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Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies

Author

Listed:
  • Alireza Mostafizi

    (Oregon State University)

  • Haizhong Wang

    (Oregon State University)

  • Dan Cox

    (Oregon State University)

  • Lori A. Cramer

    (Oregon State University)

  • Shangjia Dong

    (Oregon State University)

Abstract

The M9 Cascadia subduction zone earthquake represents one of the most pressing natural hazard threats in the Pacific Northwest of the USA with an astonishing high 7–12% chance of occurrence by 2060, mirroring the 2011 devastating earthquake and tsunami in Japan. Yet this region, like many other coastal communities, is underprepared, lacking a comprehensive understanding of unplanned network disruptions as a key component to disaster management planning and infrastructure resilience. The goals of this paper are twofold: (1) to conduct a network vulnerability assessment to systematically characterize the importance of each link’s contribution to the overall network resilience, with specific emphasis on identifying the most critical set of links and (2) to create an evidence-driven retrofitting resource allocation framework by quantifying the impacts of unplanned network disruptions to the critical links on network resilience and retrofitting planning. This research used the city of Seaside on the Oregon coast as a study site to create the agent-based tsunami evacuation modeling and simulation platform with an explicit focus on the transportation network. The results indicated that (1) the network bridges are not equally important and some of the critical links are counterintuitive and (2) the diverse ways of spending the limited retrofitting resources can generate dramatically different life safety outcomes. These results strongly suggest that accurate characterization and measurement of infrastructure network failures will provide evidence-driven retrofitting planning strategies and inform resource allocations that enhance network resilience.

Suggested Citation

  • Alireza Mostafizi & Haizhong Wang & Dan Cox & Lori A. Cramer & Shangjia Dong, 2017. "Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies," 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. 88(3), pages 1347-1372, September.
  • Handle: RePEc:spr:nathaz:v:88:y:2017:i:3:d:10.1007_s11069-017-2927-y
    DOI: 10.1007/s11069-017-2927-y
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    Cited by:

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    2. Chen Chen & Alireza Mostafizi & Haizhong Wang & Dan Cox & Lori Cramer, 2022. "Evacuation behaviors in tsunami drills," 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. 112(1), pages 845-871, May.
    3. Zhenqiang Wang & Gaofeng Jia, 2021. "A novel agent-based model for tsunami evacuation simulation and risk assessment," 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. 105(2), pages 2045-2071, January.
    4. Dylan Sanderson & Sabarethinam Kameshwar & Nathanael Rosenheim & Daniel Cox, 2021. "Deaggregation of multi-hazard damages, losses, risks, and connectivity: an application to the joint seismic-tsunami hazard at Seaside, Oregon," 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. 109(2), pages 1821-1847, November.
    5. 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).
    6. Tomoyuki Takabatake & Tomoya Shibayama & Miguel Esteban & Hidenori Ishii, 2018. "Advanced casualty estimation based on tsunami evacuation intended behavior: case study at Yuigahama Beach, Kamakura, Japan," 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. 92(3), pages 1763-1788, July.
    7. Kameshwar, Sabarethinam & Cox, Daniel T. & Barbosa, Andre R. & Farokhnia, Karim & Park, Hyoungsu & Alam, Mohammad S. & van de Lindt, John W., 2019. "Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    8. Karel Mls & Milan Kořínek & Kamila Štekerová & Petr Tučník & Vladimír Bureš & Pavel Čech & Martina Husáková & Peter Mikulecký & Tomáš Nacházel & Daniela Ponce & Marek Zanker & František Babič & Ioanna, 2023. "Agent-based models of human response to natural hazards: systematic review of tsunami evacuation," 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(3), pages 1887-1908, February.
    9. Tiezhong Liu & Huyuan Zhang & Hubo Zhang, 2020. "The Influence of Social Capital on Protective Action Perceptions Towards Hazardous Chemicals," IJERPH, MDPI, vol. 17(4), pages 1-12, February.
    10. Nathan Wood & Jeanne M. Jones & Yoshiki Yamazaki & Kwok-Fai Cheung & Jacinta Brown & Jamie L. Jones & Nina Abdollahian, 2019. "Population vulnerability to tsunami hazards informed by previous and projected disasters: a case study of American Samoa," 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. 95(3), pages 505-528, February.

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