Selection of water quality variables for nutrient criteria using structural equation modeling

The Environmental Protection Agency (EPA) considers over 5,000 of the waters in the U.S. impaired from eutrophication.  Eutrophication is a process fueled by excess nitrogen and phosphorous that causes problems such as anoxia and noxious algal blooms.  To protect the nation’s waterbodies from impairment, the Clean Water Act requires states to establish water quality standards.  This study builds on previous research by Reckhow et al. (2005) and addresses EPA’s national nutrient strategy, which requires states to protect designated uses, or the water quality goals, by establishing nutrient criteria.   By nutrient criteria, EPA means any measurable water quality variable(s) that can be used to detect eutrophication impairments (i.e. phosphorous, algae, etc.) and the associated criteria level.  The method we used, termed predictive nutrient criteria, is a procedure to statistically link water quality variables with the designated use.  Since there is no existing method for determining whether a waterbody is meeting its designated uses, judgments are needed to help understand what characteristics of a lake lead to attainment. Using an expert’s judgments, coupled with water quality data, we developed a statistical model, using structural equation modeling, which links eutrophication and designated use attainment.  The statistical model provides the variable(s) that are most predictive of designated use attainment. This study does not address the selection of criteria levels.   As a demonstration of our method, we reassessed North Carolina’s nutrient standards for lakes and reservoirs.  There were multiple competing models that had to be reconciled.  Ultimately we determined the most predictive criteria was total phosphorous.