Predicting river water quality across North West England using catchment characteristics

J. J. Rothwell, N. B. Dise, K. G. Taylor, T. E H Allott, P. Scholefield, H. Davies, C. Neal

Research output: Contribution to journalArticlepeer-review


Linear relationships between regional water quality and catchment characteristics (terrain, land cover, geology, base flow index and rainfall) are examined for rivers in North West England using a GIS-based approach and an extensive Environment Agency water quality database. The study considers the role of diffuse and distal point sources on river water quality. The results show that base cation concentrations are strongly linked to catchment terrain and land cover, while pH is linked to bedrock geology and land cover. Mean nitrate concentrations are most strongly related to arable cover, although distal point sources in urban and rural catchments appear to have a significant effect on river nitrate concentrations in the region. Orthophosphate and suspended sediment concentrations are most closely related to the percentage urban development. Linear models are tested on a large independent water quality dataset, resulting in maps showing predicted water quality across the region. The approach works well for the prediction of nitrate concentrations and other constituents which have predominantly diffuse sources. In contrast, the linear approach to predicting orthophosphate concentrations in North West rivers using catchment characteristics is problematic. The major influence of point sources may mask the effect of wider basin attributes on orthophosphate concentrations. Within-river processing of phosphorus may also explain why the relationship breaks down. Further work is needed to explain phosphorus contributions and variability in North West rivers, especially in the context of effective catchment management. © 2010 Elsevier B.V.
Original languageEnglish
Pages (from-to)153-162
JournalJournal of Hydrology
Issue number3-4
Publication statusPublished - 15 Dec 2010


  • Base cations
  • GIS
  • Modelling
  • Nutrients
  • PH
  • Sediments


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