Separating natural and mining-derived controls on river metal pollution in artisanal gold mining-affected basins

Artisanal and small-scale gold mining (ASGM) mobilizes metal-rich sediments and trace contaminants into river systems, creating ecological and toxicological risks in tropical catchments. Distinguishing mining-derived contamination from natural hydrogeochemical variability remains difficult in data-poor regions with strong seasonal sediment transport. Here, we combined monthly community-based water-quality observations, laboratory ICP-MS measurements, and Bayesian multivariate hierarchical modelling to quantify the relative influence of basin hydrogeochemistry, seasonal hydrology, and mining activity on river metal assemblages in two Sierra Leone basins with contrasting degrees of ASGM impact. Metal variability was dominated by basin-scale hydrogeochemical controls and particle-associated transport, while mining-affected catchments showed additional enrichment in Mn, Co, Ni, Cr, and Pb, elements of potential toxicological concern for aquatic ecosystems and downstream water users. Seasonal hydrology modulated concentrations but did not obscure the mining signal. The probabilistic modelling framework separated natural and anthropogenic controls while accounting for metal covariance and uncertainty in environmental effects. Low-cost multi-metal colorimetric kits were unreliable for detecting mining gradients, whereas community-led turbidity measurements provided an operational proxy for sediment-associated disturbance. These results support a tiered monitoring strategy combining frequent community turbidity observations with targeted laboratory analyses of Mn, Co, Ni, Cr, and Pb to identify contamination hotspots of potential ecological and exposure concern. The approach provides an adaptable early-warning framework for other data-limited ASGM-affected regions, though regional recalibration would be needed to account for differing geology, climate and hydrology.