Understanding and projecting the downstream benefits of terrestrial surface water storage (volumetric water stored in lakes and wetlands, SWstorage) requires watershed hydrologic models. Use of external datasets to calibrate and validate modeled SWstorage dynamics remains uncommon, particularly across major river basins. Here, we: (1) develop and assess the utility of a novel remote sensing-based (RS) SWstorage approach for verifying watershed-model SWstorage estimates, (2) compare average modeled and RS SWstorage volume across the landscape, and (3) compare variability in modeled and RS SWstorage through time. We used SWstorage informed by Sentinel-1 and -2 (RS SWstorage), with Soil and Water Assessment Tool (SWAT) model simulations (SWAT SWstorage) across the ~450,000 km2 Upper Mississippi River Basin. We found that RS SWstorage was, on average, lower than SWAT SWstorage in tile-drained agricultural regions where static Digital Elevation Model (DEM)-generated depressions used in the SWAT model often did not contain RS surface water. Conversely, RS SWstorage was higher than SWAT SWstorage in wetland-rich regions where surface water was shallower than DEM vertical accuracy. In modeled subbasins where DEM-generated maximum SWstorage capacity was low relative to SWAT SWstorage volumes, SWAT SWstorage was effectively capped and unable to vary through time, whereas RS SWstorage in the same subbasins continued to vary. Thus, RS SWstorage allows for a more accurate representation of where, when, and how much water is on the landscape. This finding is useful for informing watershed model initial conditions and highlights the potential for RS to be used in SWstorage calibration or data assimilation.

subbasins for the Upper MIssissippi River Basin and total surface water storage estimates from remote sensing and from SWAT estimates. This dataset is not publicly accessible because: Data was generated by external co-authors and will be posted on Sciencebase https://www.sciencebase.gov/catalog/item/6785551fd34ec3ce63796a66. It can be accessed through the following means: https://www.sciencebase.gov/catalog/item/6785551fd34ec3ce63796a66 in the repository for reviewers to access the data. The DOI for the final data release will be: 10.5066/P14WAHYW. Data files will be located this address. Format: FGDC metadata .xml file as well as a csv file have been included along with model results for both remote sensing at the SWAT model subbasins.

Globally, many waterbodies and floodplains have been lost, degraded, or are at risk for further loss, which may have unintended consequences for rivers, including exacerbating flood and drought conditions. We explored how including surface water storage time series in deep learning models influences our ability to predict river discharge. We utilized Sentinel-1 and Sentinel-2 algorithms to generate time series of surface water extent. Surface water extent (m2) was converted to storage (m3) using topographic estimates of depression probability and depth. These surface water storage estimates were then tested with meteorological data and catchment characteristics in four Long Short-Term Memory (LSTM) models, each containing a different combination of variable groups, to simulate daily river discharge (2016-2023) for 72 watersheds across the conterminous United States.

Variability in river discharge, particularly very high flow and low flow conditions, has far-reaching environmental and economic consequences. The retention of water in surface storage, concentrated in lakes, ponds, wetlands, floodplains, and temporary water in flood prone areas, can potentially contribute to flow generation and flood regulation. However, the impact of surface water storage on river discharge can be challenging to isolate and quantify. A suite of hydrologic signatures were generated for 72 gages across the conterminous United States. The hydrologic signatures were selected to characterize all flows as well as isolating high and low flows, and machine learning models were developed to explain watershed variability in signature values. Wetland related variables, including multi-sensor-based surface water extent and hydroperiod, were compared with other drivers, including climate, topography, and land cover. An improved understanding of how surface water dynamics influence river discharge can be used to improve the resilience of river systems to climate extremes.

