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Wet detention ponds are the best management systems for the control of urban stormwater. The objective of this study is to develop optimum pollution control performance of wet detention ponds using an analytical probabilistic model (APM) and particle swarm optimization (PSO). An urban catchment, in a tropical region, was selected as a case study and APM parameters were developed using long-term rainfall data. Firstly, the active storage was kept constant while the permanent pool was varied and PSO simulations conducted. Secondly, PSO simulations were conducted, keeping the permanent pool constant and varying the active storage. The pollution control increased with increasing detention time, reached a peak value and thereafter declined. However, the pollution control was more sensitive to permanent pool than active storage as higher pollution control is attained at a shorter time using the former. The PSO captures the optimum detention time and the corresponding peak pollution control performance by five iterations and the computational time required for the PSO is much shorter than the APM which has to be exhaustively enumerated. The optimum detention time in tropical climates is found to be shorter than temperate regions and recommendations given in existing literature cannot be applied to tropical regions.

Optimization of pollution control performance of wet detention ponds in tropical urban catchments using particle swarm optimization