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Aquifer characterization and salinization origin using unsupervised machine learning and 3D gravity inversion modeling, Siwa Oasis, Egypt
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DOI：10.1016/j.gsf.2026.102258.png)
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Abstract
En 中文
• Combined machine learning, gravity analysis, and 3D modeling to characterize aquifers in Siwa Oasis. • SOM outperformed k-means in resolving thin aquifer layers and estimating thickness. • Gravity data revealed NE-SW, NW-SE, and E-W faults controlling groundwater flow. • Southern Siwa Oasis identified as the best area for fresh groundwater extraction. • Central and northeastern regions at risk due to fracture-mediated leakage from hypersaline lakes.
Keywords:
Aquifer characterization
Salinization origin
Unsupervised machine learning
3D gravity inversion modeling
Fault and fracture systems
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