Basin characteristics for sites used in RESTORE Streamflow alteration assessments
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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.
Data Release: Modeling coastal salinity regime for biological application
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Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at various time scales relevant to ecology (e.g., daily, monthly, seasonally). This data release provides supporting data for the journal article titled, "Quantifying uncertainty in coastal salinity regime for biological application using quantile regression," by Yurek et al. (2022). A spatially-resolved model was developed that derives quantile distributions of salinity related to various landscape variables, such as tidal forcing, wind velocity and direction, and freshwater discharge into the Suwannee Sound estuary. The model also considers various time scales of freshwater streamflow, from daily to bi-weekly scales, which represent terrestrial watershed dynamics such as time-of-travel of overland flow from headwaters to the coast. This data release provides programming routines and supporting data for the model, including: (1) scripts used to run the model written in R programming language, (2) input data used to fit the model, and (3) model output predictions across the spatial extent of the Suwannee Sound estuary. The predictions of the model represent a method of quantifying uncertainty in predictions, and represent approximate ranges of salinity conditions. These predictions are intended for use in future ecological modeling studies and analyses of impacts of salinity uncertainty on estuarine biota. They are limited by the data set used here and are not intended to indicate exact levels for any given location or time.