Assessment of water cloud model based on sar and optical satellite data for surface soil moisture retrievals over agricultural area

Abstract

Water availability to plants a significant role in agricultural areas, especially in arid and semi-arid areas. This research aimed to evaluate the potential of Water Cloud Model (WCM) for retrieving surface soil moisture, which is associated to water availability, in a semi-arid areas based on the combination between Sentinel-1B SAR (Synthetic Aperture Radar) and optical Sentinel-2B data. The performance of the applied model was assessed using ground observed soil moisture (0-5 cm). Accuracy evaluation was performed by the cross-validation method (k-fold), it showed a coefficients of determination (R2 ) of 0.65 and RMSE of 1.45%. The obtained results show a good concordance between retrieved model and ground observed surface soil moisture. In addition, this model was used for the mapping spatio-temporal variation of soil moisture at high spatial resolution in the study areas. This approach could be used by environmentalists and decision-makers as a practical tool for monitoring and estimating the change of surface moisture content.