Study on rainfall and runoff correlation based on refined classification of urban underlying surface

In urban drainage planning, the constant runoff coefficients were generally used to estimate urban runoff. However, under the conditions of complex rainfall characteristics and diverse types of underlying surfaces, the estimation using constant runoff coefficients can hardly meet the needs of increasingly refined management.  Therefore, this study focuses on the urban area of Shanghai—characterized by complex underlying surfaces—as the research subject. Based on refined classification of 11 types of underlying surfaces from remote sensing imagery, dynamic field monitoring of rainfall-runoff processes was conducted to analyze runoff characteristics. Using the Storm Water Management Model (SWMM), hydrological parameters were determined to elucidate the correlations between regional runoff, infiltration, and rainfall factors. The results showed that, compared with impervious underlying surfaces, pervious underlying surfaces reduced the initial runoff volume by 6.4-15.7 mm under short-duration, high-intensity frontal rainfall. Under long-duration, multi-peak rainfall, the runoff generation time was delayed by 3.5-23.8 hours. Vegetation interception and soil infiltration could effectively reduce the initial runoff volume or delay the runoff generation time and runoff peak time. The runoff coefficients of the 8 types of impervious underlying surfaces were in the order of: cement flat roof > Traffic road > outdoor parking lot > square pavement > enterprise road > tile roof > residential area road > sidewalk, with Manning's coefficients ranging from 0.012 to 0.021 and depression storage capacities from 2.71 to 3.91 mm. The runoff coefficients of the 3 types of pervious underlying surfaces were in the order of: grassland > shrubland > forestland, with Manning's coefficients ranging from 0.27 to 0.41 and depression storage capacities from 4.16 to 5.32 mm. The regional runoff coefficients under 15 rainfall events ranged from 0.58 to 0.89, among which the runoff coefficients under high-intensity rainstorms, heavy rainstorms or extraordinary rainstorms were 0.76 to 0.89. There was a significant positive linear relationship between regional runoff volume and rainfall amount (R²=0.9952), while the infiltration amount had a good logarithmic relationship with rainfall amount (R²=0.9548). The research results can provide a reference for the rapid assessment of underlying surfaces and regional runoff, offer data support for runoff control and drainage system overflow simulation, and contribute to refined management of urban hydrology and drainage system overflow.