Computational methods and autonomous robotics systems for modeling and predicting harmful cyanobacterial blooms

Freshwater lakes are responsible for a variety of human and ecological services, such as providing drinking water and producing food. Lakes across the country and around the world are increasingly threatened by an increase in the incidence of harmful cyanobacterial blooms. Sometimes known as blue-green algae, harmful blooms of cyanobacteria impact the quality of lake water and can threaten human health through toxins that can damage multiple organ systems. 

 

 

Scientists know that the ultimate drivers of cyanobacterial blooms are land use change and global climate change. However, there is still a lot they do not know about what influence the spatial and temporal distribution of bloom developments in a particular lake or how these blooms are impacted by extreme flooding events. The project will develop and deploy robotic boats, buoys, traditional limnological sampling and camera-equipped drones to collect physical, chemical, and biological data in lakes where cyanobacterial blooms are detected. When combined, the technology will generate large volumes of data on the lakes and development of harmful algae as well as new algorithmic models to assess them.

With technology covering the water and air, other teams will collect information on population density in the watersheds as well and land use around the lakes and how that might impact bloom formation and development.

Information collected through the project could lead to better predictions of when and where the harmful algal blooms will take place. Those predictions might allow earlier actions to protect public health in recreational lakes and in lakes that supply drinking water.

Local homeowners and students will also form a corps of “citizen scientists” to support the project. One of the final goals of the project is to open the technologies to lake managers and citizens so that monitoring can happen throughout communities.

 

Lakes in New Hampshire, Maine, Rhode Island, and South Carolina will be studied to better understand the spatial distribution of harmful algal blooms in contrasting lake ecosystems.

In South Carolina, moored mini buoys measuring temperature and dissolved oxygen will be deployed at two stations (shallow and deep) in both Lake Murray and Wateree. Depth profiles of temperature, pH, dissolved oxygen, conductivity, total algae/phycocyanin and turbidity will be measured using YSI sensors. We will also collect samples for dissolved inorganic and organic nutrient concentrations and isotopes, dissolved gases (O2, N2, Ar) and phytoplankton community composition (collaboration with Dr. James Pinckney, University of South Carolina). Autonomously operating Jetyaks (>2 m) equipped with YSI sensors will be used to gain high spatial resolution surface water measurements (including velocity, GPS, compass, airspeed, and sonar). 

 

photo: SC DHEC

 

 

The project combines experts in freshwater systems, computer science, engineering and social science from Bates College, Colby College, Dartmouth College, the University of New Hampshire, the University of Rhode Island and the University of South Carolina.

Funding: NSF EPSCoR, Track-2, PI: Alberto Quattrini Li (Dartmouth College)

©2020 by Bourbonnais Lab (last updated April 2020)