Controls on dissolved organic carbon concentrations in surface waters assessed using INCA-C, the integrated catchments model for carbon

This thesis presents the development and application of a new model of dissolved organic carbon (DOC) in soils and surface waters. The two main goals of the project were to add to our understanding of the processes controlling [DOC] in natural and semi-natural catchments and to advance the discipline of environmental modelling. These goals were met through completion of the following objectives. (i) Development of a conceptual model based on long-term central Ontario stream monitoring data of the processes controlling DOC in soils and surface waters at a landscape scale; (ii) Development and verification of a software code implementing the conceptual model; (iii) Application of the model to sites where in-lake processes and atmospheric deposition sulphate (S042-) and chloride (Cl-) play a greater role in controlling [DOC] than was seen in central Ontario streams; (iv) Testing the hypothesis that complex process-based models can be calibrated to any data set and exploring other issues related to calibration of environmental models; (v) Assessing uncertainty in forecasts of surface water [DOC] under a changing climate is evaluated.; Accomplishing these objectives furthered the goal of understanding the processes controlling surface water [DOC] in natural and semi-natural catchments in North America and Europe. Seasonal to decadal scale variability in surface water [DOC] is controlled by the interaction of temperature, precipitation, solar radiation and atmospheric deposition of inorganic anions. Changing climate is expected to alter surface water [DOC]. Better catchment monitoring is required to parameterize the model and constrain predictions of future [DOC]. While the effects of climate on surface water [DOC] are well understood, further work is required to elucidate the mechanisms by which atmospheric deposition of S042- and Cl- control surface water [DOC]. The model, calibration strategy and model chains developed in this thesis have advanced the discipline of environmental modelling. The calibration process has been shown to be incapable of fitting complex process-based models to random data. Model chains have been developed linking climate change, rainfall-runoff and catchment biogeochemistry. These model chains are a promising tool for combining the process understanding in several areas of environmental science to predict future surface water chemistry.; Key Words. dissolved organic carbon, climate change, model, soil, surface waters.