Measures used to assess trends in the 10th, 50th, and 90th quantiles of annual peak streamflow from 1916-2015 at 2,683 U.S. Geological Survey stations and within 191 4-digit HUCs in the conterminous United States. Linear quantile regression was applied to the selected quantiles of log-transformed annual peak streamflow to represent trends for a range of flood frequencies from small, common floods to large, infrequent floods. Comparative trends in pairs of quantiles were characterized as coherent, convergent, or divergent by comparing the slopes of linear quantile regression equations.

Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annual peak flows is stationary. Better understanding of long-term climatic persistence and further consideration of potential climate and land-use changes have caused the assumption of stationarity to be reexamined. This data release contains input data and results of a study investigating hydroclimatic trends in peak streamflow (peak flow) in the Central United States, including nine states (Iowa, Illinois, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin). Peak flow records from unregulated U.S. Geological Survey (USGS) streamgages were used to evaluate changes over 30-, 50-, 75-, and 100-year trend periods, all ending in water year 2020. This data release contains station lists of the streamgages used in each of the nine states, the peak streamflow input data and peak streamflow analysis results, and the climate input data and climate analysis results. See "Station_Lists.zip" on the landing page for station lists (in text file format) for each state included in the study.

Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annual peak flows is stationary. Better understanding of long-term climatic persistence and further consideration of potential climate and land-use changes have caused the assumption of stationarity to be reexamined. This data release contains input data and results of a study investigating hydroclimatic trends in peak streamflow (peak flow) in the Central United States, including nine states (Iowa, Illinois, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin). Peak flow records from unregulated U.S. Geological Survey (USGS) streamgages were used to evaluate changes over 30-, 50-, 75-, and 100-year trend periods, all ending in water year 2020. This data release contains station lists of the streamgages used in each of the nine states, the peak streamflow input data and peak streamflow analysis results, and the climate input data and climate analysis results. See "Station_Lists.zip" on the landing page for station lists (in text file format) for each state included in the study.

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 drainage basin characteristics and peak-streamflow trend and change-point results for 2,683 U.S. Geological Survey (USGS) streamgages in the conterminous U.S. Data include streamgage identification number, name, drainage area, latitude, longitude, percent urban land use, dam storage, streamgage classification, record completeness status, lag-1 autocorrelation, trend slopes and significance, peaks-over-threshold counts, trends in the numbers of peaks-over-threshold, and change point years and values for median and scale. Also included is an R script containing the Mann-Kendall trend test for three different null hypotheses of the serial structure of the time-series data: independence, short-term persistence, and long-term persistence. Revised - April 8, 2019 (ver. 3.0).

This data release contains drainage basin characteristics and peak-streamflow trend and change-point results for 2,683 U.S. Geological Survey (USGS) streamgages in the conterminous U.S. Data include streamgage identification number, name, drainage area, latitude, longitude, percent urban land use, dam storage, streamgage classification, record completeness status, lag-1 autocorrelation, trend slopes and significance, peaks-over-threshold counts, trends in the numbers of peaks-over-threshold, and change point years and values for median and scale. Also included is an R script containing the Mann-Kendall trend test for three different null hypotheses of the serial structure of the time-series data: independence, short-term persistence, and long-term persistence. Revised - April 8, 2019 (ver. 3.0).

We projected future streamflow outcomes arising from climate change for the southwestern United States during the 21st century due to climate change under two possible greenhouse gas concentration pathways (RCP4.5 and 8.5). The results inform water managers about the future risks of drought in their water resource regions by providing bounds on the possible locations and extents of streamflow loss. To get to these results, we used downscaled future and historical climate data from seven models to drive a new, calibrated SPAtially Referenced Regression On Watershed attributes (SPARROW) streamflow model (Wise and others, 2019, Miller and others, 2020). Temperature and precipitation data come from the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30, Thrasher and others, 2013 and Thrasher and others, 2015), and actual and potential evapotranspiration come from the NEX-DCP30 temperature and precipitation used in the Monthly Water Balance Model (MWBM, Hostetler and Alder, 2016 and Alder, 2017a,b,c). This data set comprises climate data preprocessing code to convert the gridded, monthly-scale climate data to reach scale multidecadal averages for the intervals 1975-2005, 2020-2049, 2040-2069 and 2070-2099, the model input (data1) and model control files, the model code, model results files, and code to post-process and analyze the streamflow model results. The raw climate data (NEX-DCP30, MWBM), and SPARROW model calibration documentation are publicly available elsewhere and are cross linked with this data release (see crossref section). The full data preparation, modeling, and analysis methods, as well as results are described in Miller and others, (2021)

We projected future streamflow outcomes arising from climate change for the southwestern United States during the 21st century due to climate change under two possible greenhouse gas concentration pathways (RCP4.5 and 8.5). The results inform water managers about the future risks of drought in their water resource regions by providing bounds on the possible locations and extents of streamflow loss. To get to these results, we used downscaled future and historical climate data from seven models to drive a new, calibrated SPAtially Referenced Regression On Watershed attributes (SPARROW) streamflow model (Wise and others, 2019, Miller and others, 2020). Temperature and precipitation data come from the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30, Thrasher and others, 2013 and Thrasher and others, 2015), and actual and potential evapotranspiration come from the NEX-DCP30 temperature and precipitation used in the Monthly Water Balance Model (MWBM, Hostetler and Alder, 2016 and Alder, 2017a,b,c). This data set comprises climate data preprocessing code to convert the gridded, monthly-scale climate data to reach scale multidecadal averages for the intervals 1975-2005, 2020-2049, 2040-2069 and 2070-2099, the model input (data1) and model control files, the model code, model results files, and code to post-process and analyze the streamflow model results. The raw climate data (NEX-DCP30, MWBM), and SPARROW model calibration documentation are publicly available elsewhere and are cross linked with this data release (see crossref section). The full data preparation, modeling, and analysis methods, as well as results are described in Miller and others, (2021)

This data release contains results of a study investigating changes in streamflow seasonality associated with hydroclimatic variability in the north-central United States, including nine States (Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin). Peak-flow records from unregulated U.S. Geological Survey streamgages were used to evaluate changes in streamflow seasonality over 75-, 50-, and 30-year trend periods through water year 2020. The streamgages in each of the nine states used in the analysis and the results of the seasonal characteristics and statistical analyses are provided in tabular form (in csv file format) in file "Results.zip" under "Attached Files" below.