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Remote sensing applications in agricultural practices are comprehensively reliable and cover a multidisciplinary fundamental interest both in local and regional level. Significantly, vegetation indices are the foremost essential in remote sensing applied for agricultural activities related to vegetation and/or water, particularly in an arid environment. Adequate water resources management plans are based on better fulfilling the 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 by 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 dynamics of surface water. The study area is located within the main agricultural region of Wadi As-Sirhan. The area is characterized by flourishing agricultural activities. Remote sensing data acquired by Sentinal-2 proved to be statistically sufficient to estimate soil water content in two different climatic conditions. Statistically, estimated winter indices are with better fit than summer indices. Modified Normalized Difference Water Index and second Normalized Difference Water Index best fitted winter soil water content estimations. Meanwhile, RMSE showed no differences between Normalized Difference Water Index and Normalized Difference Turbidity Index for both climatic conditions.

CONSIDERATION OF SEASONAL VARIATIONS OF WATER RADIOMETRIC INDICES FOR THE ESTIMATION OF SOIL MOISTURE CONTENT IN ARID ENVIRONMENT IN SAUDI ARABIA