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

Alireza Mostafizi (), Haizhong Wang (), Dan Cox (), Lori A. Cramer () and Shangjia Dong ()
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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

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 88, issue 3, No 4, 1347-1372

Abstract: 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.

Keywords: Unplanned network disruption; Agent-based tsunami evacuation modeling; Evidence-driven resource allocation; Retrofitting planning; Community resilience (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s11069-017-2927-y

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