Research On Resilience Type Of Urban Built Environment In Response To Rainstorm Waterlogging

Under the background of rapid urbanization,the contradiction between urban space and ecological environment intensifies.Various disasters represented by urban rainstorm and waterlogging occur frequently,which seriously threatens the safety and sustainable development of the city.The concept of urban resilience takes improving the integrity of urban system as the starting point,and has made some progress in disaster mechanism analysis,risk assessment and promotion methods.However,there is still a large development space in the perspective and methods of rainstorm and waterlogging resilience research.This paper selects the typical areas of Beijing-TianjinHebei region as the research object and uses Arc GIS spatial analysis technology and machine learning clustering algorithm to study the resilience type of typical regions,in order to provide reference for further theoretical research and practice.Firstly,the built environmental resilience unit to deal with rainstorm and waterlogging is defined,the multidisciplinary boundary conditions and data types of rainstorm and waterlogging are obtained through literature research,and the administrative division,watershed / drainage division,river system and road boundary are selected and determined as the boundary conditions of resilience unit,and the boundary is proved to be effective by SWMM simulation.Through the empirical study of typical regions,the spatial superposition of multi boundary conditions is completed,and a multi-level resilience unit system at the regional,urban,district and block level is built.On this basis,the resilience type pedigree of dealing with rainstorm and waterlogging was studied.Through literature research,the macro,medium and micro rainstorm and waterlogging resilience evaluation factors based on resilience attributes are proposed.And the cluster analysis of regional resilience units in three typical cities of Beijing,Tianjin and Shijiazhuang was completed by using Py Charm software,forming 3 resilience categories based on resilience attributes: advantage cluster,combination cluster and disadvantage cluster,as well as 16 resilience subcategories such as High Robustness – High Redundancy-High Resourcefulness-High Rapidity(HB-HD-HS-HP).Secondly,the research on the resilience grade zoning of dealing with rainstorm and waterlogging is carried out,the resilience evaluation system of dealing with rainstorm and waterlogging is constructed by using the factor analysis method of SPSS tool,and the typical regional resilience units are divided into grades of 1-9.Finally,the resilience type pedigree is combined with the resilience grade zoning results to form a typical regional resilience spatial pattern of Beijing,Tianjin and Hebei based on 9 grades and 16 categories.The characteristics of the current resilience spatial pattern are analyzed and summarized:(1)the resilience pattern differentiation between cities is obvious;(2)The spatial heterogeneity of resilience pattern is strong,showing the characteristics of agglomeration;(3)Insufficient balance between resilience system attributes.On this basis,this paper puts forward the promotion focus and timing of different types of resilience units,that is,first promote the inferior low-level units,focus on the inferior units with single attribute,give play to the role of superior high-level units,and build the urban resilience interactive network.In terms of research perspective,this paper overlaps the unit delimitation conditions of a single discipline,completes the superposition of multi-disciplinary research boundary conditions to deal with rainstorm and waterlogging,and forms a multi-level research unit delimitation method in the field of resilience;In terms of research methods,this paper introduces the machine learning clustering algorithm into the classification of resilience units,expands the current classification and evaluation research for a limited number of units,and completes the double restrictions of horizontal classification and vertical classification of all resilience units in the research area,so as to provide reference for further practice and improvement.