The main sources of uncertainty in rainfall-runoff models are found in the input variables where the largest impact on estimated streamflow is generally given by the catchment rainfall. Hence, by quantifying the uncertainty of catchment rainfall, it is possible to provide an estimate, albeit conservative, of streamflow estimation uncertainty. In this article, 42 series of catchment average rainfall were used to estimate monthly streamflow for two river catchments in the United Kingdom over a period of 8 years, these were as follows: a composite series based on weighted rain gauge series, a series based on interpolated gridded rainfall data and an ensemble of 40 series, based on simulated rainfall grids conditioned on observed rainfall statistics. This study shows that, on average, the uncertainty in monthly streamflow, as given from the mean range of monthly simulated data, were approximately 28 and 42% of the long-term mean for the two catchments respectively. By quantifying uncertainty in streamflow due to catchment rainfall uncertainty it was possible to identify contributions of other factors to the total streamflow estimation uncertainty. For example, streamflow uncertainty was, in this experiment, shown to respond also to the absolute magnitude of the streamflow, a consequence of the model being optimized for low flows.