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Input data for chloride-specific conductance regression models

This data set includes input data for the development of regression models to predict chloride from specific conductance (SC) data at 56 U. S. Geological Survey water quality monitoring stations in the eastern United States. Each site has 20 or more simultaneous observations of SC and chloride. Data were downloaded from the National Water Information System (NWIS) using the R package dataRetrieval. Datasets for each site were evaluated and outliers were removed prior to the development of the regression model. This file contains only the final input dataset for the regression models. Please refer to Moore and others (in review) for more details. Moore, J., R. Fanelli, and A. Sekellick. In review. High-frequency data reveal deicing salts drive elevated conductivity and chloride along with pervasive and frequent exceedances of the EPA aquatic life criteria for chloride in urban streams. Submitted to Environmental Science and Technology.

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Author(s) Rosemary M Fanelli orcid, Andrew J Sekellick orcid, Joel Moore
Publication Date 2019-11-04
Beginning Date of Data 1953-09-17
Ending Date of Data 2018-09-28
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DOI https://doi.org/10.5066/P9YN2QST
Citation Fanelli, R.M., Sekellick, A.J., and Moore, J., 2019, Input data for chloride-specific conductance regression models: U.S. Geological Survey data release, https://doi.org/10.5066/P9YN2QST.
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Metadata Date 2020-08-21
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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2021-11-19T04:42:53.907Z