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.
| Original language | English |
|---|---|
| Pages (from-to) | 4323-4335 |
| Number of pages | 13 |
| Journal | Biogeosciences |
| Volume | 9 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 6 Clean Water and Sanitation
Keywords
- Metals
- organic carbon
- modeling
- lead
- zinc
- chromium
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver