Abstract. China is undergoing rapid urbanization during the past decades. For example, the proportion of urban population in Beijing has increased from 57.6 % in 1980 to 86.3 % in 2013. Rapid urbanization has an adverse impact on the urban rainfall-runoff processes, which may result in the increase of urban flood risk. In the present study, the major purpose is to investigate the impact of land use/cover change on hydrological processes. The intensive human activities, such as the increase of impervious area, changes of river network morphology, construction of drainage system and water transfer, were considered in this study. Landsat TM images were adopted to monitor urbanization process based on Urban Land-use Index (ULI). The SWMM model considering different urbanized scenarios and anthropogenic disturbance was developed. The measured streamflow data was used for model calibration and validation. Precipitation with different return periods was taken as model input to analyse the changes of flood characteristics under different urbanized scenarios. The results indicated that SWMM provided a good estimation for storms under different urbanized scenarios. The volume of surface runoff after urbanization was 3.5 times greater than that before urbanization; the coefficient of runoff changed from 0.12 to 0.41, and the ratio of infiltration decreased from 88 to 60 %. After urbanization, the time of overland flow concentration increased while the time of river concentration decreased; the peak time did not show much difference in this study. It was found that the peak flow of 20-year return-period after urbanization is greater than that of 100-year return-period before urbanization. The amplification effect of urbanization on flood is significant, resulting in an increase of the flooding risk. These effects are especially noticeable for extreme precipitation. The results in this study will provide technical support for the planning and management of urban storm water and the evaluation on Low Impact Development (LID) measures.