PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 22, 2026Water0 citationsOpen Access

Optimization of Low-Impact Development Spatial Layout Under Multi-Objective Constraints for Sponge City Retrofitting in Older Communities

View Full Paper
WZWenjie ZhangDWDian WuLKLingzhong Kong

Key Points

  • To optimize the spatial layout of Low-Impact Development practices for retrofitting Sponge Cities in older communities.
  • Coupled NSGA-II with SWMM to create a Pareto front for optimal solutions
  • Used Analytic Hierarchy Process to select optimal LID facility placements
  • Refined configuration through iterations of exhaustive search with Euclidean distance analysis
  • Euclidean distance decreased from 5 to 3 to 1 after LID retrofitting in Scenario 3
  • Optimal locations for LID facilities became progressively clearer
  • LID measures effectively managed stormwater and pollution

Abstract

Old urban areas are often prone to waterlogging and sewage contamination owing to their haphazard spatial arrangements, extensive impervious surfaces, and insufficient drainage infrastructure, thereby posing significant risks to both public safety and aquatic ecosystems. Sponge City retrofitting offers a viable solution. Currently, the study area is facing issues of waterlogging and pollution caused by rainfall. Conventional modeling approaches for optimizing the spatial allocation of Low-Impact Development (LID) practices typically quantify only the overall retrofit proportion. However, these methods fail to specify the optimal placement of individual facilities to balance hydrological benefits against construction costs. To bridge this gap between theoretical optimization and practical implementation, this study proposes an iterative approximation framework. First, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) was coupled with the Storm Water Management Model (SWMM) to generate a Pareto front, from which optimal solutions were selected using the Analytic Hierarchy Process (AHP). The configuration was further refined through multiple iterations of “exhaustive search combined with Euclidean distance” analysis to determine the optimal types and locations of LID facilities. The results show that: In Scenario 3, the Euclidean distance after LID retrofitting achieved a narrowing gap from 5 to 3 to 1. This indicates that the proposed progressive approximation solving process can be directly applied to specific retrofit targets, providing concrete construction guidance for LID retrofitting in older communities’ areas. Conclusions showed that (1) the specific locations for implementing LID facilities within sub-catchments become progressively clearer, ultimately defining precise retrofitting sites. (2) The proposed progressive approximation approach effectively and systematically reduces this disparity. (3) Retrofitted LID measures effectively managed stormwater and controlled pollution.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/699a9d3c482488d673cd3098https://doi.org/10.3390/w18040513
Ask AI
Helpful
Bookmark
Share
View Full Paper