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Surface-water characteristics and phytoplankton taxonomy in selected north Texas reservoirs using biological, hyperspectral, and water-quality methods, 2019-2020

A study to develop an earth observation monitoring system to detect harmful algal bloom (HABs) presence within selected north Texas reservoirs using satellite imagery was conducted by the U.S. Geological Survey (USGS). This data release provides the data collected for this study including site locations, water-quality, phytoplankton, and hyperspectral water surface reflectance data. Data were collected between September of 2019 and December of 2020 at 39 sites distributed across 16 reservoirs and 1 stream. The stream site was sampled in response to an algal bloom in August of 2019 in Austin Tex., and is included herein but the reservoir sites are the focus of this data release. The datasets include all routine and quality assurance/quality control (QA/QC) samples collected at each of the sites. Water-quality samples were analyzed for chlorophyll a and total suspended solids (TSS). Phytoplankton were identified to the lowest possible taxonomic level with abundance (density reported as both natural units and cells) and biovolume reported. Hyperspectral water surface reflectance was acquired for the visible and near infrared (NIR) (325-1075 nanometers) spectral range using an ASD Field Spec Handheld 2 spectroradiometer (ASD Inc., 2010). These data are given as digital number (DN, a unitless number representing intensity observed by the spectroradiometer that has not been calibrated) , white reference, and reflectance tabular data with accompanying photographs showing observed water surface conditions at the time of acquisition. There were from one to seven open-water sampling sites distributed across the water surface of each reservoir depending on drainage area, land use within the drainage area, and reservoir morphology. Additionally, most sites were at least 600 meters from the shoreline. The 600-meter 'buffer zone' was to ensure data were acquired from parts of the reservoir areas representing pure water reflectance per pixel spatial resolution for Sentinel 2a/b, Sentinel 3 and Landsat 8 satellite imagery (pixels representing reflectance from only water as opposed to reflectance from a mixture of land and water). At each site, water-quality field properties were measured every five feet to the bottom of the water column starting at the surface. Chlorophyll a was analyzed by the Trinity River Authority Central Laboratory in Dallas, Texas. Samples were analyzed for TSS by the USGS National Water Quality Laboratory in Denver, Colorado. Water-quality field properties (water temperature, dissolved-oxygen concentration and percent saturation, pH, specific conductance, turbidity, chlorophyll fluorescence, phycocyanin fluorescence, and Secchi depth) were also measured at each sampling site. PhycoTech, Inc. determined phytoplankton taxonomy and biomass. Phytoplankton samples were collected at one-two open-water sites at each reservoir. Hyperspectral water surface reflectance was acquired for a subset of field sites and visits from pre-determined positions around the perimeter of the boat at the beginning and the end of sampling to ensure there was minimal interference from sun-angle, shadow and glint from movement of the water surface, movement of the boat, and as the sun moved across the sky.

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Author(s) Jeffrey M Sievers orcid, Victoria G Stengel orcid, Jessica M Trevino orcid
Publication Date 2022-03-11
Beginning Date of Data 2019-08-30
Ending Date of Data 2020-11-16
Data Contact
DOI https://doi.org/10.5066/P9X1R5IM
Citation Sievers, J.M., Stengel, V.G., and Trevino, J.M., 2022, Surface-water characteristics and phytoplankton taxonomy in selected north Texas reservoirs using biological, hyperspectral, and water-quality methods, 2019-2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9X1R5IM.
Metadata Contact
Metadata Date 2022-04-01
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Loading https://doi.org/10.1016/J.RSE.2022.113089

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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2025-01-07T16:23:15.254Z