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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.
Author(s) |
Rosemary M Fanelli |
Publication Date | 2019-11-04 |
Beginning Date of Data | 1953-09-17 |
Ending Date of Data | 2018-09-28 |
Data Contact | |
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. |
Metadata Contact | |
Metadata Date | 2020-08-21 |
Related Publication | Loading... |
Citations of these data | Loading https://doi.org/10.1021/acs.est.9b04316 |
Access | public |
License | http://www.usa.gov/publicdomain/label/1.0/ |
Harvest Date: 2021-11-19T04:42:53.907Z