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A critical re-evaluation of the prediction of alkalinity and base cation chemistry from BGS sediment composition data

Research output: Contribution to journalArticlepeer-review



Publication details

JournalScience of the Total Environment
DateE-pub ahead of print - 20 Mar 2014
DatePublished (current) - 1 Jun 2014
Number of pages11
Pages (from-to)283-293
Early online date20/03/14
Original languageEnglish


The model of Begum et al. (2010) that predicts alkalinity and Ca and Mg concentrations in river water from available sediment composition data has been critically re-evaluated using an independent validation data set. The results support the hypothesis that readily available stream water sediment elemental composition data are useful for prediction of mean and minimum concentrations of alkalinity and Ca and Mg in river water throughout the River Derwent catchment in North Yorkshire without requiring land-use data inputs as stream water sediment composition reflects all aspects of the riparian zone soil system, including land-use. However, it was shown for alkalinity prediction that rainfall exerts a significant dilution effect and should be incorporated into the model in addition to flow path-weighted sediments Ca% and Mg%. The results also strongly suggest that in catchments with substantial rough moorland land-use neutralization of organic acids consumes alkalinity and this fact should be considered in any future development of the model.

    Research areas

  • Alkalinity, Calcium/Magnesium, River sediment, Predict, Rainfall, River Derwent

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