Groundwater fluoride and nitrate contamination poses critical public health risks in northern Ghana. The Volta Basin is widely reported as a fluorosis-endemic region in Ghana, where agriculture constitutes the primary economic activity. However, there remains a notable gap in the use of quantitative modelling approaches to predict both the mechanisms and levels of contamination within the basin. Therefore, this study aimed to identify the processes controlling elevated fluoride (F−) and nitrate (NO3−) concentrations in Gushegu's Voltaian aquifers, build parsimonious prediction models, and quantify age-stratified health risks. Fifteen groundwater samples were analysed using hydrogeochemical techniques, including Piper and Gibbs plots, saturation indices, and multivariate statistical analyses. Additionally, 88 prior samples (total n = 103) were used to compare six machine learning algorithms against Multiple Linear Regression (MLR) through cross-validation and permutation importance analysis. The results revealed that Mg2+ and HCO3− dominate groundwater chemistry, with Mg-K-HCO3 as the common water type. Fluoride ranged 0.001–19.5 mg/L (mean 6.38 mg/L), with 93.3 % of samples exceeding the World Health Organization (WHO) limit of 1.5 mg/L; NO3− ranged 2.50–92.5 mg/L (mean 38.1 mg/L), with 40 % exceeding 50 mg/L. Fluoride was geogenically controlled and strongly correlated with pH (r = 0.94), while NO3− was consistent with agricultural/anthropogenic inputs. MLR performed best for both contaminants, with high prediction accuracy (NO3−: R2 = 0.901; F−: R2 = 0.666). Health-risk assessment indicated the highest vulnerability in infants: Total Hazard Index (HI) for F− up to 45.69 and for NO3− up to 5.42 (children: F− HI ≤ 28.25; adults: F− HI ≤ 15.10). Hotspots (e.g., Yishei) require priority mitigation. Findings demonstrate a concise, transferable workflow that integrates process understanding with prediction to inform targeted source protection, water-treatment options, and alternative-supply planning in data-limited settings.
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