ArticleScientific reports2026
Enhancing groundwater potential mapping in arid regions through integrated microwave remote sensing, statistical analysis, and geophysical-based modeling.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The increasing water scarcity in arid regions underscores the urgent necessity to map and manage structurally controlled aquifers (SCAq), which play a pivotal yet underappreciated role as water sources. This study presents an integrative framework that synergistically combines statistical remote sensing methods with geophysical investigations to precisely delineate groundwater potential (GwP) within the Wadi Hodein basin in the Eastern Desert of Egypt. Microwave remote sensing data from Sentinel-1 SAR, ALOS PALSAR, and IMERG were integrated with geophysical techniques, including aeromagnetic surveys and DC resistivity measurements, to enhance predictive accuracy for structurally controlled aquifer characterization. The workflow involved developing ensemble bivariate models, namely EBF-IOE and WOE-IOE, leveraging morphometric, climatic, and hydrogeological datasets, followed by geophysical validations to identify and characterize high-potential zones. The EBF-IOE model exhibited exceptional predictive performance (AUC = 80.11%), highlighting areas predominantly influenced by lineament density, lithologic variations, and fault networks. Geophysical analyses revealed that these promising zones are compartmentalized by NNW-SSE and E-W fault systems, providing insights into local variability in well yield and water quality that statistical models alone could not capture. Aeromagnetic data established a structural context, while DC resistivity measurements quantified aquifer geometry, linking resistivity values (17-111 Ω·m) with productive areas and water salinity levels (824-2120 ppm). This study demonstrates that integrating statistical modeling with geophysical methods is crucial for transitioning from broad regional predictions to a nuanced understanding of SCAqs. The proposed framework presents a scalable model that mitigates risks in groundwater exploration across arid regions globally, thereby promoting sustainable extraction and managed aquifer recharge strategies.
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