Enhancing tsunami evacuation strategies in Puerto Rico using open-source least-cost path analysis

Abstract Effective disaster planning strengthens community resilience and reduces both damage and casualties from tsunamis. In Puerto Rico, municipal emergency management planners need data on the tsunami evacuation zone (TEZ), wave run-up heights, and estimated evacuation times to inform constituents. There are 46 coastal municipalities within the TEZ. Due to evolving methodologies, software, and staffing, the Puerto Rico Seismic Network’s TsunamiReady Program has only provided walking-time estimates to a subset of communities. This study introduces an effective, repeatable methodology to generate distance to safety and pedestrian evacuation times across all impacted zones. The approach—an iterative least-cost path analysis from road points to safety areas, followed by spatial interpolation—produced evacuation time maps for all 46 municipalities. The longest modeled evacuation time was 184 min in Loíza, though average times across most municipalities were under 35 min. For comparison, historical tsunami evidence suggests that waves can reach Puerto Rico’s western coast within 2 to 45 min of a generating event. The open-source methodology used here is transferable to other tsunami-prone regions and offers significant advantages over proprietary systems. The results provide Puerto Rico’s emergency managers, and the public, with essential spatial information to identify the highest-risk portions of their TEZ and improve evacuation planning.

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Publication Details

Journal
Journal of Disaster Science and Management
Published
2025-09-10
DOI
https://doi.org/10.1007/s44367-025-00018-y
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Enhancing tsunami evacuation strategies in Puerto Rico using open-source least-cost path analysis

Christopher Sherman, Elvin Cordero, Roy Ruiz Vélez, Víctor Huérfano Moreno
Journal of Disaster Science and Management
Evacuation and Crowd Dynamics
article

Enhancing tsunami evacuation strategies in Puerto Rico using open-source least-cost path analysis

Christopher Sherman, Elvin Cordero, Roy Ruiz Vélez, Víctor Huérfano Moreno
article en

Abstract

Abstract Effective disaster planning strengthens community resilience and reduces both damage and casualties from tsunamis. In Puerto Rico, municipal emergency management planners need data on the tsunami evacuation zone (TEZ), wave run-up heights, and estimated evacuation times to inform constituents. There are 46 coastal municipalities within the TEZ. Due to evolving methodologies, software, and staffing, the Puerto Rico Seismic Network’s TsunamiReady Program has only provided walking-time estimates to a subset of communities. This study introduces an effective, repeatable methodology to generate distance to safety and pedestrian evacuation times across all impacted zones. The approach—an iterative least-cost path analysis from road points to safety areas, followed by spatial interpolation—produced evacuation time maps for all 46 municipalities. The longest modeled evacuation time was 184 min in Loíza, though average times across most municipalities were under 35 min. For comparison, historical tsunami evidence suggests that waves can reach Puerto Rico’s western coast within 2 to 45 min of a generating event. The open-source methodology used here is transferable to other tsunami-prone regions and offers significant advantages over proprietary systems. The results provide Puerto Rico’s emergency managers, and the public, with essential spatial information to identify the highest-risk portions of their TEZ and improve evacuation planning.

Journal of Disaster Science and ManagementVol. 1(1)
Geospatial Research (United Kingdom) (GB), University of Puerto Rico-Mayaguez (PR)
National Oceanic and Atmospheric Administration
Openalex Percentile: Top 70%
Evacuation and Crowd Dynamics
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Enhancing tsunami evacuation strategies in Puerto Rico using open-source least-cost path analysis — Christopher Sherman, Elvin Cordero, et al. · Journal of Disaster Science and Management (2025) | TGRS Research Map | TGRS