Abstract

Long-term data series (1996–2009) for eleven acidic headwater streams ( < 10 km 2 ) in Sweden were ana- lyzed to determine factors controlling concentrations of trace metals. In-stream chemical data as well climatic, flow, and deposition chemistry data were used to develop models pre- dicting concentrations of chromium (Cr), lead (Pb), and zinc (Zn). Data were initially analyzed using partial least squares to determine a set of variables that could predict metal con- centrations across all sites. Organic matter (as absorbance) and iron related positively to Pb and Cr, while pH related negatively to Pb and Zn. Other variables such as conduc- tivity, manganese, and temperature were important as well. Multiple linear regression was then used to determine mini- mally adequate prediction models which explained an aver- age of 35 % (Cr), 52 % (Zn), and 72 % (Pb) of metal variation across all sites. While models explained at least 50 % of vari- ation in the majority of sites for Pb (10) and Zn (8), only three sites met this criterion for Cr. Investigation of varia- tion between site models for each metal revealed geographi- cal (altitude), chemical (sulfate), and land-use (silvaculture) influences on predictive power of the models. Residual anal- ysis revealed seasonal differences in the ability of the mod- els to predict metal concentrations as well. Expected future changes in model variables were applied and results showed the potential for long-term increases (Pb) or decreases (Zn) for trace metal concentrations at these sites.

Keywords

Metals, organic carbon, modeling, lead, zinc, chromium

Published in

Biogeosciences
2012, volume: 9, number: 11, pages: 4323-4335

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