Can sediment data be used to predict alkalinity and base cation chemistry of surface waters?

We hypothesise that stream sediment elemental composition can predict mean and minimum concentrations of alkalinity, Ca and Mg in the river water throughout a river network. We tested this hypothesis for the River Derwent catchment in North Yorkshire, England, by using 6 years of water chemistry data from the Environment Agency and a digital elevation model to flow path-weight British Geological Survey (BGS) sediment element concentration data. The predictive models for mean concentrations were excellent for Ca and alkalinity, but less good for Mg, and did not require land use data inputs as stream water sediment composition seems to reflect all aspects of the riparian zone soil system. Predictive model forms were linear. Attempts to predict minimum values for Ca and alkalinity also were less satisfactory. This probably is due to variations in hydrological response times to individual precipitation events across the catchment.

Research Highlights
► Changes in river solute chemistry are predictable from pre-existing sediment data.
► Flow path-weighted sediment % Ca and % Mg are used as independent variables.
► Ca and Mg concentrations and alkalinity are predictable.
► The concept is validated for the River Derwent in N. Yorkshire, UK.
► Both mean and minimum Ca and alkalinity concentrations may be predicted.