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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/hess-2020-436
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-436
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  03 Sep 2020

03 Sep 2020

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This preprint is currently under review for the journal HESS.

The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model

Rui Tong1,2, Juraj Parajka1,2, Andreas Salentinig3, Isabella Pfeil1,3, Jürgen Komma2, Borbála Széles1,2, Martin Kubáň4, Peter Valent2,4, Mariette Vreugdenhil3, Wolfgang Wagner1,3, and Günter Blöschl1,2 Rui Tong et al.
  • 1Centre for Water Resource Systems, TU Wien, Vienna, 1040, Austria
  • 2Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna, 1040, Austria
  • 3Department of Geodesy and Geoinformation, TU Wien, Vienna, 1040, Austria
  • 4Department of Land and Water Resources Management, Slovak University of Technology, Bratislava, 810 05, Slovakia

Abstract. Recent advances in soil moisture remote sensing have produced satellite datasets with improved soil moisture mapping under vegetation and with higher spatial and temporal resolutions. In this study, we evaluate the potential of a new, experimental version of the ASCAT Soil Water Index dataset for multiple objective calibration of a conceptual hydrologic model. The analysis is performed in 213 catchments in Austria for the period 2000–2014. An HBV type hydrologic model is calibrated to runoff data, ASCAT soil moisture data, and MODIS snow cover data for various calibration variants. Results show that the inclusion of soil moisture data in the calibration mainly improves the soil moisture simulations; the inclusion of snow data mainly improves the snow simulations; and including both of them improves both soil moisture and snow simulations to almost the same extent. The snow data are more efficient in improving snow simulations than the soil moisture data are in improving soil moisture simulations. The improvements of both runoff and soil moisture model efficiencies are larger in low elevation and agricultural catchments than in others. The calibrated snow-related parameters are strongly affected by including snow data, and to a lesser extent by soil moisture data, while the soil-related parameters are only affected by the inclusion of soil moisture data.

Rui Tong et al.

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Short summary
The authors used a new and experimental version of ASCAT Soil Water Index dataset and MODIS C6 snow cover products for multiple objective calibrations of TUWmodel (HBV type) in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
The authors used a new and experimental version of ASCAT Soil Water Index dataset and MODIS C6...
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