데이터셋 상세
미국
Data for the Potomac River Watershed Accumulated Wastewater Viewer
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).
데이터 정보
연관 데이터
Potomac River Watershed Accumulated Wastewater Ratios and Predicted Environmental Concentrations
공공데이터포털
Treated effluent from wastewater treatment plants (WWTPs) contains contaminants not fully removed during the treatment process and that may pose environmental health risks when discharged to surface waters. This data release presents inputs for and results from a wastewater reuse model that used data compiled from several sources to calculate the following estimates for each non-tidal, non-coastline, initialized 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%); and (2) predicted environmental concentrations (PECs, in micrograms per liter) of 69 municipal effluent-derived contaminants. ACCWW% values were calculated for mean-monthly and mean-annual streamflow conditions for both municipal (model results table: Table1_PotomacACCWW_municipal.csv) and industrial-plus-municipal effluent discharges (model results table: Table2_PotomacACCWW_municipal_plus_industrial.csv). PECs were calculated for mean-monthly and mean-annual streamflow conditions for municipal effluent discharges (model results tables: Table3_PotomacPECs.zip, containing comma separated value files of results for mean-monthly and mean-annual conditions). Model estimates at a stream reach of interest represent the combined total upstream wastewater discharges as well as direct discharges into the segment. Model input data included: (1) National Pollutant Discharge Elimination System-permitted facility outfall locations and 2016 average daily effluent discharges linked to a NHDPlus V2 stream Common Identifier (COMID) and facility-specific information on treatment levels and population served per capita (model input table: Table4_PotomacWWTPs.csv); (2) NHDPlus V2 stream geometry and hydrologic attributes (hydrosequence, startflag, terminalfl, divergence, fromnode, tonode, and Enhanced Runoff Method mean-monthly and mean-annual gage-adjusted streamflow and velocity, 1971-2000) (model input table: Table5_PotomacNHDPlusV2.1_flowlines_hydrology.csv); and (3) contaminant-specific data on consumption, fate, and transport compiled from literature sources or estimated from physicochemical properties (see: supplementary table in Larger Work Citation). In Table 4, where information on population served by the facility was missing, this value was estimated by standardizing to 100 gallons per capita per day. Information on population served was only acquired and estimated for municipal facilities. Where treatment level information was missing, the treatment level was assumed to be primary. Ninety-two percent of WWTPs have an assumed treatment as none was reported. R (version 4.0.4) and Python (version 2.7.16) scripts were used to summarize wastewater inputs from outfall locations by COMID and route and accumulate each wastewater and predicted contaminant loads while accounting for in-stream dilution and attenuation of contaminants. Any users of these data should review the entire metadata record and the associated manuscript (see Larger Work Citation). See 'Distribution liability' statements for more information.
Potomac River Watershed Accumulated Wastewater Ratios and Predicted Environmental Concentrations
공공데이터포털
Treated effluent from wastewater treatment plants (WWTPs) contains contaminants not fully removed during the treatment process and that may pose environmental health risks when discharged to surface waters. This data release presents inputs for and results from a wastewater reuse model that used data compiled from several sources to calculate the following estimates for each non-tidal, non-coastline, initialized 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%); and (2) predicted environmental concentrations (PECs, in micrograms per liter) of 69 municipal effluent-derived contaminants. ACCWW% values were calculated for mean-monthly and mean-annual streamflow conditions for both municipal (model results table: Table1_PotomacACCWW_municipal.csv) and industrial-plus-municipal effluent discharges (model results table: Table2_PotomacACCWW_municipal_plus_industrial.csv). PECs were calculated for mean-monthly and mean-annual streamflow conditions for municipal effluent discharges (model results tables: Table3_PotomacPECs.zip, containing comma separated value files of results for mean-monthly and mean-annual conditions). Model estimates at a stream reach of interest represent the combined total upstream wastewater discharges as well as direct discharges into the segment. Model input data included: (1) National Pollutant Discharge Elimination System-permitted facility outfall locations and 2016 average daily effluent discharges linked to a NHDPlus V2 stream Common Identifier (COMID) and facility-specific information on treatment levels and population served per capita (model input table: Table4_PotomacWWTPs.csv); (2) NHDPlus V2 stream geometry and hydrologic attributes (hydrosequence, startflag, terminalfl, divergence, fromnode, tonode, and Enhanced Runoff Method mean-monthly and mean-annual gage-adjusted streamflow and velocity, 1971-2000) (model input table: Table5_PotomacNHDPlusV2.1_flowlines_hydrology.csv); and (3) contaminant-specific data on consumption, fate, and transport compiled from literature sources or estimated from physicochemical properties (see: supplementary table in Larger Work Citation). In Table 4, where information on population served by the facility was missing, this value was estimated by standardizing to 100 gallons per capita per day. Information on population served was only acquired and estimated for municipal facilities. Where treatment level information was missing, the treatment level was assumed to be primary. Ninety-two percent of WWTPs have an assumed treatment as none was reported. R (version 4.0.4) and Python (version 2.7.16) scripts were used to summarize wastewater inputs from outfall locations by COMID and route and accumulate each wastewater and predicted contaminant loads while accounting for in-stream dilution and attenuation of contaminants. Any users of these data should review the entire metadata record and the associated manuscript (see Larger Work Citation). See 'Distribution liability' statements for more information.
