of waterlogging points at different scales, especially with the strongest spatial clustering within a 3km scale; There is a significant scale effect in the explanatory power of driving factors, with socioeconomic and urban construction driving factors having the greatest explanatory power at different scales, and the combined effect of factors significantly surpasses the independent effects of single factors.

, authors=Jie ZHENG^a, Xue-ni WANG^{a, b}, Hua JIN^a, Zhong-feng ZHAO^a, authorsList=Jie ZHENG, Xue-ni WANG, Hua JIN, Zhong-feng ZHAO, authorCompany=null, correspAuthors=Xue-ni WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311351199136313839, articleId=1311351198637191661, tenantId=1146029695717560320, journalId=1205116964453384197, language=CN, title=郑州市城市内涝多尺度时空分布特征及其驱动力分析, columnId=1207627659488632924, journalTitle=水电能源科学, columnName=水文水资源与环境, runingTitle=null, highlight=null, articleAbstract=

近年来频发的暴雨令郑州市饱受城市内涝危害，明确内涝时空分布特征及驱动力有助于改善郑州市当前易涝现状。基于郑州市2020~2024年内涝数据，采用标准差椭圆法、自相关法、核密度估计法和参数最优地理探测器，从多尺度出发系统分析了郑州市内涝点的时空分布特征及其驱动力。研究结果表明，郑州市内涝点年际分布不均；空间上内涝重心位于老城区，不同尺度内涝点均存在显著的聚集性，且3 km尺度下空间聚集性最强；驱动因子解释力存在显著尺度效应，不同尺度下社会经济类和城市建设类驱动因子解释力均最强，因子协同作用的解释力显著超越单因子的独立作用。

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郑婕（1997-），女，硕士研究生，研究方向为海绵城市建设及城市内涝模拟，E-mail: zhengjie324@163.com

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郑婕（1997-），女，硕士研究生，研究方向为海绵城市建设及城市内涝模拟，E-mail: zhengjie324@163.com

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