Freshwater salinization is an emerging water quality issue for non-tidal streams and rivers in the Chesapeake Bay watershed (CBW), USA region. A model was developed to predict specific conductance (SC; a proxy for salinity) conditions across the CBW and departures from background SC. Discrete observations of SC from 1999-2016 were acquired from a published SC data inventory and explanatory variables describing sources of SC were compiled from several sources. Random forests modeling was conducted to predict SC at four time periods (1999-2001, 2004-2006, 2009-2011, and 2014-2016) at all non-tidal National Hydrography Dataset Plus Version 2.1 (NHDPlusV2.1; 1:100K scale) stream reaches. These predictions were then compared to a national background SC dataset to determine relative departures from background SC for each NHDPlusV2.1 reach ID. This data release contains model input data, model output data, and predictions of SC. This data release contains the following three files: 1."Model_input.csv": Contains SC observations, explanatory variables, and additional columns relevant to the model application. 2. "Model_output.csv": Contains predicted SC values for the reaches contained in either the testing or training datasets, as well as the feature contributions for each explanatory variable. 3. "Model_predictions.csv": Contains predicted SC, predicted/expected (or P/E) ratios, and departure categories for all non-tidal reach IDs in the CBW for the four time periods.

Measured, continuous, and intermittent Allegheny River conductivity by site. This dataset is associated with the following publication: Brown, K., G. Norris, K. Kovalcik, A. Kamal, K. Patnode, and M. Landis. Signal Decomposition of Conductivity Sensor Measurements on the Allegheny River, Pennsylvania. JOURNAL OF ENVIRONMENTAL ENGINEERING. American Society of Civil Engineers (ASCE), Reston, VA, USA, 144(10): 04018103, (2018).

There are 3 data sets. Two zip files contain paired biological (benthic macroinvertebrate genera) (Data Biological.zip) and water quality data (Data Environmental.zip). These were used to estimate background specific conductivity from these state data and estimate the HC05 using the field based extirpation concentration method (USEPA 2011). The zipped files (Griffith ion MG20150729) contains two csv miles with ions summaries and ion and specific conductivity data from the combined EPA survey data. This dataset is associated with the following publication: Cormier, S., L. Zheng, R. Novak, and C. Flaherty. A flow-chart for developing water quality criteria from two field-based methods. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 633: 1647-1656, (2018).

This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. The htmls files can be opened with a browser such as Internet Explorer or Chrome. This dataset is associated with the following publication: McManus, M., E. DAmico, E. Smith, R. Polinsky, J. Ackerman, and K. Tyler. Variation in stream network relationships and geospatial predictions of watershed conductivity. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 39(4): 1-18, (2020).

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.

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.

This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. The htmls files can be opened with a browser such as Internet Explorer or Chrome. This dataset is associated with the following publication: McManus, M., E. DAmico, E. Smith, R. Polinsky, J. Ackerman, and K. Tyler. Variation in stream network relationships and geospatial predictions of watershed conductivity. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 39(4): 1-18, (2020).

This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. The htmls files can be opened with a browser such as Internet Explorer or Chrome. This dataset is associated with the following publication: McManus, M., E. DAmico, E. Smith, R. Polinsky, J. Ackerman, and K. Tyler. Variation in stream network relationships and geospatial predictions of watershed conductivity. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 39(4): 1-18, (2020).

This dataset shows the observed and predicted values of specific conductivity at 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. This dataset is associated with the following publication: McManus, M., E. DAmico, E. Smith, R. Polinsky, J. Ackerman, and K. Tyler. Variation in stream network relationships and geospatial predictions of watershed conductivity. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 39(4): 1-18, (2020).

This is a Data Release containing conductivity and water temperature data for selected springs in the headwaters of the Potomac River basin. This work is supported by USGS Chesapeake Bay studies.