Datasets and scripts used for estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system, water years 2006-15
공공데이터포털
This U.S. Geological Survey (USGS) data release contains estimated daily streamflow and base flow for HUC12 in the nontidal areas of the Chesapeake Bay watershed, monthly average streamflow and base flow, flow statistics, MATLAB scripts, and a document that describes how to create similar datasets in other watersheds. Daily streamflow was estimated for all the nontidal parts of the Chesapeake Bay watershed with the program "Unit Flows in Networks of Channels" (UFINCH; Holtschlag, 2016), together with the observations of measured streamflow at gages at the downstream ends of major rivers. The estimated streamflow was aggregated at the HUC12 level and reformatted as an Optimal Hydrograph Separation (OHS) input file using MATLAB scripts. Base flow was calculated at each HUC12 outlet using the base flow index (BFI) hydrograph separation methods developed by Wahl and Wahl (Wahl and Wahl, 1988; Wahl and Wahl, 1995) and by Eckhardt (Eckhardt, 2005) with the parameter estimation method developed by Collischonn and Fan (Collischonn and Fan, 2013) which are incorporated into the OHS program (Raffensperger and others, 2017). This data release supports the following publication: • Buffington, P.C., and Capel, P.D., 2020, Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system: U.S. Geological Survey Scientific Investigations Report 2020-5055, 26 p., https://doi.org/10.3133/sir20205055. References cited: • Collischonn, W. and Fan, F.M., 2013, Defining parameters for Eckhardt's digital baseflow filter: Hydrological Processes, v. 27, no. 18, p. 2614-2622, https://doi.org/10.1002/hyp.9391. • Eckhardt, K., 2005, How to construct recursive digital filters for baseflow separation: Hydrological Processes, v. 19, no. 2, p. 507-515, https://doi.org/10.1002/hyp.5675. • Holtschlag, D.J., 2016, UFINCH-A method for simulating unit and daily flows in networks of channels described by NHDPlus using continuous flow data at U.S. Geological Survey streamgages: U.S. Geological Survey Scientific Investigations Report 2016-5074, 17 p., https://doi.org/10.3133/sir20165074. • Raffensperger, J.P., Baker, A.C., Blomquist, J.D., and Hopple, J.A., 2017, Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds: U.S. Geological Survey Scientific Investigations Report 2017-5034, 51 p., https://doi.org/10.3133/sir20175034. • Wahl, K.L., and Wahl, T.L., 1988, Effects of regional ground water declines on streamflows in the Oklahoma Panhandle, in Symposium on Water-Use Data for Water Resources Management, Tucson, Arizona, American Water Resources Association, p. 239-249. • Wahl, K.L., and Wahl, T.L., 1995, Determining the flow of Comal Springs at New Braunfels, Texas, Texas Water '95: San Antonio, Texas, American Society of Civil Engineers, p. 77-86, http://www.usbr.gov/tsc/techreferences/hydraulics_lab/pubs/PAP/PAP-0708.pdf.
