Assessing Heat Stress Impacts on Cotton Yield and Revenue: A Multilevel Regression Approach in the Southern U.S.

Climate change-induced heat stress significantly threatens cotton production in the Southern United States, reducing yields and farm revenue. This study quantifies the impact of rising temperatures using a multilevel regression model applied to historical climate and yield data (1980–2018) from key cotton-growing regions. The analysis examines how maximum and minimum temperatures, precipitation, and growing degree days influence yield at different growth stages. Results show that a 1°C increase in maximum temperature during the flowering stage (TmaxGS2) reduces cotton yield by 5.5%, leading to revenue losses of up to $219 per acre. Conversely, higher precipitation during critical growth periods increases yield by 183 lb/acre, partially offsetting heat stress effects. Given these findings, adaptation strategies are essential. We recommend the development of heat-tolerant cotton varieties, improved irrigation management, and expanded financial support programmes, including climate-based crop insurance. Additionally, optimising planting schedules and adopting precision agriculture can help mitigate yield losses. These measures will strengthen the resilience of cotton farming against escalating climate risks, ensuring long-term sustainability. This study provides valuable insights for farmers, policymakers, and researchers working to safeguard cotton production in a changing climate.