A total of 193 streamflow characteristics (SFCs) were calculated from daily streamflow values for data from 1,371 USGS streamgages located on tributaries and streams flowing to the Gulf of Mexico. Streamgages used to calculate SFCs required a minimum of 10 years of continuous daily streamflow data. Data presented will be used to: (1) identify regions which are statistically similar for estimating streamflow characteristics; (2) develop regional regression models to predict SFC values for current and reference basin conditions at ungaged sites; and (3) identify trends related to changing streamflow and streamflow alteration over time.

This geospatial dataset includes a one-point feature-class shapefile, one-polygon feature-class shapefile, and associated FGDC-compliant metadata to define 193 streamflow and 299 basin characteristics at 1,320 U.S. Geological Survey streamflow gaging stations. Sites included in the dataset either (1) drain to the Gulf of Mexico or (2) are adjacent to watersheds that flow to the Gulf of Mexico and are considered both physiographically similar and valuable for analysis. Drainage area to the sites varies from less than 1 to approximately 67,500 square miles. Data presented describe the streamflow regime (Rossman, 1990; Thompson and Archfield, 2014), climate (Daly and others, 2008), land use and land-use change (Sohl and others, 2014; Sohl and others, 2016), and anthropogenic features. Basins were identified following Hirsch and DiCicco (2015), and daily value streamflow data were retrieved from the USGS National Water Information System (U.S. Geological Survey, 2017). Daily value streamflow data were available beginning in 1892 through the 2016 water year (a 12-month period beginning October 1, for any given year through September 30 of the following year). All characteristics based on time series (streamflow, climate, land use for example) were summarized in terms of period of record and 10 water year increments (for example, 1930 – 1939). Data presented provide a numerical foundation supporting the: (1) development of statistical models of streamflow characteristics; (2) evaluation of spatial and temporal trends in streamflow characteristics; and (3) development of network optimization analysis. Basin characteristics will be used as independent variables to estimate streamflow characteristics (measures of the magnitude, duration, frequency, timing, and rate of change of the annual hydrograph) in a manner similar to Knight and others (2012). Daly, C., Halbleib, M., Smith, J.I., Gibson, W.P., Doggett, M.K., Taylor, G.H., Curtis, J., and Pasteris, P.P., 2008, Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States: International Journal of Climatology, v. 28, no. 15, p. 2031–2064. Dunne, T., and Black, R., 1970. “An experimental investigation of runoff production in permeable soils.” Water Resour. Res., 6(2), 478–490 ESRI 2011. ArcGIS Desktop: Release 10.4.1 Redlands, CA: Environmental Systems Research Institute. Falcone, J.A., Carlisle, D.M., Wolock, D.M., and Meador, M.R., 2010b. GAGES: A stream gage database for evaluating natural and altered flow conditions in the conterminous United States, Ecology, 91 (2), p 621; Data Paper in Ecological Archives E091-045-D1; available online at: http://esapubs.org/Archive/ecol/E091/045/metadata.htm. Hamon, W.R., 1961. Estimating Potential Evaporation. Journal of the Hydraulics Division, Proceedings of American Society of Civil Engineers 87:107-120. Horton, Robert E. (1933) "The role of infiltration in the hydrologic cycle" Transactions of the American Geophysics Union, 14th Annual Meeting, pp. 446–460. Hirsch, R.M., and DiCicco, L.A., 2015, User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data (version 2.0, February 2015):, accessed at https://pubs.usgs.gov/tm/04/a10/. Juracek, K.E., 1999, Estimation of potential runoff contributing areas in the Kansas-Lower Republican River Basin, Kansas: U.S. Geological Survey Water Resources Investigations Report 99-4089, 24 p Kjelstrom, L.C., 1998, Methods for estimating selected flow-duration and flood-frequency characteristics at ungaged sites in central Idaho: U.S. Geological Survey Water-Resources Investigations Report 94-4120, 10 p Knight, R.R., Gain, W.S., and Wolfe, W.J., 2012, Modelling ecological flow regime: an example from the Tennessee and Cumberland River basins: Ecohydrology, v. 5, no. 5, p. 613–627. NAWQA- U.S. Department of the Interior, U.S. Geological Survey. National Water-Quality Assessment (NAWQA) Program.

