Abstract

Urban water pollution is an important issue of global concern. An integrated model that can be employed to efficiently and accurately simulate the whole system of urban surfaces, underground drainage systems and river and lake water environments is an important tool for comprehensively treating urban water pollution. Therefore, we developed a 1D-2D dynamic bidirectional coupling model for high-resolution simulation of the entire urban water environment (GAST-GCSE) comprising the graphics processing unit (GPU)-accelerated surface water flow and transport (GAST) model and the storm water management model (SWMM). The SWMM and GAST model were used for coupled simulation of hydrological and hydrodynamic quantities and water quality in 1D and 2D regions, respectively. The time steps of the two models are the same. Compute Unified Device Architecture (CUDA) parallel architecture programming and advanced model algorithms were adopted to improve the simulation accuracy and efficiency of the GAST model. The two models were dynamically coupled by calling the dynamic link library (DLL) in the SWMM and adding external functions. Two test cases were considered to verify the performance of the proposed model. The results showed that the proposed model provides high simulation accuracy. Compared with the results obtained by commercial software and theoretical values, the relative errors of the water quantity and water quality simulation results were less than 3%. The whole water environment of the main urban area of Changzhi city in North China was evaluated by the GAST-GCSE model, and the simulation results were compared with monitoring data and pure SWMM simulation results. The simulation errors at three waterlogging points were less than 14%, and the Nash efficiency coefficients (NSE) of the NH4+-N concentration in the three river sections were 0.77, 0.56 and 0.64, respectively. Notably, the model needed only 4.39 h to simulate rainfall production and confluence on a 2D surface, a river flood in complex terrain and its accompanying pollutant evolution process involving 3,849,428 cells over 4 h. This study provides new insights, ideas and tools for urban water environment simulation and change mechanism study.

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