This data release supports publications on the Sleepers River Research Watershed near Danville, Vermont. Most of the research at Sleepers River takes place at W-9, the 40.5-hectare forested headwater site. Topics include understanding hydrologic flow paths, biogeochemical cycling, and organic carbon dynamics. Flow and precipitation data are integral to understanding these processes, for example by combining flow and chemical concentrations to compute solute export from the catchment. These records begin in late September 1991 and extend through calendar year 2018. The release includes five-minute data for discharge, daily data for precipitation, runoff, and maximum and minimum air temperature, and an annual tabulation of precipitation and runoff.

As the climate warms and dry periods become more extreme, shallow groundwater discharge is generally becoming a less reliable source of streamflow while deep groundwater discharge remains a more resilient source. The implications of shifts in the relative balance of shallow and deep groundwater discharge sources are profound in gaining streams. These different sources exert critical controls on stream temperature and water quality as influenced by legacy groundwater contaminant transport. Groundwater discharge flux rates over time were used for the inference of source groundwater characteristics to prominent riverbank groundwater discharge faces along the mainstem Farmington River, CT USA. To estimate groundwater discharge rates, we deployed sediment temperature loggers (iButton #DS1922L, Maxim Integrated, Inc., San Jose, CA, USA) in vertical profilers installed directly into mapped preferential groundwater discharge points across extensive riverbank discharge face features.Temperature data contained in this release were collected from June 24 to November 5, 2020, at 40 distinct discharge point riverbank locations, similar to those described by Barclay et al. (2022) and Briggs et al. (2022). Saturated sediment thermal conductivity and heat capacity were measured in-situ with a TEMPOS Thermal Property Analyzer (TEMPOS, Meter Group, Inc., Pullman, WA, USA) at multiple points across each riverbank discharge face to aid in estimating groundwater discharge flux rates. Barclay, J. R., Briggs, M. A., Moore, E. M., Starn, J. J., Hanson, A. E. H., & Helton, A. M. (2022). Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale. Advances in Water Resources, 160. https://doi.org/10.1016/j.advwatres.2021.104108 Briggs, M. A., Jackson, K. E., Liu, F., Moore, E. M., Bisson, A., & Helton, A. M. (2022). Exploring Local Riverbank Sediment Controls on the Occurrence of Preferential Groundwater Discharge Points. Water, 14(1). https://doi.org/10.3390/w14010011

As the climate warms and dry periods become more extreme, shallow groundwater discharge is generally becoming a less reliable source of streamflow while deep groundwater discharge remains a more resilient source. The implications of shifts in the relative balance of shallow and deep groundwater discharge sources are profound in gaining streams. These different sources exert critical controls on stream temperature and water quality as influenced by legacy groundwater contaminant transport. Groundwater discharge flux rates over time were used for the inference of source groundwater characteristics to prominent riverbank groundwater discharge faces along the mainstem Farmington River, CT USA. To estimate groundwater discharge rates, we deployed sediment temperature loggers (iButton #DS1922L, Maxim Integrated, Inc., San Jose, CA, USA) in vertical profilers installed directly into mapped preferential groundwater discharge points across extensive riverbank discharge face features.Temperature data contained in this release were collected from June 24 to November 5, 2020, at 40 distinct discharge point riverbank locations, similar to those described by Barclay et al. (2022) and Briggs et al. (2022). Saturated sediment thermal conductivity and heat capacity were measured in-situ with a TEMPOS Thermal Property Analyzer (TEMPOS, Meter Group, Inc., Pullman, WA, USA) at multiple points across each riverbank discharge face to aid in estimating groundwater discharge flux rates. Barclay, J. R., Briggs, M. A., Moore, E. M., Starn, J. J., Hanson, A. E. H., & Helton, A. M. (2022). Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale. Advances in Water Resources, 160. https://doi.org/10.1016/j.advwatres.2021.104108 Briggs, M. A., Jackson, K. E., Liu, F., Moore, E. M., Bisson, A., & Helton, A. M. (2022). Exploring Local Riverbank Sediment Controls on the Occurrence of Preferential Groundwater Discharge Points. Water, 14(1). https://doi.org/10.3390/w14010011