This dataset contains statistical descriptions of observed daily-mean streamflow for 956 sites in the southeast United States. For each site, statistical descriptions are provided according to decade for up to six decades, beginning in 1950 (1950-59 calendar years) and ending with 2000 (2000 - 2009 calendar years) with no more than 7 missing values per year in total (continuous or noncontinuous). There are 40 statistical descriptions including 28 flow-duration curve values, 8 L-moments, and 4 describing the minimum, maximum, median flow for days not equal to zero, and number of zero-flow days. Site information is provided by decade - the number of rows per site varies from 1 to 6 depending on the number of decades with observed record available. This information was used as the response variable(s) for statistical models for estimating the same characteristics at nearly 10,000 ungaged locations throughout the southeast United States. The dataset has been provided as a shapefile and a comma-delimited file. The comma-delimited file is an exact copy of the attribute table of the shapefile.

Trend Departure Index (TDI) is computed as: (number of quantiles for which the trend result departs from the result for the associated reference site) / (total number of quantiles). In a Quantile-Kendall analysis for the annual time frame, the denominator, or total number of quantiles, is 365. TDI varies from 0 to 1; a TDI of 0 indicates the trend results for the site are identical to the reference site and any value larger than 0 indicates some departure compared to the reference condition. The larger the number (the closer to 1) the more departure or deviation relative to the reference site in trend across all the quantiles for the site.

Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles by non-exceedance probability (NEP). For both U.S. Geological Survey streamflow-gaging stations (streamgages) and level-12 hydrologic unit code (HUC12) catchments, as defined by Crowley-Ornelas and others (2019), the 27 quantiles were estimated and tabulated in this data release. Three probability distributions were used and are summarized by Asquith and others (2017): the asymmetric exponential power (AEP4) (4-parameter), generalized normal (GNO) (3-parameter log-normal), and kappa (KAP) (4-parameter). A summary of the mathematics for these distributions is provided in the README files within this data release and close consultation of the mathematical discussion in Asquith and others (2017) also is suggested. The lmomco R package (Asquith, 2020) was used for distribution fitting and the technically-demanding implementation for a single location is archived in the RESTORE/fdclmrpplo software release within file fdclmrpplo/scripts/pred_fdc_ref/pred_fdc_ref.R (Asquith and others, 2020). The implementation for the streamgages is archived in the RESTORE/fdclmrpplo software release within file fdclmrpplo/scripts/pred_fdc_gage/pred_fdc_gage.R, and the implementation for the HUC12s is archived file fdclmrpplo/scripts/pred_fdc_huc12/pred_fdc_huc12.R and README files therein. For a given data set of no-flow fraction and L-moments, the three distributions will have similar results in the central parts of NEP and differences will be largest in the far left (low flow) and far right (flood flow) tails. No opinion that a particular distribution is more suitable than another is provided with exception that the GNO is fit to the first three L-moments and the AEP4 and KAP are fit to the first four L-moments. As a result, it is logical to state that more information on the distribution of streamflow is retained by the AEP4 and KAP distributions than the GNO. The availability of three distributions with the data release is considered a feature because a semi-quantitative assessment of model error (uncertainty attributed to choice of model) can be made. Asquith, W.H., 2020, lmomco—L-moments, censored L-moments, trimmed L-moments, L-comoments, and many distributions: R package version 2.3.6, https://CRAN.R-project.org/package=lmomco. Asquith, W.H., Kiang, J.E., and Cohn, T.A., 2017, Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities: U.S. Geological Survey Scientific Investigation Report 2017–5038, 93 p., https://doi.org/10.3133/sir20175038. Asquith, W.H., Knight, R.R., and Crowley-Ornelas, E.R., 2020, RESTORE/fdclmrpplo—Source code for estimation of L-moments and percent no-flow conditions for decadal flow-duration curves and estimation at level-12 hydrologic unit codes along with other statistical computations: U.S. Geological Survey software release, Reston, Va., https://doi.org/10.5066/P93CKH92. Crowley-Ornelas, E.R., Worland, S.C., Wieczorek, M.E., Asquith, W.H., Knight, R.R., 2019, Summary of basin characteristics for National Hydrography Dataset, version 2 catchments in the Southeastern United States, 1950–2010: U.S. Geological Survey data release, https://doi.org/10.5066/P9KXTDU4. Robinson, A.L., Asquith, W.H., and Knight, R.R., 2019, Summary of decadal no-flow fractions and decadal L-moments of nonzero streamflow flow-duration curves for National Hydrography Dataset, version 2 catchments in the southeastern United States, 1950–2010: U.S. Geological Survey data release, https://doi.org/10.5066/P9Z4PM55.

