Modeling stream dissolved organic carbon concentrations during spring flood in the boreal forest: A simple empirical approach for regional predictions
2010 (English)In: Journal of Geophysical Research, ISSN 0148-0227, E-ISSN 2156-2202, Vol. 115, no G1, G01012- p.Article in journal (Refereed) Published
Changes in dissolved organic carbon (DOC) concentration are clearly seen for streams in which chemistry is measured on a high-frequency/episode basis, but these high-frequency data are not available in long-term monitoring programs. Here we develop statistical models to predict DOC concentrations during spring flood from easily available geographic information system data and base flow chemistry. Two response variables were studied, the extreme DOC concentration and the concentration during peak flood. Ninety-seven streams in boreal Scandinavia in two different ecoregions with substantially different mean water chemistry and landscape characteristics (covering a large climatic gradient) were used to construct models where 56% of the extreme DOC concentration and 63% of the concentration during peak flood were explained by altitude. This highlights important regional drivers (gradients in altitude, runoff, precipitation, temperature) of material flux. Spring flood extreme DOC concentration could be predicted from only base flow chemistry (r(2) = 0.71) or from landscape data (r(2) = 0 .74) but combining them increased the proportion of explained variance to 87%. The "best" model included base flow DOC (positive), mean annual runoff (negative), and wetland coverage (positive). The root mean square error was 1.18 mg L-1 for both response variables. The different ecoregions were successfully combined into the same regression models, yielding a single approach that works across much of boreal Scandinavia.
Place, publisher, year, edition, pages
2010. Vol. 115, no G1, G01012- p.
dissolved organic carbon, model, spring flood, base flow, landscape characteristics, Sweden
IdentifiersURN: urn:nbn:se:uu:diva-140492DOI: 10.1029/2009JG001013ISI: 000275858700001OAI: oai:DiVA.org:uu-140492DiVA: diva2:383688