A field-based characterization of conductivity in areas of minimal alteration: A case example in the Cascades of northwestern United States.

Sci Total Environ

U.S. Environmental Protection Agency, Office of Water, Office of Science and Technology, Health and Ecological Criteria Division, 1200 Pennsylvania Avenue, N. W., Washington, DC 20460, USA.

Published: August 2018

The concentration of salts in streams is increasing world-wide making freshwater a declining resource. Developing thresholds for freshwater with low specific conductivity (SC), a measure of dissolved ions in water, may protect high quality resources that are refugia for aquatic life and that dilute downstream waters. In this case example, methods are illustrated for estimating protective levels for streams with low SC. The Cascades in the Pacific Northwest of the United States of America was selected for the case study because a geophysical model indicated that the SC of freshwater streams was likely to be very low. Also, there was an insufficient range in the SC data to accurately derive a criterion using the 2011, US Environmental Protection Agency field-based extirpation concentration distribution method. Instead, background and a regression model was used to estimate chronic and acute SC levels that could extirpate 5% of benthic invertebrate genera. Background SC was estimated at the 25th centile (33μS/cm) of the measured data and used as the independent variable in a least squares empirical background-to-criteria (B-C) model. Because no comparison could be made with effect levels estimated from a paired SC and biological data set from the Cascades, the lower 50% prediction limit (PL) was identified as an example chronic water quality criterion (97μS/cm). The maximum exposure threshold was estimated at the 90th centile SC of streams meeting the chronic SC level. The example acute SC level was 190μS/cm. Because paired aquatic life and SC data are often sparse, the B-C method is useful for developing SC criteria for other systems with limited data.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6880308PMC
http://dx.doi.org/10.1016/j.scitotenv.2018.02.018DOI Listing

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