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A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall‐Induced Multihazards

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  • Kai Liu
  • Ming Wang
  • Yinxue Cao
  • Weihua Zhu
  • Jinshan Wu
  • Xiaoyong Yan

Abstract

Climate change and its projected natural hazards have an adverse impact on the functionality and operation of transportation infrastructure systems. This study presents a comprehensive framework to analyze the risk to transportation infrastructure networks that are affected by natural hazards. The proposed risk analysis method considers both the failure probability of infrastructure components and the expected infrastructure network efficiency and capacity loss due to component failure. This comprehensive approach facilitates the identification of high‐risk network links in terms of not only their susceptibility to natural hazards but also their overall impact on the network. The Chinese national rail system and its exposure to rainfall‐related multihazards are used as a case study. The importance of various links is comprehensively assessed from the perspectives of topological, efficiency, and capacity criticality. Risk maps of the national railway system are generated, which can guide decisive action regarding investments in preventative and adaptive measures to reduce risk.

Suggested Citation

  • Kai Liu & Ming Wang & Yinxue Cao & Weihua Zhu & Jinshan Wu & Xiaoyong Yan, 2018. "A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall‐Induced Multihazards," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1618-1633, August.
    • Handle: RePEc:wly:riskan:v:38:y:2018:i:8:p:1618-1633
    DOI: 10.1111/risa.12968
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    References listed on IDEAS

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    Cited by:

    1. Liang Jia & Saini Yang & Weiping Wang & Xinlong Zhang, 2022. "Impact analysis of highways in China under future extreme precipitation," 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. 110(2), pages 1097-1113, January.
    2. Liu, Kai & Zhu, Jiatong & Wang, Ming, 2021. "An event-based probabilistic model of disruption risk to urban metro networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 93-105.
    3. Lam, C.Y. & Cruz, A.M., 2019. "Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 198-212.

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