These data include annual instantaneous maximum discharge record for 156 streams and rivers in Vermont and adjacent areas of New Hampshire, Massachusetts, and New York through the 2023 water year. The data also include flood-frequency estimates for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities that were analyzed using the discharge data. These flood-frequency data were used to develop regression equations for estimating the magnitude of floods at the selected annual exceedance probabilities on ungaged, unregulated, rural streams in Vermont. The regression equations use the basin characteristics of drainage area, percentage of wetland area in the basin, and the basinwide mean of the annual precipitation as explanatory variables. These basin characteristics for the streamgages and the Geographic Information System datasets for computing the basin characteristics are also in this data release. This data release is structured with the streamgage data, the input and output files for the version 7.5.1 PeakFQ software (U.S. Geological Survey, 2024) used to conduct flood-frequency analysis, the flood-frequency results, the streamgage basin characteristics, and the geographic information system datasets used to determine the basin characteristics on the main page. There is one sub-page which is used as a model archive for the regression analysis. U.S. Geological Survey, 2024, Water resources application software, PeakFQ, accessed March 4, 2024, at http://water.usgs.gov/software/peakfq.html.

In cooperation with the West Virginia Division of Transportation, Department of Highways (WVDOH), precipitation and streamflow were measured at four streamgages in West Virginia to compute time of concentration (Tc) and compare it to Tc estimates made using accepted methods. Precipitation and streamflow data were collected during 2017-2020. Storms were identified and classified through an iterative process relying heavily on inspection of graphs. Three hydrograph time metrics that represent Tc were computed for this study: time to rise, time to recede from a high point on the hydrograph to an inflection on the recession, and the time between an inflection on the hyetograph and an inflection on the recession of the hydrograph (PI-to-RI). Seven-minute running averages were used to compute time metrics for the sites with flow data collected at 1-minute intervals. Storms were designated as beginning when precipitation began. A new storm was designated if six or more hours had passed since the previous rain. Periods of intermittent rain were classified as part of the same storm if breaks were less than six hours. Inspection of graphs confirmed that for all sites and storms, a six-hour break in precipitation was enough time for stormflows to end. Subsequent periods were included in the previous storm until another storm began or until flows reached zero. Cumulative total precipitation was computed for each storm. Storms that did not result in measurable flow were identified and excluded from further analysis. This process through this step resulted in the identification of 529 storms. Storms were then ranked by peak flow. The storms with the smallest peaks and therefore the least relevance for design were discarded. The 50 biggest storms from each site were retained for analysis. Three types of hydrograph time metrics were delineated: time to rise, time to recede, and PI-to-RI. To be counted, the rise needed to be (1) at a steady rate, (2) clearly the result of a specific spate of rain, (3) visually distinct, and (4) representative of a meaningful change in flow magnitude. Time to recede was assessed similarly, with the additional constraint that when repeated or sustained rain fell during the recession and caused flow to rise, the event was excluded. The time between PI-to-RI was determined as the difference between a (1) final inflection on the hyetograph before a visually distinct storm peak and (2) the inflection on the receding limb of the hydrograph from a steep decrease in stormflow to a part of the hydrograph with a flatter slope. Hydrograph events were included in analyses if (1) their maximum values were above the flow threshold for the site, (2) the event was not affected by snow, (3) the slope of the rise or recession was consistent and steady during a relevant part of an event, (4) the flow record during the hydrograph event was complete without estimated values, (5) the event in question represented a meaningful change in flow, (6) for recessions, rain that continued while flow receded was minimal and did not appear to interrupt the recession with secondary rises in flow, and (7) whether changes between successive unit flow measurements during the hydrograph event were primarily either increases or decreases, indicating it was primarily stormflow, or largely stable, which characterized minor rises and recessions that exceeded flow thresholds only because they began when baseflow was already high. Quality-assurance metrics were developed and computed to show how well the hydrograph time metrics met these criteria; these metrics are included in this data release.

