Modeling urban storm rainfall runoff from diverse underlying surfaces and application for control design in Beijing

Managing storm rainfall runoff is paramount in semi-arid regions with urban development. In Beijing, pollution prevention in urban storm runoff and storm water utilization has been identified as the primary strategy for urban water management. In this paper, we sampled runoff during storm rainfall events and analyzed the concentration of chemical oxygen demand (COD), total suspended solids (TSS) and total phosphorus (TP) in the runoff. Furthermore, the first flush effect of storm rainfall from diverse underlying surfaces was also analyzed. With the Storm Water Management Model (SWMM), the different impervious rates of underlying surfaces during the storm runoff process were expressed. The removal rates of three typical pollutants and their interactions with precipitation and underlying surfaces were identified. From these rates, the scenarios regarding the urban storm runoff pollution loading from different designs of underlying pervious rates were assessed with the SWMM. First flush effect analysis showed that the first 20% of the storm runoff should be discarded, which can help in utilizing the storm water resource. The results of this study suggest that the SWMM can express in detail the storm water pollution patterns from diverse underlying surfaces in Beijing, which significantly affected water quality. The scenario analysis demonstrated that impervious rate adjustment has the potential to reduce runoff peak and decrease pollution loading.

► Identify the dynamics of pollutant load in storm rainfall on different types of urban underlying surfaces.
► Storm Water Management Model is calibrated in the downtown of Beijing.
► First flush effect analysis shows that the initial 20% runoff transport more than 60% of pollutants.
► Less impervious underlying surface decreases the load of COD and TSS, but not TP.