Cross-scale ensemble projections of dissolved organic carbon dynamics in boreal forest streams
2014 (English)In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 42, no 9-10, 2305-2321 p.Article in journal (Refereed) Published
Climate is an important driver of dissolved organic carbon (DOC) dynamics in boreal catchments characterized by networks of streams within forest-wetland landscape mosaics. In this paper, we assess how climate change may affect stream DOC concentrations ([DOC]) and export from boreal forest streams with a multi-model ensemble approach. First, we apply an ensemble of regional climate models (RCMs) to project soil temperatures and stream-flows. These data are then used to drive two biogeochemical models of surface water DOC: (1) The Integrated Catchment model for Carbon (INCA-C), a detailed process-based model of DOC operating at the catchment scale, and (2) The Riparian Integration Model (RIM), a simple dynamic hillslope scale model of stream [DOC]. All RCMs project a consistent increase in temperature and precipitation as well as a shift in spring runoff peaks from May to April. However, they present a considerable range of possible future runoff conditions with an ensemble median increase of 31 % between current and future (2061–2090) conditions. Both biogeochemical models perform well in describing the dynamics of present-day stream [DOC] and fluxes, but disagree in their future projections. Here, we assess possible futures in three boreal catchments representative of forest, mire and mixed landscape elements. INCA-C projects a wider range of stream [DOC] due to its temperature sensitivity, whereas RIM gives consistently larger inter-annual variation and a wider range of exports due to its sensitivity to hydrological variations. The uncertainties associated with modeling complex processes that control future DOC dynamics in boreal and temperate catchments are still the main limitation to our understanding of DOC mechanisms under changing climate conditions. Novel, currently overlooked or unknown drivers may appear that will present new challenges to modelling DOC in the future.
Place, publisher, year, edition, pages
2014. Vol. 42, no 9-10, 2305-2321 p.
Ensemble projections, Climate change, Dissolved organic carbon, Boreal forest, Bias correction, RCM
Climate Research Physical Geography Oceanography, Hydrology, Water Resources
IdentifiersURN: urn:nbn:se:uu:diva-223465DOI: 10.1007/s00382-014-2124-6ISI: 000336983900004OAI: oai:DiVA.org:uu-223465DiVA: diva2:713116