This metadata record describes monthly estimates of natural baseflow for 15,866 stream reaches, defined by the National Hydrography Dataset Plus Version 2.0 (NHDPlusV2), in the Delaware River Basin for the period 1950-2015. A statistical machine learning technique - random forest modeling (Liaw and Wiener, 2018; R Core Team, 2020) - was applied to estimate natural flows using about 150 potential predictor variables (Miller and others, 2018). Calibration data used for the random forest model are available from (Foks and others, 2020). Each model was run twice, first using all potential predictor variables, which represents a "full" model run, and a second time using the top 20 predictors from the original run, which represents the "partial" model run. Model performance of the full and partial models were compared and identified to be similar. Therefore, predictions for all NHDPlusV2 stream reaches were made using the partial model. Methods used to calibrate the random forest models, and references to predictor data sources are detailed in (Miller and others, 2018). The R scripts used and directions to run the scripts are included in this data release. References cited: Liaw, A., and Wiener, M., 2018, Package 'randomForest': The Comprehensive R Archive Network, https://cran.r-project.org/web/packages/randomForest/randomForest.pdf. Miller, M.P., Carlisle, D.M., Wolock, D.M., and Wieczorek, M., 2018, A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States: Journal of the American Water Resources Association, v. 54, no. 6, p. 1258-1269, https://doi.org/10.1111/1752-1688.12685. Foks, S.S., Miller, M.P., and Hopple, J.A., 2020, Daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary for the years 1950 through 2015: U.S. Geological Survey data release, https://doi.org/10.5066/P9XY70L4. R Core Team, 2020, R-A language and environment for statistical computing: R Foundation for Statistical Computing, https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006.

This USGS data release contains daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary. Estimates are provided for the available period of record of streamflow data at each site between 1950 and 2015. A two-parameter recursive digital filter was used to estimate baseflow at the selected stream gaging stations using U.S. Geological Survey Groundwater Toolbox (Barlow and others, 2017; Eckhardt, 2005). References cited: Barlow, P.M., Cunningham, W.L., Zhai, T., and Gray, M., 2017, U.S. Geological Survey Groundwater Toolbox version 1.3.1, a graphical and mapping interface for analysis of hydrologic data: U.S. Geological Survey Software Release, 26 May 2017, https://doi.org/10.5066/F7R78C9G. Eckhardt, K., 2005, How to construct recursive digital filters for baseflow separation: Hydrological Processes - An International Journal, v. 19, p. 50-515, https://doi.org/10.1002/hyp.5675.

This USGS data release contains daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary. Estimates are provided for the available period of record of streamflow data at each site between 1950 and 2015. A two-parameter recursive digital filter was used to estimate baseflow at the selected stream gaging stations using U.S. Geological Survey Groundwater Toolbox (Barlow and others, 2017; Eckhardt, 2005). References cited: Barlow, P.M., Cunningham, W.L., Zhai, T., and Gray, M., 2017, U.S. Geological Survey Groundwater Toolbox version 1.3.1, a graphical and mapping interface for analysis of hydrologic data: U.S. Geological Survey Software Release, 26 May 2017, https://doi.org/10.5066/F7R78C9G. Eckhardt, K., 2005, How to construct recursive digital filters for baseflow separation: Hydrological Processes - An International Journal, v. 19, p. 50-515, https://doi.org/10.1002/hyp.5675.

This metadata record describes monthly estimates of natural stream flows for greater than 2.5 million stream reaches, defined by the National Hydrography Dataset (NHD) Version 2.0, in the conterminous United States for the period 1950-2015. A statistical machine learning technique - random forest modeling - was applied to estimate natural flows using 200 potential predictor variables. The dataset is organized by level 3 ecoregions, with each ecoregion having its own directory. Separate .csv files for each stream reach in the NHD network belonging to a given ecoregion are contained within the respective ecoregion directories. The stream reach .csv files are named as the NHD COMID corresponding to that stream reach. Methods used to calibrate the random forest models, and references to predictor data sources are detailed in the Journal of the American Water Resources Associate paper "A database of natural monthly flow estimates from 1950-2015 for the conterminous United States" by Miller and others (2018). See the discussion paper link in the "Related External Resources" section for access.