Datasets and scripts used for estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system, water years 2006-15
공공데이터포털
This U.S. Geological Survey (USGS) data release contains estimated daily streamflow and base flow for HUC12 in the nontidal areas of the Chesapeake Bay watershed, monthly average streamflow and base flow, flow statistics, MATLAB scripts, and a document that describes how to create similar datasets in other watersheds. Daily streamflow was estimated for all the nontidal parts of the Chesapeake Bay watershed with the program "Unit Flows in Networks of Channels" (UFINCH; Holtschlag, 2016), together with the observations of measured streamflow at gages at the downstream ends of major rivers. The estimated streamflow was aggregated at the HUC12 level and reformatted as an Optimal Hydrograph Separation (OHS) input file using MATLAB scripts. Base flow was calculated at each HUC12 outlet using the base flow index (BFI) hydrograph separation methods developed by Wahl and Wahl (Wahl and Wahl, 1988; Wahl and Wahl, 1995) and by Eckhardt (Eckhardt, 2005) with the parameter estimation method developed by Collischonn and Fan (Collischonn and Fan, 2013) which are incorporated into the OHS program (Raffensperger and others, 2017). This data release supports the following publication: • Buffington, P.C., and Capel, P.D., 2020, Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system: U.S. Geological Survey Scientific Investigations Report 2020-5055, 26 p., https://doi.org/10.3133/sir20205055. References cited: • Collischonn, W. and Fan, F.M., 2013, Defining parameters for Eckhardt's digital baseflow filter: Hydrological Processes, v. 27, no. 18, p. 2614-2622, https://doi.org/10.1002/hyp.9391. • Eckhardt, K., 2005, How to construct recursive digital filters for baseflow separation: Hydrological Processes, v. 19, no. 2, p. 507-515, https://doi.org/10.1002/hyp.5675. • Holtschlag, D.J., 2016, UFINCH-A method for simulating unit and daily flows in networks of channels described by NHDPlus using continuous flow data at U.S. Geological Survey streamgages: U.S. Geological Survey Scientific Investigations Report 2016-5074, 17 p., https://doi.org/10.3133/sir20165074. • Raffensperger, J.P., Baker, A.C., Blomquist, J.D., and Hopple, J.A., 2017, Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds: U.S. Geological Survey Scientific Investigations Report 2017-5034, 51 p., https://doi.org/10.3133/sir20175034. • Wahl, K.L., and Wahl, T.L., 1988, Effects of regional ground water declines on streamflows in the Oklahoma Panhandle, in Symposium on Water-Use Data for Water Resources Management, Tucson, Arizona, American Water Resources Association, p. 239-249. • Wahl, K.L., and Wahl, T.L., 1995, Determining the flow of Comal Springs at New Braunfels, Texas, Texas Water '95: San Antonio, Texas, American Society of Civil Engineers, p. 77-86, http://www.usbr.gov/tsc/techreferences/hydraulics_lab/pubs/PAP/PAP-0708.pdf.
Accumulated wastewater calculations for smallmouth bass sampling sites in the Shenandoah River Watershed, USA
공공데이터포털
This data release presents calculated accumulated wastewater (ACCWW, as a percent of total streamflow) values for 43 National Hydrologic Dataset Version 2.1 (NHDPlus V2.1) stream segments coinciding with long-term smallmouth bass sampling locations (Table 1) in the Shenandoah River Watershed (encompassing parts of Virginia and West Virginia, USA). Values are calculated for quarter-year (Quarter 1 [Q1], January - March; Quarter 2 [Q2], April - June; Quarter 3 [Q3], July-September; Quarter 4 [Q4], October-December) time scales (Table 2) and annual time scales (Table 3) for years 2000 to 2018. Estimates at a stream segment represent the combined total upstream wastewater discharges as well as direct discharges into the stream segment. Any users of these data should review the entire metadata record and the associated manuscript (see Larger Work Citation). See 'Distribution Liability' statements for more information.
Accumulated wastewater calculations for smallmouth bass sampling sites in the Shenandoah River Watershed, USA
공공데이터포털
This data release presents calculated accumulated wastewater (ACCWW, as a percent of total streamflow) values for 43 National Hydrologic Dataset Version 2.1 (NHDPlus V2.1) stream segments coinciding with long-term smallmouth bass sampling locations (Table 1) in the Shenandoah River Watershed (encompassing parts of Virginia and West Virginia, USA). Values are calculated for quarter-year (Quarter 1 [Q1], January - March; Quarter 2 [Q2], April - June; Quarter 3 [Q3], July-September; Quarter 4 [Q4], October-December) time scales (Table 2) and annual time scales (Table 3) for years 2000 to 2018. Estimates at a stream segment represent the combined total upstream wastewater discharges as well as direct discharges into the stream segment. Any users of these data should review the entire metadata record and the associated manuscript (see Larger Work Citation). See 'Distribution Liability' statements for more information.
