This study evaluates the use of remote sensing data to improve the understanding of groundwater resources in climate-sensitive regions with limited data availability and increasing agricultural water demands. The research focuses on estimating groundwater reserve dynamics in two major river basins in Morocco, characterized by significant local variability. The study employs data from Gravity Recovery and Climate Experiment satellite (GRACE) and ERA5-Land reanalysis. Two GRACE terrestrial water storage (TWS) products, CSR Mascon and JPL Mascon (RL06), were analyzed, along with auxiliary datasets generated from ERA5-Land, including precipitation, evapotranspiration, and surface runoff. The results show that both GRACE TWS products exhibit strong correlations with groundwater reserves, with correlation coefficients reaching up to 0.96 in the Oum Er-rbia River Basin and 0.95 in the Tensift River Basin (TRB). The root mean square errors (RMSE) were 0.99 cm and 0.88 cm, respectively. GRACE-derived groundwater storage (GWS) demonstrated a moderate correlation with observed groundwater levels in OERRB (R = 0.59, RMSE = 0.82), but a weaker correlation in TRB (R = 0.30, RMSE = 1.01). On the other hand, ERA5-Land-derived GWS showed a stronger correlation with groundwater levels in OERRB (R = 0.72, RMSE = 0.51) and a moderate correlation in TRB (R = 0.63, RMSE = 0.59). The findings suggest that ERA5-Land may provide more accurate assessments of groundwater storage anomalies, particularly in regions with significant local-scale variability in land and water use. High-resolution datasets like ERA5-land are, therefore, more recommended for addressing local-scale heterogeneity in regions with contrasted complexities in groundwater storage characteristics.

A reliable estimate of reference evapotranspiration (ET0) requires several meteorological inputs, which may be unavailable in regions with limited data availability. In this regard, this study aimed to address the following objectives: First, to evaluate the effectiveness of ERA5_Land (ERA5_L hereafter) weather forecasts in providing daily agrometeorological variables for the period 2003–2021 at 10 study sites distributed over both plain and mountainous areas in a North African basin. Second, to investigate whether downscaling the ERA5_L data (10 km) to station scale (250 m) using a quasi-physical based model, MicroMet, could improve the reliability of the meteorological variables. Third, to compare the performance of the original ERA5_L reanalysis data and the disaggregated ERA5_L data (MicroMet) as potential sources for accurate estimation of ET0 on a daily time scale. Finally, to assess the long-term spatiotemporal changes in ET0 across the Tensift basin over the period 1950–2021, and the influence of climate variables and topography on ET0 variability. The findings of the study revealed that the original ERA5_L estimates of air temperature (Tair) were the most accurate among the studied variables, followed by solar radiation (Rs), relative humidity (RH), and wind speed (u2). When considering the disaggregated daily ERA5_L data, Tair exhibited the highest performance, followed by RH, u2, and Rs. Tair and especially u2 demonstrated an improvement across the plain and mountainous sites. However, Rs was generally degraded after MicroMet. Then, a comparison was conducted between daily ET0 obtained considering both datasets and show similar correlations between ground and simulated data but with an overestimation of ET0 after MicroMet. Finally, the retrospective analysis of ET0 showed three main phases with a decrease of ET0 between 1950 and 1970, a nearly steady period during 1970–2000, and a significant increase from 2000 to 2021. This study provides a comprehensive insight on the potential and limitations of ERA5_L products in arid North African regarding irrigation and water management under climate variability.

