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Drought to Imperil US Winter Wheat in Run-up to Dormancy

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Ongoing drought, limited rainfall in the forecast for the Great Plains, and the increased likelihood of a triple-dip La Niña are threatening the US’ hard red winter (HRW) crop six to eight weeks ahead of its dormant stage. Without adequate soil moisture during this stage, next year’s US HRW crop is at risk for lower yields. 

The US Climate Prediction Center is now assigning a 75% chance that La Niña weather conditions - which tend to bring warm and abnormally dry conditions to the southern Great Plains - will continue until March. US HRW production fell nearly 30% this year, due to the La Niña-fueled drought in the Plains. 

Already, Gro’s Drought Index, weighted to the US’ top HRW-producing states of Kansas, Oklahoma, and Texas in the southern Great Plains, is showing much more dire drought conditions compared with last year. And, according to Gro’s Climate Risk Navigator for Agriculture, only minimal rainfall is expected in Kansas, Oklahoma, and Texas during the next 15 days. As these three states produce about 70% of US HRW wheat, their yields are key determinants of US production. 

In the US’ top HRW-producing states, farmers have already planted more than half the upcoming crop, but, as dryness limits the volume of nutrients available to the young crop, emergence rates have slipped slightly behind their five-year average. 

HRW, which accounts for nearly 40% of total US wheat production, is grown primarily in the Great Plains states of Colorado, Kansas, Nebraska, Oklahoma, Texas, Montana, South Dakota, North Dakota, Oregon, and Wyoming. 

With wheat production shortfalls expected in Argentina and Ukraine, lower US wheat production would present a significant setback for efforts to rebuild global wheat supplies. Overall, global wheat ending stocks, excluding China, are forecasted to be the tightest in 14 years

While the impact on final wheat crop yields will depend on the intensity and duration of the La Niña, Gro’s US Hard Red Wheat Yield Model, like all of our machine-learning based yield models, updates daily with yield forecasts at the district level and offers in-season, near-real-time yield analysis. 

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