Urban flood resilience assessment using RAGA-PP and KL-TOPSIS model based on PSR framework: A case study of Jiangsu province, China

Abstract

The research on urban flood resilience will contribute to building a more resilient city and provide valuable reference for municipal decisionmakers. There are many frameworks and approaches for empirical studies on what constitutes urban flood resilience and how to evaluate it. In this study, a typical region suffering from flood disaster in China-Jiangsu Province was selected as the study area, including 13 prefecturelevel cities. The pressure-state-response (PSR) framework, the projection pursuit based on real-coded accelerated genetic algorithm (RAGAPP) and the technique for order preference by similarity to an ideal solution based on the Kullback-Leibler distance (KL-TOPSIS) were combined to develop a hybrid multi-criteria approach for assessing urban flood resilience. Then the grey relational analysis obtained the important factors. The results illustrate that (1) the development of each subsystem in the city is uncoordinated, that is, the pressure-subsystem has little influence on urban flood resilience, while the state-subsystem and the response-subsystem have great influence. (2) The urban flood resilience in Jiangsu Province presents obvious polarization trend, that is, Southern Jiangsu is more resilient than Northern Jiangsu. The underlying factors are closely related to the level of economic development. Furthermore, the proposed method provides a practical evaluation approach for other fields.