Water scarcity has received global attention in the last decade as it challenges food security in arid and semi-arid regions, particularly in the Middle East and North Africa. This research assesses the possible alleviation of water scarcity by reducing the water footprint in crop production through the application of soil mulching and drip irrigation. The study is the first to do so at catchment scale, taking into account various crops, multi-cropping, cropping patterns, and spatial differences in climate, soil, and field management factors, using field survey and local data. The AquaCrop-OS model and the global water footprint assessment (WFA) standard were used to assess the green and blue water footprint (WF) of ten major crops in the Upper Litani Basin (ULB) in Lebanon. The blue water saving and blue water scarcity reduction under these two alternative practices were compared to the current situation. The results show that the WF of crop production is more sensitive to climate than soil type. The annual blue WF of summer crops was largest when water availability was lowest. Mulching reduced the blue WF by 3.6% and mulching combined with drip irrigation reduced it by 4.7%. The blue water saving from mulching was estimated about 6.3 million m3/y and from mulching combined with drip irrigation about 8.3 million m3/y. This is substantial but by far not sufficient to reduce the overall blue WF in summer to a sustainable level at catchment scale.

The Food and Agricultural Organization of the United Nations (FAO) portal to monitor water productivity through open‐access of remotely sensed derived data (WaPOR) offers continuous actual evapotranspiration and interception (ETIa‐WPR) data at a 10‐day basis across Africa and the Middle East from 2009 onwards at three spatial resolutions. The continental level (250 m) covers Africa and the Middle East (L1). The national level (100 m) covers 21 countries and 4 river basins (L2). The third level (30 m) covers eight irrigation areas (L3). To quantify the uncertainty of WaPOR version 2 (V2.0) ETIa‐WPR in Africa, we used a number of validation methods. We checked the physical consistency against water availability and the long‐term water balance and then verify the continental spatial and temporal trends for the major climates in Africa. We directly validated ETIa‐WPR against in situ data of 14 eddy covariance stations (EC). Finally, we checked the level consistency between the different spatial resolutions. Our findings indicate that ETIa‐WPR is performing well, but with some noticeable overestimation. The ETIa‐WPR is showing expected spatial and temporal consistency with respect to climate classes. ETIa‐WPR shows mixed results at point scale as compared to EC flux towers with an overall correlation of 0.71, and a root mean square error of 1.2 mm/day. The level consistency is very high between L1 and L2. However, the consistency between L1 and L3 varies significantly between irrigation areas. In rainfed areas, the ETIa‐WPR is overestimating at low ETIa‐WPR and underestimating when ETIa is high. In irrigated areas, ETIa‐WPR values appear to be consistently overestimating ETa. The relative soil moisture content (SMC), the input of quality layers and local advection effects were some of the identified causes. The quality assessment of ETIa‐WPR product is enhanced by combining multiple evaluation methods. Based on the results, the ETIa‐WPR dataset is of enough quality to contribute to the understanding and monitoring of local and continental water processes and water management.

Remote sensing techniques have been shown, in several studies, to be an extremely effective tool for assessing the performance of irrigated areas at various scales and diverse climatic regions across the world. Open access, ready-made, global ET products were utilized in this first-ever-countrywide irrigation performance assessment study. The study aimed at identifying ‘bright spots’, the highest performing sugarcane growers, and ‘hot spots’, or low performing sugarcane growers. Four remote sensing-derived irrigation performance indicators were applied to over 302 sugarcane growers; equity, adequacy, reliability and crop water productivity. The growers were segmented according to: (i) land holding size or grower scale (ii) management regime, (iii) location of the irrigation schemes and (iv) irrigation method. Five growing seasons, from June 2005 to October 2009, were investigated. The results show while the equity of water distribution is high across all management regimes and locations, adequacy and reliability of water needs improvement in several locations. Given the fact that, in general, water supply was not constrained during the study period, the observed issues with adequacy and reliability of irrigation in some of the schemes were mostly due to poor scheme and farm level water management practices. Sugarcane crop water productivity showed the highest variation among all the indicators, with Estate managed schemes having the highest CWP at 1.57 kg/m³ and the individual growers recording the lowest CWP at 1.14 kg/m³, nearly 30% less. Similarly center pivot systems showed to have the highest CWP at 1.63 kg/m³, which was 30% higher than the CWP in furrow systems. This study showcases the applicability of publicly available global remote sensing products for assessing performance of the irrigated crops at the local level in several aspects.

Crop water productivity (CWP) has become a recognised indicator in assessing the state of Sustainable Development Goals (SDG) 6.4—to substantially increase water use efficiency. This indicator, while useful at a global scale, is not comprehensive at a local scale. To fill this gap, this research proposes a CWP framework, that takes advantage of the spatio-temporal availability of remote sensing, that identifies CWP goals and sub-indicators specific to the needs of the targeted domain. Three sub-indicators are considered; (i) a global water productivity score (GWPS), (ii) a local water productivity score (LWPS) and (iii) a land and water use productivity score (YWPS). The GWPS places local CWP in the global context and focuses on maximised CWP. The LWPS differentiates yield zones, normalising for potential product, and focuses on minimising water consumption. The YWPS focuses simultaneously on improving land and water productivity equally. The CWP framework was applied to potato in the West Bank, Palestine. Three management practices were compared under each sub-indicator. The case study showed that fields with high and low performance were different under each sub-indicator. The performance associated with different management practices was also different under each sub-indicator. For example, a winter rotation had a higher performance under the YWPS, the fall rotation had a higher performance under the LWPS and under the GWPS there was little difference. The results showed, that depending on the basin goal, not only do the sub-indicators required change, but also the management practices or approach required to reach those basin goals. This highlights the importance of providing a CWP framework with multiple sub-indicators, suitable to basin needs, to ensure that meeting the SDG 6.4 goal does not jeopardise local objectives.

This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit of physical crop production/yield per unit water consumption)—are evaluated in five irrigation schemes for three spatial resolutions—250 m, 100 m, and 30 m. Each scheme has varying plot sizes and distributions, with average plot sizes ranging from 0.2 ha to 13 ha. The datasets are derived from the United Nations Food and Agricultural Organization (FAO) water productivity through open access of remotely sensed–derived data (the Water Productivity Open Access Portal—WaPOR) database. Irrigation indicators performed differently in different aspects; for adequacy, all three resolutions show similar spatial trends for relative evapotranspiration (ET) across levels for all years. However, the estimation of relative ET is often higher at higher resolution. In terms of equity, all resolutions show similar inter-annual trends in the coefficient of variation (CV); higher resolutions usually have a higher CV of the annual evapotranspiration and interception (ETIa) while capturing more spatial variability. For productivity, higher resolutions show lower crop water productivity (CWP) due to higher aboveground biomass productivity (AGBP) estimations in lower resolutions; they always have a higher CV of CWP. We find all resolutions of 250 m, 100 m, and 30 m suitable for inter-annual and inter-scheme assessments regardless of plot size. While each resolution shows consistent temporal trends, the magnitude of the trend in both space and time is smoothed by the 100 m and 250 m resolution datasets. This frequently results in substantial differences in the irrigation performance assessment criteria for inter-plot comparisons; therefore, 250 m and 100 m are not recommended for inter-plot comparison for all plot sizes, particularly small plots (<2 ha). Our findings highlight the importance of selecting the spatial resolution appropriate to scheme characteristics when undertaking irrigation performance assessment using remote sensing.