Evacuation behaviors in tsunami drills

Chen Chen (), Alireza Mostafizi (), Haizhong Wang (), Dan Cox () and Lori Cramer ()
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Chen Chen: Oregon State University
Alireza Mostafizi: Oregon State University
Haizhong Wang: Oregon State University
Dan Cox: Oregon State University
Lori Cramer: Oregon State University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 112, issue 1, No 36, 845-871

Abstract: Abstract This paper presents the use of tsunami evacuation drills within a coastal community in the Cascadia Subduction Zone (CSZ) to better understand evacuation behaviors and thus to improve tsunami evacuation preparedness and resilience. Evacuees’ spatial trajectory data were collected by Global Navigation Satellite System (GNSS) embedded in mobile devices. Based on the empirical trajectory data, probability functions were employed to model people’s walking speed during the evacuation drills. An Evacuation Hiking Function (EHF) was established to depict the speed–slope relationship and to inform evacuation modeling and planning. The regression analysis showed that evacuees’ speed was significantly negatively associated with slope, time spent during evacuation, rough terrain surface, walking at night, and distance to destination. We also demonstrated the impacts of milling time on mortality rate based on participants’ empirical evacuation behaviors and a state-of-the-art CSZ tsunami inundation model. Post-drill surveys revealed the importance of the drill as an educational and assessment tool. The results of this study can be used for public education, evacuation plan assessment, and evacuation simulation models. The drill procedures, designs, and the use of technology in data collection provide evidence-driven solutions to tsunami preparedness and inspire the use of drills in other types of natural disasters such as wildfires, hurricanes, volcanoes, and flooding.

Keywords: Tsunami evacuation; Evacuation drill; Walking speed; Preparedness and resilience; Cascadia Subduction Zone (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11069-022-05208-y

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