Article(id=1308453921056379042, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2026.02.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1749052800000, receivedDateStr=2025-06-05, revisedDate=1758556800000, revisedDateStr=2025-09-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1789889324678, onlineDateStr=2026-09-20, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789889324678, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789889324678, creator=13701087609, updateTime=1789889324678, updator=13701087609, issue=Issue{id=1308453915104665783, tenantId=1146029695717560320, journalId=1146123302524792850, year='2026', volume='39', issue='2', pageStart='1', pageEnd='160', issueExtLink='null', onlineDate='null', pubDate='1775750400000', pubDateStr='2026-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789889323259, creator='13701087609', updateTime=1789889766020, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308455772237615687, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308455772237615688, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=65, endPage=72, ext={EN=ArticleExt(id=1308453921270288547, articleId=1308453921056379042, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Vulnerability Assessment Method for Metro Stations under Rainstorm Waterlogging Based on the DPSRC Model, columnId=1152669335454658940, journalTitle=Urban Rapid Rail Transit, columnName=Academic Discussion, runingTitle=null, highlight=null, articleAbstract=

To address the high risks faced by metro systems due to their enclosed underground spaces, vulnerable facilities, and structural complexity amidst frequent rainstorm waterlogging, it is imperative to develop a scientific vulnerability assessment method for metro stations to enhance comprehensive resilience. Based on the chain analysis framework of the driver-pressure-state-response-control (DPSRC) model, this study systematically analyzes the dynamic causality of metro rainstorm waterlogging risks and constructs an assessment index system comprising 5 criterion layers and 20 indicator layers. By integrating subjective and objective weights using the AHP-entropy weight method, a comprehensive vulnerability assessment approach for metro stations was proposed and applied to an empirical analysis of 99 stations in the Ningbo Metro. The results indicate that: ① The proposed method can accurately and effectively assess station vulnerability; ② Stations vulnerabilities exhibit an asymmetric distribution across high (19.10%), medium (51.69%), and low (29.21%) vulnerability levels, with 70.79% of stations exposed to risk, highlighting an urgent need for systemic prevention and control; ③ Waterlogging prevention capacity, monitoring and early warning capabilities, and emergency equipment reserves constitute the key contributing factors to high-vulnerability stations. This research provides a reference for rainstorm waterlogging risk management, disaster prevention, mitigation planning, and resilient transportation development in urban metro systems.

, authors=Kesheng YAN1, 2, Jingya ZHAO1, 2, Hongchuan YUAN2, authorsList=Kesheng YAN, Jingya ZHAO, Hongchuan YUAN, authorCompany=null, correspAuthors=Jingya ZHAO, 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=1308453921639387300, articleId=1308453921056379042, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=基于DPSRC模型的地铁车站暴雨内涝脆弱性评估方法, columnId=1152669335668568445, journalTitle=都市快轨交通, columnName=学术探讨, runingTitle=null, highlight=null, articleAbstract=

针对城市暴雨内涝灾害频发面临的高风险问题,构建地铁车站暴雨内涝脆弱性评估方法。基于驱动力-压力-状态-响应-调控(driver-pressure-state-response-control, DPSRC)模型的链式分析框架,系统解析地铁暴雨内涝风险动态因果,构建包含5个准则层、20个指标层的评估指标体系;采用AHP-熵权法融合主客观权重,提出地铁车站暴雨内涝脆弱性综合评估方法,并以宁波地铁99座车站进行实证分析。结果显示:①所提方法能准确有效地评估各车站的脆弱性;②高(19.10%)、中(51.69%)与低(29.21%)脆弱性站点构成非对称分布,其中70.79%的站点处于风险暴露状态,系统防控需求迫切;③站点防洪能力、站点监测预警能力与应急物资设备是主导高脆弱性站点形成的关键致因。研究可为城市地铁系统暴雨内涝风险管理、防灾减灾规划及韧性交通建设提供参考。

, authors=颜克胜1, 2, 赵婧雅1, 2, 袁宏川2, authorsList=颜克胜, 赵婧雅, 袁宏川, authorCompany=null, correspAuthors=赵婧雅, authorNote=

颜克胜,男,博士,副教授,主要从事交通基础设施韧性评估与管理研究,

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赵婧雅,女,硕士研究生,从事交通基础设施韧性评估与管理研究,
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基于DPSRC模型的地铁车站暴雨内涝脆弱性评估方法
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颜克胜 1, 2 , 赵婧雅 1, 2 , 袁宏川 2
都市快轨交通 | 学术探讨 2026,39(2): 65-72
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都市快轨交通 |学术探讨 2026 , 39 (2) : 65 -72
基于DPSRC模型的地铁车站暴雨内涝脆弱性评估方法
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颜克胜1, 2 , 赵婧雅1, 2 , 袁宏川2
作者信息
  • 1.水电工程施工与管理湖北省重点实验室,湖北 宜昌 443002
  • 2.三峡大学水利与环境学院,湖北 宜昌 443002
通讯作者:
赵婧雅,女,硕士研究生,从事交通基础设施韧性评估与管理研究,
作者简介:

