Optimal detention ponds in urban drainage systems

Abstract

<p>Urban development and the increase of impervious surfaces have a broad impact on the hydrological cycle leading to increased peak flow and flooding, especially in downstream areas. Surface water detention ponds are among the most common measures to attenuate the peak flow and return it from development to pre-development conditions. The effect of these ponds on reducing a flood depends on the location and the dimensions. This paper presents a new framework for identifying the best strategies for using the detention ponds to flood control in urban drainage systems. The stormwater management model (SWMM) was applied for hydraulic and hydrological simulations of urban drainage systems. In addition, a multi-objective optimisation model was used to find the optimal location and size of detention ponds. The effect of physiographic and social factors on selecting ponds was analysed by simulating and examining the GIS environment. Based on the criteria reviewed in the previous steps, the best management solutions were prioritised by a multi-criteria decision-making method (MCDM) named Compromise Programming (CP). The methodology was then demonstrated on the real-world case study of the Karaj city basin in Iran. The results show that these detention ponds can improve current drainage performance and decrease flooding damage.</p>

A new multi‐criteria framework to identify optimal detention ponds in urban drainage systems

“…Optimal detention basins in urban stormwater management can be found using optimisation models developed in recent years (Zhao et al, 2021). The common objectives used in similar studies in the recent decade include minimisation of flood volume (Hosseinzadeh et al, 2022), maximisation of water quality of surface runoff (Li et al, 2019) and minimisation of the flood risk (Karami et al, 2022). Most of these models considered optimisation for some design parameters, such as site location, dimensions of detention ponds, and water quality control.…”