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Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science

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  • Amirhassan Kermanshah

    (University of Illinois at Chicago)

  • Sybil Derrible

    (University of Illinois at Chicago)

Abstract

The main objective of this article is to study the robustness of road networks to extreme flooding events that can negatively affect entire regional systems in a relatively unpredictable way. Here, we adopt a deterministic approach to simulate extreme flooding events in two cities, New York City and Chicago, by removing entire sections of road systems using U.S. FEMA floodplains. We then measure changes in the number of real trips that can be completed (using travel demand data), Geographical Information Systems properties, and network topological indicators. We notably measure and discuss how betweenness centrality is being redistributed after flooding. Broadly, robustness in spatial systems like road networks is dependent on many factors, including system size (number of nodes and links) and topological structure of the network. Expectedly, robustness also depends on geography, and cities that are naturally more at risk will tend to be less robust, and therefore the notion of robustness rapidly becomes sensitive to individual contexts.

Suggested Citation

  • Amirhassan Kermanshah & Sybil Derrible, 2017. "Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science," 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. 86(1), pages 151-164, March.
    • Handle: RePEc:spr:nathaz:v:86:y:2017:i:1:d:10.1007_s11069-016-2678-1
    DOI: 10.1007/s11069-016-2678-1
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    6. Gangwal, Utkarsh & Dong, Shangjia, 2022. "Critical facility accessibility rapid failure early-warning detection and redundancy mapping in urban flooding," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    7. Weiping Wang & Saini Yang & Jianxi Gao & Fuyu Hu & Wanyi Zhao & H. Eugene Stanley, 2020. "An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1780-1794, September.
    8. Ahmad, Nasir & Derrible, Sybil, 2018. "An information theory based robustness analysis of energy mix in US States," Energy Policy, Elsevier, vol. 120(C), pages 167-174.
    9. Madeline Allen & Leslie Gillespie-Marthaler & Mark Abkowitz & Janey Camp, 2020. "Evaluating flood resilience in rural communities: a case-based assessment of Dyer County, Tennessee," 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. 101(1), pages 173-194, March.

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