Assessment and modelling of water chemistry in a large catchment : River Dee, NE Scotland
Wade, Andrew John
PublisherUniversity of Aberdeen
MetadataShow full item record
This thesis describes the water chemistry of the River Dee and its tributaries, and the potential water chemistry changes that may occur under acid deposition and land use change scenarios. The Dee is a large (2100 km2) river system in NE Scotland, considered nationally important in terms of water supply, recreation and conservation. This is the first study to describe the hydrochemical functioning of the entire catchment, setting it within the contemporary framework of other new research initiatives (LOIS). Historic water quality and flow records were collated and supplemented with new water chemistry data. These data were analysed in relation to catchment geography and river flow using both mathematical modelling and novel, GIS based techniques. This analysis established the importance of diffuse inputs and highlighted differences between upland and lowland regions in the catchment. In headwater streams, different geological types create hydrochemical source areas that strongly influence stream chemistry whilst in lowland tributaries, agricultural sources are particularly important. In the upland region most major ions were diluted as flows increased, further emphasizing the influence of deeper geological sources on baseflow chemistry, but showing soilwater controls on stormflow composition. The headwaters, which drain predominantly acid rocks, are presently oligotrophic but threatened by the impact of acid deposition and land use change (re-afforestation). In some of the lowland tributaries, increased N03-N concentrations have resulted from more intensive land management. The potential impacts of acid deposition and land use change were simulated in both upland and lowland catchments by considering existing and new models within a Functional Unit Network. For upland regions this consisted of developing a new, two component hydrochemical mixing model to simulate the spatial and flow-related variations in streamwater acidity. The mixing model was based on End Member Mixing Analysis (EMMA), and site specific end members (alkalinity and Ca) could be predicted from emergent catchment characteristics (soil and land use) using linear regression. The Model of Acidification of Groundwater in Catchments (MAGIC) simulated the long term end member changes (in alkalinity) and these outputs were combined with the mixing model to predict changes in stream V chemistry. Given a limited commercial exploitation and emphasis on regeneration of native trees, the model simulations suggest that significant streamwater acidification is unlikely. For both upland and lowland regions the Integrated Nitrogen in Catchments model (INCA) was used to assess the impacts of N deposition and land use change on mean annual streamwater N03-N concentrations. Results suggest reductions in streamwater N03-N following decreased N deposition and removal of land from intensive agricultural production. The combination of approaches considered within the FUN framework have provided an appropriate framework in which to consider the issue of water quality and spatial scale. The utility of these modelling approaches is discussed in relation to the increased need for water quality models for Integrated Catchment Management.