The Layout Optimization of low-impact Development Facilities is Based on a Multi-Objective Genetic Algorithm and the SWMM Model The Layout Optimization of low-impact Development Facilities is Based on a Multi-Objective Genetic Algorithm and the SWMM Model

The intensifying impermeability caused by urbanization has led to frequent global flood disasters. In order to mitigate the impact, low-impact development (LID) technology is employed to maintain urban underlays closer to their pre-development state through distributed rainwater control. However, th...

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Vydané v:Water resources management Ročník 39; číslo 7; s. 2993 - 3014
Hlavní autori: Wang, Xiaoyue, Sun, Wenzhuo, Lan, Yumeng, Ge, Xiaoyu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 01.05.2025
Springer Nature B.V
Predmet:
Algorithms
Atmospheric Sciences
Cities
Civil Engineering
Disasters
Earth and Environmental Science
Earth Sciences
Empirical analysis
Environment
Facilities management
Genetic algorithms
Geotechnical Engineering & Applied Earth Sciences
Green infrastructure
Hydrogeology
Hydrologic models
Hydrology
Hydrology/Water Resources
Layouts
Multiple objective analysis
Optimization
Pareto optimization
Pareto optimum
Permeability
Rain
Rain water
Rainfall
Runoff
Social factors
Sorting algorithms
Urbanization
Sponge city
NSGA-II
SWMM
Low Impact Development Facilities
Multi-objective Optimization
ISSN:0920-4741, 1573-1650
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Shrnutí:The intensifying impermeability caused by urbanization has led to frequent global flood disasters. In order to mitigate the impact, low-impact development (LID) technology is employed to maintain urban underlays closer to their pre-development state through distributed rainwater control. However, the layout of LID often requires consideration of multiple factors. Against this backdrop, this paper introduces a scenario simulation approach utilizing hydrological models in conjunction with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimize the types and scales of LID facilities. .Regarding the trade-offs between multiple objectives and facility configurations, the NSGA-II algorithm effectively handles multi-objective optimization problems by automatically balancing conflicts among objectives, thereby avoiding the subjectivity and limitations of manual layout schemes. Aiming to maximize runoff control capacity, minimize lifecycle costs, and achieve the greatest comprehensive benefits, we explore optimal layout strategies for LID facilities An empirical analysis was conducted on the green space of Binhu East Road in Qian’an City, Hebei Province, China, with evaluations performed within the Pareto optimal solution set (a set of solutions that perform well across multiple objectives).The contributions of LID facilities to optimal scenarios in terms of runoff control capacity, lifecycle costs, and comprehensive benefits were quantified. The results indicate that under different rainfall recurrence intervals, the model is able to identify optimal solution sets across varying preference levels for each objective, enabling decision-makers to select suitable layout schemes based on their preferences. This study translates complex multi-objective problems into specific practices of LID facility layout optimization, focusing on runoff control and cost optimization while integrating multi-dimensional benefit assessments encompassing environmental, environmental, and social aspects. Through the coupling of hydrological models and algorithms, it achieves automatic optimization and evaluation of LID facility layout schemes, providing scientific basis and diverse options for the construction of sponge cities.
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-024-04032-2