• The U.S. Environmental Protection Agency (EPA) has awarded one million dollars to support a UF Agricultural and Biological Engineering (ABE) project in the Gulf of America that will leverage artificial intelligence and machine learning tools to improve water quality.
• This project will strengthen UF/IFAS leadership in developing innovative, science-based solutions for protecting water resources that support agriculture, aquaculture, and rural communities.
• This ecological engineering project is a multi-faceted approach that not only improves water quality in the region, but supports the seafood and tourism industries, and as a bonus provides sargassum seaweed removal, recycling, and reuse.

You’re not alone if you’ve ever looked forward to a beach day only to find that the shoreline is piled with thick, ropey mounds of seaweed and dead fish due to harmful algal blooms. Algal blooms affect aquatic creatures, the seafood industry and the tourism industry- business that coastal communities cannot afford to compromise. A group of researchers from the University of Florida’s Department of Agricultural and Biological Engineering are looking to solve these problems, practically in their own backyard.

There are a lot of issues with water quality along the coastline of the Gulf of America. Agricultural, urban, and stormwater runoff from watersheds throughout the Gulf Coast region contribute excess nutrient loading, including nitrogen and phosphorus, to coastal waters.

UF ABE researcher Dengjun Wang, Ph.D. is the Principal Investigator for an innovative way to treat the water quality problems that are occurring in that area, with the added benefits of supporting the local seafood economies and cleaning up the shore as well.

“Algae and cyanobacteria feed off fertilizer nutrients resulting in an algal bloom and levels of cyanobacteria that are harmful to fish and wildlife. Harmful algal blooms can produce cyanotoxins and, as algae decompose, consume dissolved oxygen in the water, leading to fish kills and ecosystem stress. This project aims to reduce nutrient pollution and cyanotoxins, while improving coastal water quality, ” Wang said.

The project involves using living and engineered filters to remove both cyanotoxins and excess nutrients from the water. In the test area, off the coast of Alabama, biochar, an engineered carbon-rich material produced through the thermal conversion of biomass, is used to absorb cyanotoxins. And the excess nutrients? Believe it or not, the solution is oysters. Cages of farmed oysters are strategically deployed to help reduce nutrient concentrations and improve water quality.

“We grow oysters in aquaculture cages. Oysters improve water quality by filtering phytoplankton and suspended particles that contain nitrogen and phosphorus, converting a portion of those nutrients into harvestable biomass. When they grow to a larger size, they are more desirable to sell to restaurants and markets,” Wang said.

Another important feature of the project is where the biochar comes from. Sargassum seaweed, a macroalgae, is good in water- it provides a habitat for fish and other aquatic organisms. But when that algae begins to proliferate due to excess nutrients, it can flush up on the shore in big stinking piles. It negatively impacts tourism.

“The beauty of this project is we also collect the beached sargassum and convert it into engineered biochar. We remove the problem and create a biochar industry. Someone has to pick up the sargassum and dump it somewhere, right? We convert the collected sargassum into engineered biochar that is incorporated into treatment systems designed to remove cyanotoxins from coastal waters. It’s a circular, integrated technology,” Wang explained.

Wang and his colleagues Nasser Najibi, Ph.D. and Changying (Charlie) Li, Ph.D. at UF/ABE use AI and machine learning to quantify the degree by which this project is improving water quality. The researchers will collect high-resolution imagery by using a large drone to fly over the watershed, and employ AI-assisted analysis to estimate water-quality indicators and track ecological changes over time to evaluate treatment performance of our technology. By comparing drone images before and after implementing the technology, they can quantify water quality improvement.

“We will use a multi-sensor unmanned aerial vehicle payload (multispectral and thermal) to collect the data and develop AI and machine learning pipelines combining spectral–spatial models to estimate water quality and detect harmful algal blooms across a range of water bodies in the gulf,” Li said. 

While oyster and biochar technology purify the water and drone technology provides imaging and data, will also use life-cycle analysis technology and techno-economic analysis to evaluate the environmental and economic benefits of the project. This technology will paint a full picture of the real economic benefit, factoring in the sargassum removal, the potential benefit to oyster production, coastal tourism, and water-resource management.

“Using state-of-the-art machine-learning based prediction framework, we can determine the nutrient reduction and mitigation of harmful algal blooms achieved by our restoration technology,” Najibi said.

The nearshore pollution project is truly a multidisciplinary, all hands on deck group effort. Wang and his Co-PIs have a project team that can install the oysters and the biochar in the gulf and conduct bimonthly sampling of the water quality to determine the degree of removal of nutrients and cyanotoxins. There’s buy in from oyster industry stakeholders, who want to see what the benefit of this project is as well.

“We are benefiting multiple different stakeholder groups. We are providing cost-effective technology that will improve the water quality in the Gulf of America, while also creating a biochar industry that will address the sargassum problem. We are supporting the oyster industry. There are lots of benefits from this project. We can use these technologies alongside AI and machine learning to help us to do some amazing things,” Wang said.

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