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Updated: Jul 11, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Design and spatial pattern optimization for a sponge city using factor analysis and geographical statistics to
Yingwei Yuan1, Qian Zhang2, Sheming Chen3
1College of Water Conservancy Engineering, Tianjin Agricultural University, Tianjin 300384, China
Abstract:
The sponge city is a new concept of stormwater management for ecological city construction, which aims to restore water-cycle processes and reduce runoff. Cities in coastal districts are suffering from serious instability due to high population density, urbanization, and land-use changes. However, previous research contains few evaluations of balancing urban ecological indicators of sponge city performance, including geographical, environmental, economic, and social factors, and their effect on resilience at a macro level to develop low-impact development schemes. In this study, we developed an integrated framework using factor analysis, geographical statistics, multi-objective analysis, and remote sensing methods to extract the factors influencing sponge city resilience and to establish spatial pattern schemes. The results indicated that the urbanization degree and plant adaptability had the greatest impact on sponge city performance, with weights of 45 and 27%, respectively. Sponge city spatial pattern schemes performed the best in the combination scenario of 14.8-46.8% green roofs (by area ratio) supported by grooves and rain barrels +10% herbaceous basins divided into units by ecological tree pools +10% permeable pavements and sidewalks. This scenario balanced facilities and cost to optimize the spatial pattern, which improved sponge city adaptability and urban ecological conditions.
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