Variability in river discharge, particularly very high flow and low flow conditions, has far-reaching environmental and economic consequences. The retention of water in surface storage, concentrated in lakes, ponds, wetlands, floodplains, and temporary water in flood prone areas, can potentially contribute to flow generation and flood regulation. However, the impact of surface water storage on river discharge can be challenging to isolate and quantify. A suite of hydrologic signatures were generated for 72 gages across the conterminous United States. The hydrologic signatures were selected to characterize all flows as well as isolating high and low flows, and machine learning models were developed to explain watershed variability in signature values. Wetland related variables, including multi-sensor-based surface water extent and hydroperiod, were compared with other drivers, including climate, topography, and land cover. An improved understanding of how surface water dynamics influence river discharge can be used to improve the resilience of river systems to climate extremes.

This data release (DR) is the update of the U.S. Geological Survey - ScienceBase DR (Bera, 2024b), with the processed data for the period October 1, 2022, through September 30, 2023. This DR describes the watershed data management (WDM) database file SC23.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around Salt Creek watershed in DuPage County, Illinois, as described in Bera (2014). Hourly precipitation and hydrologic data for the period October 1, 2022, through September 30, 2023, are processed following the guidelines described in Bera (2014) and Murphy and Ishii (2006) and appended to SC22.WDM (Bera, 2024b) and renamed as SC23.WDM. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) from October 1, 2022, through September 30, 2023, are copied from ARGN23.WDM (Bera, 2024a) and uploaded to SC23.WDM. Data in dataset number (DSN) 107 and 801–810 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-810 contains the processed Next Generation Weather Radar (NEXRAD)-multisensor precipitation estimates (MPE) data from 10 NEXRAD–MPE subbasins in the Salt Creek watershed (Bera and Ortel, 2018). Data in these DSNs are not quality-assured and quality-controlled. The data are downloaded and uploaded daily into a WDM database that is used for the near-real-time streamflow simulation system. Data from DSN 107 and 801-810 are copied from this WDM and stored in the SC23.WDM. DSN 107 and 801-810 in the SC23.WDM are updated with the data through September 30, 2023. Data in DSN 5400 (water-surface elevation at the Elmhurst Quarry at Elmhurst, Illinois) and 5700 (water surface elevation at Thorndale Avenue in Wood Dale, Illinois) are copied and updated through September 30, 2023, similarly (Murphy and Ishii, 2006). The Gage at Thorndale Avenue in Wood Dale, Illinois is maintained by DuPage County Stormwater Department. The complete list of missing precipitation data periods and the nearby stations used to fill in those missing periods from October 1, 2022, through September 30, 2023, is given in Table1.csv. This file is in the comma separated values (CSV) file format and can be downloaded from this landing page. The list of snow affected days of precipitation data and the missing and estimated period of the stage and flow data in SC23.WDM database during the period October 1, 2022, through September 30, 2023, are given in the USGS annual Water Data Report at https://waterdata.usgs.gov/nwis. To open the WDM database SC23.WDM the user may use the Sara Timeseries Utility executable file attached in this page. Table1.csv can be opened with any text editor or Microsoft Excel. References Cited: Bera, M., 2024a, Meteorological Database, Argonne National Laboratory, Illinois: U.S. Geological Survey data release, https://doi.org/10.5066/P146RBHK. Bera, M., 2024b, Watershed Data Management (WDM) Database (SC22.WDM) for Salt Creek Streamflow Simulation, DuPage County, Illinois, January 1, 1997, through September 30, 2022: U.S. Geological Survey data release, https://doi.org/10.5066/P14D6FRA. 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., 2014, Watershed Data Management (WDM) database for Salt Creek streamflow simulation, DuPage County, Illinois, water years 2005–11: U.S. Geological Survey Data Series 870, 18 p., https://doi.org/10.3133/ds870. Murphy, E.A., and Ishii, A.L., 2006, Watershed Data Management (WDM) Database for Salt Creek Streamflow Simulation, DuPage County, Illinois:

