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.

This data set archives all inputs, outputs and scripts needed to reproduce the findings of W.H. Farmer and G.F. Koltun in the 2017 Journal of Hydrology Regional Studies article entitled “Geospatial Tools Effectively Estimated Nonexceedance Probabilities of Daily Streamflow at Ungauged and Intermittently Gauged Locations in Ohio”. Input data includes observed streamflow values, in cubic feet per second, for 152 streamgages in and around Ohio from 01 January 2009 through 31 August 2015. Data from the Ohio Environmental Protection Agency on where and when water quality samples were taken are also provided. Geospatial locations are provided for all streamgages and sampling sites considered. ESRI ArcGIS shapefiles are available for all maps produced in the original publication. Comma-separated-value files contain the output data required to reproduce every figure in the report. This archive also includes an R script capable of reading the input files and producing output files and figures. See the README.txt file for a full description of model application.

In cooperation with the Ohio Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration, the USGS developed a database of geomorphic data for a sampling of unregulated natural alluvial streams in Ohio. The vector point shapefile that these metadata describe is based on this geomorphic database and consists of 50 points and associated attributes. The database was developed as part of a study to develop methods to estimate bankfull characteristics of Ohio streams and to relate geomorphic characteristics of Ohio streams to peak streamflows of selected recurrence intervals. The results of the study are presented in a report by Sherwood and Huitger (2005). The database developed for this study consists of geomorphic, basin, and flood-frequency characteristics for 50 study sites in Ohio, of which 40 sites are near streamflow-gaging stations. Field surveys were done at each site to collect the geomorphic data. Bankfull indicators were identified and evaluated, cross-section and longitudinal profiles were surveyed, and bed- and bank-material were sampled. Field data were analyzed to determine various geomorphic characteristics such as bankfull width, bankfull mean depth, bankfull cross-sectional area, bankfull discharge, streambed slope, and bed- and bank-material particle-size distribution. The various geomorphic characteristics were analyzed by means of a combination of graphical and statistical techniques. These techniques resulted in a set of regional curves, simple-regression (drainage-area only) equations, and multiple-regression equations to estimate bankfull width, bankfull mean depth, bankfull cross-sectional area, and bankfull discharge. Explanatory variables included drainage area, main-channel slope, main- channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope. Average standard errors of prediction for bankfull width equations ranged from 20.6 to 24.8 percent; for bankfull mean depth, 18.8 to 20.6 percent; for bankfull cross-sectional area, 25.4 to 30.6 percent; and for bankfull discharge, 27.0 to 78.7 percent. The simple-regression (drainage-area only) equations have the highest average standard errors of prediction. The multiple-regression equations-in which the explanatory variables included drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope-have the lowest average standard errors of prediction. Statistical and graphical analyses were done to investigate development of methods to estimate flood-peak discharges from geomorphic characteristics based on the 40 study sites at streamflow-gaging stations. The logarithms of the annual peak discharges for each site were fit by a Pearson Type III frequency distribution to develop a flood-peak-frequency relation for each site. The peak-frequency data were related to geomorphic, basin, and climatic variables of the 40 study sites by multiple-regression analysis. The analyses resulted in a set of multiple-regression equations to estimate flood-peak discharge having recurrence intervals of 2, 5, 10, 25, 50, and 100 years from bankfull cross-sectional area, in which the average standard errors of prediction are 31.6, 32.6, 35.9, 41.5, 46.2, and 51.2 percent, respectively. Sherwood, J.M. and Huitger, C.A., 2005, Bankfull Characteristics of Ohio Streams and Their Relation to Peak Streamflows: U.S. Geological Survey Scientific Investigations Report 2005-5153

