Optimum Combination of Volume and Outlet Capacity of a Detention Pond using Particle Swarm Optimization and Analytical-Probabilistic Model

Detention ponds are best management practices designed for the control of urban stormwater and their design objectives are mainly controlling the quantity and quality of urban stormwater at the minimum cost. In this research, long term hourly rainfall data of Kerman and Mehrabad synoptic stations were analyzed and the three rainfall characteristics (rainfall duration, rainfall volume and inter event time duration) were obtained. Analytical probabilistic models (APM) were employed and the model parameters were derived from the closest stations to the study areas. The APM parameters, along with the catchment parameters, were used to develop the optimal combination of the pond volume and outlet capacity. Also, the PSO model led to lower computational   costs in comparison with the APM model. Comparison of the PSO with APM showed that the PSO results were more accurate than the results of APM and there was no need for determination capacity in the forementional model as it did not need outlet size. The PSO model was also found to be more computationally implemented more cheaper and faster.