The watershed data management (WDM) database SC16.WDM is updated with the processed data for the period October 1, 2016, through September 30, 2017, and renamed as SC17.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around DuPage County, Illinois. Hourly precipitation and hydrologic data for the period October 1, 2016, through September 30, 2017, are processed following the guidelines described in Bera (2014) and appended to SC16.WDM and renamed as SC17.WDM. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) from October 1, 2016, through September 30, 2017, are copied from ARGN17.WDM and appended to SC17.WDM. Data in dataset number (DSN) 107 and 801–810 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-810 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 10 NEXRAD–MPE subbasins in the Salt Creek watershed as described in Bera and Ortel (2018). Data in these DSNs are not quality-assured and quality-controlled. 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 801-810 are copied from this WDM and stored in SC17.WDM. DSN 107 and 801-810 are updated with the data through September 30, 2017. Data in DSN 5400 (water-surface elevation at the quarry) and 5700 (water surface elevation at Thorndale) are updated through September 30, 2017, similarly (Murphy and Ishii, 2006). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During the period October 1, 2016, through September 30, 2017, the daily total value (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 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. Errors have been found in each of ARGNXX.WDM prior to WY23. XX represents last two digits of a water year (WY). A WY is the 12-month period, October 1 through September 30, in which it ends. SC17.wdm contains erroneous meteorological data and related flag values thereby. SC17.WDM is removed. User is advised to download SC22.WDM from a link at https://doi.org/10.5066/P14D6FRA. SC22.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 (2014). While SC17.WDM is available from the author, all the records in SC17.WDM can be found in SC22.WDM as well. The complete list of missing

The watershed data management (WDM) database SC16.WDM is updated with the processed data for the period October 1, 2016, through September 30, 2017, and renamed as SC17.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around DuPage County, Illinois. Hourly precipitation and hydrologic data for the period October 1, 2016, through September 30, 2017, are processed following the guidelines described in Bera (2014) and appended to SC16.WDM and renamed as SC17.WDM. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) from October 1, 2016, through September 30, 2017, are copied from ARGN17.WDM and appended to SC17.WDM. Data in dataset number (DSN) 107 and 801–810 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-810 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 10 NEXRAD–MPE subbasins in the Salt Creek watershed as described in Bera and Ortel (2018). Data in these DSNs are not quality-assured and quality-controlled. 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 801-810 are copied from this WDM and stored in SC17.WDM. DSN 107 and 801-810 are updated with the data through September 30, 2017. Data in DSN 5400 (water-surface elevation at the quarry) and 5700 (water surface elevation at Thorndale) are updated through September 30, 2017, similarly (Murphy and Ishii, 2006). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During the period October 1, 2016, through September 30, 2017, the daily total value (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 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. Errors have been found in each of ARGNXX.WDM prior to WY23. XX represents last two digits of a water year (WY). A WY is the 12-month period, October 1 through September 30, in which it ends. SC17.wdm contains erroneous meteorological data and related flag values thereby. SC17.WDM is removed. User is advised to download SC22.WDM from a link at https://doi.org/10.5066/P14D6FRA. SC22.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 (2014). While SC17.WDM is available from the author, all the records in SC17.WDM can be found in SC22.WDM as well. The complete list of missing

The watershed data management (WDM) database SC16.WDM is updated with the processed data for the period October 1, 2016, through September 30, 2017, and renamed as SC17.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around DuPage County, Illinois. Hourly precipitation and hydrologic data for the period October 1, 2016, through September 30, 2017, are processed following the guidelines described in Bera (2014) and appended to SC16.WDM and renamed as SC17.WDM. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) from October 1, 2016, through September 30, 2017, are copied from ARGN17.WDM and appended to SC17.WDM. Data in dataset number (DSN) 107 and 801–810 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-810 contains the processed Next Generation Weather Radar (NEXRAD)-Multisensor Precipitation Estimates (MPE) data from 10 NEXRAD–MPE subbasins in the Salt Creek watershed as described in Bera and Ortel (2018). Data in these DSNs are not quality-assured and quality-controlled. 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 801-810 are copied from this WDM and stored in SC17.WDM. DSN 107 and 801-810 are updated with the data through September 30, 2017. Data in DSN 5400 (water-surface elevation at the quarry) and 5700 (water surface elevation at Thorndale) are updated through September 30, 2017, similarly (Murphy and Ishii, 2006). Each rain gage station uses one of two different data loggers: the HOBO® or the WaterLOG® H-522+ XL™ Data Collection Platform (DCP). During the period October 1, 2016, through September 30, 2017, the daily total value (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 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. Errors have been found in each of ARGNXX.WDM prior to WY23. XX represents last two digits of a water year (WY). A WY is the 12-month period, October 1 through September 30, in which it ends. SC17.wdm contains erroneous meteorological data and related flag values thereby. SC17.WDM is removed. User is advised to download SC22.WDM from a link at https://doi.org/10.5066/P14D6FRA. SC22.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 (2014). While SC17.WDM is available from the author, all the records in SC17.WDM can be found in SC22.WDM as well. The complete list of missing

