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This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies' technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This review addresses the growth and development of medicinal plants under arid land conditions and the potential use of remote sensing technologies to map their distribution, as well as morphological and physiological responses in Arid lands. Plant morpho-physiological variables including, chlorophyll content, and gas exchange (photosynthesis, transpiration, vapor pressure, and stomatal conductance) are linked to plant water status. Multispectral and hyperspectral remote sensing techniques are promising for detecting morphological physiological changes. Vegetation indices derived from hyperspectral and multispectral imagery makes it possible to assess medicinal plants' health through successful detection of the ground plant physiological variables and canopy cover including chlorophyll, canopy density, gas exchange (red, 600-700 nm, nearinfrared spectrum, 700-1100 nm) as well as water status (shortwave infrared, 1300-2500 nm). Surface reflectance data within the shortwave infrared bands (water bands) revealed significant differences between well-watered and drought-stressed plants. However, the moderate spatial resolution (Sentinel-2: 20 m, Landsat: 30 m) for the space-born free sensors and the need for a cloud-free sky could be limitations. Overall, vegetation indices derived from remotely sensed data are a useful approach for estimating the physiology of plants (medicinal plants) especially those under drought stress. [ABSTRACT FROM AUTHOR]

Remote sensing can provide important and updated information for agricultural water accounting (AWA). In this study, data from the open-access portal (WaPOR) of the Food and Agricultural Organization was used in AWA to assess levels of agricultural water consumption and to provide possible solutions for water deficiency in the North Jordan Valley (NJV). Consolidated procedures have been applied to complement and validate the WaPOR products. These included the use of climatic and ground data, the multispectral remote-sensing data of Sentinel-2 and Landsat 8 to derive land use/cover maps, GIS layers, and calibrated evapotranspiration (ET) estimates using the surface energy balance algorithm for land (SEBAL). The data of water inflows and outflows were analyzed using the water accounting plus (WA+) system. Results showed that the WaPOR data of actual ET and interception (AETI) were highly correlated with SEBAL-ET, with WaPOR data overestimating ET for irrigated areas. Precipitation data from WaPOR, on the other hand, were underestimating inflow from rainfall, although significant correlations were observed between these data and rainfall records. As a result, the quality of WaPOR data affected the outputs from agricultural water accounting. The main impact on water accounting outputs was the underestimation of percolated water that could be utilized as a possible solution to water deficiency in the NJV. In addition, the water accounting performance indicators were relatively affected, although they reflected the nature of the study area where water deficiency predominated as a result of inter-basin transfer. The study compared outputs from water accounting in terms of the possible solutions to water deficiency in the NJV and concluded that considerable amounts of recoverable water could be developed when compared with the option of developing surface water from the side wadis. Also, it emphasized the important role of remote-sensing sources for providing information for AWA needed for improved water management and governance. [ABSTRACT FROM AUTHOR]

This research shows a case from Jordan where geospatial techniques were utilized for irrigation water auditing. The work was based on assessing records of groundwater abstraction in relation to irrigated areas and estimated crop water consumption in three water basins: Yarmouk, Amman-Zarqa and Azraq. Mapping of irrigated areas and crop water requirements was carried out using remote sensing data of Landsat 8 and daily weather records. The methodology was based on visual interpretation and the unsupervised classification for remote sensing data, supported by ground surveys. Net (NCWR) and gross (GCWR) crop water requirements were calculated by merging crop evapotranspiration (ETc), calculated from daily weather records, with maps of irrigated crops. Gross water requirements were compared with groundwater abstractions recorded at a farm level to assess the levels of abstraction in relation to groundwater safe yield. Results showed that irrigated area and GCWR were higher than officially recorded cropped area and abstracted groundwater. The over abstraction of groundwater was estimated to range from 144% to 360% of the safe yield in the three basins. Overlaying the maps of irrigation and groundwater wells enabled the Ministry of Water and Irrigation (MWI) to detect and uncover violations and illegal practices of irrigation, in the form of unlicensed wells, incorrect metering of pumped water and water conveyance for long distances. Results from the work were utilized at s high level of decision-making and changes to the water law were made, with remote sensing data being accredited for monitoring water resources in Jordan. [ABSTRACT FROM AUTHOR]

Remote sensing, climate, and ground data were used within a geographic information system (GIS) to map desertification risk in the north-west of Jordan. The approach was based on modelling wind and water erosion and incorporating the results with a map representing the severity of drought. Water erosion was modelled by the universal soil loss equation, while wind erosion was modelled by a dust emission model. The extent of drought was mapped using the evapotranspiration water stress index (EWSI) which incorporated actual and potential evapotranspiration. Output maps were assessed within GIS in terms of spatial patterns and the degree of correlation with soil surficial properties. Results showed that both topography and soil explained 75% of the variation in water erosion, while soil explained 25% of the variation in wind erosion, which was mainly controlled by natural factors of topography and wind. Analysis of the EWSI map showed that drought risk was dominating most of the rainfed areas. The combined effects of soil erosion and drought were reflected on the desertification risk map. The adoption of these geospatial and remote sensing techniques is, therefore, recommended to map desertification risk in Jordan and in similar arid environments. [ABSTRACT FROM PUBLISHER]

An estimate of evapotranspiration (ET) is needed for many applications in diverse disciplines such as agriculture, hydrology, and meteorology. The objective of this study was to compare two methods for estimating daily actual ET (ETa) from six sites located in four different ecological zones within Jordan. The first method used the analytical land–atmosphere radiometer model (ALARM) and the dimensionless temperature procedure, whereas the second method used ETa calculated from the FAO-56 reference evapotranspiration. ALARM converts general remotely sensed surface temperatures to aerodynamic temperature. Standard meteorological data from weather stations were used with both methods, and the Moderate Resolution Imaging Spectroradiometer (MODIS)–based leaf area index, surface temperature, and albedo were obtained to estimate ETa, using the former method. A validation study was conducted on an alfalfa field in Jordan Valley using ALARM and the American Society of Civil Engineers’ (ASCE) method, which is very similar to FAO-56 except it uses alfalfa as a reference crop. Because this alfalfa field was irrigated and because of warm air advection, ET rates based on measurements of soil moisture change ranged from about 6 to 10 mm day-1. For this range, the root-mean-square error (RMSE) for ALARM was 0.87 mm day-1 and the coefficient of determination r 2 was 0.36, whereas the RMSE for ASCE was 1.25 mm day-1 and r 2 = 0.06. There was good agreement between minimum, maximum, and average ETa for the two methods at all sites except for Irbid, for which the minimum and, consequently, the average were different. Much of the site-to-site and temporal variability was found to be statistically significant. Reasons for this variability include soil types, vegetation cover, irrigation, and warm advection. [ABSTRACT FROM AUTHOR]