Remote Sensing for Agricultural Water Management in Jordan

This study shows how remote sensing methods are used to support and provide means for improving agricultural water management (AWM) in Jordan through detailed mapping of irrigated areas irrigation consumption (IWC). Digital processing classification were applied on multi-temporal data Landsat 8 Sentinel-2 derive maps the period 2017–2019. Different relationships developed between normalized difference vegetation index (NDVI) crop coefficient (Kc) map evapotranspiration (ET). Using ground data, ET transferred IWC whole country. Spatial analysis was then delineate hotspots where shifts groundwater abstraction observed. Results showed that provided accurate areas. The NDVI-Kc significant, with coefficients determination (R2) ranging from 0.89 0.93. Subsequently, estimates agreement remotely sensed modeled by SEBAL (NSE = 0.89). In context Jordan, results country reached 98 thousand ha 2019, 64% this area located highlands. main crops vegetables (55%) fruit trees olives (40%). total 702 MCM constituting 56% 375 amount being pumped groundwater, while reported only 235 MCM. identified illegal or incorrect metering existed. Furthermore, it emphasized roles AWM, as updated figures forecasts future IWC, which would reach 986 2050. Therefore, approach be highly recommended present IWC.