Construction And Application Of A Novel Assessment Model For Urban Flood Resilience

With the acceleration of urbanization,urban production factors are highly concentrated,and industrial chains and supply chains are becoming increasingly complex.As central cities become more interconnected,they become stronger and more vulnerable.The intertwining of various disaster risks has undoubtedly become a major factor limiting sustainable urban development.In addition,the increasing frequency of floods has greatly affected society and people’s lives and caused serious economic losses.The floods in China are among the most frequent in the world.Since the 1990s,the direct economic losses caused by floods in China have been almost 40 times greater than those in the United States.This creates an urgent need to improve the resilience of cities to flood risks.Thus,improving urban flood resilience has become a key issue in urban management.With cities under increasing pressure,it has become a global consensus to improve urban resilience to achieve sustainable urban development.Resilience concept provides a new set of ideas,tools and methods for exploring urban disaster resilience enhancement.It differs from previous disaster prevention and mitigation studies that focused on certain parts of the disaster process,but provides a perspective for understanding urban disaster response in a holistic manner.The concept of resilience was first mentioned in the 14th Five-Year Plan proposed in 2020 and the long-term goals for 2030.In the process of combing through past studies,it was found that few studies have selected urban flood assessment indicators from a resilience perspective,which implies the need for a new framework to quantify resilience assessment indicators.In addition,existing studies use the TOPSIS(Technique for Order Preference by Similarity to an Ideal Solution)assessment method for disaster assessment,which lacks the consideration of evaluation solutions located at the midpoint of positive and negative ideal solutions.There is also a need for good prediction models that can accurately predict the future resilience of cities so that measures can be taken in advance.To address these issues,this study establishes a novel assessment model for urban flood resilience,which consists of two parts:an assessment model and a prediction model.The specific works are as follows:(1)This paper adopts the TOSE(Technical,Organizational,Social and Economic)framework and selects nine indicators from four dimensions:technical,organizational,social and economic,as influencing factors for urban flood resilience assessment.These nine indicators are annual precipitation,total kilometers of roads,population density,old and young population,beds and medical technicians,education level,local fiscal revenue,GDP per capita,and per capita disposable income.(2)To make up for the shortcomings of TOPSIS,the VIKOR(VlseKriterijumska Optimizacija I Kompromisno Resenje)method is introduced in this paper to construct an urban flood resilience assessment model.In order to prevent the failure of full ranking when using VIKOR sorting,GRA(Grey Relational Analysis)method is introduced for auxiliary ranking so that all solutions can be fully ranked.In summary,this paper establishes a VIKOR-GRA based urban flood resilience assessment model.(3)In order to further improve the prediction accuracy of the neural network,this paper uses genetic algorithm(GA)to optimize the weights and thresholds of the BP(Back Propagation)neural network.Thus,an urban flood resilience prediction model based on GA-BP neural network is constructed.Finally,this paper validates and analyzes the novel assessment model for urban flood resilience,using 18 cities in Henan Province as examples.The results show that local fiscal revenue(L7)and total road kilometers(L2)have the largest weights among all the indicators.In terms of resilience assessment,Zhengzhou city and Luoyang city have the highest resilience level,while Puyang city and Xinyang city have the lowest resilience level.In terms of resilience prediction,by comparing the predicted ranking of the resilience of each city in Henan in 2020 with the actual ranking,it can be seen that the prediction model developed in this paper can effectively predict urban flood resilience.The evaluation and prediction results can suggest practical measures for cities to improve resilience.Through the analysis of actual cases,it can be seen that the model has good applicability and can better reflect the actual situation.Knowledge about the flood resilience assessment methodology is of particular value to policy makers,researchers and industry experts in assessing potential risks and recognizing the importance of flood prevention mechanisms.