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Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

Author

Listed:
  • Liudan Jiao

    (Chongqing Jiaotong University)

  • Yinghan Zhu

    (Nanjing University)

  • Xiaosen Huo

    (Chongqing Jiaotong University)

  • Ya Wu

    (Southwest University)

  • Yu Zhang

    (Chongqing Jiaotong University)

Abstract

Extremely heavy rainfall has posed a significant hazard to urban growth as the most common and disaster-prone natural calamity. Due to its unique geographical location, the metro system is more vulnerable to waterlogging caused by rainstorm disaster. Research on resilience to natural disasters has attracted extensive attention in recent years. However, few studies have focused on the resilience of the metro system against rainstorms. Therefore, this paper aims to develop an assessment model for evaluating metro stations’ resilience levels. Twenty factors are carried out from dimensions of resistance, recovery and adaptation. The methods of ordered binary comparison, entropy weight and cloud model are proposed to build the assessment model. Then, taking Chongqing metro system in china as a case study, the resilience level of 13 metro stations is calculated. Radar charts from dimensions of resistance, recovery, and adaptation are created to propose recommendations for improving metro stations’ resilience against rainstorms, providing a reference for the sustainable development of the metro system. The case study of the Chongqing metro system in china demonstrates that the assessment model can effectively evaluate the resilience level of metro stations and can be used in other infrastructures under natural disasters for resilience assessment.

Suggested Citation

  • Liudan Jiao & Yinghan Zhu & Xiaosen Huo & Ya Wu & Yu Zhang, 2023. "Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(2), pages 2311-2337, March.
    • Handle: RePEc:spr:nathaz:v:116:y:2023:i:2:d:10.1007_s11069-022-05765-2
    DOI: 10.1007/s11069-022-05765-2
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    References listed on IDEAS

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    1. Xie, Shuyi & Dong, Shaohua & Chen, Yinuo & Peng, Yujie & Li, Xincai, 2021. "A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
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    3. Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Sybil Derrible & Christopher Kennedy, 2010. "Characterizing metro networks: state, form, and structure," Transportation, Springer, vol. 37(2), pages 275-297, March.
    5. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.
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