Changes in climate patterns have a significant impact on agricultural production. A comprehensive understanding of weather changes in arable farming is essential to ensure practical and effective strategies for farmers. Our research aimed to investigate how different fertilization interacts with environmental factors, examine their effects on wheat yield and varietal response over time, minimize nitrogen (N) fertilizer using alfalfa as a proceeding crop, and recommend an optimum N dose based on the latest weather conditions. A long-term experiment including 15 seasons (1961–2022) was studied, where a wheat crop followed alfalfa with different N applications. Our results indicated that the average temperature in the Caslav region has increased by 0.045°C per year, more significantly since 1987. Moreover, precipitation slightly decreased by 0.247 mm, but not significantly. The average November temperatures are gradually rising, positively affecting wheat grain yield. July precipitation negatively impacted grain yield only in years with extraordinary rainfall. Additionally, new wheat varieties (Contra, Mulan, Julie) yielded statistically more than the old variety (Slavia). Effectively managing nitrogen under various climate conditions is essential for promoting plant growth and reducing environmental N losses. The optimal N dosage was determined at 65 kg/ha N, resulting in an average yield of 9.1 t/ha following alfalfa as a preceding crop. Alfalfa reduces the need for N fertilization and contributes to sustainable conventional agriculture. Our findings will serve as a foundation for designing future climate change adaptation strategies to sustain wheat production.

This study utilizes a dynamic programming decision model, considering an intertemporal nitrogen carryover function, combined with both linear stochastic and deterministic plateau response functions to evaluate optimal nitrogen fertilizer decision rules and net present values (NPVs) in Texas High Plains cotton production. Nitrogen recommendations and NPVs are influenced by response function choice and nitrogen-to-cotton price ratios. Results indicate the stochastic plateau function better describes the data; the optimum nitrogen recommendation is to apply approximately 40 lb. of nitrogen for each bale of cotton production when considering nitrogen carryover information.