In cooperation with the Ohio Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration, the USGS developed a database of geomorphic data for a sampling of unregulated natural alluvial streams in Ohio. The vector point shapefile that these metadata describe is based on this geomorphic database and consists of 50 points and associated attributes. The database was developed as part of a study to develop methods to estimate bankfull characteristics of Ohio streams and to relate geomorphic characteristics of Ohio streams to peak streamflows of selected recurrence intervals. The results of the study are presented in a report by Sherwood and Huitger (2005). The database developed for this study consists of geomorphic, basin, and flood-frequency characteristics for 50 study sites in Ohio, of which 40 sites are near streamflow-gaging stations. Field surveys were done at each site to collect the geomorphic data. Bankfull indicators were identified and evaluated, cross-section and longitudinal profiles were surveyed, and bed- and bank-material were sampled. Field data were analyzed to determine various geomorphic characteristics such as bankfull width, bankfull mean depth, bankfull cross-sectional area, bankfull discharge, streambed slope, and bed- and bank-material particle-size distribution. The various geomorphic characteristics were analyzed by means of a combination of graphical and statistical techniques. These techniques resulted in a set of regional curves, simple-regression (drainage-area only) equations, and multiple-regression equations to estimate bankfull width, bankfull mean depth, bankfull cross-sectional area, and bankfull discharge. Explanatory variables included drainage area, main-channel slope, main- channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope. Average standard errors of prediction for bankfull width equations ranged from 20.6 to 24.8 percent; for bankfull mean depth, 18.8 to 20.6 percent; for bankfull cross-sectional area, 25.4 to 30.6 percent; and for bankfull discharge, 27.0 to 78.7 percent. The simple-regression (drainage-area only) equations have the highest average standard errors of prediction. The multiple-regression equations-in which the explanatory variables included drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope-have the lowest average standard errors of prediction. Statistical and graphical analyses were done to investigate development of methods to estimate flood-peak discharges from geomorphic characteristics based on the 40 study sites at streamflow-gaging stations. The logarithms of the annual peak discharges for each site were fit by a Pearson Type III frequency distribution to develop a flood-peak-frequency relation for each site. The peak-frequency data were related to geomorphic, basin, and climatic variables of the 40 study sites by multiple-regression analysis. The analyses resulted in a set of multiple-regression equations to estimate flood-peak discharge having recurrence intervals of 2, 5, 10, 25, 50, and 100 years from bankfull cross-sectional area, in which the average standard errors of prediction are 31.6, 32.6, 35.9, 41.5, 46.2, and 51.2 percent, respectively. Sherwood, J.M. and Huitger, C.A., 2005, Bankfull Characteristics of Ohio Streams and Their Relation to Peak Streamflows: U.S. Geological Survey Scientific Investigations Report 2005-5153

This data release includes datasets with annual streamflow statistics determined with the Indicators of Hydrologic Alteration software and R source code to create time-series plots with overlaid locally weighted scatterplot smoothing (lowess) lines.

This data release includes datasets with annual streamflow statistics determined with the Indicators of Hydrologic Alteration software and R source code to create time-series plots with overlaid locally weighted scatterplot smoothing (lowess) lines.

This data release includes datasets with annual streamflow statistics determined with the Indicators of Hydrologic Alteration software and R source code to create time-series plots with overlaid locally weighted scatterplot smoothing (lowess) lines.

This data release consists of 5390 streamflow gages within the conterminous United States that will serve as version 1.0 of streamflow benchmark locations for hydrologic model evaluation and benchmarking.

This data release consists of 5390 streamflow gages within the conterminous United States that will serve as version 1.0 of streamflow benchmark locations for hydrologic model evaluation and benchmarking.

This data release comprises the tabular data used to develop regression equations for estimating selected low-flow statistics for ungaged streams in Ohio that are not substantially affected by regulation, diversions, or other anthropogenic influences, and the geographic information systems (GIS) layer to implement them in the U.S. Geological Survey StreamStats application (https://streamstats.usgs.gov). A statewide recharge-based estimate of streamflow variability index (SVI) was used as an explanatory variable in developing many of the equations to estimate selected low-flow statistics at ungaged sites in Ohio and is included as part of this data release. Regressions, using SVI as the explanatory variable, were used to develop equations for predicting annual and seasonal minimum 1-, 7-, 30-, and 90-day mean flows with 10-year recurrence intervals, the harmonic mean flow, and the 80 percent duration flow. The resulting equations are presented in VonIns and Koltun (2024). To apply the equations to ungaged sites in Ohio, a raster (grid) of estimated streamflow variability index (SVI) for Ohio is included. The raster was developed using Environmental Systems Research Institute (ESRI) Spatial Analyst Software’s Empirical Bayesian kriging (EBK) geoprocessing function with at-gage computed SVIs used as the dependent variable and a recharge raster (grid) of estimated mean annual natural ground-water recharge (Wolock, 2003) as the explanatory variable. Other explanatory variables used to develop the equations and included in tabular form as part of this data release include decimal longitude and drainage area. A statewide coverage of decimal longitude and drainage area were not included as part of this data release because they are already available for ungaged streams within StreamStats.