市政技术2026，Vol.44Issue(8)：183-188,242,7.DOI:10.19922/j.1009-7767.2026.08.183
基于SSA-PP模型的城市洪涝韧性评价方法研究
Urban Flood Resilience Assessment Based on SSA-PP Model
摘要
Abstract
Under the background of frequent extreme rainfall events and continuous urbanization,scientific evalua-tion of urban flood resilience is of significant engineering importance for improving drainage and flood prevention systems and enhancing urban operational safety.Addressing problems such as high dimensionality,significant non-linearity among indicators,and strong subjectivity in weighting methods in urban flood resilience assessment,an evaluation indicator system was constructed based on 3 aspects of defense and resistance,response and coping and adaptation and recovery.Furthermore,a urban flood resilience assessment model is proposed using the projection pursuit(PP)optimized by the sparrow search algorithm(SSA).Taking 12 districts and counties of Baoji City as an example,the urban flood resilience levels and their spatiotemporal evolution characteristics from 2018 to 2022 were quantitatively evaluated.The results indicate that the overall flood resilience of Baoji City exhibited a fluctuating upward trend during the study period;However,there are significant disparities among districts and counties.Spa-tially,the distribution pattern was characterized by higher resilience in central urban areas and lower resilience in peripheral districts and counties;Some districts and counties still exhibit prominent weaknesses in defense/resis-tance and post-disaster recovery capabilities.The findings provide a scientific basis for decision-making regarding drainage and flood control facility construction,the refinement of emergency management systems,and the opti-mization of municipal engineering layouts in medium-sized cities.关键词
洪涝/韧性/投影寻踪模型/麻雀搜索算法Key words
flood/resilience/projection pursuit(PP)model/sparrow search algorithm(SSA)分类
建筑与水利引用本文复制引用
赵平,马万腾,张宁宁,卢椿锦..基于SSA-PP模型的城市洪涝韧性评价方法研究[J].市政技术,2026,44(8):183-188,242,7.基金项目
宁夏重点研发计划项目(2025BEE02011) （2025BEE02011）
