Journal article
Optimal Simulation for Refuge Space in Earthquake-Prone Areas Orienting Population Structure Change
Natural hazards review, v 26(4), 04025043
01 Nov 2025
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Abstract
AbstractEvacuation simulations in disaster-prone areas have been extensively studied and applied in regional disaster protection, emergency evacuation, and urban and rural planning and management. By simulating the evacuation process and optimizing the layout of evacuation spaces, it is possible to enhance evacuation efficiency and minimize disaster losses. However, the changing population structure, characterized by increased life expectancy and declining birth rates, has exacerbated the issue of population aging, presenting challenges for the planning and management of evacuation spaces in disaster-prone areas. In this paper, we propose a novel optimization strategy for evacuation spaces in disaster-prone regions, specifically addressing the influence of population aging. We introduce a population prediction strategy to forecast changes in population structure and spatial distribution. Subsequently, we employ AnyLogic simulation software to simulate pedestrian evacuation and utilize ArcGIS for the optimization of the evacuation space system. Taking the town of Aba, a disaster-prone and densely populated area located in western Sichuan, China, as a case study, we initially simulate the original evacuation space system before proceeding with its optimization. The research demonstrates that our proposed approach can effectively enhance evacuation space planning in the area, potentially leading to significant positive impacts in reducing disaster losses and improving evacuation efficiency.
Practical ApplicationsThis study proposes a data-driven approach to optimize evacuation spatial systems in small towns, enhancing resident safety during earthquakes. By integrating demographic trend analysis with spatial planning standards, we develop a method to assess evacuation system effectiveness and validate it using computer simulation and geographic information technology. We employ a population projection model to analyze future demographic shifts and incorporate building vector data and land use information to simulate population distribution. Using ArcGIS, we map evacuation routes and shelter locations, then construct a spatial evacuation model in AnyLogic to evaluate evacuation time, shelter capacity, and congestion. Unlike traditional planning methods, this approach precisely identifies system weaknesses and proposes targeted optimization strategies for shelter layout and evacuation routes. A case study in Aba Town reveals a projected elderly population increase to 35.56% within two decades, placing greater demands on the evacuation system. Simulation results highlight issues in shelter distribution and evacuation path design, while optimization measures significantly enhance efficiency, reduce congestion, and improve shelter capacity. This study underscores the need for adaptive evacuation planning amid demographic changes and offers insights for similar small towns in China.
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Details
- Title
- Optimal Simulation for Refuge Space in Earthquake-Prone Areas Orienting Population Structure Change
- Creators
- Haijin Zhang - Sichuan Agricultural UniversityFengchao Guo - Sichuan Agricultural UniversityYunxia Lai - Sichuan Agricultural UniversityYiru Wang - University of Hong KongLu Gan - Sichuan Agricultural UniversityBenjamin Lev - Drexel University
- Publication Details
- Natural hazards review, v 26(4), 04025043
- Publisher
- American Society of Civil Engineers
- Number of pages
- 17
- Grant note
- National Natural Science Foundation of China: 72104165 Foundation of Sichuan Province Cyclic Economy Research Center: XHJJ-2105 Sichuan Philosophy and Social Science Foundation: SCJJ23ND206 Sichuan Old Revolutionary Base Area Development Research Center: SLQ2023SB-07 National Student Innovation and Entrepreneurship Training Program Project: 202410626018
We would like to acknowledge the financial support from the National Natural Science Foundation of China (Grant No. 72104165), the Foundation of Sichuan Province Cyclic Economy Research Center (Grant No. XHJJ-2105), the Sichuan Philosophy and Social Science Foundation (No. SCJJ23ND206), the Sichuan Old Revolutionary Base Area Development Research Center (No. SLQ2023SB-07), and the National Student Innovation and Entrepreneurship Training Program Project (Grant No. 202410626018), which were instrumental in conducting this research.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001575394000014
- Scopus ID
- 2-s2.0-105011278903
- Other Identifier
- 991022065042304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Civil
- Environmental Studies
- Geosciences, Multidisciplinary
- Meteorology & Atmospheric Sciences
- Water Resources