306-6 Global spatial prediction modeling of groundwater manganese

Abstract:

Although manganese (Mn) is necessary for human health, high levels of Mn consumption may be toxic. In addition to food, drinking water coming from groundwater can provide a substantial amount of Mn to the diet. Several years ago, the World Health Organization (WHO) reduced its Mn drinking water guideline from 400 µg/L to 80 µg/L due to greater adverse health effects than previously known, particularly for infants. To assess how this large decrease in the Mn drinking water guideline affects the areas and people at risk, we have created global prediction maps of Mn in groundwater using machine learning. The first step was to compile a large dataset of Mn concentrations along with spatially continuous environmental variables relating to climate, hydrogeology, soil and topography. Once the best model was determined, this was applied to the predictor variables to produce global hazard and health risk maps. Based on these, we estimate that over 200 million people are potentially exposed to Mn concentrations in drinking water >80 µg/L, as opposed to 39 million people potentially exposed to the previous WHO guideline of 400 µg/L. This number of people at risk is comparable to that associated with the other geogenic groundwater contaminants of arsenic and fluoride, though Mn generally receives much less attention. Therefore, the new prediction maps produced in this study are important for raising awareness of the hazard posed by Mn in groundwater and in helping identify safe groundwater sources.

© Copyright 2026 The Geological Society of America (GSA), all rights reserved.