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Journal Article

Citation

Fathianpour A, Evans B, Jelodar MB, Wilkinson S. Prog. Disaster Sci. 2023; 17: e100277.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.pdisas.2023.100277

PMID

unavailable

Abstract

The associated tsunami risks posed to coastal regions in earthquake-prone areas highlight the importance of an effective emergency evacuation plan for these regions. Evacuation simulations have shown to be a valuable tool in assessing the effectiveness of existing evacuation plans and providing solutions for risk reduction, and improving community readiness. This paper describes the development of a micro-simulation evacuation model (MSEM) to assess the effectiveness of local tsunami evacuation processes and test the results with a velocity-based theoretical model. As an agent-based model, the MSEM considers both pedestrian and vehicle interactions and their interactions with each other. The models were used to assess the evacuation scenarios for a tsunami-prone city Napier, in New Zealand. The evacuation process was evaluated based on a local 8.4 Mw earthquake that would trigger a tsunami event, with an evacuation time of 50 min between feeling the initial shake in Napier City and the time of arrival of the tsunami wave. The study outlined within this paper assumes two scenarios: (1) effected population would evacuate by foot, and (2) affected population would evacuate by car, considered to take place during the afternoon at the traffic peak time. The results of the MSEM show factors such as evacuation method, lane and sidewalk capacities, and interactions between individuals affect the individuals' ability to safely evacuate. The MSEM model based on scenario 1 and 2 for Napier City, demonstrated around 85% of residents would reach designated safe area when all evacuating by foot, whilst, only 45% of evacuees will reach their designated safe zone if all individuals attempted to use vehicles as their means of evacuation.


Language: en

Keywords

Emergency management; Evacuation modelling; micro-simulation model

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