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Abstract
This study aims to calibrate and validate the EPA Storm Water Management Model from field measurements of rainfall and runoff, in order to simulate the rainfall-runoff process in an urban watershed of Tehran metropolis, Iran. During and after three significant storm events, the flow rates, total suspended solids (TSS), total phosphorus (TP), and total Kjeldahl nitrogen (TKN) concentrations were measured at the outlet of the catchment, and were used in the model calibration and validation process. The performance of the SWMM model was evaluated based on the statistical criteria, as well as graphical techniques. In this study, a local sensitivity analysis was carried out to identify the key model parameters, show that “the percentage of impervious surface in each subwatershed had the most effect on the model output”. Based on the analysis of the results, SWMM model calibration and validation can be judged as satisfactory, and the goodness-of-fit indices for simulating runoff quality and quantity are placed in acceptable ranges. The adjustment obtained for the variations in the measured and simulated flow rates, pollutograph concentrations, total pollutant load, peak concentration, and the event mean concentration (EMC) confirms the considerable predictive capability of the SWMM model when it is well calibrated by using field measurements.
Highlights
Urbanization contributes to the development level of a country [1]
As the percent of impervious area and the average surface slope were varied within −50% to +50% ranges, the percentage rate of changes in peak flow were from −22.43% to 21.50% and −0.084% to 0.017%, respectively
The results showed that for the hydraulic validation, the values of Nash–Sutcliffe efficiency coefficient (NSC), R2, RMSE-observations standard deviation ratio (RSR) and percent bias (PBIAS) (%) were 0.72, 0.73, 0.53 and 6.21, respectively, which were within the acceptable ranges [65], indicating a good relationship between the simulated and observed runoff discharge time series
Summary
Urbanization contributes to the development level of a country [1]. Rapid urbanization and the increase in impervious surface areas in urban regions could increase runoff volume by two to six times that of normal runoff [2,3]. Continued urbanization and development increase the potential for floods, and can cause intensive water quality degradation by increasing associated pollutants, such as suspended solids, fine particles, heavy metals, nutrients, and organic chemicals [4,5,6,7,8], which can all seriously impact public health and threaten environmental quality [9]. Stormwater runoff quantity and quality management for urban regions is a complex task, which has become an increasingly important environmental issue for urban communities [10]. Extensive monitoring campaigns are not always feasible, due to resource availability and the associated uncertainties. In such a situation, stormwater modelling is a useful tool, which uses limited data resources
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