Abstract. Travel-time distributions are a comprehensive tool for the characterization of hydrological system dynamics. Unlike the streamflow hydrograph, they describe the movement and storage of water within and throughout the hydrological system. Until recently, studies using such travel-time distributions have generally either been applied to lumped models or to real-world catchments using available time series, e.g., stable isotopes. Whereas the former are limited in their realism and lack information on the spatial arrangements of the relevant quantities, the latter are limited in their use of available data sets. In our study, we employ the spatially distributed mesoscale Hydrological Model (mHM) and apply it to a catchment in central Germany. Being able to draw on multiple large data sets for calibration and verification, we generate a large array of spatially distributed states and fluxes. These hydrological outputs are then used to compute the travel-time distributions for every grid cell in the modeling domain. A statistical analysis indicates the general soundness of the upscaling scheme employed in mHM and reveals precipitation, saturated soil moisture and potential evapotranspiration as important predictors for explaining the spatial heterogeneity of mean travel times. In addition, we demonstrate and discuss the high information content of mean travel times for characterization of internal hydrological processes.