Effect of endogenous and anthropogenic factors on the alkalinisation and salinisation of freshwater in United States by using explainable machine learning

Freshwater salinisation and alkalinisation strongly depend on human and natural factors. We used an explainable machine learning approach to investigate the impact of natural and human factors on the salinity and alkalinity in rivers in the United States. The model achieved coefficient of determination of 0.89 for salinity predictions and 0.92 for alkalinity predictions. Shapley additive explanations revealed salinisation is driven mainly by human factors like population density (18 %) and impervious surface percentage (13 %) and natural factors like run-off (14 %). The alkalinisation is mainly influenced by natural processes such as runoff (36 %) and soil-pH (20 %).