Accurate information on crop types and irrigation systems is a fundamental input for improving our understanding of land-atmosphere interactions and monitoring agricultural dynamics in semi-arid environments. This paper presents a comprehensive, open-access ground-truth dataset of 10000 geolocated agricultural parcels collected across the five major agricultural regions of Morocco, El Gharb, Tadla, Doukkala, El Haouz, and Souss, between December 2023 and January 2025. The dataset encompasses 45 distinct crop types, including main seasonal crops such as wheat, corn, and alfalfa, as well as perennial crops including olives, citrus, and argan. In addition, six different irrigation systems were observed, from the traditional flood irrigation to advanced pivot systems, reflecting the diversity of Moroccan agro-ecosystems. Field data were collected using the GIS-based mobile application QField, ensuring high positional accuracy and detailed attribute information for each parcel. To evaluate dataset consistency, Normalized Difference Vegetation Index (NDVI) values were analyzed for all surveyed plots throughout 2024, revealing coherent seasonal dynamics in agricultural activity. Each record is accompanied by a geo-referenced photograph, providing an additional visual reference for validation and contextual understanding. The freely available dataset offers a high-quality reference for calibrating and validating Earth Observation (EO)-based crop type and irrigation mapping products. By representing the diversity of cropping systems and irrigation practices across Morocco’s climatic zones, this dataset provides a valuable foundation for advancing EO-driven agricultural monitoring, supporting policy assessment, and promoting sustainable land and water management in Morocco and the wider North African region.

Piedmonts around the Mediterranean are important hydro-agro-systems bridging between the mountains (upstream) where streamflow is generated, and the adjacent plains (downstream) where water is used. In Morocco, the piedmonts of the High-Atlas Mountains host secular irrigation channels (seguia) that divert the streamflow for irrigating a traditional agriculture since hundreds of years. These traditional hydro-agro-systems might be threatened by the effects of global change that requires in-depth study to identify the main causes and propose better sustainable management. The present study was carried out in the semi-arid piedmont of the High-Atlas mountains. A detailed analysis of hydro-climatological data was performed between 1965 and 2018 together with associated agricultural trends over the period 1984-2020. Statistical tests (Mann-Kendall and Pettitt) were used to assess whether there were significant trends or not in the long-term evolution of water resources. The findings revealed a significant decrease of the surface water and groundwater resource. The SPI meteorological drought index delineated three main droughts during 1982-1986, 1998-2008 and 2013-2017. Paradoxically, the scarcity and decrease trends in water resources are associated with an agricultural change from seasonal crops (cereals) to perennial crops (trees). The subsequent growing agricultural water demand exacerbates the water shortage and worsen the groundwater depletion.

A reliable estimate of reference evapotranspiration (ET0) requires several meteorological inputs, which may be unavailable in regions with limited data availability. In this regard, this study aimed to address the following objectives: First, to evaluate the effectiveness of ERA5_L weather forecasts in providing daily agrometeorological variables for the period 2003-2021 at 10 study sites distributed over both plain and mountainous areas in a North African basin. Second, to investigate whether downscaling the ERA5_L data (10 km) to station scale (250 m) using a quasi-physical based model, MicroMet, could improve the reliability of the meteorological variables. Third, to compare the performance of the original ERA5_L reanalysis data and the disaggregated ERA5_L data (MicroMet) as potential sources for accurate estimation of ET0 on a daily time scale. Finally, to assess the long-term spatiotemporal changes in ET0 across the Tensift basin over the period 1950-2021, and, the influence of climate variables and topography on ET0 variability. The findings of the study revealed that the original ERA5_L estimates of air temperature (Tair) were the most accurate among the studied variables, followed by solar radiation (Rs), relative humidity (RH), and wind speed (u2). When considering the disaggregated daily ERA5_L data, Tair exhibited the highest performance, followed by RH, u2, and Rs. Tair and especially u2 demonstrated an improvement across the plain and mountainous sites. However, Rs was generally degraded after Micromet. Then, a comparison was conducted between daily ET0 obtained considering both datasets and show similar correlations between ground and simulated data but with an overestimation of ET0 after MicroMet. Finally, the retrospective analysis of ET0 showed three main phases with a decrease of ET0 between 1950 and 1970, a nearly steady period during 1970-2000, and a significant increase from 2000-2021. This study provides a comprehensive insight about the potential and limitations of ERA5_L products in arid North African regarding irrigation and water management under climate variability. Keywords: ERA5_Land, downscaling, MicroMet, Reference evapotranspiration, Data-scarce basins, North Africa.