The primary advantage of radar observations of precipitation compared with traditional rain gauge measurements is their high spatial and temporal resolution and large areal coverage. Unfortunately, radar data require vigorous quality control before being converted into precipitation products that can be used as input to hydrologic models. In this study we coupled a physically based atmospheric model of convective rainfall with an active microwave radiative transfer model to simulate radar observation of thunderstorms. We used the atmospheric model to simulate a well-documented tornadic supercell storm that occurred near Del City, Oklahoma, on 20 May 1977. We then generated radar observations of that storm and used them to evaluate the propagation of radar rainfall errors through distributed hydrologic simulations. This physically based methodology allows us to directly examine the impact of radar rainfall estimation errors on land-surface hydrologic predictions and to avoid the limitations imposed by the use of rain gauge data. Results indicate that the geometry of the radar beam and coordinate transformations, due to radar-watershed-storm orientation, have an effect on radar rainfall estimation and runoff prediction errors. In addition to uncertainty in the radar reflectivity versus rainfall intensity relationship, there are significant range-dependent and orientation-related radar rainfall estimation errors that should be quantified in terms of their impact on runoff predictions. Our methodology provides a tool for performing experiments that address some operational issues related to the process of radar rainfall estimation and its uses in hydrologic prediction.