Freshwater salinization is an emerging issue for freshwater environments in the Chesapeake Bay, USA region. Salinization is often described by measurements of specific conductance (SC). This data release contains specific conductance observations collected by multiple regional agencies for streams within the Chesapeake Bay Watershed. This inventory compiles and harmonizes data from the Water Quality Portal (WQP), which is a data repository developed by the National Water Quality Monitoring Council and supported by the U.S. Environmental Protection Agency and U.S. Geological Survey, and the U.S. Geological Survey National Water Information System (NWIS). Both discrete measures of SC, which are single measures taken on a particular time and day, and continuous measures of SC, which are repeated measures of SC taken at regular, short intervals, such as 15-minute or hourly intervals, were compiled for this data release. The discrete data were also processed to screen out non-relevant observations and harmonize units. The WQP uses "MonitoringLocationIdentifier" to identify each unique site and monitoring activities, and this term is used throughout the data release to differentiate among unique sites and monitoring activities as well. The data release includes four items: 1. ["Site_inventory_for_specific_conductance_measures.csv"]: This is a site inventory of all locations where SC data had been collected and compiled for the data release. This file includes information on the monitoring location (coordinates, state, and county), the organization responsible for the data collection, the type of data available (discrete, continuous, or both) and its unique monitoring location and activity. 2. ["Discrete_specific_conductance_results.txt"]: This file contains all discrete SC observations. Identifying information (coordinates, monitoring location name and identifier), along with the observation value, units, and multiple flagging columns which denoted whether any changes were made to the observation or units during the processing steps. Full details are included in the "readme_file_for_Ches_Bay_specific_conductance_inventory.pdf" file. 3. ["Continuous_specific_conductance_results.zip"]: This zipped folder contains 89 .csv files for all the continuous USGS SC data available in the Chesapeake Bay watershed. Each file name includes each unique MonitoringLocationIdentifier. 4. ["readme_file_for_Ches_Bay_specific_conductance_inventory.pdf"]: This document describes all the processing and harmonization steps to generate the site inventory and discrete SC dataset, and for downloading the high frequency SC datasets.

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.

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.

This dataset provides analysis results for status values representing the period of 2015 through 2017 for six indicators of river and stream condition in the Chesapeake Bay watershed. Status (condition at a point in time) was calculated yearly for metrics of the following indicators: stream nutrients and suspended sediment, salinity, temperature, hydromorphology, streamflow and biological assemblages. These yearly status values were then averaged to create mean status values for each indicator and metric. The mean status values were then used to score indicator sites as high quality, low quality, or intermediate quality. Additionally, the relationship between mean status values and three land use/land cover types (developed, agriculture and urban) were analyzed via simple linear regression. Detailed data preparation information, analytical methods and results are presented and discussed in the associated Scientific Investigative Report (https://doi.org/10.3133/sir20255072).

Drainage basins of the 123 Non-Tidal Monitoring Stations in the Chesapeake Bay Watershed.

Drainage basins of the 123 Non-Tidal Monitoring Stations in the Chesapeake Bay Watershed.

This data release collates stream water temperature observations across the Chesapeake Bay watershed from the USGS National Water Information System (NWIS), Water Quality Portal (WQP) and the USGS Aquarius (AQ) Time-Series database. Data retrieved from NWIS consists of aggregate (minimum, maximum and mean) daily values and continuous data from USGS monitoring stations. Values from the WQP contain discrete data from multiple agencies. The dataset compiled from AQ includes miscellaneous stream temperature observations collected during discharge measurements. This stream temperature data release was completed to support the USGS goal to make scientific data publicly usable, easily discoverable, and widely available. A subset of these data will be used and published in the future to assess the status and trends of key indicators of stream health in the Chesapeake Bay watershed.

This data release collates stream water temperature observations across the Chesapeake Bay watershed from the USGS National Water Information System (NWIS), Water Quality Portal (WQP) and the USGS Aquarius (AQ) Time-Series database. Data retrieved from NWIS consists of aggregate (minimum, maximum and mean) daily values and continuous data from USGS monitoring stations. Values from the WQP contain discrete data from multiple agencies. The dataset compiled from AQ includes miscellaneous stream temperature observations collected during discharge measurements. This stream temperature data release was completed to support the USGS goal to make scientific data publicly usable, easily discoverable, and widely available. A subset of these data will be used and published in the future to assess the status and trends of key indicators of stream health in the Chesapeake Bay watershed.

