Spatial prediction of groundwater potential area using fractal models, aeromagnetic and geospatial data in Tata basin, Morocco

The necessity to safeguard groundwater resources in arid and semi-arid regions has driven the development of advanced spatial planning tools for mapping. This study aims to delineate potential groundwater zones (GWPA) in the Tata Basin, Morocco, utilizing the Data-Driven Multi-Index Overlay (DMIO) model. The analysis incorporates nine conditioning factors: elevation, slope, proximity to rivers, proximity to lineaments, drainage density, permeability, lineament density, topographic wetness index (TWI), and lineament intersection density. Despite its utility, the GWPA mapping process is challenged by uncertainties inherent in these factors. To assess the impact of such uncertainties, three parameters (normalized density (Nd), weight (We), and the Receiver Operating Characteristic (ROC) curve) were employed. The GWPA model classified the study area into five classes: very low (20.77%), low (44.78%), moderate (16.83%), high (13.97%), and very high (3.65%) groundwater potential. The model demonstrated a predictive capacity with Nd = 3.76 and We = 1.31, corroborated by the success curve analysis, thus confirming its reliability in GWPA mapping. Additionally, geological structures in the Tata Basin related to groundwater potential were analyzed using magnetic data processed with various filtering techniques. The results were consistent, further validating the model's accuracy and dependability. These findings highlight the DMIO model's efficacy in GWPA mapping and its potential application in other regions requiring sustainable groundwater resource management.