The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting the methods, results, and applications of an updated flood-frequency study for the State of Illinois. This data release contains data related to the analysis completed to determine peak-flow quantiles (flood frequency estimates) at streamgages in Illinois for 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs), as well as data used to develop regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example water year 2017 was from October 1, 2016 to September 30, 2017). There is one set of equations for each of Illinois’ seven hydrologic regions, and, for each region, one equation for each AEP. These regional equations allow the estimation of peak-flow quantiles at ungaged locations throughout the state and their uncertainties. This data release contains a figure of the study area in addition to seven tables that provide both input data and results in tabular format. See metadata for detailed information.

The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting methods, results, and applications of an updated flood-frequency study for the State of Illinois. The study developed regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). The data provided through this data release are those digital datasets of basin characteristics that have been collected, tested, and ultimately selected for use in regional regression equations. These datasets consist of raster grid files for slope (slope100.zip), calculated from a published digital elevation model (DEM) (Schafer and Sharpe, 2023), soil slope (stats_slope100.zip) subsetted and resampled from Wolock (1997), a soil texture permeability index (texp_indx_rnd.zip) computed using data from Wolock (1997), land cover (nlcd16_22_23_24.zip) adapted from Yang and others (2018), a basin soil wetness measure (drclass1a.zip) computed from U.S. Department of Agriculture (USDA) (2013), and an urbanization fraction (urbthe2010.zip) computed from Theobald 2010 data (Theobald, 2005). Some basin characteristics are not included in this data release as they are easily derived from StreamStats basin delineations themselves, such as basin drainage area. The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation (ICT) and the Illinois Department of Transportation (IDOT), prepared these digital datasets of basin characteristics for use in the Illinois StreamStats application (https://streamstats.usgs.gov/ss/). Two additional shapefiles are provided: a shapefile of the streamgages (IL_StreamStats_Gages.zip) and a shapefile of the associated delineated streamgage drainage basins (IL_StreamStats_DrainageBasins.zip) used in analysis (Over and others, 2023).

The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting methods, results, and applications of an updated flood-frequency study for the State of Illinois. The study developed regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). The data provided through this data release are those digital datasets of basin characteristics that have been collected, tested, and ultimately selected for use in regional regression equations. These datasets consist of raster grid files for slope (slope100.zip), calculated from a published digital elevation model (DEM) (Schafer and Sharpe, 2023), soil slope (stats_slope100.zip) subsetted and resampled from Wolock (1997), a soil texture permeability index (texp_indx_rnd.zip) computed using data from Wolock (1997), land cover (nlcd16_22_23_24.zip) adapted from Yang and others (2018), a basin soil wetness measure (drclass1a.zip) computed from U.S. Department of Agriculture (USDA) (2013), and an urbanization fraction (urbthe2010.zip) computed from Theobald 2010 data (Theobald, 2005). Some basin characteristics are not included in this data release as they are easily derived from StreamStats basin delineations themselves, such as basin drainage area. The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation (ICT) and the Illinois Department of Transportation (IDOT), prepared these digital datasets of basin characteristics for use in the Illinois StreamStats application (https://streamstats.usgs.gov/ss/). Two additional shapefiles are provided: a shapefile of the streamgages (IL_StreamStats_Gages.zip) and a shapefile of the associated delineated streamgage drainage basins (IL_StreamStats_DrainageBasins.zip) used in analysis (Over and others, 2023).

The U.S. Geological Survey (USGS) Central Midwest Water Science Center (CMWSC) completed a report (Over and others, 2023) documenting methods for peak-flow frequency analysis in Illinois following Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs) for selected USGS streamgages. This data release presents peak-flow frequency analyses for selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). References Cited: England, J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O., Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., Jr., 2019, Guidelines for determining flood flow frequency — Bulletin 17C (ver. 1.1, May 2019): U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p., https://doi.org/10.3133/tm4B5. Over, T.M., Marti, M.K., O'Shea, P.S., Sharpe, J.B., 2023, Estimating peak-flow quantiles for selected annual exceedance probabilities in Illinois (Report No. FHWA-ICT-23-014). Illinois Center for Transportation. https://doi.org/10.36501/0197-9191/23-019.

