What is in this article?:
• The study underscores the problem of current drought prediction practices.
• 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.
The study found that drought is a major cause of limited productivity in rainfed agroecosystems throughout the world, accounting for a large proportion of the crop losses and yearly yield variation of annual crops. Drought costs are estimated to vary from $6 billion to 8 billion year in the United States alone, but single events have caused losses as high as $39 billion.
Drought is a climatological event characterized by low precipitation and intensified by weather factors such as low atmospheric humidity, high wind speeds, and high temperatures. Different types of drought are recognized, including meteorological, agricultural, and hydrological drought, each with specific characteristics and magnitudes.
The study defines meteorological drought as persistent below-average precipitation that can alter the seasonal replenishment of soil water, which may lead to agricultural drought. Agricultural drought is a deficiency in soil water that is severe enough to harmfully stress rangelands and pastures and to decrease crop production.
According to the OSU study, accurate assessment of seasonal patterns in drought probability is important because if the crop cycle can be matched with periods when drought is less likely to occur, yield losses due to drought may be reduced.
“We are in a time of rapid increase in the availability of soil moisture data, but many users will still have to rely on the atmospheric water deficit method for locations where soil moisture data are insufficient,” Ochsner says.
Ochsner and his team hope that their research will help farmers better plan the cultivation of their crops and avoid costly losses to drought conditions.