Assessing Skill of Eutrophication Models for Water Quality Managers

The value of predictive mechanistic models of nutrients, primary production, and dissolved oxygen has long been recognized by natural resource and water quality managers for their utility in assisting in the evaluation of the potential effectiveness of nutrient management in reducing cultural eutrophication. However, there is also a corresponding need to assess the degree of confidence one has in the model projections. This is particularly true as mathematical models of eutrophication continue to be used to determine the total maximum daily loads (TMDLs) necessary to attain water quality standards for dissolved oxygen and since the potential cost to implement these TMDLs can be a significant cost burden to the affected community. A review of the literature suggests that a number of possible statistical measures are available which can be used by modelers and water quality managers to assess model skill and help quantify uncertainty in model projections. This paper presents an overview of these measures and suggests that no single metric is suitable for assessing model skill. Instead, a combination of quantitative and qualitative measures should be used for skill assessment and defining model uncertainty.