Abstract: Current urban drainage planning typically employs constant runoff coefficients to estimate urban runoff.However, under complex rainfall characteristics and diverse land cover types, the use of a single runoff coefficient is insufficient to meet the demands of increasingly refined management.Therefore, taking the complex urban area of Shanghai as the study subject, 11 land cover types were classified using high-resolution remote sensing imagery.Field dynamic runoff monitoring was conducted to analyze runoff characteristics across these land covers.Hydrological parameters were determined using the SWMM model to investigate the relationships between runoff, infiltration, and rainfall factors in the region.Results indicated: ① compared with impervious surfaces, permeable surfaces exhibited reduced initial runoff of 6.4~15.7 mm during short-duration, high-intensity frontal rainfall events.Under prolonged, multi-peak rainfall, runoff onset was delayed by 3.5~23.8 hours.Vegetation interception and soil infiltration effectively reduced initial runoff or delayed runoff onset and peak timing.② Among eight impervious surfaces, runoff coefficients ranked as follows: concrete roofs > motor vehicle roads > outdoor car parks > plaza pavements > institutional pavements > tiled roofs > residential area pavements > sidewalks.Manning′s coefficients ranged from 0.012 to 0.021, while depression storage capacities varied between 2.71 mm and 3.91 mm.③ The runoff coefficient of three permeable surface types followed the order: grassland > scrubland > woodland.Manning′s coefficients and depression storage capacities ranged from 0.27 to 0.41 mm and 4.16 to 5.32 mm, respectively.④ Regional runoff coefficients under 15 rainfall events ranged from 0.58 to 0.89, with coefficients under heavy, torrential, or extreme downpours ranging from 0.76 to 0.89.⑤ Regional runoff volume exhibited a positive linear relationship with rainfall (R²= 0.995), while infiltration volume demonstrated a strong logarithmic correlation with rainfall (R²= 0.955).These findings provide data support for runoff source control and drainage system overflow simulation, thereby contributing to more refined management of urban hydrology and drainage system overflows.