Salinity and variability of salinity in shallow waters shape living resources and habitat within Gulf of Mexico estuaries. The salinity gradient is widely recognized as foundational in maintaining biological diversity and productivity of estuaries. A clear understanding of the factors controlling salinity and variability of salinity in estuarine surface waters is essential for proper stewardship and for sustaining ecological structure and function. Salinity data are collected by numerous Federal, State, and local agencies and universities as part of routine data collection programs. We used online databases to compile salinity data in Gulf of Mexico estuaries. The primary criteria for inclusion in the compilation were a lengthy record of continuous collection with data sondes of at least hourly intervals. Stations that represented full estuarine gradients, from fresh to saline, were prioritized. Data were compiled in separate spreadsheets for each State using comma-delimited formatting. For each State, a second spreadsheet provides information on each station. A few stations started collecting salinity as early as the mid-1980s. More stations came on line by the mid- to late 1990s. Starting in the late 2000s many more stations came on line.

The presence of salinity in shallow waters influences living resources and habitats within Gulf of Mexico estuaries. The salinity gradient is widely recognized as foundational in maintaining biological diversity and productivity of estuaries. A clear understanding of the factors controlling salinity and its variability in estuarine surface waters is essential for proper stewardship and for sustaining ecological structure and function. Salinity data are collected by numerous Federal, State, and local agencies and universities as part of routine data-collection programs. The U.S. Geological Survey compiled salinity data from existing online databases – all water samples were collected in Gulf of Mexico estuaries. The primary criterion for data from a station to be included in the compilation was a lengthy record of continuous collection using a data sonde programmed to at least hourly intervals. Stations that represented full estuarine gradients, from fresh to saline, were prioritized. Data were compiled from salinity stations in the five Gulf states and combined into one .txt file and one .feather file. Continuous data collection of salinity concentrations began at a few stations in the mid-1980s, and the number of stations with data sondes has increased over time for a total of 532,076 observations at 92 stations provided in this data release.

Salinity and variability of salinity in shallow waters shape living resources and habitat within Gulf of Mexico estuaries. The salinity gradient is widely recognized as foundational in maintaining biological diversity and productivity of estuaries. A clear understanding of the factors controlling salinity and variability of salinity in estuarine surface waters is essential for proper stewardship and for sustaining ecological structure and function. Salinity data are collected by numerous Federal, State, and local agencies and universities as part of routine data collection programs. We used online databases to compile salinity data in Gulf of Mexico estuaries. The primary criteria for inclusion in the compilation were a lengthy record of continuous collection with data sondes of at least hourly intervals. Stations that represented full estuarine gradients, from fresh to saline, were prioritized. Data were compiled in separate spreadsheets for each State using comma-delimited formatting. For each State, a second spreadsheet provides information on each station. A few stations started collecting salinity as early as the mid-1980s. More stations came on line by the mid- to late 1990s. Starting in the late 2000s many more stations came on line.

The presence of salinity in shallow waters influences living resources and habitats within Gulf of Mexico estuaries. The salinity gradient is widely recognized as foundational in maintaining biological diversity and productivity of estuaries. A clear understanding of the factors controlling salinity and its variability in estuarine surface waters is essential for proper stewardship and for sustaining ecological structure and function. Salinity data are collected by numerous Federal, State, and local agencies and universities as part of routine data-collection programs. The U.S. Geological Survey compiled salinity data from existing online databases – all water samples were collected in Gulf of Mexico estuaries. The primary criterion for data from a station to be included in the compilation was a lengthy record of continuous collection using a data sonde programmed to at least hourly intervals. Stations that represented full estuarine gradients, from fresh to saline, were prioritized. Data were compiled from salinity stations in the five Gulf states and combined into one .txt file and one .feather file. Continuous data collection of salinity concentrations began at a few stations in the mid-1980s, and the number of stations with data sondes has increased over time for a total of 532,076 observations at 92 stations provided in this data release.

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 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.

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.

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.

The polygon datasets were created to assist in visualizing the results of salinity modeling in Gulf of Mexico estuaries and bays. Statistical algorithms (Asquith and others, 2023) were developed to predict daily salinities for 91 salinity monitoring sites (Rodgers and Swarzenski, 2019) operated by 7 agencies in near coastal United States waters of the Gulf of Mexico. These monitoring sites are assigned to 15 salinity groups roughly corresponding to distinct bays and estuaries. The statistical algorithms facilitate the study of trends and drivers of salinity in near coastal waters. The groups polygon dataset consists of 15 polygons representing the outer boundary or hull of each of the 15 salinity groups. The site polygons dataset consists of 91 polygons—one polygon each per salinity monitoring site. The polygons were created using the Watershed Boundary Dataset, the National Hydrography Dataset, and aerial imagery. A detailed description of the polygon creation method is in the metadata processing steps. Creation of the polygons was motivated by a need to construct visual cues (maps and map animations) for testing the veracity of the statistical algorithms.

The polygon datasets were created to assist in visualizing the results of salinity modeling in Gulf of Mexico estuaries and bays. Statistical algorithms (Asquith and others, 2023) were developed to predict daily salinities for 91 salinity monitoring sites (Rodgers and Swarzenski, 2019) operated by 7 agencies in near coastal United States waters of the Gulf of Mexico. These monitoring sites are assigned to 15 salinity groups roughly corresponding to distinct bays and estuaries. The statistical algorithms facilitate the study of trends and drivers of salinity in near coastal waters. The groups polygon dataset consists of 15 polygons representing the outer boundary or hull of each of the 15 salinity groups. The site polygons dataset consists of 91 polygons—one polygon each per salinity monitoring site. The polygons were created using the Watershed Boundary Dataset, the National Hydrography Dataset, and aerial imagery. A detailed description of the polygon creation method is in the metadata processing steps. Creation of the polygons was motivated by a need to construct visual cues (maps and map animations) for testing the veracity of the statistical algorithms.