||Nutrients are the number one water pollution problem for U.S. lakes, reservoirs, and
ponds. Excessive nutrients, such as nitrogen and phosphorus, lead to eutrophication,
a condition that can include low oxygen levels, noxious algal blooms, and fish kills.
Since eutrophication is a condition that manifests itself differently in different
systems, there is not a criterion variable with a clear threshold that can be used
to set the criterion level. This dissertation presents an approach to address the
question: How should States and Tribes choose nutrient criteria to determine eutrophication-related
impairments of the designated use? To address this question I used a combination
of water quality modeling and decision analysis to determine the optimal nutrient
criterion variables and levels. To choose criterion variables that are predictive
of the designated use, I utilized statistical models (structural equation models,
multiple regression, and binomial regression model) to link the measured water quality
variables to expert elicited categories of eutrophication and the designated uses.
These models were applied successfully to single waterbodies, the Kissimmee Chain-of-Lakes
region, and the State of North Carolina to assess which candidate criterion variables
were the most predictive. Additionally, the models indicated that the variables that
were most predictive of eutrophication were also the most predictive of the designated
use. Using the predictive nutrient criteria variables, I applied a decision-analytic
approach to nutrient criteria setting in North Carolina. I developed a nutrient criteria
value model that included two submodels, a water quality model and a multiattribute
value model. The submodels were parameterized using a combination of water quality
data, expert elicitation data, and utility assessments. The outcome of the nutrient
criteria value model is the overall expected value for a criterion level choice; the
optimal criterion level would be the choice that maximized the expected value. Using
the preferences of North Carolina environmental decision-makers and a total phosphorus
criterion variable, the optimal criterion level was between 0.03 mg/L and 0.07 mg/L.
Ultimately, I hope this research will establish methodology used to set appropriate
water quality criteria.