The Hydrology Feature Dataset contains photogrammetrically compiled water drainage features and structures including rivers, streams, drainage canals, locks, dams, lakes, ponds, reservoirs and mooring cells. Lakes are large standing bodies of water greater than 5 acres in size. Ponds are large standing bodies of water greater than 1 acre and less than 5 acres in size. Polygons are created from Stream edges and River Edges. The Ohio River, Monongahela River and Allegheny River are coded as Major River polygons. All other River and Stream polygons are coded as River. A Drainage Canal is a manmade or channelized hydrographic feature. Drainage Canals are differentiated from streams in that drainage canals have had the sides and/or bottom stabilized to prevent erosion for the predominant length of the feature. Streams may have had some stabilization done, but are primarily in a natural state. Lakes are large standing bodies of water greater than five acres in size. Ponds are large standing bodies of water greater than one acre in size and less than five acres in size. Reservoirs are manmade embankments of water. Included in this definition are both covered and uncovered water tanks. Reservoirs that are greater than one acre in size are digitized. Hidden Streams, Hidden Rivers and Hidden Drainage Canal or Culverts are those areas of drainage where the water flows through a manmade facility such as a culvert. Hydrology Annotation is not being updated but will be preserved. If a drainage feature has been removed, as apparent on the aerial photography, the associated drainage name annotation will be removed. A Mooring Cell is a structure to which tows can tie off while awaiting lockage. They are normally constructed of concrete and steel and are anchored to the river bottom by means of gravity or sheet piling. Mooring Cells do not currently exist in the Allegheny County dataset but will be added. Locks are devices that are used to control flow or access to a hydrologic feature. The edges of the Lock are captured. Dams are devices that are used to hold or delay the natural flow of water. The edges of the Dam are shown.

This coverage contains land-cover information for all of Ohio and portions of Indiana, Michigan, Kentucky, West Virginia, Pennsylvania, and New York. This dataset was derived from the U.S. Geological Survey's National Land Cover Dataset (NLCD). NLCD raster grids were downloaded from the USGS EROS Data Center web server at http://landcover.usgs.gov/natllandcover.html, by state. These grids were then reprojected, mosaiced and clipped against a polygon coverage representing the study area. Grid cell resolution is approximately 30 meters or 1 arc-second.

This data release contains measured streamflow data from U.S. Geological Survey (USGS) streamgages and reported wastewater data from wastewater treatment plants (WWTP) discharge monitoring reports (DMRs) within the Potomac River watershed between October 1, 2021 and September 30, 2024. Mean monthly streamflow data was obtained from 117 USGS streamgages (Table1_Streamgages.csv). Average monthly reported wastewater discharge volumes to surface water were obtained from National Pollutant Discharge Elimination System (NPDES) permits using the United States Environmental Protection Agency’s (USEPA) Environment and Compliance History Online (ECHO) database to obtain DMRs from the Integrated Compliance Information System National Pollutant Discharge Elimination System (ICIS-NPDES). Quality assurance procedures that were used to avoid inclusion of inaccurate data that can be reported on DMRs (Table2_WWTP_DMRs.csv) are documented within the Process Step fields of the metadata. At each streamgage the average monthly accumulated wastewater percentage (ACCWW) was calculated by dividing the total amount of reported wastewater upstream of the streamgage by the measured amount of streamflow (Table3_Streamgage_ACCWW.csv) following similar methods described in Miller and others (2024) and Barber and others (2025). The ACCWW calculations were computed monthly at each streamgage using reported total wastewater discharge, municipal wastewater discharge, and municipal-plus-industrial per- and polyfluoroalkyl substances (PFAS) wastewater discharge which includes municipal wastewater in addition to wastewater from industrial WWTPs that are potential PFAS handling industry sectors defined by the USEPA (2023). The term ‘municipal’ is used here to represent NPDES-permitted facilities with the Standard Industrial Classification code 4952 (‘sewerage systems’) and 'industrial' refers to permitted facilities with Standard Industrial Classification codes other than 4952. Monthly predicted environmental concentrations and constituent loads (i.e. mass fluxes) of eight PFAS and 14 pesticides were estimated at each streamgage following methodology presented by Barber and others (2025) and Miller and others (2024). Monthly PFAS loads were computed by multiplying the discharge volumes from municipal and industrial WWTPs that are potential PFAS handling industry sectors by the median PFAS concentrations measured and reported in Barber and others (2025). Monthly pesticide loads were computed by multiplying the discharge volumes from municipal WWTPs by the median pesticide concentrations reported in Miller and others (2024). Wastewater effluent concentrations from Miller and others (2024) and Barber and others (2025) are provided in Table4_Parameters.csv. Monthly predicted constituent loads from wastewater were summed from WWTPs that discharged to every National Hydrography Dataset Version 2.1 (NHDPlus V2; USEPA, 2012) stream segment Common Identifier (COMID) upstream of each streamgage, not including the COMID where the streamgage was located, to calculate the predicted monthly load at each streamgage (Table5_Streamgage_Parameter_Predictions.csv). Predicted monthly concentrations from wastewater were calculated by dividing the predicted monthly load by measured monthly streamflow at each streamgage (Table5_Streamgage_Parameter_Predictions.csv).