The U.S. Geological Survey (USGS) Central Midwest Water Science Center (CMWSC) completed a report (Over and others, 2023) documenting methods for peak-flow frequency analysis in Illinois following Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs) for selected USGS streamgages. This data release presents peak-flow frequency analyses for selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). References Cited: England, J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O., Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., Jr., 2019, Guidelines for determining flood flow frequency — Bulletin 17C (ver. 1.1, May 2019): U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p., https://doi.org/10.3133/tm4B5. Over, T.M., Marti, M.K., O'Shea, P.S., Sharpe, J.B., 2023, Estimating peak-flow quantiles for selected annual exceedance probabilities in Illinois (Report No. FHWA-ICT-23-014). Illinois Center for Transportation. https://doi.org/10.36501/0197-9191/23-019.

This data release contains data in support of "Regional Analysis of the Dependence of Peak-Flow Quantiles on Climate with Application to Adjustment to Climate Trends" (Over and others, 2025). It contains input and output data used to analyze the effect of climate changes on trends in floods using three regression approaches. The input consists of two files. The first, "station_list.csv," contains streamgage information for the 404 streamgages considered for use in Over and others (2025). Only 330 of the 404 streamgages were considered non-redundant and used in the final analysis; these streamgages have a value of "Non-redundant" in the "redundancy_status" column. This file includes calibrated Monthly Water Balance Model (MWBM) parameters and basin characteristics. The second, "regression_input.csv," contains regression input data, including observed peak streamflow and precipitation. MWBM-simulated streamflow data was created using two sets of MWBM parameters: at-site calibrated parameters and median calibrated parameters. At-site calibrated parameters varied by station and represent the best-performing set of parameters per station. These parameters can be found in "station_list.csv". The median calibrated parameters were obtained by taking the median of all at-site calibrated parameters for the 330 streamgage basins used in analysis. See the Entity and Attribute section for details. The output files consist of nine Comma Separated Value (CSV) files. "Kendall_cor.csv" contains Mann-Kendall trend analysis results by streamgage. The regression results for annual maximum streamflow from at-site calibrated MWBM parameters by streamgage are provided in "byStation-sqrt_ann_max_MWBM_Q.csv". The regression results for annual maximum streamflow from median calibrated MWBM parameters by streamgage are provided in "byStation-sqrt_ann_max_MWBM_Q-medianMWBM.csv". "FixedEffects-sqrt_ann_max_MWBM_Q.csv" contains fixed effects for annual maximum streamflow from at-site calibrated MWBM parameters by streamgage. "FixedEffects-sqrt_ann_max_MWBM_Q-medianMWBM.csv" contains fixed effects for annual maximum streamflow from median calibrated MWBM parameters by streamgage. "MMQR-sqrt_ann_max_MWBM_Q_adjusted_moments.csv" contains observed and adjusted peak discharge moments from the method-of-moments quantile-regression (MMQR) method. "MMQR-sqrt_ann_max_MWBM_Q_adjusted_quantiles.csv" contains observed and adjusted discharge quantiles from the MMQR method. "QR-sqrt_ann_max_MWBM_Q_adjusted_moments.csv" contains observed and adjusted moments from the single-station quantile regression (QR) method. "QR-sqrt_ann_max_MWBM_Q_adjusted_quantiles.csv" contains observed and adjusted discharge quantiles from the QR method. Also included is "ModelArchive.zip", which contains the R scripts used to create the data provided in this data release and in Over and others, 2025. It contains the input data necessary to run the scripts and readMe files with directions for running the scripts locally.

