Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas - Xinyue Gu; Yan Mao; Xintao Liu (Annals of GIS)
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.