Potential of the Modified Water Cloud Model to Estimate Soil Moisture in Drip-Irrigated Pepper Fields Using ALOS-2 and Sentinel-1 Data
Résumé
In this paper, we investigate the potential of the modified water cloud model to estimate soil moisture in pepper crop fields with drip irrigation in a semiarid area in Tunisia using cross-polarized L-band data (ALOS-2) and C-band data (Sentinel-1) data in Horizontal-Horizontal (L-HH) and Vertical-Vertical (C- VV) polarization, respectively. Within the context of spatially heterogeneous soil moisture, the total backscattering is the sum of pepper row scattering weighted by the vegetation fraction cover (Fe) and the inter-row soil scattering weighted by (1-Fc). The vegetation row contribution is calculated as the sum of volume scattering contribution of pepper and underlying soil components attenuated by the vegetation cover. Due to the presence of drip irrigation, the underlying soil zone is divided into two parts: irrigated and non-irrigated parts. To assess the calibrated model performance, various simulations are performed under different conditions of soil moisture and vegetation biophysical properties. Under various conditions of soil moisture, the results revealed the potential of the suggested model to simulate SAR signal where cover fraction and pepper height values are under 0.4 and 0.5 m, respectively, using L-HH and cover fraction value under 0.3 and vegetation height value 0.3 m, using C-VV data.