Coupling a Distributed Time Variant Gain Model into a Storm Water Management Model to Simulate Runoffs in a Sponge City

Abstract

The storm water management model (SWMM) has been used extensively to plan, implement, control, and evaluate low impact development facilities and other drainage systems to solve storm-related problems in sponge cities. However, the calibration of SWMM involves a variety of sensitive parameters and may bring significant uncertainties. Here we incorporated the distributed time variant gain model (DTVGM), a model with a simple structure and few parameters, into the SWMM (called DTVGM-SWMM) to reduce the complexity but keep the mechanistic representation of the hydrological process. The DTVGM runoff module parameters were calibrated and validated using the Nash–Sutcliffe efficiency (NSE), based on measured data and the results of SWMM. It was then coupled with the SWMM routing module to estimate catchment runoffs and outflows. Finally, the performance was evaluated using NSE (0.57~0.94), relative errors of the flow depth (−7.59~19.79%), and peak flow rate (−33.68~54.37%) under different storm events. These implied that the DTVGM-SWMM simulations were generally consistent with those of the control group, but underperformed in simulating peak flows. Overall, the proposed framework could reasonably estimate the runoff, especially the outflow process in the urban catchment. This study provides a simple and reliable method for urban stormwater simulation.

Simulation and Comprehensive Evaluation of the Multidimensional Environmental Benefits of Sponge Cities

“…The rainfall events used for calibration were 0729, 0804, 0809 and 0823 and for validation were 0830, 0831, 0901 and 0926, taking into account the number of peaks in the rainfall events and the amount of rainfall. Both the calibration and validation NSE values were above 0.8 [66,67], and R 2 exceeded 0.9 [68], which indicates satisfactory simulation results. The simulation of the validation event 0831 was less effective than the other three rainfall events, presumably because the rate period did not include the type of short-duration heavy rainfall like 0831, so the parameter set obtained from the rate was not as effective as the other rainfall events for this type of rainfall simulation.…”

Simulation and Comprehensive Evaluation of the Multidimensional Environmental Benefits of Sponge Cities

“…The rainfall events used for calibration were 0729, 0804, 0809 and 0823 and for validation were 0830, 0831, 0901 and 0926, taking into account the number of peaks in the rainfall events and the amount of rainfall. Both the calibration and validation NSE values were above 0.8 [59,60], and R 2 exceeded 0.9 [61], which indicates satisfactory simulation results. The simulation of the validation event 0831 was less effective than the other three rainfall events, presumably because the rate period didn't include the type of short duration heavy rainfall like 0831, so the parameter set obtained from the rate was not as effective as the other rainfall events for this type of rainfall simulation.…”

Systematic Assessment on Waterlogging Control Facilities in Hefei City of Anhui Province in East China

“…The SWMM is primarily used for one-dimensional (1D) stormwater network simulations, and is not able to represent the hydrodynamics of 1D networks as well as two-dimensional (2D) surface water accumulation [27]. The accuracy of the SWMM model often depends on the completeness and precision of the underlying data [28]. However, such data are frequently hard to obtain, which results in low accuracy and weak visualization for urban waterlogging.…”