Urban large-scale evacuation zoning planning methods for flooding disasters

doi:10.16511/j.cnki.qhdxxb.2024.26.014

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Journal of Tsinghua University(Science and Technology) ›› 2024, Vol. 64 ›› Issue (11) : 1880-1892. DOI: 10.16511/j.cnki.qhdxxb.2024.26.014

SPECIAL SECTION: PUBLIC SAFETY SCIENCE AND TECHNOLOGY

Urban large-scale evacuation zoning planning methods for flooding disasters

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Abstract

[Objective] Safe and effective evacuation of individuals during extreme weather conditions is critical in evacuation planning. Compared with traditional personnel evacuation and emergency transportation studies, evacuation zone planning is in its early stages. It lacks comprehensive consideration of major urban disaster scenarios, particularly beyond hurricanes. Additionally, there is no unified system for defining problems or measuring urban population hotspots, spatiotemporal disaster impacts, and exit distribution in evacuation planning. To address the practical issues of evacuating affected individuals during heavy rain and flood disasters, this paper proposes a model for delineating evacuation zones. [Methods] Starting with establishing evacuation needs and quantifying the impact of disasters on road segments, this study considers urban population distribution hotspots and the characteristics of heavy rain and flood disasters. Through modeling analysis, geographic information system (GIS) visualization, and other methods, a model is developed for the integrated delineation of evacuation zones and the allocation of evacuees at exits. The main components include the following: (1) To identify hotspot areas in urban functional zones and establish evacuation needs based on the city’s road network. (2) To assess the risk of heavy rain and flood disasters, establish a risk indicator system for flood risk assessment (including causative factors, disaster-prone environments, disaster-prone bodies, and disaster prevention and mitigation capabilities), and develop a road damage model to determine road network damage. (3) To construct a two-tier planning optimization model to determine evacuation paths and exit allocations. (4) To use Wuhan’s Wuchang district as an example, the effectiveness of the proposed method for large-scale urban evacuation zone planning under flood disasters is validated. The upper-level model provides the proportion of evacuees that each evacuation point should accommodate, with these allocation ratios stored in chromosomes as input for the lower level. The lower-level problem uses the incoming allocation ratios to calculate the evacuation flow for each OD pair and evaluates the fitness of the upper-level chromosomes. This is achieved using the Frank-Wolfe algorithm. The two-tier framework allows for detailed treatment of complex evacuation planning problems, ensuring the global minimization of total evacuation time and individual minimization of evacuee travel time. [Results] The innovative aspects included identifying evacuation needs in urban hotspots and constructing road damage levels under risk zoning for heavy rain and flood disasters. The two-tier planning optimization model minimized overall evacuation time and individual travel time, making the evacuation plan more realistic and reasonable. [Conclusions] The proposed method for large-scale urban evacuation zone planning is feasible, risk assessment is essential in actual evacuation planning. Significant differences exist in day and night population distribution with daytime populations primarily concentrated in commercial and work areas and nighttime populations concentrated in residential areas. Emergency management departments should develop varied evacuation plans for different periods. Due to potential road damage during disasters, preplan alternative evacuation routes and make real-time dynamic adjustments during evacuations.

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evacuation zone planning / two-tier planning and optimization model / urban hotspots / disaster risk

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LÜ Wei, JIANG Huihua, WANG Jinghui, YANG Xiaoting. Urban large-scale evacuation zoning planning methods for flooding disasters[J]. Journal of Tsinghua University(Science and Technology). 2024, 64(11): 1880-1892 https://doi.org/10.16511/j.cnki.qhdxxb.2024.26.014

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