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Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. (Miljöanalys)
Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Sweden.
U.S. Geological Survey, USA.
Department of Ecosystem Science and Management, Pennsylvania State University, USA.
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2015 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 520, 260-269 p.Article in journal (Refereed) Published
Abstract [en]

Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type).

Catchment area (0.18–47,000 km2) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6 years of monthly water quality observations between 1990 and 2010. Statistically significant models (p < 0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3 mg l− 1 (13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17 mg l− 1 year− 1 (1.6% year− 1).

Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality.

Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.

Place, publisher, year, edition, pages
2015. Vol. 520, 260-269 p.
National Category
Environmental Sciences
Research subject
Earth Science with specialization in Environmental Analysis
URN: urn:nbn:se:uu:diva-234354DOI: 10.1016/j.scitotenv.2015.03.041ISI: 000353509500028PubMedID: 25817763OAI: oai:DiVA.org:uu-234354DiVA: diva2:756360
Available from: 2014-10-17 Created: 2014-10-17 Last updated: 2016-02-11Bibliographically approved
In thesis
1. Water Quality in Swedish Lakes and Watercourses: Modeling the Intra-Annual Variability
Open this publication in new window or tab >>Water Quality in Swedish Lakes and Watercourses: Modeling the Intra-Annual Variability
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Water quality is of great importance for ecosystems and society. This thesis characterized and modeled the variation in several key constituents of Swedish surface waters, with particular consideration given to intra-annual variability and sensitivity to climate change. Cyanobacterial data from 29 lakes and basins as well as total organic carbon (TOC) from 215 watercourses were used. Extensive data on catchment characteristics, morphometry, discharge, temperature and other water chemistry data were also analyzed. Models characterizing the seasonality in cyanobacterial concentration and relative cyanobacterial abundance were developed with common lake variables. Concentrations of TOC, iron and absorbance were simulated using discharge, seasonality and long-term trend terms in the Fluxmaster modeling system. Spatial patterns in these model terms were investigated, and the sensitivity of cyanobacteria and TOC to future climate was explored.

Nutrients were the major control on cyanobacterial concentration seasonality, while temperature was more important for relative cyanobacterial abundance. No cyanobacterial blooms occurred below a total phosphorus threshold of 20 µg l-1. Discharge and seasonality explained much of the intra-annual variability in TOC, but catchment characteristics could only explain a limited amount of the spatial patterns in the sensitivity to these influences. North of Limes Norrlandicus the discharge term had a larger impact on the TOC concentration in large catchments than in small catchments, while south of Limes Norrlandicus the seasonality had a larger impact in small catchments than in larger catchments. According to the climate change scenarios, both TOC and cyanobacterial concentrations will be higher in the future. The cyanobacterial dominance will start earlier and persist longer. The spring TOC concentration peak will come earlier. The changes in TOC loads are more uncertain due to predicted declines in discharge.

Parsimonious statistical regression models could explain observed variability in cyanobacteria and TOC. For predictions, these models assume that future aquatic ecosystems will exhibit the same sensitivity to major drivers as in the past. If this proves not to be the case, the modeling can serve as a sentinel for changing catchment function as indicated by degradation in model performance when calibrations on older data are used to model later observations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. 39 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1194
Total organic carbon, cyanobacteria, seasonality, water quality modeling, climate change, surface water
National Category
Environmental Sciences Oceanography, Hydrology, Water Resources
Research subject
Earth Science with specialization in Environmental Analysis
urn:nbn:se:uu:diva-234480 (URN)978-91-554-9078-2 (ISBN)
Public defence
2014-12-05, Hambergsalen, Villavägen 16, Uppsala, 10:00 (English)
Available from: 2014-11-14 Created: 2014-10-20 Last updated: 2015-02-03

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Hytteborn, Julia K.Bishop, Kevin H.
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