We describe and evaluate a model chain for studying streamflow responses to climate variations and anthropogenic climate change. The model chain was developed for the Rhine basin upstream of Cologne, a 145,000 km2 river basin in Central Europe north of the Alps. It encompasses a regional climate model (RCM) at grid spacings of 56 and 14 km, and a distributed hydrological model with a grid spacing of 1 km. The hydrological model is one-way nested into the RCM through a downscaling interface, which introduces fine-scale structures in the forcing data (i.e. temperature, precipitation, total net surface radiation, 10-m wind speed, and relative humidity). Biases in precipitation and temperature are accounted for by catchment-dependent but seasonally constant correction factors. Apart from these bias corrections, the hydrological model is forced by hourly RCM data. In the evaluation we compare a 5-year integration driven by observed lateral boundary conditions (ECMWF reanalysis) against daily analysis of high-density rain-gauge data and streamflow data. The regional climate model is found to qualitatively reproduce the main mesoscale precipitation patterns and their seasonal evolution. Systematic biases are, however, found in the distribution of precipitation with topographic height in the Alpine region and at adjacent hill ranges. The RCM also reproduces intercatchment variations in the frequency distribution of daily precipitation. Simulated runoff resembles closely the mean annual cycle, and daily runoff agrees well with observations in timing and amplitude of runoff events for lowland gauges. Larger model errors are found for high-altitude Alpine catchments. The 14-km RCM provides much finer and more realistic precipitation fields compared to the 56-km RCM, but these improvements did not have a significant impact on the skill of the hydrological model to simulate streamflow. The model chain was found to reproduce observed month-to-month variations of basin-mean winter precipitation and streamflow with correlations between 0.85 and 0.95. This result provides confidence that the model chain is able to represent key processes related to streamflow variations in response to climate variations and climate change.