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A problem encountered by many distributed hydrological modelling  studies is high simulation errors at interior gauges when the model is  only globally calibrated at the outlet. We simulated river runoff in  the Elbe River basin in central Europe (148 268 km<sup>2</sup>) with  the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While  global parameter optimisation led to Nash–Sutcliffe efficiencies of  0.9 at the main outlet gauge, comparisons with measured runoff series  at interior points revealed large deviations. Therefore, we compared  three different strategies for deriving sub-basin evapotranspiration:  (1) modelled by SWIM without any spatial calibration,  (2) derived from remotely sensed surface temperatures, and  (3) calculated from long-term precipitation and discharge data. The  results show certain consistencies between the modelled and the remote  sensing based evapotranspiration rates, but there seems to be no  correlation between remote sensing and water balance based  estimations. Subsequent analyses for single sub-basins identify  amongst others input weather data and systematic error amplification  in inter-gauge discharge calculations as sources of uncertainty.  The results encourage careful utilisation of different data sources  for enhancements in distributed hydrological modelling

hydrology and earth system sciences

Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances