A predictive approach to nutrient criteria.
Violation of a water quality standard triggers the need for a total maximum daily load (TMDL); this should result in actions that improve water quality, but sometimes at significant cost. If the standard is well-conceived, a designated-use statement characterizes societal values, and a criterion provides a measurable surrogate for designated use. This latter provision means that scientists measure the criterion and view violations of the criterion as equivalent to noncompliance with the designated use. However, if a criterion is not a good indicator of designated use, it is apt to result in misallocation of the limited resources for water quality improvement through the TMDL process. This concern provides the basis for our assessment of the national nutrient criteria strategy recently proposed by the U.S. EPA. We acquired data sets for four case studies (Lake Washington, Neuse River Estuary, San Francisco Bay, and Lake Mendota) and then used expert elicitation to quantify designated-use attainment for each case. Applying structural equation modeling, we identified good water quality criteria as the best predictors of the designated use elicited response variable. Further, we used the model to relate the level (concentration) of each criterion to the probability of compliance with the designated use; this provides decision-makers with an estimate of risk associated with the criterion level, facilitating the selection of appropriate water quality criteria.
Reckhow
K H
KH
Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina 27708, USA. reckhow@duke.edu
Arhonditsis
G B
GB
Kenney
M A
MA
Hauser
L
L
Tribo
J
J
Wu
C
C
Elcock
K J
KJ
Steinberg
L J
LJ
Stow
C A
CA
McBride
S J
SJ
D005544:Forecasting; D008962:Models, Theoretical; D009584:Nitrogen; D010758:Phosphorus; D011786:Quality Control; D045483:Rivers; D014481:United States; D014484:United States Environmental Protection Agency; D014876:Water Pollution / Q000517:prevention & control* / Q000706:statistics & numerical data*
D010758:Phosphorus; D009584:Nitrogen