This data release presents streamflow recession analyses and supporting statistics for 164 U.S. Geological Survey (USGS) streamgages located in or near the watersheds of Mobile and Perdido Bays in the south-central United States (see Tatum and others, 2024). Streamgages were selected based on a minimum of two complete decades of daily streamflow data since January 1, 1950, with the additional requirement that data coverage includes the entire 2010s decade. Daily streamflow data were retrieved on March 8, 2024 (U.S. Geological Survey, 2024). The primary output of this release, gfactor.txt, is a pipe-delimited text file containing 22 attributes and over 1,000 unique records summarizing decadal streamflow statistics for each site. Key identifying attributes include the USGS site identification number (site_no), streamgage name (station_nm), geographic coordinates (dec_lat_va, dec_long_va), contributing drainage area (CDA), and projected coordinates (xkm, ykm). Key statistical attributes consist of decadal counts of daily streamflow conditions (decreasing_count, increasing_count, nochange_count, total_count), as well as summary statistics that characterize the declining days distribution, including the 50th percentile (median), L-moments (L1, L2, T3, T4, T5), and streamflow recession indices associated with the 90th percentile (gfactor, gfactor_emp). Additional attributes capture adjusted statistics produced through a detrending procedure designed to assess and remove potential decadal biases in the declining day distribution. Core statistical computations were carried out using custom functions developed in the R environment for statistical computing (R Core Team, 2024).

This dataset provides numerical and categorical descriptions of 48 basin characteristics for 956 basins with observed streamflow information at U.S. Geological Survey (USGS) streamflow-gaging stations. Characteristics are indexed by National Hydrography Dataset (NHD) version 2 COMID (integer that uniquely identifies each feature in the NHD) and USGS station number for streamflow-gaging station. The variables represent mutable and immutable basin characteristics and are organized by characteristic type: physical (5), hydrologic (6), categorical (12), climate (6), landscape alteration (7), and land cover (12). Mutable characteristics such as climate, land cover, and landscape alteration variables are reported in decadal increments (for example, average percent forest for the decade 1950-1959, 1960-1969, etc). The majority of basin characteristics in this dataset were calculated using divergence-routing methods and are often referred to as “network-accumulated”. This method uses a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the values derived from the reach catchment scale (Schwarz, G.E., and Wieczorek, M.E., 2018, Database of modified routing for NHDPlus version 2.1 flowlines: ENHDPlusV2_us: U.S. Geological Survey data release, https://doi.org/10.5066/P9PA63SM ). In four instances, values are also provided for the entire catchment above a site and area designated using the “CAT_” prefix.

Censored and uncensored generalized additive models (GAMs) are developed from 955 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of streamflow. The streamgages are located on streams draining to the Gulf of Mexico. Decadal statistics include no-flow fractions and selected L-moments of nonzero streamflow for six decades (1950s—2000s). These statistics represent metrics of decadal flow-duration curves (dFDCs) derived from about 10 million daily mean streamflows. The L-moments include the mean, coefficient of L-variation, and the third through fifth L-moment ratios. The models are fit using watershed properties such as basin area and slope, decadal precipitation and temperature and decadal values of flood storage and urban development percentages. The GAMs then estimate decadal statistics for 8,988 prediction locations (stream reaches) coincident with outlets of level-12 hydrologic unit codes. Both the entire dataset (whole model) and leave-one-watershed-out model results are reported. No-flow fractions are censored data and Tobit extensions to GAMs are effective in estimation of ephemeral streamflow conditions. Uncensored GAMs conversely were used for estimation of the L-moments. The R language was used to pull and process the streamflow data, and the scripts can be found online at https://code.usgs.gov/water/restore/fdclmrpplo.