This data release is the update of the watershed data management (WDM) database file WBDR17.WDM, with the processed data for the period October 1, 2016, through September 30, 2017. The WDM database file WBDR16.WDM is updated with the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2016, through September 30, 2017, following the guidelines documented in Bera (2017) and is renamed as WBDR17.WDM. Meteorological data other than precipitation (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) are copied from ARGN17.WDM and stored in this WDM file. Errors have been found in each of ARGNXX.WDM prior to Water Year (WY) 2023. XX represents last two digits of a WY. A WY is the 12-month period, October 1 through September 30, in which it ends. WBDR17.WDM contains erroneous meteorological data and related flag values thereby. WBDR17.WDM is removed. User is advised to download WBDR22.WDM from https://doi.org/10.5066/P1LDIASU. WBDR22.WDM contains corrected meteorological data from ARGN23.WDM (Bera, 2024a) for the period from January 1, 1997, through September 30, 2022. This database file also contains the quality-assured and quality-controlled hydrologic data for the period January 1, 1997, through September 30, 2022, processed following the guidelines documented in Bera (2017). While WBDR17.WDM is available from the author, all the records in WBDR17.WDM can be found in WBDR22.WDM as well. Data in dataset number (DSN) 107 and 801–811 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data from tipping bucket raingages collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-811 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 11 NEXRAD–MPE subbasins in the West Branch DuPage River watershed as described in Bera and Ortel (2018). The data are downloaded and uploaded daily into a WDM database that is used for the real-time streamflow simulation system. Data from DSN 107 and 801-811 are copied from this WDM and stored in WBDR22.WDM. DSN 107 and 801-811 are updated with the data through September 30, 2022. Data in DSN 4031 (water-surface elevation from West Branch DuPage River at Fawell Dam) is updated through September 30, 2022, similarly (Bera, 2017). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During October 1, 2016, through September 30, 2017, the daily total rainfall (in the water year summary for water year 2017) from the rain gage using the HOBO® logger did not match with the sum of the instantaneous values pulled from NWIS-WEB for several days. This is due to multiple tips occurring within the same minute. NWIS-WEB is only counts the first tip, and ignores any other tips that occur within the same minute. HOBO® loggers only record the time of a tip, and the data is post processed to apply midnight time stamps and backfill 5- or 15-minute instantaneous values into the data log. The multiple tips occurring in the same minute are accurate, thus so is the daily total in the water year summary table. Table 1 shows the list of station(s) using the HOBO® logger that had different daily total rainfall in the Water Data Report than those computed from the data pulled from NWIS-WEB. The days with the difference of 0.03 inches or more are filled with the nearby stations as listed in Table 1. The DCP loggers on the other hand, provide a value or data point every 5 or 15 minutes. The rain gage using a DCP logger does not show any such difference from the instantaneous values pulled from NWIS-WEB. The complete list of missing precipitation data period and the nearby stations used to fill in those missing periods from October 1, 2016, through September 30, 2017, is given in Table 2. The list of snow affected days of precipitation data and the missing

