A new University of Florida-led study shows how Australian wheat farmers can use hypothetical 10-day weather forecasts to increase their annual profits by hundreds of thousands of dollars, a finding that can be applied to other parts of the globe.
Scientists now want to know how a real 10-day weather forecast will affect farmers’ decisions on when to plant and fertilize, said Senthold Asseng, a professor of agricultural and biological engineering at the UF Institute of Food and Agricultural Sciences. They may apply their new findings on a fresh study that would predict crop yield based on 10-day forecasts in the United States.
“U.S. farmers make decisions based on anticipated growing conditions, including rainfall and temperature,” said Asseng, who led the study. “So I think it would be very useful to develop a project with farmers to explore if they could make more money or be more sustainable when considering a short-term forecast in their decision making. If so, real forecasts need to be analyzed and combined with farmers’ decisions.”
Similar to the 10-day forecasts one might find on The Weather Channel, the Australian Bureau of Meteorology projects weather for 10 days at a time. In this study, scientists estimated how much more wheat could have been produced in Western Australia when adjusting management to a 10-day rainfall forecast from 1980 through 2006.
Although the study was conducted in Western Australia, its findings can apply to any area around the globe where rainfall variability causes large differences in crop yield, Asseng said. Those include many regions in the U.S. and elsewhere where rainfall limits yields in many seasons.
Researchers used a dynamic simulation model to generate grain yields for various sowing dates, nitrogen fertilizer response and non-rust-damaged crops for four soil types in the southwest wheat belt in Western Australia. They also plugged into the model a hypothetical, perfect, 10-day weather forecast that included more than 10 millimeters of rainfall in three days.
Scientists then compared a situation where a farmer doesn’t know predicted rainfall for the next 10 days with a situation where the farmer knows with 100 percent certainty the rainfall amount and makes sowing decisions based on this data, Asseng said.
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