This metadata record describes monthly estimates of natural stream flows for greater than 2.5 million stream reaches, defined by the National Hydrography Dataset (NHD) Version 2.0, in the conterminous United States for the period 1950-2015. A statistical machine learning technique - random forest modeling - was applied to estimate natural flows using 200 potential predictor variables. The dataset is organized by level 3 ecoregions, with each ecoregion having its own directory. Separate .csv files for each stream reach in the NHD network belonging to a given ecoregion are contained within the respective ecoregion directories. The stream reach .csv files are named as the NHD COMID corresponding to that stream reach. Methods used to calibrate the random forest models, and references to predictor data sources are detailed in the Journal of the American Water Resources Associate paper "A database of natural monthly flow estimates from 1950-2015 for the conterminous United States" by Miller and others (2018). See the discussion paper link in the "Related External Resources" section for access.

The U.S. Geological Survey (USGS) in cooperation with the Pennsylvania Department of Conservation and Natural Resources (PA DCNR), Bureau of Geological Survey, provides estimates of groundwater recharge at 197 streamflow gaging stations where streamflow is relatively unaffected by regulation. Baseflow, runoff, and groundwater Recharge estimates were conducted via the Hydrologic toolbox by use of automated streamflow-hydrograph-analysis methods HySEP-Fixed, HySEP-LocMin, HySEP-Slide, PART, BFI-Standard, BFI-Modified, DF-One Param, DF-Two Param, and RORA.

The U.S. Geological Survey (USGS) in cooperation with the Pennsylvania Department of Conservation and Natural Resources (PA DCNR), Bureau of Geological Survey, provides estimates of groundwater recharge at 197 streamflow gaging stations where streamflow is relatively unaffected by regulation. Baseflow, runoff, and groundwater Recharge estimates were conducted via the Hydrologic toolbox by use of automated streamflow-hydrograph-analysis methods HySEP-Fixed, HySEP-LocMin, HySEP-Slide, PART, BFI-Standard, BFI-Modified, DF-One Param, DF-Two Param, and RORA.

Base flow, the groundwater contribution to streamflow, is beneficial data for analysis of groundwater-flow systems. This data release includes base-flow estimates and streamflow data for 471 Oregon streamgage sites. Categories of data include: (1) site information, (2) water year estimates of base flow and streamflow, and (3) daily estimates of base flow. Water-year base-flow estimates are considered most reliable; daily estimates are provided for completion and summarization purposes only. Daily discharge (streamflow) data from water years 1980–2023 were obtained from the United States Geological Survey (USGS; https://waterdata.usgs.gov) and the Oregon Water Resources Department (OWRD; https://apps.wrd.state.or.us/apps/sw/hydro_report/) online databases and used to estimate base flow using three methods: low-flow, graphical hydrograph separation (GHS), and chemical hydrograph separation (CHS). Specific conductance (SC) data from continuous SC monitoring at streamgages were obtained from the USGS database and used for CHS base-flow analysis at 15 sites. Data are in .csv file and .txt file format.

This data set provides estimated and measured streamflow data and hydrograph-separation results for five sites located in northwest Mississippi. Streamflow data were collected by the U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers. Hydrograph-separation results provide runoff and baseflow estimates at each site that were calculated using four methods: PART, HYSEP Fixed, HYSEP Local Minimum, and BFI Standard, as well as an average base flow index (BFI) for all four methods.

This data set provides estimated and measured streamflow data and hydrograph-separation results for five sites located in northwest Mississippi. Streamflow data were collected by the U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers. Hydrograph-separation results provide runoff and baseflow estimates at each site that were calculated using four methods: PART, HYSEP Fixed, HYSEP Local Minimum, and BFI Standard, as well as an average base flow index (BFI) for all four methods.