Abstract
Increasing demand for food, climate change, and other human interventions are leading to significant increases in water consumption by the agricultural sector. This requires rationalizing the water used for the production of agricultural crops through improved irrigation management practices. Therefore, this study aimed to estimate the water footprint (WF) of onion (Allium cepa L.) and carrot (Daucus carota) crops using the CROPWAT model and the SSEB (Simplified Surface Energy Balance) algorithm. Experiments were carried out at two center-pivot irrigated fields belonging to Tawdeehiya Commercial Farms in the southeastern region of the Riyadh governorate, Saudi Arabia. Individual bands and vegetation indices (VIs) were retrieved from Sentinel-2 satellite data, including the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), optimized soil adjusted vegetation index (OSAVI), renormalized difference vegetation index (RDVI), and enhanced vegetation index (EVI), and the land surface temperatures (LST) extracted from Landsat-8 data were used to estimate crop productivity (CP), crop water use (CWU) (i.e., evapotranspiration-ETa), and crop WF. Crop growth/phenology stages and georeferenced biophysical parameters were recorded during the growth period, and crop yield samples were collected randomly from predetermined sampling locations. It was found that the NIR band was appropriate for predicting onion yield (R-2 = 0.68; p > F = 0.02) and carrot yield (R-2 = 0.77; p > F = 0.02). The results also showed the feasibility of using the RDVI and EVI to estimate the yields of onion and carrot crops, with bias values of 15% and -17%, respectively. The CWU has also been successfully estimated using the SSEB algorithm, with an overall accuracy of 89%. The SSEB-estimated CWU was relatively high compared to the applied amounts by 10.6% (onions) and 12.6% (carrots). Finally, the crop WF was successfully estimated at 312 m(3) t(-1) and 230 m(3) t(-1) for carrots and onions, respectively, with an overall accuracy of 71.11%. The outcomes of this study can serve as a reference for crop irrigation management practices in the study region and areas with similar environmental conditions.