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A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods

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  • Rob Lamb
  • Paige Garside
  • Raghav Pant
  • Jim W. Hall

Abstract

Scour (localized erosion by water) is an important risk to bridges, and hence many infrastructure networks, around the world. In Britain, scour has caused the failure of railway bridges crossing rivers in more than 50 flood events. These events have been investigated in detail, providing a data set with which we develop and test a model to quantify scour risk. The risk analysis is formulated in terms of a generic, transferrable infrastructure network risk model. For some bridge failures, the severity of the causative flood was recorded or can be reconstructed. These data are combined with the background failure rate, and records of bridges that have not failed, to construct fragility curves that quantify the failure probability conditional on the severity of a flood event. The fragility curves generated are to some extent sensitive to the way in which these data are incorporated into the statistical analysis. The new fragility analysis is tested using flood events simulated from a spatial joint probability model for extreme river flows for all river gauging sites in Britain. The combined models appear robust in comparison with historical observations of the expected number of bridge failures in a flood event. The analysis is used to estimate the probability of single or multiple bridge failures in Britain's rail network. Combined with a model for passenger journey disruption in the event of bridge failure, we calculate a system‐wide estimate for the risk of scour failures in terms of passenger journey disruptions and associated economic costs.

Suggested Citation

  • Rob Lamb & Paige Garside & Raghav Pant & Jim W. Hall, 2019. "A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods," Risk Analysis, John Wiley & Sons, vol. 39(11), pages 2457-2478, November.
  • Handle: RePEc:wly:riskan:v:39:y:2019:i:11:p:2457-2478
    DOI: 10.1111/risa.13370
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    References listed on IDEAS

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    1. Alberto Decò & Dan M. Frangopol, 2011. "Risk assessment of highway bridges under multiple hazards," Journal of Risk Research, Taylor & Francis Journals, vol. 14(9), pages 1057-1089, October.
    2. Hong, Liu & Ouyang, Min & Peeta, Srinivas & He, Xiaozheng & Yan, Yongze, 2015. "Vulnerability assessment and mitigation for the Chinese railway system under floods," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 58-68.
    3. Caroline Keef & Jonathan A. Tawn & Rob Lamb, 2013. "Estimating the probability of widespread flood events," Environmetrics, John Wiley & Sons, Ltd., vol. 24(1), pages 13-21, February.
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    Cited by:

    1. Yiming Cao & Hengxing Lan & Langping Li, 2023. "Disaster Risk Assessment for Railways: Challenges and a Sustainable Promising Solution Based on BIM+GIS," Sustainability, MDPI, vol. 15(24), pages 1-27, December.
    2. Johnson, Caroline A. & Flage, Roger & Guikema, Seth D., 2021. "Feasibility study of PRA for critical infrastructure risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Vijendra Kumar & Hazi Md. Azamathulla & Kul Vaibhav Sharma & Darshan J. Mehta & Kiran Tota Maharaj, 2023. "The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management," Sustainability, MDPI, vol. 15(13), pages 1-33, July.
    4. Weihua Zhu & Kai Liu & Ming Wang & Sadhana Nirandjan & Elco E. Koks, 2023. "Improved assessment of rainfall-induced railway infrastructure risk in China using empirical data," 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. 115(2), pages 1525-1548, January.
    5. Argyroudis, Sotirios A. & Mitoulis, Stergios Aristoteles, 2021. "Vulnerability of bridges to individual and multiple hazards- floods and earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 210(C).

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