Work

Urban spatial layout optimization from the “Double E” perspective to mitigate urban flooding in the context of urban expansion

Year: 2025
Type: article
Abstract: Shenzhen, a coastal megacity in southern China, is characterized by limited land resources and frequent typhoon-induced rainstorms, both of which intensify urban flooding. Optimizing the area and location of construction land to reduce surface runoff has proven to be an effective measure for mitigating urban flooding. However, balancing the effectiveness and expense—the “Double E”—of such measures under urban expansion remains insufficiently explored. This study aims to develop an integrated optimization framework to address this gap by coupling the Soil Conservation Service Curve Number (SCS-CN) model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to simulate runoff and identify optimal land conversion strategies under territorial spatial planning constraints. The proposed framework contributes to improving urban resilience in the context of construction land expansion. The results show that 37.71 km² of cropland, 108.48 km² of woodland, and 3.81 km² of grassland, primarily in the city’s eastern regions, can be converted to construction land within the constraints of Shenzhen’s territorial spatial planning (construction land may increase by 150 km²). Compared to a randomly generated baseline solution, the optimized solution increases costs by only 1.8 % while reducing the additional runoff volume (∆RV) by 4.5 %–6.3 % across different rainfall return periods. Additionally, eight grid types were identified to guide decision-makers in addressing flood prevention, economic feasibility, and balanced development. • A spatial layout optimization framework for urban expansion is proposed. • It pursues the balance between effectiveness of flood mitigation and expense. • Imperviousness and rainfall impact the potential for optimizing urban flood control. • Urban expansion optimized solutions based on different needs are delivered.
Language: English
Open Access status: gold
Estimated APC paid: $2,600
OpenAlex ID: W4414477163
FWCI: 0.292
Cites: 63
Cited by: 1
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