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Influence of Rainfall, Model Parameters and Routing Methods on Stormwater Modelling

Gong, Yongwei, Li, Xiaoning, Zhai, Dandan, Yin, Dingkun, Song, Ruining, Li, Junqi, Fang, Xing, Yuan, Donghai
Water resources management 2018 v.32 no.2 pp. 735-750
Monte Carlo method, United States Environmental Protection Agency, decision making, drainage, hydrograph, hydrologic models, prediction, rain, stormwater, stormwater management, uncertainty, watersheds, China
Quantification of the uncertainty associated with stormwater models should be analyzed before using modelling results to make decisions on urban stormwater control and management programs. In this study, the InfoWorks Integrated Catchment Modelling (ICM) rainfall-runoff model was used to simulate hydrographs at the outfall of a catchment (drainage area 8.3 ha, with 95% pervious areas) in Shenzhen, China. The model was calibrated and validated for two rainfall events with Nash-Sutcliffe efficiency >0.81. The influence of rainfall, model parameters and routing methods on outflow hydrograph of the catchment was systematically studied. The influence of rainfall was analyzed using generated rainfall distributions with random errors and systematic errors (± 30% offsets). Random errors had less influence than systematic errors on peak flow and runoff volume, especially for two rainfall events with larger depths and longer durations. The Monte Carlo simulations using 500 parameter sets were used to verify the equifinality of the nine model parameters and determine the prediction uncertainty. Most of the monitored flows were within the uncertainty range. The influence of two routing methods from rainfall excess to hydrograph was studied. The InfoWorks ICM model incorporating double quasilinear reservoir routing was found to have a larger effect on the simulated hydrographs for rainfall events having larger depths and longer durations than using the U.S. EPA’s Storm Water Management Model nonlinear reservoir routing method did.