Optimization Simulation Study of Urban Flood Drainage Rescue Unit Layout:A Case Study of Beijing Under a Century-Extreme Rainfall Scenario
The continuous and frequent urban flooding presents a formidable impediment to social and economic progress,imperiling community welfare. A critical aspect of urban flood emergency management involves enhancing the efficiency of drainage in rescue and relief operations. In this study,we combined diverse datasets encompassing the spatial distribution of urban rescue units,urban flooding occurrences,traffic dynamic flows,and traffic signal placements. We devised a multi-scenario simulation model for urban flood emergency response employing multi-agent based model guided by a "information integration-simulation modeling-emergency scenarios-efficiency comparison-optimization scheme". The model embedded Dijkstra algorithm to solve the optimal path for rescue and optimized the spatial layout of rescue points of rescue units with K-means algorithm. Through simulation experiments,we investigated the interaction between behavioral subjects and geographic environments,wherein rescue units navigate waterlogged areas,considering traffic constraints. The culmination of rescue and relief efforts is deemed achieved upon reducing water depth at all inundated points below the 15cm threshold. By formulating scenarios mirroring morning and evening peaks,diverse rescue levels,and rescue combination,we dissected the influence mechanisms of varied factors on rescue efficiency. Focused on the Liangshui River basin in Beijing,against the backdrop of a century-extreme rainfall event,our study scrutinized diverse emergency rescue scenarios,analyzed factors affecting rescue efficiency,and proffered optimization strategies for rescue unit layouts,to explore the path for the enhancement of rescue and relief efficiency. Our findings proposed optimized strategies for rescue unit deployment,advocating a spatial layout scheme emphasizing "global dispersion and local aggregation". Implementation of this scheme yielded substantial efficiency improvements by 18.27％,18.24％,and 10.34％during morning and evening peak scenarios,varying rescue levels,and different rescue compositions,respectively. In addition,the efficiency of rescue during off-peak hours was significantly higher than that during peak hours. Moreover,we underscored the pivotal role of rescue personnel efficiency in dictating overall rescue efficacy,observing nonlinear,and accelerated efficiency declines with diminishing rescue personnel levels. Depending on the road conditions,there was uncertainty in the rescue efficiency of both joint rescues and individual stationary teams. Hence,within the realm of practical rescue operations,it is imperative to adeptly tailor rescue strategies to the nuanced dynamics of each scenario,encompassing variables such as rainfall intensity,traffic congestion,resource availability,and other pertinent factors. These adaptive measures ensure a nimble response that optimally addresses the evolving exigencies of urban flooding emergencies. Notably,our model attained a commendable stability rate of 93.85％. This study offers strategic recommendations for enhancing emergency rescue efficiency and assuaging the societal ramifications of urban flood risk,as well as scientific insights for urban flood emergency management.
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