Estimation Site 03105927; Spreadsheets and Metadata
공공데이터포털
Streamflow was collected at various streamgages in western Pennsylvania in support of the scientific investigations report "Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania". Data observed at the streamgages for the period of August 1, 2014 through March 31, 2017 are considered. This dataset includes 1) all data used to develop prediction intervals for the titled estimation site based upon the titled index streamgage for the period of May 1, 2015 to March 31, 2017 and 2) evaluation of data observed before May 1, 2015. For prediction interval development, a Move.1 regression was developed between the titled estimation site and titled index streamgage. From this regression model, Pearson's correlation coefficient (r) is reported, and the Nash-Sutcliffe efficiency value is computed. The prediction interval development is included for the 95% prediction interval for both the nonparametric and parametric methods. For the parametric method, any prediction interval can be developed by changing Student's t critical value. Any data that were observed before May 1, 2015 were evaluated to see if they fell within the 95% nonparametric prediction interval. The data chosen for the regression development and evaluation is streamflow that is not influenced by runoff. Streamflow that occurred the day of precipitation and two days after is considered influenced by runoff and not included in the dataset. Not all streamgages have the same period of record; dates where data were observed both at the titled index streamgage and estimation site are described below in the "Time Period of Data" section.
Estimation Site 03105927; Spreadsheets and Metadata
공공데이터포털
Streamflow was collected at various streamgages in western Pennsylvania in support of the scientific investigations report "Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania". Data observed at the streamgages for the period of August 1, 2014 through March 31, 2017 are considered. This dataset includes 1) all data used to develop prediction intervals for the titled estimation site based upon the titled index streamgage for the period of May 1, 2015 to March 31, 2017 and 2) evaluation of data observed before May 1, 2015. For prediction interval development, a Move.1 regression was developed between the titled estimation site and titled index streamgage. From this regression model, Pearson's correlation coefficient (r) is reported, and the Nash-Sutcliffe efficiency value is computed. The prediction interval development is included for the 95% prediction interval for both the nonparametric and parametric methods. For the parametric method, any prediction interval can be developed by changing Student's t critical value. Any data that were observed before May 1, 2015 were evaluated to see if they fell within the 95% nonparametric prediction interval. The data chosen for the regression development and evaluation is streamflow that is not influenced by runoff. Streamflow that occurred the day of precipitation and two days after is considered influenced by runoff and not included in the dataset. Not all streamgages have the same period of record; dates where data were observed both at the titled index streamgage and estimation site are described below in the "Time Period of Data" section.
Estimation Site 03105927; Spreadsheets and Metadata
공공데이터포털
Streamflow was collected at various streamgages in western Pennsylvania in support of the scientific investigations report "Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania". Data observed at the streamgages for the period of August 1, 2014 through March 31, 2017 are considered. This dataset includes 1) all data used to develop prediction intervals for the titled estimation site based upon the titled index streamgage for the period of May 1, 2015 to March 31, 2017 and 2) evaluation of data observed before May 1, 2015. For prediction interval development, a Move.1 regression was developed between the titled estimation site and titled index streamgage. From this regression model, Pearson's correlation coefficient (r) is reported, and the Nash-Sutcliffe efficiency value is computed. The prediction interval development is included for the 95% prediction interval for both the nonparametric and parametric methods. For the parametric method, any prediction interval can be developed by changing Student's t critical value. Any data that were observed before May 1, 2015 were evaluated to see if they fell within the 95% nonparametric prediction interval. The data chosen for the regression development and evaluation is streamflow that is not influenced by runoff. Streamflow that occurred the day of precipitation and two days after is considered influenced by runoff and not included in the dataset. Not all streamgages have the same period of record; dates where data were observed both at the titled index streamgage and estimation site are described below in the "Time Period of Data" section.
Estimation Site 03111215; Spreadsheets and Metadata
공공데이터포털
Streamflow was collected at various streamgages in western Pennsylvania in support of the scientific investigations report "Estimation of Base Flow on Ungaged, Periodically Measured Streams in Small Watersheds in Western Pennsylvania". Data observed at the streamgages for the period of August 1, 2014 through March 31, 2017 are considered. This dataset includes 1) all data used to develop prediction intervals for the titled estimation site based upon the titled index streamgage for the period of May 1, 2015 to March 31, 2017 and 2) evaluation of data observed before May 1, 2015. For prediction interval development, a Move.1 regression was developed between the titled estimation site and titled index streamgage. From this regression model, Pearson's correlation coefficient (r) is reported, and the Nash-Sutcliffe efficiency value is computed. The prediction interval development is included for the 95% prediction interval for both the nonparametric and parametric methods. For the parametric method, any prediction interval can be developed by changing Student's t critical value. Any data that were observed before May 1, 2015 were evaluated to see if they fell within the 95% nonparametric prediction interval. The data chosen for the regression development and evaluation is streamflow that is not influenced by runoff. Streamflow that occurred the day of precipitation and two days after is considered influenced by runoff and not included in the dataset. Not all streamgages have the same period of record; dates where data were observed both at the titled index streamgage and estimation site are described below in the "Time Period of Data" section.
목록