Predicting current and future background ion concentrations in German surface water under climate change

Salinization of surface waters is a global environmental issue that can pose a regional risk to freshwater organisms, potentially leading to high environmental and economic costs. Global environmental change including climate and land use change can increase the transport of ions into surface waters. We fit both multiple linear regression (LR) and random forest (RF) models on a large spatial dataset to predict Ca2+ (266 sites), Mg2+ (266 sites), and (357 sites) ion concentrations as well as electrical conductivity (EC—a proxy for total dissolved solids with 410 sites) in German running water bodies. Predictions in both types of models were driven by the major factors controlling salinity including geologic and soil properties, climate, vegetation and topography. The predictive power of the two types of models was very similar, with RF explaining 71–76% of the spatial variation in ion concentrations and LR explaining 70–75% of the variance. Mean squared errors for predictions were all smaller than 0.06. Th...