Examining the Impact of Risk Perception on the Accuracy of Anisotropic, Least-Cost Path Distance Approaches for Estimating the Evacuation Potential for Near-Field Tsunamis
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Coastal hazards that can strike with little or no warning, such as tsunamis, are problematic in terms of population exposure and the threat of loss of life. With projected increases in coastal populations, exposure is likely to increase among these communities. For near-field tsunamis, the evacuation window can be as little as 15 to 20 min, and evacuation can be problematic for numerous reasons, such as population demographics, limited road networks, local topographic constraints, lack of proper education, and misaligned risk perception of the general populace. It is therefore critical for tsunami evacuation planning and education to be highly effective. To address this need, we employed a participatory mapping approach to explore potential evacuation enhancement by evaluating existing least-cost path pedestrian evacuation models, perception of landscape constraints, and additional risks to nearfield tsunamis in Aberdeen, Washington. Stakeholders were tasked with drawing their understood evacuation routes on maps which were analyzed for approximate time to reach safety and compared to least-cost path pedestrian evacuation models. A quantitative analysis of selected evacuation pathways revealed participants consistently overestimated evacuation time and did not follow modeled least-cost pathways. The results suggest traditional modeling (e.g., least-cost path and agent-based models) underestimate travel time to safety. Thus, there is a need for additional outreach, notably in communities where traditional evacuation models might create a false sense of security.
KeywordsPedestrian evacuation Near-field tsunamis Participatory mapping Risk perception Evacuation modeling
Compliance with Ethical Standards
This article conforms to the ethical responsibilities of authors as described on the ‘Instructions for Authors’ webpage. The research presented herein does not misrepresent research results, nor has the manuscript been submitted to more than one journal for simultaneous consideration or published previously, either in part or full. No data have been fabricated or manipulated, nor is the article plagiarized. The manuscript adheres to the other responsibilities detailed on the instructional webpage.
Conflict of Interest
For reviewers, please exclude Dr. Nathan Wood (USGS).
This research was approved by the Institutional Review Board of Binghamton University.
All authors consent to the submission and publication of this manuscript.
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