Lindsey J. Boyle Samuel H. Austin Rosemary M. Fanelli 20250815 spreadsheet https://doi.org/10.5066/P13FB2KQ Lindsey J. Boyle Samuel H. Austin Matthew J. Cashman John W. Clune James E. Colgin Kaitlyn E. M. Elliott Rosemary M. Fanelli Ellie P. Foss Nathaniel P. Hitt Coral M. Howe Emily H. Majcher Kelly O. Maloney Christopher A. Mason Douglas L. Moyer Trevor P. Needham Karli M. Rogers Joshua J. Thompson Guoxiang Yang Tammy M. Zimmerman 20250815 publication https://doi.org/10.3133/sir20255072 The Chesapeake Bay is greatly affected by freshwater flows from streams and rivers draining its watershed. Variations in the amount and timing of streamflow can change water temperature, salinity, suspended sediment and contaminants levels, and affect the amount of nutrients in freshwater streams. Additionally freshwater flows affect the amount of in-stream habitat available to freshwater flora and fauna. Metrics characterizing streamflow extremes such as magnitude, frequency and duration of high and low flows are helpful indicators of long-term patterns, shifts in streamflow regimes, and the interpretation of their effects on stream biota. Generalized additive models were used to analyze long term changes in annual metrics of streamflow extrema from water year 1985 through water year 2022. Detailed data preparation information, analytical methods and results are presented and discussed in the associated Scientific Investigative Report (https://doi.org/10.3133/sir20255072). This dataset provides analysis results for status and trends of streamflow for select streams within the Chesapeake Bay watershed. 1985 2022 observed Complete None planned Chesapeake Bay Watershed -80.4381 -74.5926 43.0066 36.6971 ISO 19115 Topic Category environment health inlandWaters USGS Streamflow Water resources Hydrology Chesapeake Bay Watershed USGS Metadata Identifier USGS:661feb43d34e7eb9eb7ed116 Geographic Names Information System (GNIS) Chesapeake Bay Watershed Pennsylvania Maryland Virginia West Virginia Delaware District of Columbia New York None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Samuel H Austin U.S. Geological Survey, Northeast Region Hydrologist mailing address

1730 East Parham Road

Richmond VA 23228 United States 804-261-2600 804-261-2657 saustin@usgs.gov U.S. Geological Survey, 2019, USGS water data for the nation: U.S. Geological Survey National Water Information System database, accessed March 20, 2023 at https://nwis.waterdata.usgs.gov/nwis. No formal attribute accuracy tests were conducted. Data were checked for duplicates and screened for irregular values. Dataset is considered complete for the information presented, as described in the abstract and process steps. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted. No formal positional accuracy tests were conducted. U.S. Geological Survey 2023 tabular digital data https://doi.org/10.5066/p9rh71wy Digital and/or Hardcopy 19841001 20220930 observed NWIS Source of the streamflow data R Core Team 2024 software https://www.r-project.org/ Digital and/or Hardcopy 2024 publication date R 4.4.1 Statistical software used for analysis Simon N. Wood 2017 software package https://cran.r-project.org/web/packages/mgcv/index.html Digital and/or Hardcopy 2017 publication date mgcv 1.9-1 Statistical software package used for analysis. Streamflow daily data were acquired from records of 587 gaged basins located within the boundaries of the Chesapeake Bay watershed. Of these gages, 211 were determined suitable for analysis, having complete daily value data for all years within the interval beginning in water year 1985 and ending in water year 2022, as listed in the USGS NWIS (U.S. Geological Survey, 2019) (accessed 03-20-2023). NWIS 2023 Metrics of mean annual high and low streamflow frequency, duration and magnitude were calculated for each site using daily value streamflow data. Metrics were defined as follows and calculated using R version 4.4.1. Low Flow Magnitude - The annual 1st- percentile of daily flow values divided by drainage area expressed as cubic foot per second/square mile (ft^3/s)/(mi^2) Low Flow Frequency - The annual number of low flow events where daily flow values were less than or equal to the 10th-percentile of all daily flows in the water year 1986-2022 period Low Flow Duration - The annual average length (in days) of low flow events with daily flow values less than the 10th-percentile of all daily flows in the water year 1986-2022 period High Flow Magnitude - The annual 99th- percentile of daily flow values divided by drainage area expressed as (ft^3/s)/(mi^2) High Flow Frequency - The annual number of high flow events with daily flow values greater than or equal to the 90th -percentile of all daily flows in the water year 1986-2022 period High Flow Duration - The annual average length (in days) of high flow events with daily flow values greater than the 90th-percentile of all daily flows for the water year 1986-2022 period Though all sites had 37 complete years of data, some sites had fewer than 37 years of low or high streamflow duration values because some years did not have any daily values exceeding the low or high flow percentile threshold. R 4.4.1 20241011 For each site with a metric value for water year 2022, status was calculated as the percent difference between the water year 2022 metric value and the mean of the metric value over the full 37-year interval. Trend analysis was conducted for each site with metric values available for at least 30 years in the 37-year interval. Analysis was conducted in R version 4.4.1 using the package 'mgcv'. For each site, trends were estimated separately for each high and low flow metric using individual GAMs with a single smooth term for year as a predictor variable. Restricted maximum likelihood (REML) was utilized for the smoothing parameter and the flexibility of the smooth function was limited by setting k to be an integer no more than half the total data points per trend. For use in determining trend strength, a null model was built with the same model parameters but excluding the year predictor variable. Trend results were labeled "Strong" if the AIC value was at least 7 points lower than the null model and p≤0.05 indicating a high likelihood of a positive or negative trend. Trend results were labeled “Possible” if AIC values were ≥ 4 and < 7 points lower than the null mode and “Unlikely” if AIC values were < 4 points below the null. mgcv 1.9-1 R 4.4.1 20241104 0.00001 0.00001 Decimal degrees North American Datum of 1983 (NAD 83) Geodetic Reference System 1980 6378137.000000 298.257222 streamflow_data_dictionary.csv - Comma Separated Value (CSV) file containing entity attribute information for all data files streamflow_status_and_trends.csv - Comma Separated Value (CSV) file containing summarized results for streamflow metric data trend model output and status values Data dictionary describing the data, and available files; https://doi.org/10.5066/P13FB2KQ GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Digital Data https://doi.org/10.5066/P13FB2KQ None 20250815 Lindsey J. Boyle U.S. Geological Survey Fish Biologist mailing address

11649 Leetown Road

Kearneysville WV 25430 US 304-724-4468 lboyle@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999