Researchers at The Ohio State University developed impacts-based thresholds for drought in Ohio, looking specifically at how corn yield and streamflow were affected by various drought indicators, such as notable changes in soil moisture, crops, and even livestock losses in the state.

The results suggest this impacts-based approach could give Ohio farmers earlier and more accurate notice when drought conditions are approaching, said Steven Quiring, co-author of the study and a professor of geography at Ohio State.

“We want to better understand what steps should be taken so that Ohio can better prepare for and also monitor the onset of drought conditions because a lot of the best ways to respond to drought is taking action early,” said Quiring. Moreover, with a more precise early warning system, agriculture producers might be able to save time and money by implementing water restrictions, or by switching to different or more drought-resistant crops.

The study was published in the Journal of Hydrometeorology. 

The Ohio State researchers compared how their method performed at predicting droughts with data from the U.S Drought Monitor (USDM). 

The problem with the USDM is that it uses fixed drought thresholds, or guidelines that use the same parameters to measure changes in all seasons and climate regions of the country. Unfortunately, this one-size-fits-all approach can cause monitoring plans to inaccurately gauge local weather conditions and how they impact those in certain communities, Quiring said.

By analyzing data from four drought indices commonly used in previous studies to monitor drought intensity across the United States, researchers were able to show that fixed thresholds tend to indicate milder drought conditions in Ohio than are indicated by the impacts-based thresholds identified in their study. 

It’s why Quiring and his team want to use the impacts-based method to revamp those thresholds to better reflect drought conditions in Ohio, a move that starts by updating The Ohio Emergency Management Agency’s state drought plan. 

To accomplish their goal, the researchers investigated how data from the four indices impacted streamflow, or how much water discharges over a designated point in a fixed period of time, and Ohio’s total corn yield, mainly because the crop covers an extensive area within the state, and nearly every county grows it. 

Identifying agricultural drought thresholds that are specific to Ohio is important, said Quiring. Because the impacts of drought can vary from region to region, using the same drought thresholds in California as in Ohio is absurd, he said. Additionally, the types of drought that occur can differ. Ohio, for example, in particular is prone to “flash droughts” — shortages caused by warm weather that can happen quickly over a few days or weeks. 

“These rapid-onset droughts can be particularly challenging for the agricultural community because they arrive quickly and conditions can rapidly go from normal to drier than normal,” said Quiring. “All of a sudden soil moisture is depleted, the crops are stressed and yield losses and impacts on the ecosystem occur.”  

The last time severe drought caused major losses in the United States was in 2012 when a record-breaking heat wave resulted in $34.2 billion in economic losses, 123 direct deaths and a 26% decrease in total corn crop yield across the country. 

As large areas of the country dried out, Ohio’s corn yield dropped from about 160 bushels per acre to 120 bushels per acre within a year. While such considerable losses have not happened since, according to the State Climate Office of Ohio, some areas of the state have experienced abnormally dry drought conditions this year.  

What’s more, the researchers’ impacts-based method of drought monitoring also takes into account how climate change can worsen flash drought events.

“One of the impacts that we found to be counterintuitive in Ohio is that with climate change, we do expect more rainfall overall, but we also expect to see more droughts because there are longer periods of time where no rain occurs,” said Quiring. 

The results of this study suggest that following guidelines that aren’t specific to a region’s issues can end up either systematically underestimating the impacts of severe drought conditions in some locations or overestimating them in others, Quiring said. 

While it’ll be some time before Quiring’s team can get their research incorporated into the next edition of the state drought plan, the study emphasizes that its methods could easily be applied to other regions beyond Ohio where long-term streamflow and crop yield data are readily available. Optimistically, it could help to improve drought monitoring worldwide and provide useful information to future agriculture producers and decision-makers, said Quiring. 

“This work is actually timely because it will provide a basis for decision-making in Ohio, rather than using research that’s been done in other parts of the country,” said Quiring. “Hopefully we can give better guidance to those who are making decisions on the ground.”

This study was supported by the National Integrated Drought Information System (NIDIS). Co-authors were Ning Zhang and Zhiying Li, who were both at Ohio State when the study was conducted. Zhang is now at the University of California, Davis and Li is at Indiana University.  

Made by pyrolysis, a process that involves heating organic material in a low-oxygen environment, biochar – a charcoal-like, porous substance – has long been utilized for crop production as a soil amendment or carbon sequestration agent. In recent years,  researchers have seen a resurgence of heightened interest in the technology due to its unique physical structure and its various agricultural and environmental benefits.

It’s for these reasons that biochar’s potential to remove large amounts of greenhouse gases from the atmosphere deserves to be re-evaluated, said Raj Shrestha, lead author of the study and a research associate in horticulture and crop science at The Ohio State University.  

“When farmers grow their crops, they apply fertilizer and/or manure and use different kinds of machinery to till the soil,” said Shrestha. “In the process, greenhouse gases are produced and released into the atmosphere.”

But farmers could lessen this impact by applying biochar to their fields, according to the paper, recently published in the Journal of Environmental Quality.

“If we can convince farmers that converting biomass to biochar is good for the long-term sustainability of soils, the economy, and good for the environment, then we’ll be able to see wide adoption of this technology,” said Shrestha.

The researchers reviewed more than 200 field studies conducted across the globe that examined the impact of biochar application in agriculture on emissions of nitrous oxide, methane and carbon dioxide – heat-trapping gases that cause Earth’s atmosphere to warm.

