Satellite-based observations of soil moisture, leaf area index, precipitation, and evapotranspiration facilitate agro-hydrological modeling thanks to the spatially distributed information. In this study, the Climate Change Initiative Soil Moisture dataset (CCI SM, a product of the European Space Agency (ESA)) adjusted based on Soil Water Index (SWI) was used as an additional (in relation to discharge) observed dataset in agro-hydrological modeling over a large-scale transboundary river basin (Odra River Basin) in the Baltic Sea region. This basin is located in Central Europe within Poland, Czech Republic, and Germany and drains into the Baltic Sea. The Soil and Water Assessment Tool+ (SWAT+) model was selected for agro-hydrological modeling, and measured data from 26 river discharge stations and soil moisture from CCI SM (for topsoil and entire soil profile) over 1476 sub-basins were used in model calibration for the period 1997-2019. Kling-Gupta efficiency (KGE) and SPAtial EFficiency (SPAEF) indices were chosen as objective functions for runoff and soil moisture calibration, respectively. Two calibration strategies were compared: one involving only river discharge data (single-objective - SO), and the second one involving river discharge and satellite-based soil moisture (multi-objective - MO). In the SO approach, the average KGE for discharge was above 0.60, whereas in the MO approach, it increased to 0.67. The SPAEF values showed that SWAT+ has acceptable accuracy in soil moisture simulations. Moreover, crop yield assessments showed that MO calibration also increases the crop yield simulation accuracy. The results show that in this transboundary river basin, adding satellite-based soil moisture into the calibration process could improve the accuracy and consistency of agro-hydrological modeling.
Keywords: Drought; Flood; Gridded datasets; Hydrology; Remote sensing.
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