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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...
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This data set includes estimated chloride concentrations for the 93 USGS water quality monitoring stations located across the eastern United States. Chloride concentrations were predicted using regression equations that established the relationship between simultaneous measurements of chloride and specific conductance (SC). Site-specific models were developed and applied when data were available, and regional regression models were used where there were insufficient data available to establish a site-specific regression model. These models were applied to high-frequency SC data sets to produce high-frequency predicted chloride concentrations at 2-minute to 1-hour intervals, depending on the frequency at which SC...
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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...
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This data set contains 18 metrics used to describe patterns in specific conductance (SC) and chloride concentrations in 93 streams located across the eastern United States. These data were quantified for an analysis described in Moore and others (in review). All metrics were quantified for a water year and a median was taken across all years for which data were available to provide a single value for each site. High-frequency SC and chloride were measured or estimated at sub-daily time steps from 2-minute intervals to hourly intervals (e.g., high-frequency) depending on the site. Moore, J., R. Fanelli, and A. Sekellick. In review. High-frequency data reveal deicing salts drive elevated conductivity and chloride...
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This data release makes available three data tables supporting a spatiotemporal analysis of riverine conductivity and streamflow trends within the Delaware River Basin. The listed datasets include baseflow and total flow time series for selected gaged basins, watershed attributes, water quality information and trend analysis results.


    map background search result map search result map Estimated high-frequency chloride concentrations Input data for chloride-specific conductance regression models Chloride-specific conductance regression model forms for estimating high-frequency chloride concentrations Response variables derived from predicted high-frequency chloride concentrations and specific conductance values Data supporting a spatiotemporal trend analysis of specific conductivity, streamflow, and landscape attributes of selected sub-basins within the Delaware River watershed, 1980 to 2018 Data supporting a spatiotemporal trend analysis of specific conductivity, streamflow, and landscape attributes of selected sub-basins within the Delaware River watershed, 1980 to 2018 Estimated high-frequency chloride concentrations Input data for chloride-specific conductance regression models Chloride-specific conductance regression model forms for estimating high-frequency chloride concentrations Response variables derived from predicted high-frequency chloride concentrations and specific conductance values