Computer software is an effective tool for simulating urban rainfall–runoff. In hydrological analyses, the storm water management model (SWMM) widely used throughout world. However, this ineffective parameter calibration and verification owing to complexity associated with monitoring data onsite. present study, general regression neural network (GRNN) predict parameters of catchment directly, w...

The intention of this paper is to evaluate the sensitivity of the Storm Water Management Model (SWMM) output to its input parameters. A global parameter sensitivity analysis is conducted in order to determine which parameters mostly affect the model simulation results. Two different methods of sensitivity analysis are applied in this study. The first one is the partial rank correlation coeffici...

Multi-objective optimization linked with an urban stormwater model is used in this study to identify cost-effective low impact development (LID) implementation designs for small urbanizing watersheds. The epsilon-Non-Dominated Sorting Genetic Algorithm II (ε-NSGAII) has been coupled with the US Environmental Protection Agency’s Stormwater Management Model (SWMM) to balance the costs and the hyd...

This article presents the elements involved in the design of a bioretention planter/trench infiltration-detention system as part of a very large-scale urban retrofit project. The prototype system was designed to intercept all of the runoff from a synthetic 5.08-mm 24-h rainfall event. Diverted flows were conveyed into bioretention planter for treatment. The bioretention systems were fingerprint...

The storm water management model (SWMM) has been used extensively to plan, implement, control, and evaluate low impact development facilities other drainage systems solve storm-related problems in sponge cities. However, the calibration of SWMM involves a variety sensitive parameters may bring significant uncertainties. Here we incorporated distributed time variant gain (DTVGM), with simple str...