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Evaluating the effect of low-impact development methods on urban runoff control using optimization algorithms
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Sedigheh Modarresi Tabatabaei  , Hamidreza Moradi * , Mehdi Vafakhah , Javad Vahidi |
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Abstract: (15 Views) |
Extended Abstract
Introduction
In recent decades, rapid urban growth, vegetation loss, and land use changes have led to increased runoff and urban flooding. Floods in cities disrupt daily life, challenge urban services, and damage infrastructure. Therefore, effectively managing the quantity and quality of runoff has become essential for reducing flooding and facilitating the reuse of water. This study aims to apply Low Impact Development (LID) methods and optimize their combinations using metaheuristic algorithms, including the non-dominated sorting genetic algorithm and gray wolf optimizer for flood control in an urban watershed in Tehran.
Methodology
The study area is located in District 7 and parts of District 1 in Region 5 of Tehran. This area is especially significant due to the densely populated residential and commercial centers, heavy rainfall events, insufficient channel capacity, and urban waste, which result in flooding and frequent problems in its drainage system. For the first time, this research utilized sixteen various combinations of 7 LID methods, including green roof, rain garden, rain barrel, infiltration trench, permeable pavement, bioretention system, and vegetative swale to control floods in the urban watershed. Hydraulic and hydrological modeling were conducted using the SWMM model, and the results were integrated and evaluated using NSGA-II and GWO in MATLAB. The innovative approach of this research simultaneously addresses runoff reduction, cost efficiency, and service performance sustainability. Introducing a desirable optimization algorithm, it proposed a suitable optimized combination for urban flood control in the study area.
Results
Considering the results of calibration and validation of SWMM, the accuracy and appropriate performance of the SWMM model in simulating flood volume were confirmed. The results of simulating total runoff and peak discharge without implementing LID methods showed that the drainage network of the study area is not suitable for rainfall with a 25-year return period, and the drainage network is unable to transfer the runoff completely. Modeling LID methods for 25-year, 6-hour rainfall, separately and in various combinations, indicated that the greatest effectiveness of LIDs on reducing runoff volume and discharge is associated with combinations of three or four methods. Comparing the answers provided by the optimization algorithms, the Pareto fronts generated by the GWO algorithm suggested suitable solutions for various values of all three objective functions, due to their better density and distribution. Therefore, the optimized combination proposed by the GWO algorithm, which included bioretention systems, green roofs, vegetative swales, and infiltration trenches, demonstrated the best performance by surpassing another method, and could reduce runoff volume by 60 to 70 percent and peak discharge by 70 percent in the study area. The cost of implementing the combination is approximately $900,000 to $1,200,000.
Discussion and Conclusion
The development of urban areas and the conversion of the natural regions into cities have led to an increase in impervious surfaces, runoff, and risk of flooding in these areas. LID methods have been proposed as an effective solution to mitigate these challenges and improve the performance of urban infrastructure. This study conducted multi-objective optimization of LID methods in an urban watershed using the SWMM model and the NSGA-II and GWO algorithms. Unlike previous studies that mainly emphasized single-objective optimization, this research simultaneously focused on minimizing runoff volume, minimizing cost, and the sustainability of methods’ performance. The findings showed that the combination of bioretention systems, green roofs, vegetative swales, and infiltration trenches is very effective in controlling runoff and flooding in the study area. The GWO algorithm is more efficient compared to NSGA-II, achieving a significant reduction of 60 to 70 percent in runoff volume at a reasonable cost. The proposed solutions of this research can play a crucial role in reducing water loss in arid and semi-arid regions, thereby facilitating the optimal utilization of water resources. Ultimately, the simulation-optimization approach serves as a reliable and effective tool for urban planning experts and flood control specialists to improve the quality and quantity of urban water by selecting the best combination of LID methods.
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Article number: 4 |
| Keywords: Flood Management, Gray Wolf Optimizer, Low impact development methods, Non-dominated sorting genetic algorithm II, Storm Water Management Model |
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Type of Study: Research |
Subject:
General
Received: 2025/11/12 | Revised: 2026/02/14 | Accepted: 2026/02/12 | Published: 2026/02/14 | ePublished: 2026/02/14
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Modarresi Tabatabaei S, Moradi H, Vafakhah M, Vahidi J. Evaluating the effect of low-impact development methods on urban runoff control using optimization algorithms. jwmseir 2025; 19 (71) : 4 URL: http://jwmsei.ir/article-1-1218-en.html
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