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Research Article

Rainstorm waterlogging vulnerability assessment of subway stations in the central area of Tianjin

, , , , , & show all
Pages 2277-2297 | Received 22 Feb 2023, Accepted 08 Sep 2023, Published online: 26 Oct 2023
 

ABSTRACT

Rainstorm and waterlogging disasters of underground rail transit have recently become a vital safety problem. In this paper, a model of vulnerability assessment is established, and 14 indicators are selected to establish an indicator system for 109 stations in the central area of Tianjin. Analytic Hierarchy Process(AHP) and Entropy Weight Method (EWM) were used to determine the subjective and objective weights of indicators. A distance function was introduced to calculate the combined weights and improve the weights’ rationality. The results show that there are 34 high and medium-high vulnerability stations, and 41 low and medium-low vulnerability stations. Except for Line 2, the vulnerability level of subway stations on the rail lines decreased from the edge to the centre. Nankai District had the most high-vulnerability stations (seven of the 20 high-vulnerability stations). The main influence factors were the waterproofing capacity of the subway, the digital elevation model, the station type, the height of the exit, and the entrance steps.

GRAPHICAL ABSTRACT

Editor A. Fiori; Associate Editor K. Kochanek

Editor A. Fiori; Associate Editor K. Kochanek

Acknowledgements

We sincerely thank the editor and the anonymous reviewers for their insightful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2023.2264839.

Additional information

Funding

This work was supported by the technical service project of the First National Survey on Natural Disaster Risks (SNDR) of the Bureau of Emergency Management of Tianjin [grant numbers 53H22002], the technical support project of the First National Survey on Natural Disaster Risks (SNDR) of the Bureau of Emergency Management of Tianjin [grant numbers 53H22048], and the Tianjin Research Innovation Project for Postgraduate Students [grant numbers 2022SKY248].

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