In water quality management, mathematical models are used to understand ecological processes, to predict aquatic ecosystem dynamics, to evaluate management alternatives/climatic scenarios, and to support the policy making process. Environmental models involve substantial uncertainty due to their structure, unknown parameters, and errors associated with calibration data and other inputs. This research program aims to address the urgent need for credible modelling tools by combining environmental mathematical modelling with Bayesian analysis. Specifically, we will develop sediment diagenesis models for the Georgian Bay and the Hamilton Harbour to evaluate the likelihood of an increased nutrient release from the sediments to delay their response to external nutrient loading reduction efforts. The two systems were selected due to their variant degree of eutrophication problems and multitude of anthropogenic stressors (urbanization, agriculture) in the corresponding watersheds. The modelling products of this project will benefit tremendously our industrial partner, as they have broad applicability to Canadian Agencies that need scientifically-robust projections to make decisions that have considerable socioeconomic implications. Sound environmental management can only result from an in-depth assessment of political/social factors, scientific knowledge, and economic impacts. The proposed methodological framework can be very useful in this direction and can facilitate decisions for sound resource allocation.
University of Toronto
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