城市空间形态与基础设施对城市洪涝的作用机制:研究进展OA
Mechanisms of Urban Spatial Patterns and Infrastructure on Urban Flooding:Research Progress
文章系统梳理了城市空间形态与基础设施对城市洪涝的作用机制,指出不透水地表、建筑布局、地形起伏、街道网络、城市扩张模式、绿地分布及水体分布等因素通过改变地表径流路径、排水效率以及雨水调蓄能力等方式直接影响城市洪涝风险;文章分析了目前排水系统等灰色基础设施与雨水花园、河湖水系等蓝绿色基础设施的协同机理及定量化研究成果,发现排水系统等灰色基础设施在应对极端降雨事件时存在排水能力不足的局限性,强调了"灰-绿-蓝"协同体系在提升城市防洪韧性中的核心作用.三者结合可增强城市防洪排涝和雨洪调蓄能力.在技术方法层面,文章总结了物理机理模型、统计经验模型与机器学习模型等模拟手段,并梳理了从传统传感器到遥感、数字孪生等智能监测技术的发展脉络.最后,针对当前研究局限提出展望:应深化结构与设施深度耦合下的空间形态优化研究;探索变化环境下防洪排涝设计标准的动态调整与有效衔接;推进"灰-绿-蓝"设施体系的协同调度与效益量化;并依托多源大数据与数字孪生技术,实现城市洪涝应急处置的智慧化转型,推动城市洪涝管理迈向精细化与高韧性发展阶段.
With the intensification of global climate change and rapid urbanization,extreme rainfall events are occurring with increasing frequency,substantially altering the hydrological characteristics of urban surfaces and weakening their natural regulation and storage capacity.Consequently,the traditional urban flood management paradigm dominated by rapid drainage has become insufficient to cope with the growing complexity of urban flood risks.This study systematically investigates the mechanisms by which urban spatial patterns and infrastructure in urban flooding and points out that impervious surfaces,building layouts,topography,street networks,urban sprawl patterns,green space distribution,and water body distribution directly affect the risk of urban flooding by altering surface runoff paths,drainage efficiency,and rainwater storage capacity.By analyzing the synergistic mechanisms and quantitative research outcomes of gray infrastructure(e.g.,drainage systems)and green-blue infrastructure(e.g.,rain gardens and river-lake systems),this study reveals that the limitations of gray infrastructure in handling extreme rainfall events have driven the development of blue-green infrastructure.This forming a"grey-green-blue"collaborative system that enhances urban flood prevention,drainage,and stormwater storage capacity.Furthermore,this study systematically summarizes the research progress on urban flood simulation methods and monitoring technologies that account for urban spatial morphology and infrastructure impacts.The results indicate that physical mechanism models(e.g.,SWMM,MIKE URBAN,and TELEMAC-2D),statistical empirical models,and machine learning models(e.g.,CNN-LSTM coupled models)each possess distinct advantages in urban flood simulation.The integration of diverse monitoring technologies,including conventional sensors,remote sensing,GIS,social media data,the Internet of Things,and digital twin systems,is accelerating the transition of urban flood management toward intelligent and data-driven frameworks.In light of the current research gaps,this study suggests that future research should adopt multi-scale,multi-factor,and multi-objective perspectives to further advance the coordinated optimization of urban spatial morphology and infrastructure systems.Particular attention should be given to exploring the dynamic adjustment and effective integration of flood control and drainage design standards under changing environmental conditions,promoting the coordinated operation and benefit quantification of"gray-green-blue"infrastructure systems,and leveraging multi-source big data and digital twin technologies to enable intelligent urban flood emergency response,thereby facilitating a shift toward more refined and resilient urban flood management.This paper provides a systematic summary of flood simulation methods,monitoring techniques,and flood risk mitigation measures that consider the influence of urban spatial patterns and infrastructure,discusses the advantages and shortcomings of various aspects of flood risk prevention and control,and highlights that future research should focus on elucidating the coupling mechanisms between spatial patterns and infrastructure and promoting the intelligence,refinement,and integration of urban flood management.
田竞;赵玲玲;夏军
广东省科学院广州地理研究所,广州 510070广东省科学院广州地理研究所,广州 510070武汉大学 水资源工程与调度全国重点实验室,武汉 430072
建筑与水利
城市洪涝城市空间形态基础设施洪涝风险
urban floodingurban spatial patterninfrastructureflood risk
《热带地理》 2026 (3)
419-433,15
评论