Groundwater sustains human activity in arid crystalline terrains where surface water is scarce and hydrogeological data are limited. However, most groundwater potential mapping approaches depend on deterministic weighting methods without quantifying model variability. This study describes an uncertainty-aware Remote Sensing and Geographic Information Systems (RS–GIS) framework to delineate groundwater potential zones in the Wadi Arab Watershed, Northeastern Sudan. Nine thematic factors—geology and lithology, rainfall, slope, drainage density, lineament density, soil, land use/land cover, topographic wetness index, and height above nearest drainage—were integrated using the Analytical Hierarchy Process (AHP), with acceptable consistency (Consistency Ratio (CR) < 0.1). To address subjectivity in weights, a Dirichlet-based Monte Carlo simulation (500 iterations) was implemented to perturb AHP weights whilst preserving compositional constraints. The resulting Groundwater Potential Index (GWPI) classified 32.69% of the watershed as high to very high potential, primarily associated with alluvial deposits and fractured crystalline rocks. Model validation using Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.704, indicating acceptable predictive performance. Uncertainty assessment showed low spatial variability (mean standard deviation (SD) = 0.215) and stable exceedance probabilities, verifying the robustness of predicted high-potential zones. The proposed probabilistic AHP framework augments decision reliability and provides a transferable, cost-effective tool for groundwater planning in data-limited arid basement environments.

In arid coastal environments, urban expansion alters land–water interactions, leading to increased soil salinity and moisture accumulation across urban landscapes. This study examines the spatiotemporal evolution of soil salinity and moisture, and land-use/land-cover (LULC) changes in Port Sudan, an arid coastal city that experienced rapid expansion from 2008 to 2024. The limited vegetation cover enables effective shortwave infrared (SWIR)-based assessment of salinity and moisture, facilitating multi-temporal analysis of LULC change and hydro-saline impacts. The findings demonstrate significant landscape transformation driven by urbanization, with built-up areas nearly doubling, substantial rangeland expansion, and a pronounced reduction in bare ground. These land-use transitions are accompanied by a marked inland expansion of salinity and moisture-affected areas, increasing from 8.12 to 40.36 km ² and from 120.15 to 245.49 km ² , respectively, particularly within low-lying and reclaimed sabkha terrains. Urban growth exhibits strong correlations with hydro-saline intensification (R ² = 0.77 and 0.82), as increased surface impermeability and disrupted drainage promote salt accumulation and subsurface water retention. Field observations in representative urban areas confirm that persistent hydro-saline ground conditions are linked to salt crust formation, sustained surface moisture, and progressive corrosion of building materials and foundations. Time-series forecasting indicates that continued urbanization is likely to further extend hydro-salinity-affected areas through 2040, with projections suggesting a substantial spatial increase under current development trajectories, although with uncertainty related to environmental variability and temporal resolution. Overall, this study presents a field-calibrated, earth observation-based framework that connects urban expansion with hydro-saline processes and related coastal infrastructure vulnerability, supporting risk-informed planning and management in arid coastal regions.