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Title: Influence of riparian geology and other catchment characteristics on streamwater chemistry at different spatial scales
Author: Smart, Richard Philip
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2002
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The River Dee in NE Scotland, an oligotrophic soft water system, has a catchment area of approximately 2100 km2, its source in the Cairngorm Mountains being approximately 140 km from its outlet to the North Sea at Aberdeen. A comprehensive sampling strategy and analytical programme have been established for major water quality determinands to identify the controls on, and origins of, dissolved species throughout the system at a range of sub-catchment scales and over a range of flow regimes. Fifty-nine sites covering a range of sub-catchment types and scales were sampled fortnightly for one year. At the basin scale, there is a general downstream increase in determinand concentrations. This produces strong linear relationships between many determinands that are unrelated in terms of a common terrestrial process or origin. At the sub-catchment scale, however, specific hydrochemical processes control streamwater chemistry. The Dee basin divides into two distinct geographic regions in terms of land use (upland and lowland) which produce clear differences in water chemistry. Individual sub-catchments can also be grouped in terms of temporal variations in streamwater chemistry. The strength of the relationship between weathering-derived ionic concentrations and flow in the upland sub-catchments has led to the identification of specific concentration limits in sub-catchments, which can be used as characteristics of soil water and groundwater end-members. This provides a basis for the prediction of upland weathering-derived component concentrations for each sub-catchment at a range of flows. A Geographical Information System (GIS - ARC/INFO) was used to collate existing spatial data sets on catchment characteristics to predict stream water quality using simple empirical models. The study found that geological maps and associated geochemical information provided a suitable framework for predicting chemical parameters associated with acidification sensitivity and marine deposition (including alkalinity, chloride and base cation concentrations).
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available