This data release is the update of the watershed data management (WDM) database file WBDR17.WDM, with the processed data for the period October 1, 2016, through September 30, 2017. The WDM database file WBDR16.WDM is updated with the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2016, through September 30, 2017, following the guidelines documented in Bera (2017) and is renamed as WBDR17.WDM. Meteorological data other than precipitation (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) are copied from ARGN17.WDM and stored in this WDM file. Errors have been found in each of ARGNXX.WDM prior to Water Year (WY) 2023. XX represents last two digits of a WY. A WY is the 12-month period, October 1 through September 30, in which it ends. WBDR17.WDM contains erroneous meteorological data and related flag values thereby. WBDR17.WDM is removed. User is advised to download WBDR22.WDM from https://doi.org/10.5066/P1LDIASU. WBDR22.WDM contains corrected meteorological data from ARGN23.WDM (Bera, 2024a) for the period from January 1, 1997, through September 30, 2022. This database file also contains the quality-assured and quality-controlled hydrologic data for the period January 1, 1997, through September 30, 2022, processed following the guidelines documented in Bera (2017). While WBDR17.WDM is available from the author, all the records in WBDR17.WDM can be found in WBDR22.WDM as well. Data in dataset number (DSN) 107 and 801–811 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data from tipping bucket raingages collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-811 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 11 NEXRAD–MPE subbasins in the West Branch DuPage River watershed as described in Bera and Ortel (2018). The data are downloaded and uploaded daily into a WDM database that is used for the real-time streamflow simulation system. Data from DSN 107 and 801-811 are copied from this WDM and stored in WBDR22.WDM. DSN 107 and 801-811 are updated with the data through September 30, 2022. Data in DSN 4031 (water-surface elevation from West Branch DuPage River at Fawell Dam) is updated through September 30, 2022, similarly (Bera, 2017). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During October 1, 2016, through September 30, 2017, the daily total rainfall (in the water year summary for water year 2017) from the rain gage using the HOBO® logger did not match with the sum of the instantaneous values pulled from NWIS-WEB for several days. This is due to multiple tips occurring within the same minute. NWIS-WEB is only counts the first tip, and ignores any other tips that occur within the same minute. HOBO® loggers only record the time of a tip, and the data is post processed to apply midnight time stamps and backfill 5- or 15-minute instantaneous values into the data log. The multiple tips occurring in the same minute are accurate, thus so is the daily total in the water year summary table. Table 1 shows the list of station(s) using the HOBO® logger that had different daily total rainfall in the Water Data Report than those computed from the data pulled from NWIS-WEB. The days with the difference of 0.03 inches or more are filled with the nearby stations as listed in Table 1. The DCP loggers on the other hand, provide a value or data point every 5 or 15 minutes. The rain gage using a DCP logger does not show any such difference from the instantaneous values pulled from NWIS-WEB. The complete list of missing precipitation data period and the nearby stations used to fill in those missing periods from October 1, 2016, through September 30, 2017, is given in Table 2. The list of snow affected days of precipitation data and the missing

This data release is the update of the watershed data management (WDM) database file WBDR17.WDM, with the processed data for the period October 1, 2016, through September 30, 2017. The WDM database file WBDR16.WDM is updated with the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2016, through September 30, 2017, following the guidelines documented in Bera (2017) and is renamed as WBDR17.WDM. Meteorological data other than precipitation (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) are copied from ARGN17.WDM and stored in this WDM file. Errors have been found in each of ARGNXX.WDM prior to Water Year (WY) 2023. XX represents last two digits of a WY. A WY is the 12-month period, October 1 through September 30, in which it ends. WBDR17.WDM contains erroneous meteorological data and related flag values thereby. WBDR17.WDM is removed. User is advised to download WBDR22.WDM from https://doi.org/10.5066/P1LDIASU. WBDR22.WDM contains corrected meteorological data from ARGN23.WDM (Bera, 2024a) for the period from January 1, 1997, through September 30, 2022. This database file also contains the quality-assured and quality-controlled hydrologic data for the period January 1, 1997, through September 30, 2022, processed following the guidelines documented in Bera (2017). While WBDR17.WDM is available from the author, all the records in WBDR17.WDM can be found in WBDR22.WDM as well. Data in dataset number (DSN) 107 and 801–811 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data from tipping bucket raingages collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-811 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 11 NEXRAD–MPE subbasins in the West Branch DuPage River watershed as described in Bera and Ortel (2018). The data are downloaded and uploaded daily into a WDM database that is used for the real-time streamflow simulation system. Data from DSN 107 and 801-811 are copied from this WDM and stored in WBDR22.WDM. DSN 107 and 801-811 are updated with the data through September 30, 2022. Data in DSN 4031 (water-surface elevation from West Branch DuPage River at Fawell Dam) is updated through September 30, 2022, similarly (Bera, 2017). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During October 1, 2016, through September 30, 2017, the daily total rainfall (in the water year summary for water year 2017) from the rain gage using the HOBO® logger did not match with the sum of the instantaneous values pulled from NWIS-WEB for several days. This is due to multiple tips occurring within the same minute. NWIS-WEB is only counts the first tip, and ignores any other tips that occur within the same minute. HOBO® loggers only record the time of a tip, and the data is post processed to apply midnight time stamps and backfill 5- or 15-minute instantaneous values into the data log. The multiple tips occurring in the same minute are accurate, thus so is the daily total in the water year summary table. Table 1 shows the list of station(s) using the HOBO® logger that had different daily total rainfall in the Water Data Report than those computed from the data pulled from NWIS-WEB. The days with the difference of 0.03 inches or more are filled with the nearby stations as listed in Table 1. The DCP loggers on the other hand, provide a value or data point every 5 or 15 minutes. The rain gage using a DCP logger does not show any such difference from the instantaneous values pulled from NWIS-WEB. The complete list of missing precipitation data period and the nearby stations used to fill in those missing periods from October 1, 2016, through September 30, 2017, is given in Table 2. The list of snow affected days of precipitation data and the missing

