New forecast scheme for heat stress in cotton
Heat stress can reduce crop yield or even cause total crop failure. The ability to predict heat stress in advance would allow growers time to implement protective measures that would help avoid such losses.
A new paper published in the Agronomy Journal by CFAN team members Emily Christ, Peter Webster and Violeta Toma presents a strategy for producing probabilistic heat stress forecasts for well-watered cotton in Georgia. The 10-day forecast scheme integrates a cotton canopy temperature model with probabilistic forecasts of surface meteorology from the ECMWF Ensemble Prediction System. A heat stress warning system was then created using the forecasts. An economic model based on the variable cost of irrigation and the cost of yield loss was developed to guide decision making regarding irrigation as a strategy to protect from heat stress. The model identified thresholds of probability for heat stress occurrence that where it is financially beneficial to protect the crops with irrigation, depending on whether the farmer is more yield conscious or water conscious.
“Through collaboration with agricultural researchers and extension experts, CFAN is developing meaningful forecast products designed to help make farming easier,” says Emily Christ, CFAN’s Product Manager for Agriculture. “Probabilistic forecasts such as these, coupled with relevant research and information from the agricultural community, can be used to provide powerful insight into implementing more efficient farming practices.”