South Atlantic Water Science Center (SAWSC)

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Filter Total Items: 215
Date published: January 1, 2018

Digital Elevation Model of the Difficult Run watershed in Fairfax County, Virginia Derived from 2012 lidar LAS Points

Aerial light detection and ranging (lidar) data were collected over the study site between April 12 – 14, 2012 as part of the Fauquier, Fairfax, Frederick (MD), and Jefferson County acquisition for FEMA Region 3 FY12 VA lidar (Dewberry 2012). Lidar points classified as ground and water were used to create a 3-m digital elevation model (DEM) clipped to the Difficult

Date published: January 1, 2018

Geomorphons of North Carolina

The 10 most common geomorphic features are identified for the state of North Carolina using Lidar derived DEMs at 30 ft. resolution. This product uses r.geomorphon, a feature in GRASS GIS, to calculate the geomorphic features for the state. The tool requires a user input length scale and slope for calculation. This dataset uses 60 cells, or 1800 ft. as the length scale and two different slope...

Date published: January 1, 2018

RUSLE2 Upland Erosion and Sediment Delivery to Stream Data Table for Difficult Run, Virginia

This table contains estimates for upland sediment erosion and delivery to the stream estimated using a modified Revised Universal Soil Loss Equation 2 (RUSLE2) approach (USDA-ARS, 2013). Upland erosion (Eu) was calculated as the sum of the product of the erosivity factor (Rm) estimated for each month, the soil erodibility factor (K), the length-slope factor (LS), C

Date published: January 1, 2018

Data for trends in water quality of selected reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013

This U.S. Geological Survey Data Release contains the associated data described in the Scientific Investigations Report, "Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013". Since 1989, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in the

Date published: January 1, 2018

Difficult Run field estimated floodplain and bank flux and toolbox geomorphic metrics for field sites

A cvs file containing field datasets used to develop regression models to predict sediment and nutrient retention services for streams within the Difficult Run watershed. Field measurements of floodplain deposition and bank erosion were provided in previously published datasets from Hupp et al. (2013) and Gellis et al. (2017). At each field site, 3-5 nearby cross sections from the Toolb

Date published: January 1, 2018

Hydrologically Conditioned Digital Elevation Model of the Difficult Run watershed in Fairfax County, Virginia Derived from 2012 lidar LAS Points

Hydrologically conditioned digital elevation model (DEM) generated from lidar data clipped to the Difficult Run watershed with a 500-m buffer in ArcGIS 10.3.1 (ESRI, Redlands, CA). The DEM was hydrologically corrected by breaching through pits with no downslope neighboring cells to force surface flow to continuously move downslope using Whitebox Geospatial Analysis Tools (Lindsay an

Date published: January 1, 2018

Thermal Imagery along Ellerbe Creek in Durham, North Carolina

An initial reconnaissance survey in March 2016 and a subsequent survey in July 2016 was conducted to identify possible groundwater discharge points along the stream reach using a forward-looking infrared (FLIR) camera in seasonal extremes. The high-resolution thermal imaging camera captures the emitted infrared radiation of the objects in view. Recent studies using similar ground-based therma...

Date published: January 1, 2018

Autonomous Underwater Vehicle Water-Quality Surveys for Indian River Lagoon, near Titusville, Florida, August 2016-November 2017

The Indian River Lagoon (IRL) extends for 160 miles along Florida's east coast and is a complex system of three estuaries - Mosquito Lagoon, Banana River Lagoon, and Indian River Lagoon. Two concurrent phytoplankton blooms occurred in the IRL in 2011 that had detrimental ecological effects on the estuarine system. St. Johns River Water Management District (SJRWMD) is participating i

Date published: January 1, 2018

Nutrient concentrations, streamflow, and geospatial data for 76 wadeable streams in the Piedmont Ecoregion of the Southeastern United States

Water samples were collected by the USGS National Water Quality Program (NWQP) Southeastern Stream Quality Assessment (SESQA) from 76 perennial, wadeable (less than 10 m width and 1 m depth at base-flow) headwater stream sites in watersheds with varying degrees of urban land use in four states. Dataset includes sample site locations and information, water sample nutrient concentra

Date published: January 1, 2018

Target-Chemical Concentrations, Exposure Activity Ratios, and Bioassay Results for Assessment of Mixed-Organic/Inorganic-Chemical Exposure in USA Tapwater, 2016

Chemical and biological concentration results, quality assurance and quality control and statistical summaries from 26 tapwater samples, collected from paired residential and work place sites in 11 states in 2016. Samples were analylzed at U.S. Geological Survey and U.S. Environmental Protection Agency laboratories.

Date published: January 1, 2018

Difficult Run Floodplain Sediment and Nutrient Retention Ecosystem Service Datasets, Fairfax County, Virginia

Datasets used to quantify and value the ecosystem service of sediment and nutrient retention for floodplains within the Difficult Run watershed located in Fairfax County, Virginia. Geospatial datasets include a digital elevation model (DEM), a hydrologically conditioned DEM, output from the USGS Stream Channel and Floodplain Metric Toolbox, and field data sets used to develop regressi

Date published: January 1, 2018

Lidar-derived Data Layers for South Carolina StreamStats, 2007-2013

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey developed a StreamStats web application ( that provides analytical tools for water-resources planning and management (Ries and others, 2017). This data set presents the lidar-derived flow direction, flow...