First HAB report on Seneca Lake
Saturday, Aug. 22 saw the first confirmed harmful algal bloom (HAB) report of the season on Seneca Lake. It occurred in the southeastern part of the lake, between Burdett and Hector. The timing is in line with previous years’ experience. Now that blooms have been spotted, expect to see more until they peak in mid-September.
More information and an interactive map can been viewed at the Seneca Lake Pure Waters (SLPW) website (www.senecalake.org/blooms).
The Finger Lakes Institute at Hobart and William Smith Colleges is collaborating with regional industry and university partners to monitor harmful algae blooms (HABs) in the Finger Lakes and other New York waterways using exciting cutting-edge technology.
The occurrence of HABs is increasing worldwide, including in New York. While cyanobacteria are natural components of aquatic ecosystems, certain conditions (e.g., high nutrients and warm temperatures) can cause them to grow quickly and form surface blooms, which are unsightly and negatively impact the ecosystem. Some types of cyanobacteria can also produce toxins that are dangerous to humans, pets, and wildlife.
Monitoring HABs using traditional techniques (e.g., boat surveys, water sample collection) can be expensive and time consuming. However, simply observing the color of the water can be a very effective method of spotting blooms. Cyanobacteria contain unique pigments that cause HABs to appear as specific colors, such as turquoise or pea-green, allowing them to be distinguished from the surrounding water and other types of phytoplankton.
The HAB Drone Surveillance Program uses drones equipped with advanced optical sensors, along with novel data processing methodologies to monitor HABs in New York waterways. With drones, large portions of lakes and rivers will be routinely observed. The drone-mounted sensors are hyperspectral, measuring light over many wavelengths, and will precisely determine the color of the water. These sensors collect large volumes of data. Innovative computer algorithms, including machine learning techniques, will sift through the imagery identifying HABs based on their specific color signals.
The primary benefit of this work will be the development of an effective and low-cost method to monitor HABs in New York waterways at high spatiotemporal resolutions that will integrate into existing observation networks. This in turn will help ensure public safety, as well as improve the understanding of HAB ecology, leading to better prediction models and improved impact mitigation strategies.
The COVID situation has slowed the project as the full team has not been able to assemble. However, SUNY Binghamton is test flying the hyperspectral camera and collecting preliminary data through the fall.
Partners for this project include Corning Inc., SUNY Binghamton, SUNY Fredonia, SUNY Oneonta, and the Cary Institute for Ecosystem Studies.