Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas

Flooding caused by extreme climate change is becoming increasingly severe, especially in high-density coastal areas worldwide. Although many studies have conducted risk assessments of urban floods, most have not formed a comprehensive evacuation plan considering population distribution and flood dis...

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Main Authors: Xinyue Gu, Yan Mao, Xintao Liu
Format: Article
Language:English
Published: Taylor & Francis Group 2025-01-01
Series:Annals of GIS
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Online Access:https://www.tandfonline.com/doi/10.1080/19475683.2025.2451236
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author Xinyue Gu
Yan Mao
Xintao Liu
author_facet Xinyue Gu
Yan Mao
Xintao Liu
author_sort Xinyue Gu
collection DOAJ
description Flooding caused by extreme climate change is becoming increasingly severe, especially in high-density coastal areas worldwide. Although many studies have conducted risk assessments of urban floods, most have not formed a comprehensive evacuation plan considering population distribution and flood disaster risk. To further enhance urban flood planning and emergency management for coastal areas, this study uses Victoria Harbor in Hong Kong, a typical flood-prone region, as a research area. The study first conducts a flood exposure risk assessment and classifies different regions according to flood risk levels. Then, by combining evacuation ability with the changing flood disaster and road evacuation flows, a novel bi-level optimization model is proposed to allocate zones for the citizens day and night. With the upper level using a genetic algorithm to minimize the total system evacuation time and the lower level applying a user equilibrium model for evacuee allocation, this model forms an evacuation that considers the distribution of population hotspots and the impact of flood risks on the road network. The findings of the study show that functional urban areas with high pedestrian flow, tourist spots, commercial centres, and schools are exposed to higher flood risk. Besides, the evacuation simulation of the bi-level optimization model proposed in this study matches the zoning results of actual urban activities and can effectively achieve the goal of evacuating 480,000 people within 12–18 minutes. This study innovatively proposes an effective evacuation plan that can reference the government’s emergency evacuation planning work.
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spelling doaj-art-cc763abcb4094ea5a93f634e2809f7ce2025-08-20T03:12:54ZengTaylor & Francis GroupAnnals of GIS1947-56831947-56912025-01-01311152710.1080/19475683.2025.2451236Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areasXinyue Gu0Yan Mao1Xintao Liu2Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaInstitute for Public Policy, Zhejiang University, Hangzhou, ChinaDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaFlooding caused by extreme climate change is becoming increasingly severe, especially in high-density coastal areas worldwide. Although many studies have conducted risk assessments of urban floods, most have not formed a comprehensive evacuation plan considering population distribution and flood disaster risk. To further enhance urban flood planning and emergency management for coastal areas, this study uses Victoria Harbor in Hong Kong, a typical flood-prone region, as a research area. The study first conducts a flood exposure risk assessment and classifies different regions according to flood risk levels. Then, by combining evacuation ability with the changing flood disaster and road evacuation flows, a novel bi-level optimization model is proposed to allocate zones for the citizens day and night. With the upper level using a genetic algorithm to minimize the total system evacuation time and the lower level applying a user equilibrium model for evacuee allocation, this model forms an evacuation that considers the distribution of population hotspots and the impact of flood risks on the road network. The findings of the study show that functional urban areas with high pedestrian flow, tourist spots, commercial centres, and schools are exposed to higher flood risk. Besides, the evacuation simulation of the bi-level optimization model proposed in this study matches the zoning results of actual urban activities and can effectively achieve the goal of evacuating 480,000 people within 12–18 minutes. This study innovatively proposes an effective evacuation plan that can reference the government’s emergency evacuation planning work.https://www.tandfonline.com/doi/10.1080/19475683.2025.2451236Urban floodingInVEST modelBi-level programmingdisaster evacuation strategieshazard management
spellingShingle Xinyue Gu
Yan Mao
Xintao Liu
Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
Annals of GIS
Urban flooding
InVEST model
Bi-level programming
disaster evacuation strategies
hazard management
title Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
title_full Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
title_fullStr Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
title_full_unstemmed Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
title_short Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas
title_sort urban flood risk assessment and evacuation planning a bi level optimization model for sustainable high density coastal areas
topic Urban flooding
InVEST model
Bi-level programming
disaster evacuation strategies
hazard management
url https://www.tandfonline.com/doi/10.1080/19475683.2025.2451236
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AT yanmao urbanfloodriskassessmentandevacuationplanningabileveloptimizationmodelforsustainablehighdensitycoastalareas
AT xintaoliu urbanfloodriskassessmentandevacuationplanningabileveloptimizationmodelforsustainablehighdensitycoastalareas