Integrating unsupervised machine learning, statistical analysis, and Monte Carlo simulation to assess toxic metal contamination and salinization in non-rechargeable aquifers

Integrating unsupervised machine learning, statistical analysis, and Monte Carlo simulation to assess toxic metal contamination and salinization in non-rechargeable aquifers

This study presents the first comprehensive evaluation of groundwater quality in Siwa Oasis, Egypt, integrating advanced machine learning and statistical approaches to assess contamination, health risks, and industrial suitability. Thirty samples from the Nubian Sandstone Aquifer (NSAS) and karst sp...

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Bibliographic Details
Main Authors: Mohamed Hamdy Eid, Omar Saeed, András Székács, Mostafa R. Abukhadra, Haifa A. Alqhtani, Attila Kovács, Péter Szűcs
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Results in Engineering
Subjects:
Water salinization
SOM
PCA
CWQI
Toxic metals: Risk simulation
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025010655
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