Abstract

Previous tsunami evacuation simulations have mostly been based on arbitrary assumptions or inputs adapted from non-emergency situations, but a few studies have used empirical behavior data. This study bridges this gap by integrating empirical decision data from local evacuation expectations surveys and evacuation drills into an agent-based model of evacuation behavior for a Cascadia Subduction Zone community. The model also considers the impacts of liquefaction and landslides from the earthquake on tsunami evacuation. Furthermore, we integrate the slope-speed component from Least-cost-distance to build the simulation model that better represents the complex nature of evacuations. The simulation results indicate that milling time and evacuation participation rate have significant non-linear impacts on tsunami mortality estimates. When people walk faster than 1 m/s, evacuation by foot is more effective because it avoids traffic congestion when driving. We also find that evacuation results are more sensitive to walking speed, milling time, evacuation participation, and choosing the closest safe location than to other behavioral variables. Minimum tsunami mortality results from maximizing the evacuation participation rate, minimizing milling time, and choosing the closest safe destination outside of the inundation zone. This study's comparison of the agent-based model and BtW model finds consistency between the two models' results. By integrating the natural system, built environment, and social system, this interdisciplinary model incorporates substantial aspects of the real world into the multi-hazard agent-based platform. This model provides a unique opportunity for local authorities to prioritize their resources for hazard education, community disaster preparedness, and resilience plans.

Highlights

  • The unique characteristics of ABMS include a bottom-up structure and ability to model heterogeneous agents and their interactions with other agents. These unique characteristics meet the needs of disaster evacuation simulation (Gilbert, 2007)

  • This study considered evacuees’ car following and dynamic routing behaviors, it was based on many arbitrary assumptions about evacuation behavior

  • When optimizing evacuation participation, milling time, and choosing closest destinations outside of the inundation zone, the results show that almost all residents can be saved

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Summary

Introduction

Recent devastating earthquakes and tsunamis have placed immense burdens on their affected communities, such as the 2011 Tohoku tsunami (Mori et al, 2011), the 2009 American. Samoa tsunami (Lindell et al, 2015), and the 2018 Indonesia Sulawesi tsunami (Sassa and Takagawa, 2019). Due to a small evacuation time window between the end of earthquake shaking and the arrival of the first tsunami wave, a high level of evacuation efficiency is essential for minimizing the loss of life in low-lying coastal communities (Wang et al, 2016; Raskin and Wang, 2017). Decision time, warning dissemination time, households’ preparation time, and evacuation travel time) and maximize survival rates during tsunamis, researchers and practitioners have developed evacuation simulations to support decision-making, public education, and community emergency planning and management

Previous ABMSs for Earthquake and Tsunami Evacuation
Other Models for Earthquake and Tsunami Evacuation
Research Objectives and Questions
Agent-based Modeling Environment
Study Area
Model Components
Social System and Agent Behavior
Built Environment
Natural environment
Results and Discussion
Evacuation Decision and Milling Time
Mode Choice and Walking Speed
Other Variables and Combinations of Variables
Scenario 2: considering network disruption when only walking is available
Conclusion
Full Text
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