EGU23-4911, updated on 10 Jan 2024
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Satellite-based soil moisture could enhance the reliability of agro-hydrological modeling in large transboundary river basins

Mohammad Reza Eini1, Christian Massari2, and Mikołaj Piniewski1
Mohammad Reza Eini et al.
  • 1Department of Hydrology, Meteorology, and Water Management, Institute of Environmental Engineering, Warsaw University of Life Sciences, Warsaw, Poland
  • 2Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy

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.

How to cite: Eini, M. R., Massari, C., and Piniewski, M.: Satellite-based soil moisture could enhance the reliability of agro-hydrological modeling in large transboundary river basins, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4911,, 2023.

Supplementary materials

Supplementary material file