Abstract
Remote Sensing applications in agricultural practices are comprehensively reliable and cover a multidisciplinary fundamental interest on a local as well as on a regional level. Significantly, vegetation indices are foremost essential remote sensing applications in agricultural activities related to vegetation and/or water, particularly in an arid environment. Adequate water resources management plans are based on better fulfilment of water demand and supply equation. In arid environments, this equation is barely achieved due to water resources limitations. Remote sensing techniques improve the water resources management schemes using five different water radiometric indices of Sentinel-2. Each of them plays a specific role in the quantification of soil/plant water content based on the interpretation of map surface water features and monitors the dynamic of surface water. The study area is located within the main agricultural region of Wadi As-Sirhan, Saudi Arabia. The area is characterized by flourishing agricultural activities. Remote Sensing data acquired by Sentinel-2 proved to be statistically sufficient to estimate soil water content in two different climatic conditions. Statistically, winter estimated indices are a better fit than summer indices. MNDWI and NDWI-2 were best to fit winter soil water content estimations. Meanwhile, RMSE shows no differences between NDWI and NDTI in both climatic conditions.