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Updated: Jul 3, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Using field data and weight of evidence to develop water quality criteria
Susan M Cormier1, John F Paul, Robert L Spehar
1U.S. Environmental Protection Agency, Office of Research and Development, 26 W Martin Luther King Drive, MS-A 110, Cincinnati, Ohio 45268, USA. Cormier.Susan@epa.gov
Abstract:
In the United States, ambient aquatic life water quality criteria are derived using guidelines developed in 1985 that include a clear and consistent methodology using data from standard toxicity tests. The methodology from these guidelines has been successful, but a broader methodology is needed because some effects of pollutants do not lend themselves to conventional toxicity testing. Criterion assessment is proposed as that methodology. In criterion assessment, a specific environmental goal is translated into a measurable benchmark of effect that is used together with a modeled exposure-response relationship to estimate a range of exposures that will achieve the specific goal. The model of the exposure-response relationships and the benchmark effect are developed from field data and laboratory data using multiple analytical methods. Then the model is solved for the effect, thereby estimating the criterion, an upper threshold for acceptable exposures. The resulting candidate criteria are synthesized to select criteria and other benchmark values, such as remedial goals. The criterion assessment process is illustrated using the US Environmental Protection Agency Framework for Developing for Suspended and Bedded Sediments Water Quality Criteria, which recommends developing alternative candidate criterion values and then evaluating them to select a final criterion. Candidate criteria may be derived from models of field observations, field manipulations, laboratory tests, or empirical and theoretical models. Final selection of a criterion uses a weight-of-evidence comparison that engenders confidence because causal associations are confirmed on the basis of different assumptions, independent data sets, and varied statistical methods, thereby compensating for the concerns raised by individual studies and methods. Thus, it becomes possible to specify criteria for agents with biological or physical modes of action, as well as those with chemical modes of action, to best achieve environmental goals.
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