This dataset is a continuous parameter grid (CPG) of baseflow index values (percent of discharge as baseflow) estimated at U.S. Geological Survey (USGS) streamgages in the Pacific Northwest. Source data was produced by David Wolock of USGS.

This dataset is a continuous parameter grid (CPG) of baseflow index values (percent of discharge as baseflow) estimated at U.S. Geological Survey (USGS) streamgages in the Pacific Northwest. Source data was produced by David Wolock of USGS.

A generalized streamflow-variability index coverage was created by interpolating a grid (with 6,066-ft^2 cells) from at-site values of the streamflow-variability index computed for 133 rural, unregulated streamflow-gaging stations in Ohio and nearby areas of adjacent states. Grid interpolation was done by means of the interpolate surface routine contained in the Spatial Analyst extension of ArcView. The inverse distance weighting (IDW) algorithm was used based on the 12 nearest neighbors. The streamflow-variability index at a streamflow-gaging station is defined as the standard deviation of the logarithms of the 19 streamflow values at 5-percent class intervals from 5 to 95 percent on the flow-duration curve (Searcy, 1959) of daily mean streamflow for the analysis period. Searcy, J.K., 1959, Flow-duration curves, manual of hydrology-part 2, low-flow techniques: U.S. Geological Survey Water-Supply Paper 1542-A, 33 p.

A generalized streamflow-variability index coverage was created by interpolating a grid (with 6,066-ft^2 cells) from at-site values of the streamflow-variability index computed for 133 rural, unregulated streamflow-gaging stations in Ohio and nearby areas of adjacent states. Grid interpolation was done by means of the interpolate surface routine contained in the Spatial Analyst extension of ArcView. The inverse distance weighting (IDW) algorithm was used based on the 12 nearest neighbors. The streamflow-variability index at a streamflow-gaging station is defined as the standard deviation of the logarithms of the 19 streamflow values at 5-percent class intervals from 5 to 95 percent on the flow-duration curve (Searcy, 1959) of daily mean streamflow for the analysis period. Searcy, J.K., 1959, Flow-duration curves, manual of hydrology-part 2, low-flow techniques: U.S. Geological Survey Water-Supply Paper 1542-A, 33 p.

To aid in parameterization of mechanistic, statistical, and machine learning models of hydrologic systems in the contiguous United States (CONUS), flow-conditioned parameter grids (FCPGs) have been generated describing upstream basin mean elevation, slope, land cover class, latitude, and 30-year climatologies of mean total annual precipitation, minimum daily air temperature, and maximum daily air temperature. Additional datasets of upstream basin area and binary stream presence-absence are provided to help validate queries against the flow-conditioned data. These data are provided as virtual raster tile (vrt) mosaics of cloud optimized GeoTIFFs to allow point queries of the data (see Distribution Information) without requiring downloading the whole dataset.

To aid in parameterization of mechanistic, statistical, and machine learning models of hydrologic systems in the contiguous United States (CONUS), flow-conditioned parameter grids (FCPGs) have been generated describing upstream basin mean elevation, slope, land cover class, latitude, and 30-year climatologies of mean total annual precipitation, minimum daily air temperature, and maximum daily air temperature. Additional datasets of upstream basin area and binary stream presence-absence are provided to help validate queries against the flow-conditioned data. These data are provided as virtual raster tile (vrt) mosaics of cloud optimized GeoTIFFs to allow point queries of the data (see Distribution Information) without requiring downloading the whole dataset.

This metadata record describes observed and predicted baseflow recession characteristics for 300 streamflow gauges in the western United States and 282 streamflow gauges in the eastern United States. Specifically, this record describes (1) the streamflow gauge locations (west or east) in the United States (Location), (2) the U.S. Geological Survey streamflow gauge identification numbers (USGS_Site_Identifier), (3) observed regions of similar aquifer hydraulic properties (7 regions coded by color: blue, green, red, purple, grey, pink, and orange) by k-means clustering method (Observed_Class(k-means)), (4) predicted regions of similar aquifer hydraulic properties by random forest classification models (Predicted_Class(k-means)), (5) calculated long-term baseflow recession constant at streamflow gauges (Observed_a-long[ft^(-3/2)s^(-1/2)]), (6) predicted long-term baseflow recession constant by novel empirical and physical approach (Predicted_a-long(Novel)[ft^(-3/2)s^(-1/2)]), (7) predicted long-term baseflow recession constant by random forest regression (Predicted_a-long(Random_Forest_Regression)[ft^(-3/2)s^(-1/2)]), (8) calculated short-term baseflow recession constant at streamflow gauges (Observed_a-short[sft^(-6)]), (9) predicted short-term baseflow recession constant by novel empirical and physical approach (Predicted_a-short(Novel)[sft^(-6)]), (10) predicted short-term baseflow recession constant by random forest regression (Predicted_a-short(Random_Forest_Regression)[sft^(-6)]). For more details for (3) to (10), please see Eng, K., Wolock, D. M., and Wieczorek, M., 2023, Predicting baseflow recession characteristics at ungauged locations using a physical and machine learning approach. The values entered for (5) to (10) are in scientific notation, and they are character strings that will require the user to convert numeric values using methods for their software or use case. The data are in a tab-delimited text format.

This metadata record describes observed and predicted baseflow recession characteristics for 300 streamflow gauges in the western United States and 282 streamflow gauges in the eastern United States. Specifically, this record describes (1) the streamflow gauge locations (west or east) in the United States (Location), (2) the U.S. Geological Survey streamflow gauge identification numbers (USGS_Site_Identifier), (3) observed regions of similar aquifer hydraulic properties (7 regions coded by color: blue, green, red, purple, grey, pink, and orange) by k-means clustering method (Observed_Class(k-means)), (4) predicted regions of similar aquifer hydraulic properties by random forest classification models (Predicted_Class(k-means)), (5) calculated long-term baseflow recession constant at streamflow gauges (Observed_a-long[ft^(-3/2)s^(-1/2)]), (6) predicted long-term baseflow recession constant by novel empirical and physical approach (Predicted_a-long(Novel)[ft^(-3/2)s^(-1/2)]), (7) predicted long-term baseflow recession constant by random forest regression (Predicted_a-long(Random_Forest_Regression)[ft^(-3/2)s^(-1/2)]), (8) calculated short-term baseflow recession constant at streamflow gauges (Observed_a-short[sft^(-6)]), (9) predicted short-term baseflow recession constant by novel empirical and physical approach (Predicted_a-short(Novel)[sft^(-6)]), (10) predicted short-term baseflow recession constant by random forest regression (Predicted_a-short(Random_Forest_Regression)[sft^(-6)]). For more details for (3) to (10), please see Eng, K., Wolock, D. M., and Wieczorek, M., 2023, Predicting baseflow recession characteristics at ungauged locations using a physical and machine learning approach. The values entered for (5) to (10) are in scientific notation, and they are character strings that will require the user to convert numeric values using methods for their software or use case. The data are in a tab-delimited text 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.

The U.S. Geological Survey, in cooperation with Maine Department of Transportation, has compiled a series of GIS datasets to be implemented into the USGS StreamStats application for the State of Maine.These data were compiled from the high-resolution National Hydrography Dataset (NHD) and the Maine Lidar-Derived Watersheds (Sturtevant and Schoen, 2022). By using these datasets users will be able to delineate watersheds with the StreamStats application more accurately than previously possible. The datasets are provided in five separate child items.