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.

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.

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.

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.

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.

This map shows percentage changes in the minimum annual rate of water carried by rivers and streams across the country, based on the long-term rate of change from 1940 to 2018. For more information: https://www.epa.gov/climate-indicators.

Perennial streams in Idaho have been modeled using regression equations for 7-day, 2-year low flows (7Q2) described in Wood and others (2009, U.S. Geological Survey Scientific Investigations Report 2009-5015). The model produces "synthetic" streams based on 10-meter resolution digitial elevation models that have been processed to agree closely with 1:24,000-scale National Hydrography Dataset flowlines. See Larger_Work_Citation report text for a complete description of the modeling process. In this dataset, the synthetic stream lines have been indexed to the NHDPlus Version 01_02 (schema version 1, data version 2). Points along the synthetic streams where 7Q2 model estimates exceeded 0.1 cubic feet per second were snapped to the NHDPlus 1:100,000-scale flowlines, and then traced downstream using the NHDPlus network. The data are presented in the form of a dBase-format event table. The traced line events correspond to synthetic stream lines having PerCode values of 2 or 3.

To provide daily mean streamflow values at ungaged (partial-record) sites within the Yankee Fork Salmon River watershed, the U.S. Geological Survey (USGS), in cooperation with U.S. Bureau of Reclamation, used discharge measurements at three partial-record sites and related those measurements to a nearby USGS real-time streamgage (index site). Daily mean streamflow was estimated by developing a regression relationship between each partial-record site and the index site for water years 2012-2019. These data are intended to provide daily mean streamflow estimates at partial-record sites as part of a larger study (Clark and others, 2021) to estimate sediment loading for each site.

To provide daily mean streamflow values at ungaged (partial-record) sites within the Yankee Fork Salmon River watershed, the U.S. Geological Survey (USGS), in cooperation with U.S. Bureau of Reclamation, used discharge measurements at three partial-record sites and related those measurements to a nearby USGS real-time streamgage (index site). Daily mean streamflow was estimated by developing a regression relationship between each partial-record site and the index site for water years 2012-2019. These data are intended to provide daily mean streamflow estimates at partial-record sites as part of a larger study (Clark and others, 2021) to estimate sediment loading for each site.