Modelling the effects of climate on long-term patterns of dissolved organic carbon concentrations in the surface waters of a boreal catchment

摘要

Dissolved organic carbon concentrations ([DOC]) in surface waters areincreasing in many regions of Europe and North America. These increases arelikely driven by a combination of changing climate, recovery fromacidification and change in severity of winter storms in coastal areas.INCA-C, a process-based model of climate effects on surface water [DOC], wasused to explore the mechanisms by which changing climate controls seasonalto inter-annual patterns of [DOC] in the lake and outflow stream of a smallFinnish catchment between 1990 and 2003. Both production in the catchmentand mineralization in the lake controlled [DOC] in the lake. Concentrationsin the catchment outflow were controlled by rates of DOC production in thesurrounding organic soils. The INCA-C simulation results were compared tothose obtained using artificial neural networks (ANN). In general, "blackbox" ANN models provide better fits to observed data but process-basedmodels can identify the mechanism responsible for the observed pattern. Astatistically significant increase was observed in both INCA-C modelled andmeasured annual average [DOC] in the lake. This suggests that some of theobserved increase in surface water [DOC] is caused by climate-relatedprocesses operating in the lake and catchment. However, a full understandingof surface water [DOC] dynamics can only come from catchment-scaleprocess-based models linking the effects of changing climate and depositionon aquatic and terrestrial environments.