Each year from 2021 to 2024, teams from the U.S. Geological Survey and the Virginia Polytechnic Institute and State University (Virginia Tech) studied 30 streams with a targeted gradient of land use and conservation practices across the Chesapeake Bay Watershed. The four years of the study cover the following geographic areas and land use characteristics (generally referred to as typologies in associated data sets): Shenandoah Valley and Ridge pasture Delmarva row crop Pennsylvania and Maryland Piedmont mixed agriculture Maryland-Washington, DC-Virginia developed Piedmont The data here provide site names and basic identifiers that are commonly used in the many data releases associated with the larger study and serve as a key to match site ID with locations and data. Specific site location is limited to a HUC12 scale due to requests of privacy from landowners who granted access and permission.

This data release presents chemical results from investigations of surface-water quality in the Potomac River watershed (encompassing Washington, D.C. and parts of West Virginia, Virginia, Pennsylvania, and Maryland) conducted during low-flow conditions in July through September of 2022 and modeling results that support interpretative products. Water-quality sampling: A sampling campaign was conducted at 32 stream sites throughout the watershed (Table 1). A suite of field parameters and inorganic and organic chemical characteristics at each site were characterized using seven separate analytical methods at five laboratories (Table 2). The water-quality results are presented in Tables 3 and 4. Analytical methods and laboratories used were (1) major anions by ion chromatography at the U.S. Geological Survey Integrated Water Chemistry Assessment Laboratory in Boulder, Colorado (USGSIWCAL); (2) full fluorescence spectra in vectorized format, excitation-emission-matrix (EEM) fluorescence spectroscopy dissolved organic carbon (DOC), and total dissolved nitrogen (TDN) at the U.S. Geological Survey California Water Science Center Organic Matter Research Laboratory in Sacramento, California (CAWSCOMRL); (3) per-and polyfluoroalkyl substances (PFAS) using liquid chromatography with tandem mass spectrometry (LC-MS/MS), at the U.S. Geological Survey National Water Quality Laboratory in Denver, Colorado (USGSNWQL); (4) pesticides (PEST) by LC-MS/MS or gas chromatography with tandem mass spectrometry (GS-MS/MS) at the U.S. Geological Survey Organic Research Laboratory (USGSOGCA); (5) pharmaceuticals (PHARM) using LC-MS/MS at the USGSNWQL; and (6) Major elements and trace elements (TEs) using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma-optical emission spectrometry (ICP-OES) at the USGSIWCAL. Enzyme-Linked Immunosorbent Assay (ELISA) analyses were additionally performed at the U.S. Geological Survey Strategic Laboratory Science Branch in Boulder, Colorado (USGSSLSB) for the herbicides atrazine and glyphosate, the insecticide imidacloprid, and the consumer product chemical linear alkylbenzene sulfonate. Three analytes (atrazine, piperonyl butoxide, thiabendazole, and the thiabendazole surrogate standard thiabendazole-d4) were analyzed by the U.S. Geological Survey National Water Quality Laboratory (USGSNWQL) included with the pharmaceutical data in addition to being analyzed by the USGSOGCA with the pesticide data. The USGSNWQL results for these analytes were coded as replicate samples and additional time offsets were applied to create distinct times for these sample results. Samples were collected according to U.S. Geological Survey (USGS) protocols and procedures. A field blank and field replicate was collected for every analytical method, a matrix spike for PFAS, PHARM, and PEST was performed at three sites for quality assurance. Most sites were only sampled once for each parameter with the exception of four sites that had to be resampled due to samples arriving too warm to be processed for PFAS and PHARM parameters. Therefore samples for the remaining parameters were collected twice at these four sites. Water-quality modeling: This data release also contains inputs for and results from a wastewater reuse model that used data compiled from multiple sources to calculate the following estimates for each non-tidal National Hydrography Dataset Version 2.1 (NHDPlus V2) stream segment in the Potomac River watershed: (1) accumulated wastewater as a percent of total streamflow (ACCWW%) from municipal as well as municipal plus industrial PFAS wastewater treatment plants; and (2) predicted environmental concentrations (PECs, in nanograms per liter) of 14 pesticides and eight PFAS as well as the sum of the eight PFAS. ACCWW% values were calculated for mean-monthly and mean-annual streamflow conditions for municipal wastewater treatment plants (model results table: Table5_PotomacACCWW_municipal.csv) as well as