Groundwater (GW) represents a critical resource for sustaining agriculture and rural communities across the arid regions of many developing countries. This study assesses three predictive approaches boosted classification tree (BCT), the bivariate frequency ratio (FR), and a hybrid BCT–FR ensemble for mapping Potential Zones (GWPZ) in arid environments. The modelling framework integrates satellite-derived variables with pumping-test measurements (specific capacity (SPC) and transmissivity (T)) and incorporates topographic, geological, hydrogeological, and anthropogenic factors using an inventory of forty-two wells divided into calibration (70%) and validation (30%) datasets across the West El-Minia region of Upper Egypt. Change-detection analysis over the study period (2000–2025) indicated a substantial increase in agricultural activity, with cultivated lands expanding by more than 560 km². This expansion was accompanied by an observed level decline of approximately five meters over the same period, based on field measurements from 42 wells and calculated using observed water table differences. Based on SPC predictions, the BCT and hybrid FR–BCT models achieved relatively high area under the curve (AUC) values. For transmissivity, the corresponding accuracy values were 83.38% for BCT and 92.58% for FR–BCT. Model outputs were assessing their reliability by comparing the GW potential map generated with available borehole information and daily GWproductivity data from the aquifer system. The study area was classified into four GW potential categories: very high (8%), high (26%), moderate (54%), and low (12%), with the northeastern sector exhibiting the highest recharge and storage potential. Overall, the applied machine-learning techniques demonstrated good performance for GW potential assessment in data-limited environments. The results provide important guidance for GW resource management by identifying zones with substantial recharge and development potential.

Groundwater is an essential resource in arid and semi-arid areas such as Upper Egypt, especially where surface water is limited or difficult to obtain. This study explores the hydrogeochemical properties, pollution levels, and related health risks of groundwater in the northern region of Assiut Governorate, Egypt. A total of thirty groundwater samples were systematically collected and analyzed through geochemical modeling, the Nemerow Pollution Index (NPI), and health risk assessment models. The findings showed that the groundwater samples had a pH ranging from slightly acidic to neutral, which aids the dissolution of carbonate minerals and increases the mobility of trace metals. Most of the water samples were categorized as hard to very hard, exhibiting high concentrations of calcium and magnesium in comparison to sodium and potassium. Bicarbonate levels were higher than those of chloride and sulfate, further supporting the notion that carbonate dissolution is the primary geochemical process, followed by ion exchange and evaporite dissolution. Four principal hydrochemical facies were identified—Ca-Mg-HCO₃, Ca-Mg-Cl, Na-HCO₃, and Na-Cl—reflecting diverse sources and interactions within the aquifer system. Human activities, including industrial and agricultural runoff, have significantly raised the levels of cadmium (Cd) and lead (Pb), with 67% of the samples classed as severely polluted according to NPI standards. Health risk analyses indicated that Cd and Pb present significant non-carcinogenic and carcinogenic threats, particularly to infants and children, whose exposure levels surpassed US EPA guidelines. Furthermore, land use/land cover (LULC) assessments using Sentinel-2 imagery from 2000 to 2024 revealed considerable urban expansion over productive agricultural land, coupled with groundwater over-extraction and deteriorating water quality. The combination of hydrochemical analysis, multivariate statistics, remote sensing, and GIS emphasizes the urgent need for groundwater protection, pollution reduction, and regulation of land use to ensure public health and the sustainability of water resources in Upper Egypt. The quality of groundwater is at risk due to swift urban growth and the expansion of agriculture. The main geochemical process observed in groundwater samples is the dissolution of carbonates. Most groundwater samples contain cadmium and lead levels that surpass the limits set by the WHO. 67% of the water samples indicate significant contamination according to Nemerow’s Pollution Index. The study area presents the greatest health risks from cadmium and lead for infants and children. The diagrams created by Piper and Gibbs illustrate the prevailing geochemical processes. From 2000 to 2024, changes in land use indicate urban expansion over productive floodplain soils. Sustainable groundwater and land use planning is supported by remote sensing and GIS. Most water samples continue to be appropriate for irrigation, even in the presence of salinity risks. Proper measures are essential to guarantee that groundwater is safe for human consumption.

The southeastern Qattara Depression is a geomorphologically active region of Egypt’s Western Desert, where longitudinal dune fields intersect major development corridors, including the New Delta Project and petroleum concessions. This study presents the first integrated multi-temporal assessment of longitudinal dune morphodynamics over 35 years (1990–2025) using satellite imagery, digital elevation data, geological maps, and climatic records. Fifty-two dunes were analyzed using morphometric and kinematic indicators. Simple dunes dominate (78.85%), while complex forms account for 21.15%. Dune volumes range from 6.42 × 10⁶ to 4.98 × 10⁹ m³. Strong correlations between dune dimensions and volume (r = 0.73–0.89), indicate that lateral accretion as the primary growth mechanism. Dune activity has accelerated through increasing lateral migration, longitudinal growth, and vertical accretion driven by high-energy winds and prolonged drought. An Analytic Hierarchy Process (AHP) framework integrated the Sand Mobility Index, Normalized Difference Sand Index, and Normalized Difference Vegetation Index to assess geomorphological hazard and land-use vulnerability. The resulting dune hazard, vulnerability, and sand-drift risk maps spatially classify risk. ROC–AUC validation showed excellent predictive performance (AUC ≈ 0.93). High and very high hazard zones cover 22.96% of the study area, revealing substantial threats to ongoing development.