颜克胜,男,博士,副教授,主要从事交通基础设施韧性评估与管理研究,

Vulnerability Assessment Method for Metro Stations under Rainstorm Waterlogging Based on the DPSRC Model
Kesheng YAN1, 2 , Jingya ZHAO1, 2 , Hongchuan YUAN2
Affiliations
  • 1.Hubei Key Laboratory of Hydropower Engineering Construction and Management, Yichang, Hubei, 443002
  • 2. College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang, Hubei, 443002
doi: 10.3969/j.issn.1672-6073.2026.02.008
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针对城市暴雨内涝灾害频发面临的高风险问题,构建地铁车站暴雨内涝脆弱性评估方法。基于驱动力-压力-状态-响应-调控(driver-pressure-state-response-control, DPSRC)模型的链式分析框架,系统解析地铁暴雨内涝风险动态因果,构建包含5个准则层、20个指标层的评估指标体系;采用AHP-熵权法融合主客观权重,提出地铁车站暴雨内涝脆弱性综合评估方法,并以宁波地铁99座车站进行实证分析。结果显示:①所提方法能准确有效地评估各车站的脆弱性;②高(19.10%)、中(51.69%)与低(29.21%)脆弱性站点构成非对称分布,其中70.79%的站点处于风险暴露状态,系统防控需求迫切;③站点防洪能力、站点监测预警能力与应急物资设备是主导高脆弱性站点形成的关键致因。研究可为城市地铁系统暴雨内涝风险管理、防灾减灾规划及韧性交通建设提供参考。

城市轨道交通  /  地铁车站  /  暴雨内涝  /  脆弱性评估  /  DPSRC模型  /  宁波地铁

To address the high risks faced by metro systems due to their enclosed underground spaces, vulnerable facilities, and structural complexity amidst frequent rainstorm waterlogging, it is imperative to develop a scientific vulnerability assessment method for metro stations to enhance comprehensive resilience. Based on the chain analysis framework of the driver-pressure-state-response-control (DPSRC) model, this study systematically analyzes the dynamic causality of metro rainstorm waterlogging risks and constructs an assessment index system comprising 5 criterion layers and 20 indicator layers. By integrating subjective and objective weights using the AHP-entropy weight method, a comprehensive vulnerability assessment approach for metro stations was proposed and applied to an empirical analysis of 99 stations in the Ningbo Metro. The results indicate that: ① The proposed method can accurately and effectively assess station vulnerability; ② Stations vulnerabilities exhibit an asymmetric distribution across high (19.10%), medium (51.69%), and low (29.21%) vulnerability levels, with 70.79% of stations exposed to risk, highlighting an urgent need for systemic prevention and control; ③ Waterlogging prevention capacity, monitoring and early warning capabilities, and emergency equipment reserves constitute the key contributing factors to high-vulnerability stations. This research provides a reference for rainstorm waterlogging risk management, disaster prevention, mitigation planning, and resilient transportation development in urban metro systems.

urban rail transit  /  metro stations  /  rainstorm waterlogging  /  vulnerability assessment  /  DPSRC model  /  Ningbo Metro
颜克胜, 赵婧雅, 袁宏川. 基于DPSRC模型的地铁车站暴雨内涝脆弱性评估方法. 都市快轨交通, 2026 , 39 (2) : 65 -72 . DOI: 10.3969/j.issn.1672-6073.2026.02.008
Kesheng YAN, Jingya ZHAO, Hongchuan YUAN. Vulnerability Assessment Method for Metro Stations under Rainstorm Waterlogging Based on the DPSRC Model[J]. Urban Rapid Rail Transit, 2026 , 39 (2) : 65 -72 . DOI: 10.3969/j.issn.1672-6073.2026.02.008
  • 湖北省教育厅科学技术研究计划优秀中青年人才项目(Q20231212)
  • 湖北省高等学校哲学社会科学研究项目(22Q030)
  • 水电工程施工与管理湖北省重点实验室开放基金(2023KSD29)
  • 教育部人文社会科学研究一般项目(25YJCZH327)
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2026年第39卷第2期
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doi: 10.3969/j.issn.1672-6073.2026.02.008
  • 接收时间:2025-06-05
  • 首发时间:2026-09-20
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  • 收稿日期:2025-06-05
  • 修回日期:2025-09-23
基金
湖北省教育厅科学技术研究计划优秀中青年人才项目(Q20231212)
湖北省高等学校哲学社会科学研究项目(22Q030)
水电工程施工与管理湖北省重点实验室开放基金(2023KSD29)
教育部人文社会科学研究一般项目(25YJCZH327)
作者信息
    1.水电工程施工与管理湖北省重点实验室,湖北 宜昌 443002
    2.三峡大学水利与环境学院,湖北 宜昌 443002

通讯作者:

赵婧雅,女,硕士研究生,从事交通基础设施韧性评估与管理研究,
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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