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

Remote Sensing for Agricultural Water Management in Jordan

Guido D’Urso
Secondo
Methodology
;
2022

Abstract

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 and irrigation water consumption (IWC). Digital processing and classification methods were applied on multi-temporal data of Landsat 8 and Sentinel-2 to derive maps of irrigated areas for the period 2017–2019. Different relationships were developed between the normalized difference vegetation index (NDVI) and the crop coefficient (Kc) to map evapotranspiration (ET). Using ground data, ET maps were transferred to IWC for the whole country. Spatial analysis was then used to delineate hotspots where shifts between ET and groundwater abstraction were observed. Results showed that the applied remote sensing methods provided accurate maps of irrigated areas. The NDVI-Kc relationships were significant, with coefficients of determination (R2) ranging from 0.89 to 0.93. Subsequently, the ET estimates from the NDVI-Kc relationships were in agreement with remotely sensed ET modeled by SEBAL (NSE = 0.89). In the context of Jordan, results showed that irrigated areas in the country reached 98 thousand ha in 2019, with 64% of this area located in the highlands. The main irrigated crops were vegetables (55%) and fruit trees and olives (40%). The total IWC reached 702 MCM in 2019, constituting 56% of the total water consumption in Jordan, with 375 MCM of this amount being pumped from groundwater, while reported abstraction was only 235 MCM. The study identified the hotspots where illegal abstraction or incorrect metering of groundwater existed. Furthermore, it emphasized the roles of remote sensing in AWM, as it provided updated figures on groundwater abstraction and forecasts for future IWC, which would reach 986 MCM in 2050. Therefore, the approach of ET and IWC mapping would be highly recommended to map ET and to provide estimates of present and future IWC.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/906507
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