Building a better weapon against harmful algal blooms

Predicting and pinpointing which farming practices are most likely to protect against environmental harm is a complex proposition, and researchers at The Ohio State University are working to fine-tune the tools that could help farmers and others prevent harmful algal blooms.

This week at the American Geophysical Union (AGU) fall meeting in Washington, D.C, a team of scientists from Ohio State shared early results from a trio of studies that aim to improve models designed to guide agricultural practices for reducing the risk of nitrogen and phosphorous farm runoff. Such runoff leads to the growth of toxic algae in waterways.

Basic models for predicting the consequences of various decisions, such as when to apply fertilizer, are available but they must be refined in order to ensure reliability and gain the trust of interested parties, including farmers and environmental protection organizations, said Food, Agricultural and Biological Engineering (FABE) Assistant Professor Jay Martin.

Asmita Murumkar, a postdoctoral researcher at Ohio State, said her work is beginning to illuminate how the timing of fertilizer application intersects with heavy rains to contribute to nutrient runoff. She’s working with the Ohio Applicator Forecast, a tool that uses National Weather Service data to assign risk estimates to applying fertilizer at various times.

Murumkar is hopeful that her research will help quantify what impact the tool would have on the environment under different scenarios – say if a quarter of farmers in the Maumee River watershed used it, or half.

“We want to better understand how much phosphorous runoff it would reduce in the region,” Martin said, adding that there’s plenty of evidence that individual farm practices impact runoff from those farms, but less evidence in terms of larger-scale estimates.

“We know from our previous work that fertilizer timing is important, but we want to be able to look across the whole Lake Erie Basin and know best-case and worst-case scenarios and this modeling will help address that,” he said.

Margaret Kalcic, also a FABE assistant professor, said farmers are encouraged to follow the “Four Rs” for right time, source, amount and place when applying fertilizer.

“But ‘right’ is not clearly defined, and our team is working to provide our partners in Ohio, including farmers, advocates and policymakers, with better answers,” Kalcic said.

Added Martin, “There’s more subtlety here than just watching the weather and the ground moisture and we’re trying to determine the best solutions that support agricultural production and environmental protection.”

Grey Evenson, a postdoctoral researcher at Ohio State, presented initial findings on his work to identify the best data to use in modeling, so that it offers a more accurate picture of what is happening in fields and adjacent waterways.

“We don’t want to underestimate – or overestimate – the value of these best management practices. For instance, some practices may produce greater benefits than we give them credit for in the model, such as improving soil health, which leads to better water retention,” Evenson said.

Added Kalcic, “A lot of this work is about tuning existing models. By improving the quality of information we put into them we have greater confidence in the information that comes out of them.” She offered no-till farming as an example.

“We know that no-till is good for preventing soil erosion, but there are still uncertainties about its effects on water quality in the region,” Kalcic said.

Agricultural engineering graduate student Anna Apostel discussed a third project, in which she’s manipulating various parameters in one model to try to determine how reliable – or not – the model is. The long-term goal is to move toward more-robust estimates of how practices contribute to water quality.

“We really want to build trust in truly useful models that will help policymakers, farmers and others," explained Kalcic.

Martin said adjusting parameters so that magnitudes of processes better match reality and data from observations in the field is a critical part of improving model performance.

“We want to adjust our equations to better represent reality,” Apostel said.

The overarching goal of all the work, the researchers said, is to have models that better align with what the researchers have observed in field experiments but that can look at the issues on a broad, regional level.

“We know that if you build a bad model it’s not going to help anybody make any decisions,” Kalcic said. “We really want to build trust in truly useful models that will help policymakers, farmers and others."

Funding for the new research came from the Ohio Department of Higher Education Harmful Algal Bloom Research Initiative, NOAA National Weather Service and the National Science Foundation.

Addressing water quality challenges is among Ohio State’s top research priorities. In addition to studies such as the those being presented at the fall AGU meeting, faculty and staff are working with policymakers, farmers, advocacy groups and others to find solutions. Among those efforts are the Ohio Water Resources Center, led by engineering faculty, and the College of Food, Agricultural and Environmental Sciences' Water Quality Initiative.

by Misti Crane, University Research Communications