This data release contains relevant datasets used in the analysis for the Chesapeake Bay stressor identification project, for which results are described in Fanelli and others (in review). For this project, two existing information sources were compiled and summarized to identify key in-stream stressors reported by the scientific literature or through regulatory assessments to be likely affecting benthic macroinvertebrate community metrics in the Chesapeake Bay region: 1) the peer reviewed multi-stressor literature, in which the effects multiple in-stream stressors on benthic macroinvertebrate community metrics are simultaneously assessed; and 2) reported causes of biological impairment as listed by state or district regulatory agencies in the Environmental Protection Agency's Assessment and Total Maximum Daily Load Tracking and Implementation System (ATTAINS). This data release contains three child items: 1) "Data from the Assessment, Total Maximum Daily Load (TMDL) Tracking and Implementation System (ATTAINS) for evaluating multiple stressors affecting Chesapeake Bay Watershed rivers and streams": The ATTAINS dataset is for the Chesapeake Bay region, which was summarized for the jurisdictional impairment analysis (jurisdictions include the states of Maryland, Pennsylvania, Virginia, West Virginia, New York, and Delaware, as well as the District of Columbia). This compiled dataset contains information on a waterbody's Designated Uses, parameter impairments, and potential sources of that impairment. 2) "Multi-stressor literature summary information for Chesapeake Bay stressor identification project": A summary table of the peer-reviewed literature that was considered for the literature review meta-analysis. This dataset includes basic identifying information regarding the report, geographic location of the study, type of field study, the major source or driver that was the focus of the study, and which in-stream stressors were measured. 3) "Results from the literature review meta-analysis for the Chesapeake Stressor Identification Project": The results from the literature review meta-analysis. The dataset includes basic identifying information regarding the report, the response metric for which results were reported, the major source or driver that was the focus of the study, and whether or not the study found the stressor to be important.

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.

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.

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).

This dataset consists of 262 variables which describe various known and suspected point and non-point sources of contaminants and endocrine disrupting compounds (EDCs) throughout the Chesapeake Bay Watershed. Contaminant data was summarized to the NHDPlus Version 2.1 catchment level (1:100K). Contaminant data summarized span a time range of 2001 to 2016 and include regulated facilities, pesticides, manure and biosolids application data, mercury deposition, animal feeding applications, septic systems, landfills, and land use and land cover. These data are presented in a comma separated file, which includes all variables summarized and the NHDPlus Version 2.1 FEATUREID field (also known as COMID). The FEATUREID field can be used to relate these summaries to the NHDPlus Version 2.1 data suite for mapping and other analytical purposes. Total (TOT) and Divergent (DIV) upstream summaries were generated using the NHDPlusV2 Catchment Attribute Allocation and Accumulation Tool (CA3TV2). Using this method, upstreams summaries are generated for 82,263 of the 83,637 NHDPlus catchments in the Chesapeake Bay Watershed. These data will be used to investigate source-sink linkages between contaminant sources, water quality issues, and impacted receptor populations (e.g., smallmouth bass) throughout the Bay Watershed. Information gained from this work may also be used to evaluate the success of mitigation activities and help to prioritize new locations for mitigation, implementation of best management practices, or habitat conservation actions.

Indicators of estuarine ecosystem health – temperature, salinity, turbidity, dissolved oxygen, chlorophyll a, pH, nutrients - were sampled each month for twelve months at four sites in Georges Bay and at the bridge at the river mouth by the Tasmanian Aquaculture and Fisheries Institute (TAFI), community volunteers and Break O’Day Council staff. Another indicator, macroinvertebrate fauna, was sampled by TAFI in winter and summer, and data were obtained on pathogen levels from the Tasmanian Shellfish Quality Assurance Program.

Degraded physical habitat is a common stressor affecting river ecosystems and a primary focus of management activities, including stream restorations. In order to assess regional conditions and help prioritize management efforts, there is an ongoing need to provide estimates of different aspects of instream physical habitat conditions at spatially continuous scales. We utilized over 16,000 unique habitat assessments from multiple jurisdictions across the Chesapeake Bay watershed and created a spatially continuous nontidal habitat assessment using predictive random-forest modeling based on landscape attributes. Through this work, we produced predictions for the twelve rapid habitat metrics contained within the EPA Rapid Habitat Protocols (Barbour and others 1999), with a climate-normalized signal at timesteps corresponding to 2001, 2006, 2011, 2016, and 2019 landscape conditions. We also produced two summary habitat metrics, based on principal component analysis, that captured the majority of variability across the Chesapeake Watershed, which was also produced for 2001, 2006, 2011, 2016, and 2019. This data release contains tabular model inputs and outputs of the predictions for the twelve original rapid habitat metrics, plus two summary metrics, for all nontidal NHDPlus v2.1 1:100k catchments/stream reaches for the Chesapeake Watershed for 2001, 2006, 2011, 2016, and 2019. Data are provided in both .csv format and Apache Parquet (.parquet), a free and open-source column-oriented data storage format that is well-suited for large datasets, which enables smaller file sizes, faster reading, faster queries and data manipulations, and the ability to be read in multiple languages (e.g., R, Python, Rust, C++, Java, and more). This data release is the companion to the journal article Cashman and others (in review).

This data release contains land cover-derived statistics regarding estuarine vegetated wetland area change within estuary drainage areas along the conterminous U.S. This dataset includes net change in estuarine vegetated wetland area based on National Oceanic and Atmospheric Administration's (NOAA) Coastal Change Assessment Program (C-CAP) 1996 and 2016 land cover data. Net change was assessed between estuarine vegetated wetlands (i.e., estuarine marshes, mangroves, non-mangrove estuarine woody wetlands, and salt pannes, depending on vegetation coverage and type) and the following other landcover classes: 1) water; 2) unconsolidated shore; 3) freshwater woody wetlands; 4) freshwater marsh; 5) upland; and 6) agriculture. An estuarine vegetated wetland change scenario was assigned to each region depending on different combinations of positive and negative net change in some of these classes which describes how land building, transgression, or tidal restoration compare to estuarine vegetated wetland loss. This dataset also includes relative statistics of change compared to estuarine vegetated wetland and estuary area.

These data include estimates of landcover and land use characteristics including high phytoestrogen crop cover, estimated pesticide applications, EPA PFAS facilities, nutrients from biosolids, and select climate (temperature and precipitation) variables summarized for several fish health sites in the eastern United States.

water chemistry collected across multiple streams in the Chesapeake Bay area. This dataset is not publicly accessible because: data maintained and owned by University of Maryland. It can be accessed through the following means: by contacting corresponding author. Format: excel spreadsheets. This dataset is associated with the following publication: Maas, C., S. Kaushal, M. Rippy, P. Mayer, S. Grant, R. Shatkay, J. Malin, S.V. Bhide, P. Vikesland, L. Krauss, J.E. Reimer, and A.M. Yaculak. Freshwater Salinization Syndrome limits management efforts to improve water quality. Frontiers in Environmental Science. Frontiers, Lausanne, SWITZERLAND, 11: 1106581, (2023).