In this research, a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions, which was then employed to analyze the impacts of spatial and temporal rainfall heterogeneities on peak runoff for watersheds. Three scenarios were developed under multiple degrees of impermeable underlying surface areas within an urban watershed in south China. Detailed runoff processes were analyzed through the adoption of a distributed hydrological model (GSSHA). A covariance analysis method combined with rainfall spatio‐temporal heterogeneity characteristic were used to quantify heterogeneity effects on peak runoff. Results indicated that coupling short period (2008–2016) remotely rainfall data and RainyDay results could successfully reproduce designed rainfall events, spatio‐temporal heterogeneity of rainfall contributed significantly to the peak runoff, which was greater than those by rainfall duration and capacity, and the increase in impermeable underlying surface enhanced the complexities of the effects. Over each rainfall duration with increasing rainfall return period, the indicator of rainfall peak coefficient (RWD) would decrease and then increase. Regarding the total rainfall center (tg), 25 mm/h threshold rainfall spatial coverage (A25) decreased with increasing imperviousness, 1‐h maximum rainfall (Rmax) surged with increasing imperviousness at rainfall duration of 2 and 24 h. Innovations of this research lied in: combination of a rainfall generator model based on a stochastic storm transposition technique and remote‐sensing rainfall data to generate designed rainfall events, a rainfall spatial and temporal heterogeneities index system was developed to reveal how the changing characteristics of rainfall distribution and the impacts on peak runoff, and in‐depth analysis of the impacts on runoff peak under multiple urban development scenarios for increasing capability in flood control/prevention.