Improved drought prediction on the way

A new study by researchers at Oklahoma State University’s Department of Plant and Soil Sciences may well improve the predictability of seasonal droughts and provide a better way for farmers to determine when drought conditions are likely to occur.

The study, which began as a student-led class research project, was published Jan. 29 in Agronomy Journal.

Researchers Guilherme M. Torres, Romulo P. Lollato and Tyson E. Ochsner say drought can cause yearly loses of $8 million in the United States and can severely limit crop growth throughout the year in which they occur but believe a reliable calendar of seasonal drought patterns can be created that could help farmers optimize crop productions by avoiding periods of severe drought.

The study underscores the problem of current drought prediction practices, suggesting that current methods that estimate the probability of agricultural drought using atmospheric data can be widely applied but have not been compared with actual drought occurrence indicated by soil moisture measurements. The researchers’ objective was to develop a drought probability assessment method using long-term measurements of soil water deficits and to compare the resulting probabilities with those of an existing method based on atmospheric water deficits.

Tyson Ochsner, lead author of the study, says soil moisture needs to be factored into drought prediction methodologies to get a better picture of how it affects seasonal conditions.

“Soil moisture can provide an important buffer against short-term precipitation deficits,” he says, and calculating soil moisture for prediction models can greatly increase accurate drought forecasting.