Empirical models described in previous publications were developed and applied to estimate the probability of streamflow modification for every stream segment in the conterminous United States from 1980-2015. This metadata record documents 6 comma separated tables populated with predictions of streamflow modification (please see the Supplemental Element for citations or please refer to the cross-reference section). These data are based on watershed attributes computed for each NHDPlus v2.1 reach that were subsequently applied to previously published (and herein described) machine-learning models.

The statistically-based estimates of streamflow included here are for the headwater watersheds in the study area described in LaFontaine and others (2019), and were developed using the ordinary kriging methodology described in Farmer (2016). There are four files included that describe the maximum, minimum, mean, and median estimated streamflow for each headwater on a daily time step for the period 10/1/1980-9/30/2010. A GIS shapefile of the headwaters is also included here. Farmer, W.H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records: Hydrology and Earth System Sciences, v. 20, no. 7, p. 2721-2735, accessed September 27, 2017, at https://doi.org/10.5194/hess-20-2721-2016. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., in review, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

The statistically-based estimates of streamflow included here are for the headwater watersheds in the study area described in LaFontaine and others (2019), and were developed using the ordinary kriging methodology described in Farmer (2016). There are four files included that describe the maximum, minimum, mean, and median estimated streamflow for each headwater on a daily time step for the period 10/1/1980-9/30/2010. A GIS shapefile of the headwaters is also included here. Farmer, W.H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records: Hydrology and Earth System Sciences, v. 20, no. 7, p. 2721-2735, accessed September 27, 2017, at https://doi.org/10.5194/hess-20-2721-2016. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., in review, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

This data release contains inputs for and outputs from hydrologic simulations of the southeastern U.S. using the Monthly Water Balance Model, the Precipitation Runoff Modeling System (PRMS), and statistically-based methods. These simulations were developed to provide estimates of water availability and statistics of streamflow for historical and potential future conditions for an area of approximately 1.16 million square miles. These model input and output data are intended to accompany a U.S. Geological Survey Scientific Investigations Report (LaFontaine and others, 2019); they include four types of data: 1) model input parameters, 2) model output statistics, 3) GIS files of the model hydrologic response units and stream segments, and 4) statistically-based streamflow estimates for headwater watersheds. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

This data release contains inputs for and outputs from hydrologic simulations of the southeastern U.S. using the Monthly Water Balance Model, the Precipitation Runoff Modeling System (PRMS), and statistically-based methods. These simulations were developed to provide estimates of water availability and statistics of streamflow for historical and potential future conditions for an area of approximately 1.16 million square miles. These model input and output data are intended to accompany a U.S. Geological Survey Scientific Investigations Report (LaFontaine and others, 2019); they include four types of data: 1) model input parameters, 2) model output statistics, 3) GIS files of the model hydrologic response units and stream segments, and 4) statistically-based streamflow estimates for headwater watersheds. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

This dataset contains predicted flow-duration curves (FDCs) for 1,378 streamgages in 19 study regions in the conterminous U.S. from mostly undisturbed watersheds using regression models constructed with four or five binary methodological choices (thus 16 or 32 methodological combinations). The predicted FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. These data are also contained within the CSV files in child item 4, "Selected regression models for predicting FDC quantiles for selected streamgages in the conterminous United States", but are separated out here to provide more convenient access in a single Excel file (predictedFDCs.xlsx). These data support a concurrent publication (Over and others, 2018).

This dataset contains predicted flow-duration curves (FDCs) for 1,378 streamgages in 19 study regions in the conterminous U.S. from mostly undisturbed watersheds using regression models constructed with four or five binary methodological choices (thus 16 or 32 methodological combinations). The predicted FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. These data are also contained within the CSV files in child item 4, "Selected regression models for predicting FDC quantiles for selected streamgages in the conterminous United States", but are separated out here to provide more convenient access in a single Excel file (predictedFDCs.xlsx). These data support a concurrent publication (Over and others, 2018).

The dataset contains long-term and short-term summaries of streamflow alteration and measures of biological condition (fish multi-metric index). Streamflow alteration metrics include the magnitude, duration, frequency, and seasonality of high and low flow streamflow. Biological condition was estimated from the National Rivers and Streams Assessment and National Water Quality Assessment fish sampling programs. Using fish samples, a fish multi-metric index was calculated and categorized into altered versus non-altered fish communities.

The dataset contains long-term and short-term summaries of streamflow alteration and measures of biological condition (fish multi-metric index). Streamflow alteration metrics include the magnitude, duration, frequency, and seasonality of high and low flow streamflow. Biological condition was estimated from the National Rivers and Streams Assessment and National Water Quality Assessment fish sampling programs. Using fish samples, a fish multi-metric index was calculated and categorized into altered versus non-altered fish communities.

This data release contains values of 29 streamflow statistics computed from modeled and observed daily streamflows from October 1, 1983, through September 30, 2016 at 1,257 streamgages in the 19 study regions defined by Falcone (2011) covering the conterminous United States. The streamflow statistics were computed at GAGES-II non-reference streamgages (Falcone, 2011), determined to be affected by only irrigation or regulation among antrhopogenic influences. At each streamgage, statistics were computed from daily streamflow observations, from daily streamflow time series computed using the National Hydrologic Model-Precipitation Runoff Modeling System (NHM-PRMS) model (the “by headwater” and "by observation" calibrations with Muskingum routing; Hay and LaFontaine, 2020), and from daily streamflow time series computed using five statistical time series models fitted to reference basins (Russell and others, 2021). The data release comprises nine .csv files. The streamflow statistics values are provided in eight of these files, one each for the observed, the two NHM-PRMS calibrations, and the five statistical time series models. The remaining file is a summary table, which provides period-of-record information for each streamgage. References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset]: U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Hay, L.E., and LaFontaine, J.H., 2020, Application of the National Hydrologic Model Infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS), 1980-2016, Daymet Version 3 calibration: U.S. Geological Survey data release, https://doi.org/10.5066/P9PGZE0S. Russell, A.M., Over, T.M., Farmer, W.H., and Miles, K.J., 2021, Statistical daily streamflow estimates at GAGES-II non-reference streamgages in the conterminous Unites States, Water Years 1981-2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9PA9PKM.