EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

High-resolution near-surface soil moisture through the combination of Sentinel-1 and Cosmic-Ray Neutron Probe in a Mediterranean agroforestry

Aida Taghavi Bayat1, Sarah Schönbrodt-Stitt1, Paolo Nasta2, Nima Ahmadian3, Christopher Conrad3, Heye R. Bogena4, Harry Vereecken4, Jannis Jakobi4, Roland Baatz4, and Nunzio Romano2
Aida Taghavi Bayat et al.
  • 1Department of Remote Sensing, Institute of Geography and Geology, University of Würzburg, 97074 Würzburg, Germany (
  • 2Department of Agricultural Sciences, AFBE Division, University of Napoli Federico II, Portici (Naples), Italy
  • 3Department of Geoecology, Institute of Geosciences and Geography, University of Halle-Wittenberg, 06120 Halle/Saale, Germany
  • 4Agrosphere Institute (IBG-3), Forschungszentrum Jülich GmbH, Jülich 52425, Germany.

The precise estimation and mapping of the near-surface soil moisture (~5cm, SM5cm) is key to supporting sustainable water management plans in Mediterranean agroforestry environments. In the past few years, time series of Synthetic Aperture Radar (SAR) data retrieved from Sentinel-1 (S1) enable the estimation of SM5cm at relatively high spatial and temporal resolutions. The present study focuses on developing a reliable and flexible framework to map SM5cm in a small-scale agroforestry experimental site (~30 ha) in southern Italy over the period from November 2018 to March 2019. Initially, different SAR-based polarimetric parameters from S1 (in total 62 parameters) and hydrologically meaningful topographic attributes from a 5-m Digital Elevation Model (DEM) were derived. These SAR and DEM-based parameters, and two supporting point-scale estimates of SM5cm were used to parametrize a Random Forest (RF) model. The inverse modeling module of the Hydrus-1D model enabled to simulate two  supporting estimates of SM5cm by using i) sparse soil moisture data at the soil depths of 15 cm and 30 cm acquired over 20 locations comprised in a SoilNet wireless sensor network (SoilNet-based approach), and ii) field-scale soil moisture monitored by a Cosmic-Ray Neutron Probe (CRNP-based approach). In the CRNP-based approach, the field-scale SM5cm was further downscaled to obtain point-scale supporting SM5cm data over the same 20 positions by using the physical-empirical Equilibrium Moisture from Topography (EMT) model. Our results show that the CRNP-based approach can provide reasonable SM5cm retrievals with RMSE values ranging from 0.034 to 0.050 cm³ cm-3 similar to the ones based on the SoilNet approach ranging from 0.029 to 0.054 cm³ cm-3. This study highlights the effectiveness of integrating S1 SAR-based measurements, topographic attributes, and CRNP data for mapping SM5cm at the small agroforestry scale with the advantage of being non-invasive and easy to maintain.


How to cite: Taghavi Bayat, A., Schönbrodt-Stitt, S., Nasta, P., Ahmadian, N., Conrad, C., Bogena, H. R., Vereecken, H., Jakobi, J., Baatz, R., and Romano, N.: High-resolution near-surface soil moisture through the combination of Sentinel-1 and Cosmic-Ray Neutron Probe in a Mediterranean agroforestry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7582,, 2021.

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