This dataset contains gage information for 75 Hydroclimatic Data Network-2009 basins in the conterminous United States and associated annual runoff volume, winter-spring runoff volume, and winter-spring runoff timing data 1920-2014, as well as trend results for WSCVD and WSV for periods 1920-2014, 1940-2014, and 1960-2014.

Watershed Data Management (WDM) database file WBDR18.WDM is updated with the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2018, through September 30, 2019, following the guidelines documented in Bera (2017) and is renamed as WBDR19.WDM. Meteorological data other than precipitation (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) were copied from ARGN19.WDM and stored in this WDM file. Errors have been found in each of ARGNXX.WDM prior to Water Year (WY) 2023. XX represents last two digits of a WY. A WY is the 12-month period, October 1 through September 30, in which it ends. WBDR19.WDM contains erroneous meteorological data and related flag values thereby. WBDR19.WDM is removed. User is advised to download WBDR22.WDM from https://doi.org/10.5066/P1LDIASU. WBDR22.WDM contains corrected meteorological data from ARGN23.WDM (Bera, 2024a) for the period from January 1, 1997, through September 30, 2022. This database file also contains the quality-assured and quality-controlled hydrologic data for the period January 1, 1997, through September 30, 2022, processed following the guidelines documented in Bera (2017). While WBDR19.WDM is available from the author, all the records in WBDR19.WDM can be found in WBDR22.WDM as well. This version of data release describes the watershed data management (WDM) database file WBDR22.WDM (Bera, 2024b). It contains the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2007, through September 30, 2022, following the guidelines documented in Bera (2017). Data in dataset number (DSN) 107 and 801–811 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data from tipping bucket raingages collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-811 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 11 NEXRAD–MPE subbasins in the West Branch DuPage River watershed as described in Bera and Ortel (2018). The data are downloaded and uploaded daily into a WDM database that is used for the real-time streamflow simulation system. Data from DSN 107 and 801-811 are copied from this WDM and stored in WBDR22.WDM. DSN 107 and 801-811 are updated with the data through September 30, 2022. Data in DSN 4031 (water-surface elevation from West Branch DuPage River at Fawell Dam) is updated through September 30, 2022, similarly (Bera, 2017). The complete list of missing precipitation data period and the nearby stations used to fill in those missing periods from October 1, 2018, through September 30, 2019, is given in the table, missing_data (available in csv format). The list of snow affected days of precipitation data and the missing and estimated period of the stage and flow data in WBDR22.WDM database during the period October 1, 2018, through September 30, 2019, are given in the USGS annual Water Data Report at https://wdr.water.usgs.gov. To open WBDR22.WDM file user needs to install Sara Timeseries utility described in the section "Related External Resources". First posted - March 1, 2021 (available from author) References Cited: Bera, M., 2024a, Meteorological Database, Argonne National Laboratory, Illinois: U.S. Geological Survey data release, https://doi.org/10.5066/P146RBHK. ____ 2024b, Watershed Data Management (WDM) Database (WBDR22.WDM) for West Branch DuPage River Streamflow Simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2022: U.S. Geological Survey data release, https://doi.org/10.5066/P1LDIASU. Bera, M., and Ortel, T.W., 2018, Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system: U.S. Geological Survey Open-File Report 2017–1159, 16 p., https://doi.org/10.3133/ofr20171159. Bera, M., 2017, Watershed