Weather forecasts can enhance the utilization of scientific irrigation scheduling tools, crucial for maximizing agricultural water use efficiency. This study employed quantitative weather forecasts of 3-, 7- and 14-day lead times from a weather application programming interface (API) to generate irrigation schedules using the AquaCrop-OSPy model for maize, cotton and sorghum under different regulated deficit irrigation scenarios. The study aimed to determine the suitability of forecast lengths for irrigation scheduling under varying pumping capacities of center pivots (114 m³h⁻¹, 182 m³ h⁻¹ and 250 m³ h⁻¹) in the Texas High Plains and Rio Grande Basin regions, United States. A comparative analysis was carried out to evaluate the irrigation schedules and corresponding crop yields simulated using forecasted and observed weather data. Results indicated that using shorter forecast time allowed the crop model to capture more precise variations in weather patterns, however, shorter lead times also caused over-irrigation in some scenarios. Use of longer lead times tended to be less suitable for scheduling irrigation during water-sensitive growth stages. Center pivots with large pumping capacities and application rates benefited more from longer forecast lengths due to their ability to adapt to weather fluctuations. Unplanned irrigation application occurred in some instances, primarily attributed to uncertainties in weather forecasts and limitations of the crop model. The approach developed and evaluated in this study supports water conservation efforts by promoting scientific irrigation scheduling in weather-data-poor and low adoption regions.

天气预报可以提高科学灌溉调度工具的利用率，这对于最大限度地提高农业用水效率至关重要。本研究利用天气应用程序编程接口 (API) 提供 3 天、7 天和 14 天提前期的定量天气预报，并使用 AquaCrop-OSPy 模型为不同调节赤字灌溉情景下的玉米、棉花和高粱生成灌溉计划。^{该研究旨在确定中心支点不同抽水能力（114 m 3} h ⁻¹、182 m ³  h ⁻¹和 250 m ³  h ⁻¹）下灌溉调度预测长度的适用性）位于美国德克萨斯州高平原和里奥格兰德盆地地区。进行了比较分析，以评估使用预测和观测的天气数据模拟的灌溉计划和相应的作物产量。结果表明，使用较短的预报时间可以使作物模型捕获更精确的天气模式变化，但是，较短的提前时间在某些情况下也会导致过度灌溉。在对水敏感的生长阶段，使用较长的提前期往往不太适合安排灌溉。具有较大泵送能力和施用量的中心枢轴由于能够适应天气波动，因此可以从较长的预报长度中受益更多。在某些情况下发生了计划外的灌溉，主要归因于天气预报的不确定性和作物模型的局限性。本研究中开发和评估的方法通过在天气数据匮乏和采用率低的地区促进科学灌溉调度来支持节水工作。