热带地理2026，Vol.46Issue(3)：471-482,12.DOI:10.13284/j.cnki.rddl.20250873
典型设计暴雨下深圳市内涝空间分异与承灾体风险评估
Spatial Differentiation of Urban Waterlogging and Risk Assessment of Exposed Elements in Shenzhen Under Typical Design Rainstorm Scenarios
摘要
Abstract
Global climate change and rapid urbanization have intensified the occurrence of extreme rainstorm events,and urban waterlogging has emerged as a critical disaster risk constraining the sustainable development of high-density cities,posing serious threats to life,property,and urban resilience.To characterize urban waterlogging risk in Shenzhen under different design rainstorm scenarios,this study constructed three representative scenarios with distinct return periods and rainfall characteristics—Zhengzhou"7·20",Shenzhen"9·07"and Shenzhen"8·05"—using the two-dimensional hydrodynamic model LISFLOOD-FP and conducted systematic waterlogging simulations and exposure risk assessments of urban systems.Model validation using 183 historical waterlogging points demonstrated high reliability:within 50-m buffers of these points,maximum simulated water depths generally exceeded 0.3 m(with extreme values exceeding 10 m),effectively reproducing the spatial distribution and severity of severe waterlogging.The results indicate that waterlogging in Shenzhen exhibits a distinct spatial pattern characterized as"deeper in the west,shallower in the east;deeper in urban cores,shallower in suburbs,"driven by the"higher southeast,lower northwest"topography,high impervious surface coverage in western districts,and uneven drainage system loading.Among the three scenarios,the"7·20"design scenario poses the highest risk due to its high rainfall intensity,pronounced peak discharge,and extended duration,with areas experiencing water depths>30 cm accounting for 26.55%of the study area.Specifically,more than 74,000 buildings and approximately 4.68 million people were exposed to water depth exceeding 1 m,and 46.76%of the total road network(8,966.25 km)was inundated.The"9·07"scenario is characterized by nocturnally concentrated short-duration heavy rainfall,resulting in localized water accumulation in low-lying areas such as Longgang.The"8·05"design scenario exhibits a multi-peak pattern with a pronounced surge and a mid-event rainfall lull that temporarily alleviates accumulation,producing an intermediate risk level relative to the other two scenarios.Critical infrastructure elements exhibit high sensitivity to water depth,with significant differences in risk response.Under the"7·20"design scenario,1,028 medical institutions,823 elderly and childcare facilities and 106 emergency shelters,were exposed to high risk,potentially compromising emergency medical services and vulnerable populations;more than eight hazardous chemical enterprises faced potential secondary disasters at water depths exceeding 0.5 m.Spatially,risk to critical infrastructure exhibits a pattern of"western concentration and eastern dispersion."High-risk clusters are concentrated in Luohu and Longhua(medical and elderly-care facilities),Bao'an(moderate risk),and Nanshan,Luohu,and Guangming(hazardous chemical enterprises).Eastern districts exhibit generally low risk,with localized high-risk pockets confined to elderly-care facilities in Dapeng and Yantian.Futian District demonstrates the strongest protective performance,likely attributable to higher construction standards and more scientifically informed site selection.This study advances the literature by constructing cross-regional and locally representative design rainstorm scenarios and elucidating the coupling mechanism between rainfall characteristics and waterlogging risk in high-density urban environments.The findings provide a scientific basis for hierarchical disaster prevention planning and offer a transferable framework for waterlogging risk management in similar high-density cities nationwide.关键词
典型设计暴雨/内涝模拟/风险评估/LISFLOOD-FP模型/深圳市Key words
design rainstorm scenarios/urban waterlogging/risk assessment/LISFLOOD-FP/Shenzhen分类
建筑与水利引用本文复制引用
靳超,王园园,李晨溪,李娟..典型设计暴雨下深圳市内涝空间分异与承灾体风险评估[J].热带地理,2026,46(3):471-482,12.基金项目
广东省基础与应用基础研究基金(2022A1515110049) （2022A1515110049）
