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基于主体建模的城市暴雨洪涝灾害预警策略仿真研究

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灾害预警通过提前发布灾害信息,引导居民及时采取避灾行动,从而有效降低灾害损失和伤亡,在减灾管理中发挥重要作用.面对自然与社会耦合下的复杂洪涝灾害系统,如何考虑居民的预警响应行为,评估不同洪涝灾害预警策略有效性是当前亟待解决的问题.本文提出了基于主体建模的城市暴雨洪涝灾害预警策略仿真方法,设定基于降雨预报、基于洪涝淹没、基于人群暴露性的3种预警策略,并以深圳市福田区为例,分析不同预警策略下城市洪涝灾害风险的变化.结果表明:①考虑洪涝灾害风险感知与个体出行决策概率的城市暴雨洪涝灾害预警策略ABM仿真模型,能够准确模拟不同洪涝灾害预警策略下居民出行响应行为及洪涝灾害风险的变化,科学、全面评估城市洪涝灾害预警策略的有效性;②不同洪涝灾害预警策略下人群出行响应行为差异显著,导致城市暴雨洪涝灾害风险降低效果不同.面对20 a一遇的降雨情景,基于洪涝淹没和人群暴露性预警能够帮助研究区居民快速识别高危险区,从而显著降低建筑物和道路的风险;③不同暴雨情景下不同洪涝灾害预警策略效果不同.面对较小的降雨情景,基于洪涝淹没和基于人群暴露性的精细化预警策略下城市洪涝灾害风险降低效果更好;而面对极端暴雨情景,采用基于降雨预报的统一预警策略效果优于精细化预警策略.
Agent-based Modelling of Urban Rainstorm Flood Disaster Early Warning Strategy Simulation
Disaster early warning plays an important role in disaster reduction management by proactively dissem-inating disaster information to guide residents in taking timely evacuation actions,thus effectively reducing disas-ter losses and casualties.The dynamic response process of residents to disaster early warning information and the assessment of the effectiveness of different flood disaster early warning strategies are pressing issues.This paper proposes a simulation method for urban rainstorm flood disaster early warning strategies based on Agent-Based Modeling(ABM).Firstly,three warning strategies are established:rainfall forecast-based,flood inundation-based,and population exposure-based.Secondly,individual risk perception is assessed by considering a variety of socio-demographic characteristics,and a probabilistic model of individual travel decision-making is constructed.Based on this,an agent-based model for urban flood disaster early warning strategies is developed.Finally,taking Futian District in Shenzhen,China as a case study,residents'travel behavior and flood risk are simulated and analyzed with different flood warning strategies under 20-year,50-year,and 100-year return period rainstorm scenarios.The results show that:(1)The ABM simulation model,considering residents'perception of flood disaster risk and the probability of individual travel decision-making,accurately simulates residents'travel response behavior and changes in flood disaster risk under different warning strategies.It provides a scientific and comprehensive evalua-tion of the effectiveness of urban flood disaster early warning strategies;(2)Different warning strategies lead to significant differences in population travel response behavior,resulting in varying effectiveness in reducing urban rainstorm flood disaster risk.Faced with a 20-year rainfall scenario,flood inundation-based and population expo-sure-based early warning strategies help residents in the study area quickly identify high-risk areas,significantly reducing the risk to buildings and roads.Faced with a 20-year return period rainstorm scenario,the study area shows minimal changes in residents'travel behavior under rainfall forecast-based warnings.However,flood inun-dation-based,and population exposure-based warning strategies help residents rapidly identify high-risk areas,significantly reducing the number of people heading to red and orange warning zones.This results in a notice-able decrease in risks to buildings and roads;(3)Under different rainstorm scenarios,the effectiveness of various flood disaster early warning strategies varies.In the face of smaller rainstorm scenarios,refined flood disaster early warning strategies,such as flood inundation-based,and population exposure-based,demonstrate effective-ness in reducing urban flood disaster risk.However,when dealing with extreme rainstorm scenarios,adopting a unified flood disaster early warning strategy,such as rainfall forecast-based,is more effective than a refined warning strategy.Therefore,urban flood disaster early warning systems should be tailored to local conditions and varying circumstances,establishing a graded,zonal,and scenario-based warning system.

urban rainstorm flooddisaster early warning strategysimulationAgent-Based Model(ABM)di-saster riskrisk perceptionindividual travel decision-makingShenzhen

黄晶、蔡思琴、庞甜甜、王慧敏

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河海大学商学院,南京 211100

水灾害防御全国重点实验室,南京 210098

城市暴雨洪涝 灾害预警策略 仿真 主体建模 灾害风险 风险感知 行为决策 深圳市

国家自然科学基金国家自然科学基金国家自然科学基金

421710814237109272174054

2024

地球信息科学学报
中国科学院地理科学与资源研究所

地球信息科学学报

CSTPCD北大核心
影响因子:1.004
ISSN:1560-8999
年,卷(期):2024.26(5)
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