Abstract
To determine the distribution of water balance components in space and time, models are applied with a wide range of spatio‐temporal discretizations—from lumped to distributed in the spatial scale and from annual to daily (or shorter) time‐steps in the temporal scale. We present a comparative case study where we compare the simulation results of two conceptual water balance models using different spatio‐temporal discretizations. Such a comparison enables to assess if different models with different discretizations may still yield similar results in space and time. The study focuses on the mountainous catchment of the river Gail (app. 1300 km^2^) in southern Austria for the period 1971–1990. The first model uses a semi‐distributed discretization and daily data, whereas the second model uses a spatially distributed discretization (1 × 1 km raster) and monthly data. Both models use precipitation and temperature data as input. Parameters of the daily model were calibrated with runoff data of several gauges as part of a study focusing specifically on the Gail catchment. The distributed parameters of the monthly model were estimated regionally for establishing the water balance of the Hydrological Atlas of Austria. Both models perform equally well for runoff simulations. For simulation of temporal dynamics the models agree well for the main inputs and outputs of the system, with slightly lower agreements for sub‐components—such as snowmelt for instance. In the spatial domain the correlation between the models is significantly lower. Differences are mainly related to different calibration approaches and are not dependent on the spatio‐temporal discretization. Overall, the two water balance models yield consistent results, suggesting that the usage of monthly data is not inferior to the usage of daily data. Copyright © 2008 John Wiley & Sons, Ltd.