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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, helping to avoid such losses. This study presents a strategy for producing probabilistic heat stress forecasts for well-watered cotton (Gossypium hirsutum L.) in the Camilla, GA, region. Multiple linear regression was used to develop a cotton canopy temperature model based on predicted air temperature, humidity, solar radiation, and wind speed. The European Centre for Medium-Range Weather Forecasts Ensemble Prediction System was used to predict the meteorological variables used in the canopy temperature model, which produced 10-d probabilistic canopy temperature forecasts for each day of observations during 2014. A statistical mean bias correction was applied to improve on the raw model forecasts. The forecasts were found to be skillful, with relative operating characteristic areas greater than 0.5. The bias-corrected forecasts were found to increase skill. A heat stress warning system was then created using the forecasts. Additionally, an economic analysis was performed as an example of how probabilistic forecasts can be used to aid producers with financial decisions pertaining to weather-related risks. [ABSTRACT FROM AUTHOR]

In this experiment, precipitation forecasts were used to schedule irrigation for cotton (Gossypium hirsutum L.). Four irrigation treatments and two cotton varieties were evaluated at Stripling Irrigation Research Park located near Camilla, GA in 2014. Two treatments were irrigated based on forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) and The Weather Channel®'s mobile app. Irrigation amounts for these two treatments were determined by the Cotton Irrigation Schedule Suggested for High Yields (check-book recommendations). The third treatment was irrigated by the check-book method and the fourth was rainfed. Irrigation applied for each treatment was 34.8 cm, 26.7cm, and 31.9 cm for the ECMWF EPS, weather.com, and checkbook, respectively. Rainfed cotton received 16.56 cm in precipitation. All irrigation methods resulted in significantly higher yields than the rainfed cotton. Results suggest using precipitation forecasts to schedule irrigation could provide a convenient alternative to the check-book method. [ABSTRACT FROM AUTHOR]