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JDR Vol.20 No.4 pp. 459-467
(2025)
doi: 10.20965/jdr.2025.p0459

Paper:

The Numerical Analysis of Scheduled Tsunami Evacuation: Case Study of the Great East Japan Earthquake Tsunami

Tamaki Kanemura*,† and Ryota Nakamura** ORCID Icon

*Graduate School of Science and Technology, Niigata University
8050 Ikarashi 2-no-cho, Nishi-ku, Niigata, Niigata 950-2181, Japan

Corresponding author

**Civil Engineering Program, Faculty of Engineering, Niigata University
Niigata, Japan

Received:
November 13, 2024
Accepted:
April 3, 2025
Published:
August 1, 2025
Keywords:
evacuation, tsunami
Abstract

This study quantitatively examined the number of fatalities and evacuation completion rate by simulating a tsunami evacuation based on the Great East Japan Earthquake in the Shishiori district of Kesennuma City, Miyagi Prefecture, using different scheduled evacuation start times and areas. As people perceive risk differently and congestion may adversely impact the number of fatalities and evacuation completion rate, investigating efficient evacuation methods by considering various evacuation start times and areas is necessary. Simulation results revealed that for simultaneous evacuation, the number of fatalities increased, and the evacuation completion rate decreased with slower evacuation start times. For time-delayed evacuation, the number of fatalities decreased, and the completion rate increased more than that of simultaneous evacuation. Moreover, the separate-area evacuation was effective as it reduced the number of fatalities and increased the evacuation completion rate compared to the time-delayed evacuation alone. Furthermore, it was more effective to set the line of division by distance from the coastline rather than elevation. Therefore, when planning an evacuation, dividing the evacuation start area is an important means to relieve congestion.

Cite this article as:
T. Kanemura and R. Nakamura, “The Numerical Analysis of Scheduled Tsunami Evacuation: Case Study of the Great East Japan Earthquake Tsunami,” J. Disaster Res., Vol.20 No.4, pp. 459-467, 2025.
Data files:
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Last updated on Jul. 31, 2025