The team found that the amount of biochar in the soil does have variable effects on local greenhouse gas emissions, which range from a decrease to an increase, and, in some cases, no change. But in general, the team discovered that the use of biochar in field settings lowered the amount of nitrous oxide in the air by about 18% and methane by 3%.

Biochar alone was also not effective at reducing carbon dioxide emissions, but did help when combined with commercial nitrogen fertilizer or other organic materials, like manure or compost. 

“We can achieve negative emission in our agroecosystems by reducing the carbon source and enhancing carbon sink,” said Shrestha. Reducing Earth’s carbon source can be achieved by reducing greenhouse gas emissions from our activities, and enhancing carbon sink – increasing the technology’s ability to absorb more carbon than it releases into the atmosphere – can be done by increasing the long-term soil carbon pool through conversion of organic waste into biochar, he said. 

“What’s good about biochar is that it contributes to both these aspects to create net negative agriculture,” said Shrestha.

Right now, when farmers leave crop residue on the field, only about 10% to 20% of the residue carbon is recycled into soil during the decomposition process, but by converting the same amount of residue to biochar and then applying it to the field, we can store about 50% of that carbon into stable carbon forms.”

As biochar-carbon placed in the soil can also last anywhere from a few hundred to thousands of years, it’s currently one of the proposed best management practices for achieving negative emissions and preventing Earth’s average temperature from increasing to 1.5 degrees Celsius above pre-industrial levels. 

According to the study, between 2011 and 2020, global greenhouse gas emissions rose: carbon dioxide by about 5.6%, methane by 4.2%, and nitrous oxide by 2.7% – and agriculture accounts for about 16% of these emissions. While such levels have already led to irreversible changes to the global climate system, Shrestha said that future damages could be slowed by helping to curb the extent of emissions from the farming and forestry sectors. 

Yet despite biochar’s potential as a negative emission technology and the recent increase in biochar-related research, it’s difficult to get farmers to apply it, partly because it hasn’t been commercialized for widespread use or promoted well, said Shrestha. 

To better deliver more science-based, practical information about the technology and its benefits to farmers and agriculture-related businesses, many lawmakers have enacted policies meant to investigate its effectiveness across many different soil types and environmental conditions. It’s an objective that Shrestha shares, as the main goal of his team’s review paper is to improve farmers’ confidence in biochar so that more of them choose to adopt it sooner. 

This study was supported by The Arthur P. Sloan Foundation. Other Ohio State co-authors were Laura E. Lindsey, Rattan Lal, Klaus Lorenz and Scott M. Demyan, as well as Pierre-Andre Jacinthe from Indiana University Purdue University Indianapolis, Maninder P. Singh from Michigan State University and Wei Ren from the University of Kentucky. 

Published in the journal Computers and Electronics in Agriculture, the study investigates using neural networks to help characterize a crop defoliation, or the widespread loss of leaves on a plant. This destruction can be caused by disease, stress, grazing animals, and more often by infestations of insects and other pests.

If left unchecked, whole crop fields can end up damaged, drastically lowering an entire region’s agricultural productivity. To combat this, researchers chose to analyze a cash crop considered to be one of the four staples of global agriculture: soybeans. 

Between August and September of 2020, Zichen Zhang, lead author of the study and a graduate student in computer science and engineering at Ohio State,  used an Unmanned Aerial Vehicle (UAV), or a drone, to take aerial images of five soybean fields in Ohio. After cropping each UAV image into smaller images, the team eventually had more than 97,000 photos that they could label either healthy, or defoliated.

“Soybeans are one of the most important agricultural products in the United States, whether it be in exports, or in further food products,” he said. According to the USDA, the United States is the world’s leading soybean producer, and its second-leading exporter. Yet domestic farmers are racing to keep up with the demand: Last year, over 90 million acres of soybean crops were projected to be planted to keep up with consumer needs.

Because soybeans are an important source of oil, food and protein in many areas of the world, a potential drop in U.S. soybean production could have profound consequences. But Zhang’s study, one of the first to employ non-invasive technologies to characterize large-scale crop health, can help assess the likelihood of a drop in production because of defoliation. 

“Soybean defoliation is a very typical problem, but it’s one we can address,” said Zhang.

After manually sifting through the collected images, researchers found that about 67,000 of them could be labeled healthy, while almost 30,000 showed varying signs of defoliation, a ratio greater than 2-to-1. Then they used this data set to compare multiple learning algorithms’ ability to correctly infer which crops were defoliated, and to avoid making incorrect assumptions of healthy soybean crops.  

But after concluding that none of the learning classifiers could offer the precision they wanted to achieve, the researchers decided to create their own deep learning tool from scratch. This final product is called Defonet, a neural network capable of investigating and answering the study’s original defoliation inquiries correctly. “This new architecture is tailored toward this workload,” Zhang said. “It has better performance than currently available tools in accuracy, precision and efficacy.”  

If adopted in the field, Defonet may transform the agriculture industry’s decision-making process in dealing with severe crop losses, according to study co-author Christopher Stewart, an associate professor of computer science and engineering. 

“In the coming years, we’re going to have to increase food production substantially in order to just meet the demand,” said Stewart. “The idea behind digital agriculture is using computer science and other technologies to make sure that each planted seed is grown as effectively as possible.”

The study was also co-authored by Sami Khanal, an assistant professor of food, agricultural and biomedical engineering, Amy Raudenbush, a research associate in entomology, and Kelley Tilmon, an associate professor of entomology. This research was supported by the National Science Foundation.