Performance of ASCAT soil moisture and MODIS snow cover satellite data for calibration of hydrologic models in poorly gauged catchments

Remote sensing observations have significant potential for the setup and validation of hydrologic models and, consequently, predict runoff hydrographs in regions with limited runoff measurements. This study aims to analyze the spatial-temporal performance patterns of ASCAT soil moisture and MODIS snow cover to calibrate a conceptual hydrologic model in a large number of catchments in Austria. In the first step, the model (TUWmodel) is calibrated using satellite data only. Next, we analyze the regional and seasonal variability in model performance regarding snow cover error, soil moisture correlation and runoff efficiency. We compare the model efficiency of multiple objective calibrations to satellite data only to the performance of various regionalization strategies that transfer model parameters from the most similar catchments. Finally, we propose an alternative calibration strategy that combines satellite observations with a limited number of runoff observations, representing poorly gauged sites. The analyses are performed in 213 catchments in Austria representing diverse climate and physiographic conditions.