This data release (DR) is the update of the U.S. Geological Survey - ScienceBase data release Bera (2023), with the processed data for the period October 1, 2021, through September 30, 2022. This data release describes the watershed data management (WDM) database SC22.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around Salt Creek watershed in DuPage County, Illinois, as described in Bera (2014). Hourly precipitation and hydrologic data for the period October 1, 2021, through September 30, 2022, are processed following the guidelines described in Bera (2014) and Murphy and Ishii (2006) and appended to SC21.WDM and renamed as SC22.WDM. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) are copied from ARGNXX.WDM and appended to SCXX.WDM. XX represents last two digits of a water year (WY). A WY is the 12-month period, October 1 through September 30, in which it ends. Errors have been found in each of ARGNXX.WDM prior to WY23. SCXX.wdm contains erroneous meteorological data and related flag values until WY21 thereby. Meteorological data (wind speed, solar radiation, air temperature, dewpoint temperature, and potential evapotranspiration) from January 1, 1997, through September 30, 2022, are copied from ARGN23.WDM and uploaded to SC22.WDM. Bera (2024) describes the processing of the meteorological data in the database file ARGN23.WDM and Bera (2023) describes the processing of SC21.WDM. Data in dataset number (DSN) 107 and 801–810 are used in comparisons of precipitation data. DSN 107 contains hourly precipitation data collected at Argonne National Laboratory at Argonne, Illinois. DSN 801-810 contains the processed Next Generation Weather Radar (NEXRAD)-multisensor precipitation estimates (MPE) data from 10 NEXRAD–MPE subbasins in the Salt Creek watershed as described in Bera and Ortel (2018). Data in these DSNs are not quality-assured and quality-controlled. 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 801-810 are copied from this WDM and stored in SC22.WDM. DSN 107 and 801-810 are updated with the data through September 30, 2022. Data in DSN 5400 (water-surface elevation at the quarry) and 5700 (water surface elevation at Thorndale) are copied and updated through September 30, 2022, similarly (Murphy and Ishii, 2006). The complete list of missing precipitation data periods and the nearby stations used to fill in those missing periods from October 1, 2021, through September 30, 2022, is given in Table1.csv. This file is in the comma separated values (CSV) file format and can be downloaded from this landing page. The list of snow affected days of precipitation data and the missing and estimated period of the stage and flow data in SC22.WDM database during the period October 1, 2021, through September 30, 2022, are given in the USGS annual Water Data Report at https://waterdata.usgs.gov/nwis. To open the WDM database SC22.WDM user needs to install Sara Timeseries Utility, listed in the section "Related External Resources" on this page. Table1.csv can be opened with any text editor or Microsoft Excel. References Cited: Bera, M., 2024, Meteorological Database, Argonne National Laboratory, Illinois: U.S. Geological Survey data release, https://doi.org/10.5066/P146RBHK. Bera, M., 2023, Watershed Data Management (WDM) Database (SC21.WDM) for Salt Creek Streamflow Simulation, DuPage County, Illinois, January 1, 1997, through September 30, 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P9TFCGQU. 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.