Article(id=1281683237810455469, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.05.0622, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736524800000, receivedDateStr=2025-01-11, revisedDate=1742140800000, revisedDateStr=2025-03-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1783506696416, onlineDateStr=2026-07-08, pubDate=1748361600000, pubDateStr=2025-05-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783506696416, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783506696416, creator=13701087609, updateTime=1783506696416, updator=13701087609, issue=Issue{id=1281683189131359212, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='5', pageStart='1', pageEnd='268', issueExtLink='null', onlineDate='null', pubDate='1748361600000', pubDateStr='2025-05-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783506684811, creator='13701087609', updateTime=1783589333681, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282029843684504545, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282029843684504546, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=237, endPage=245, ext={EN=ArticleExt(id=1281683238041142190, articleId=1281683237810455469, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Simulation and risk assessment of urban flooding under realistic 3D data, columnId=1149735802789348081, journalTitle=China Safety Science Journal, columnName=Technology and engineering of disaster prevention and mitigation, runingTitle=null, highlight=null, articleAbstract=

In order to enhance the capacity of urban flood prevention and disaster reduction, taking Zhenba County as an example, this paper explores the coupled disaster formation process and risk assessment methods of flood disasters. By analyzing the rainfall data and flood disaster statistics in recent years, the frequent occurrence and severity of flood disasters in this area as well as the huge losses they have caused to the economy and society were revealed. High-precision terrain data was obtained through unmanned aerial vehicle technology and combined with the SWAT for flood simulation, providing accurate disaster data support. A multi-factor risk assessment matrix was constructed, and the comprehensive flood risk index was obtained through normalization processing. The risk assessment results show that 14 areas with grade IV risks are identified, and the simulation results of the model are highly consistent with the actual situation. The research results indicate that the constructed coupled disaster formation simulation and risk assessment method can accurately identify high-risk areas. Effective countermeasures are proposed for high-risk areas, including improving flood control capacity, strengthening monitoring and early warning, conducting disaster prevention and education, and strengthening land planning and management.

, authors=Lizhou WU¹, Hua LI^{**, 1}, Peng ZHANG¹, Hongyan QIAN², Fei KANG³, Guangli TAN⁴, authorsList=Lizhou WU, Hua LI, Peng ZHANG, Hongyan QIAN, Fei KANG, Guangli TAN, authorCompany=null, correspAuthors=Hua LI, 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=1281683240348009394, articleId=1281683237810455469, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=实景三维数据下城市洪涝模拟及风险评估, columnId=1149735802885817075, journalTitle=中国安全科学学报, columnName=防灾减灾技术与工程, runingTitle=null, highlight=null, articleAbstract=

为提高城市洪涝灾害防范和减灾能力，以镇巴县为例，探讨洪涝灾害的耦合成灾过程及风险评估方法。通过分析近年来降雨数据和洪涝灾害统计，揭示该地区洪涝灾害的频发和严重性，以及对经济社会造成的巨大损失。利用无人机技术获取高精度地形数据，并结合土壤和水评估工具（SWAT）进行洪涝模拟，提供准确灾害数据支持。构建基于多要素风险评估矩阵，通过归一化处理得到综合洪涝风险指数。风险评估结果显示：确认14个Ⅳ级风险区域，且模型模拟结果与实际情况吻合度高。研究结果表明：所构建的耦合成灾模拟与风险评估方法能较为准确地识别高风险区域。针对高风险区域提出有效应对措施，包括提升防洪能力、加强监测预警、开展灾害宣传教育以及加强土地规划管理。

, authors=吴立舟¹, 李华副教授^{**, 1}, 张鹏¹, 钱虹燕², 康飞³, 谭光丽⁴, authorsList=吴立舟, 李华副教授, 张鹏, 钱虹燕, 康飞, 谭光丽, authorCompany=null, correspAuthors=李华副教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=vqH4uaQ5aAZnIEjxfS0zPw==, magXml=Xz3WHXn+4ELnGfUAk/8hPA==, pdfUrl=null, pdf=GqUy+mYWzVBjKIriErNFNQ==, pdfFileSize=2212247, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=fZbAYJKDM1aD4+EXGdpZqg==, mapNumber=null, fund=null)}, authors=[Author(id=1281683242147365824, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683237810455469, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=wulizhou@xauat.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281683242428384194, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683237810455469, authorId=1281683242147365824, language=EN, stringName=Lizhou WU, firstName=Lizhou, middleName=null, lastName=WU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹School of Resources Engineering, Xi'an University of Architecture and Technology, Xi'an Shaanxi 710055, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281683242558407619, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683237810455469, authorId=1281683242147365824, language=CN, stringName=吴立舟, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹西安建筑科技大学 资源工程学院，陕西 西安 710055, bio={"content":"

吴立舟（2000—），男，陕西汉中人，硕士研究生，主要研究方向为智能施工与安全管理，计算机视觉和无人机视觉。E-mail:wulizhou@xauat.edu.cn。

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吴立舟（2000—），男，陕西汉中人，硕士研究生，主要研究方向为智能施工与安全管理，计算机视觉和无人机视觉。E-mail:wulizhou@xauat.edu.cn。

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