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This study applied machine learning techniques, specifically the Random Forest algorithm, to predict groundwater quality in the Nabogo Basin of Northern Ghana. The research utilized various environmental factors and existing borehole data to generate a Water Quality Index (WQI), revealing that 21.97% of the area has excellent groundwater quality. The findings aim to assist in groundwater management and policy development by providing a detailed understanding of groundwater quality in the region.

Author

Saquib Ahmad Khan

Language

EN