Category: Monitoring Water Quality and Hydrology
Project Team: Georgia Water Resources III
Team Location: University of Georgia – Athens, Georgia
A Python script (foreground) was developed to generate cyanobacteria biomass maps for four Georgia Power lakes. Lake Jackson (left) and the lower half of Lake Sinclair (right) are shown in the background of the above image. Image Credit: Georgia Water Resources III Team
Authors:
Benjamin Page
Vinay Kumar
Pradeep Kumar Ragu Chanthar
Caren Remillard
Mentors/Advisors:
Dr. Deepak Mishra (University of Georgia)
Susan Wilde (University of Georgia)
Past/Other Contributors:
Ike Sari Astuti
Bradley Bartelme
Elizabeth Benyshek
Shuvankar Ghosh
Danielle Haskett
Peter Hawman
Jiaying He
Simmone Simpson
Abstract:
The effects of anthropogenic eutrophication are intensified in Georgia’s watersheds due to increasing temperatures, frequent drought events and agricultural nutrient runoff that promote primary productivity in reservoirs. These factors may ultimately lead to the formation of toxic cyanobacterial Harmful Algal Blooms (HABs). The spectral properties of phycocyanin, a phycobiliprotein, may be used as a proxy to assess the amount of cyanobacterial biomass that is present in a water body and is useful as a cyanobacterial bloom indicator. The Georgia Water Resources Team I and II developed an upscaling multiple linear regression model procedure to demonstrate the feasibility of using Landsat 8 Operational Land Imager (OLI) sensors to detect phycocyanin reflectance patterns throughout four Georgia Power reservoirs. This term, we implemented this phycocyanin algorithm into a Web-based graphical user interface (GUI) which can be operated by Georgia Power Geographic Information System (GIS) specialists to generate rapid, high-quality maps characterizing the spatio-temporal distributions of cyanobacteria concentrations. This GUI will assist in the protection and restoration throughout four Georgia Power reservoirs.
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