This database was developed for the Water Availability Tool for Environmental Resources (WATER) for the Delaware River Basin (DRB), a decision support tool that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions (Williamson and others, 2015). This database provides historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover forecasts and general circulation model (global climate model; GCM) projections that focus on 2030 and 2060. The database provides for geospatial sampling, at a 10-30 m resolution, of landscape characteristics, including topographic and soil properties, land cover and impervious surface, water use, and GCM change factors for precipitation, temperature, and a radiation-based potential evapotranspiration. These data are available as a cohesive unit, that provides the file structure required by the hydrologic tool, in addition to some layers being provided as individual files. Williamson, T.N., Lant, J.G., Claggett, P.R., Nystrom, E.A., Milly, P.C.D., Nelson, H.L., Hoffman, S.A., Colarullo, S.J., and Fischer, J.M., 2015. Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER): U.S. Geological Survey Scientific Investigations Report 2015-5143, 68 p., http://doi.org/10.3133/sir20155143.

Summarization of the University of Massachusetts Landscape Ecology Lab Designing Sustainable Landscapes (DSL) datasets with the Spatial Hydro-Ecological Decision System (SHEDS) framework. These DSL data were summarized using the local and upstream total accumulation methods within SHEDS. The result are two sets of data, a continuous dataset and a discrete dataset. The continuous dataset contains the average value for the local SHEDS catchments and the area-weighted sums of the averages for the local and all upstream SHEDS catchments for all continuous variables in the DSL dataset. The discrete dataset contains the area in square meters covered by each class within all discrete variables in the DSL dataset for the local SHEDS catchments along with the area-weighted sum of the local and all upstream SHEDS catchment values.

This is an ArcGIS dataset depicting watershed segments in the Chesapeake Bay Watershed and adjacent states of New York, Pennsylvania, Maryland, West Virginia, Delaware, Virginia, North Carolina, and Tennessee. Thirty-meter-resolution Digital Elevation Model data were used to delineate watersheds for each stream reach. State watershed boundaries replaced the Digital Elevation Model-derived watersheds where coincident. The data are projected to the UTM grid coordinate system - Zone 18 NAD27.

Digital flood-inundation maps were created by the U.S. Geological Survey (USGS) in cooperation with the Muskingum Watershed Conservancy District and the City of Rittman as part of a Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS). The flood-inundation maps show estimates of the areal extent corresponding to the 1% and 0.2% annual-exceedance probability floods. Flood profiles were computed for each stream reach by means of a one-dimensional step-backwater model.

,This dataset includes drainage discharge, water chemistry, and precipitation data and GIS shapefiles for research conducted on 249-ha County Ditch 62 (CD62) and adjacent 268-ha County Ditch 30 (CD30) watersheds in Faribault County, Minnesota, from 2018—23 and 2021—23, respectively. Three large bioreactor beds treat flow from the CD62 watershed. Water table depths in the outlet structures of the three bioreactors (BR1, BR2, and BR3) are included for 2021—23. Also, water table depths at three locations in the beds are included for 2022 and 2023. The beds were recharged with new woodchips during 2020; limited bioreactor data exist for 2018, and no bioreactor data exist for 2019—20. The purpose of the research was twofold: 1) to evaluate the performance of the bioreactors and the percentage of watershed discharge that was treated by them, and 2) to establish hydrologic and nutrient load pairing of side-by-side watersheds for a future study of management change on one of the watersheds.,A related dataset includes discharge and water chemistry data for CD62 and the bioreactors for the period September 2016 through July 2017:,Water chemistry analyses are yet being conducted on calendar year 2024 samples; data from these analyses and related hydrologic data are forthcoming.,Methods of sample and data collection are similar to those described in the above-referenced dataset and the related peer-reviewed publication:,A nitrate sensor (Hach Nitratax) was installed in CD62 in 2019. The monitoring station at CD30 was instrumented similarly to CD62: discharge (in a 15-inch drainage main) with area-velocity technology (Teledyne ISCO 2150), nitrate sensor (Hach Nitratax), and flow-weighted autosampling (Teledyne ISCO 6712).,The file “CD30-62 map w labels.png” shows the watershed boundaries and the location of the woodchip bioreactors (WBR) at the outlet of CD62.,

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).