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Chloride-specific conductance regression model forms for estimating high-frequency chloride concentrations

Metadata Updated: July 6, 2024

The file "Chloride_specific_conductance_regression_model_forms_for_estimating_high-frequency_chloride_concentrations.csv" contains the regression equation forms for two types of regressions: 1) single linear (SLR) and 2) piecewise (or segmented; SEG) regression between specific conductance (SC) and chloride (Cl) concentrations for 56 USGS water-quality monitoring stations across the eastern United States, plus four regional regressions developed by pooling data for sites within a region (see Moore and others (in review) for more information). Some sites, and all regions, have both SLR and SEG models reported in this table. The analysis included in the Moore and others (in review) study used results from the SLR models if those are the only model reported, or the SEG models are both reported. This data set includes the slope, intercept, model correlation coefficient (R2) and the number of observations used to develop the regression equation for the SLR models. For the SEG models, information on the slopes and intercepts for the two linear segments are included in addition to the coefficient of determination (R2) and number of observations. Breakpoint estimates (the point separating the two line segments) and uncertainties are only reported for the SEG models. 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.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
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Identifier USGS:5d824170e4b0c4f70d058e3a
Data Last Modified 20200821
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
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Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -86.001,30.2211,-69.5215,42.9725
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash bd9e759d948a82b455008b82c35cd4967ca91abcbd901fdd2579def8fdbbaab9
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