The U.S. Geological Survey (USGS), in cooperation with Connecticut Department of Transportation, completed a study to improve flood-frequency estimates in Connecticut. This companion data release is a Microsoft Excel workbook for: (1) computing flood discharges for the 50- to 0.2-percent annual exceedance probabilities from peak-flow regression equations, and (2) computing additional prediction intervals, not available through the USGS StreamStats web application. The current StreamStats application (version 4) only computes the 90-percent prediction interval for stream sites in Connecticut. The Excel workbook can be used to compute the 70-, 80-, 90-, 95-, and 99-percent prediction intervals. The prediction interval provides upper and lower limits of the estimated flood discharge with a certain probability, or level of confidence in the accuracy of the estimate. The standard error of prediction for the Connecticut peak-flow regression equations ranged from 26.3 to 45.0 percent (Ahearn and Hodgkins, 2020). The Excel workbook consists of four worksheets. The worksheets provide an overview of how the application works; input and output tables of the explanatory variables and flood discharges, and graphical display of the results; and the computational formulas used to estimate the flood discharges and prediction intervals.

This data release presents a peak-flow frequency analysis (Eash and others, 2013) for U.S. Geological Survey streamgage 05465500 Iowa River at Wapello, Iowa. These methods are used to provide estimates of peak-flow quantiles corresponding to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs). Annual peak-flow data used in the peak-flow frequency analysis for this streamgage was retrieved from the U.S. Geological Survey National Water Information System database (U.S. Geological Survey, 2022) and used with USGS flood-frequency analysis software PeakFQ (Veilleux and others, 2014). This data release contains annual peak-flow data (05465500_ffa_2022_WATSTORE.txt), PeakFQ specifications (05465500_ffa_2022.psf), and a series of tables describing the methods and results of the peak-flow frequency analysis (Wapello_ffa_2022.xlsx)

This dataset contains annual peak-flow data, PeakFQ specifications, and results of flood-frequency analyses of annual peak flows for 368 selected streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) in the Great Lakes and Ohio River basins. "PeakFQinput_all.txt" contains annual peak-flow data, ending in water year 2013, for all 368 streamgages in the study area. Annual peak-flow data were obtained from the USGS National Water Information System (NWIS) database (https://nwis.waterdata.usgs.gov/usa/nwis/peak). "PeakFQspec_all.psf" contains PeakFQ specifications for all 368 streamgages in the study area. The specifications were developed by hydrologists in the various USGS Water Science Centers that participated in the study. "PeakFQoutput_all.PRT" contains the results of flood-frequency analyses of annual peak-flow data, for each of the 368 streamgages in the study area, that were conducted using the Expected Moments Algorithm (England and others, 2018). Using the annual peak-flow data in "PeakFQinput_all.txt" and the specifications in "PeakFQspec_all.psf", "PeakFQoutput_all.PRT" was generated in version 7.2 of USGS flood-frequency analysis software PeakFQ (https://water.usgs.gov/software/PeakFQ/; Veilleux and others, 2014). Results of the flood-frequency analyses were used to estimate regional skew for the study area using Bayesian Weighted Least Squares / Bayesian Generalized Least Squares (B-WLS / B-GLS) regression.

This dataset contains annual peak-flow data, PeakFQ specifications, and results of flood-frequency analyses of annual peak flows for 368 selected streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) in the Great Lakes and Ohio River basins. "PeakFQinput_all.txt" contains annual peak-flow data, ending in water year 2013, for all 368 streamgages in the study area. Annual peak-flow data were obtained from the USGS National Water Information System (NWIS) database (https://nwis.waterdata.usgs.gov/usa/nwis/peak). "PeakFQspec_all.psf" contains PeakFQ specifications for all 368 streamgages in the study area. The specifications were developed by hydrologists in the various USGS Water Science Centers that participated in the study. "PeakFQoutput_all.PRT" contains the results of flood-frequency analyses of annual peak-flow data, for each of the 368 streamgages in the study area, that were conducted using the Expected Moments Algorithm (England and others, 2018). Using the annual peak-flow data in "PeakFQinput_all.txt" and the specifications in "PeakFQspec_all.psf", "PeakFQoutput_all.PRT" was generated in version 7.2 of USGS flood-frequency analysis software PeakFQ (https://water.usgs.gov/software/PeakFQ/; Veilleux and others, 2014). Results of the flood-frequency analyses were used to estimate regional skew for the study area using Bayesian Weighted Least Squares / Bayesian Generalized Least Squares (B-WLS / B-GLS) regression.