This study selected the temperature Penman–Monteith (PMT) model to solve the difficulty of reference crop evapotranspiration (ET₀) prediction caused by incomplete meteorological data. Then, the principal control factor of the PMT model was determined using several indicators. The results show that the annual average correlation and sensitivity coefficients between T_max and ET₀ are the highest. Hence, among the factors, T_max is the largest contributor in contribution proportion and amount to ET₀ and the principal control factor of the PMT model. The root mean square error (RMSE), relative error (RE) and mean absolute error (MAE) of the forecast ET₀ increased by 0.7, 0.2, and 0.6 mm/day, respectively, after the 16th day compared with those on the 15th day. Thus, a remarkable drop in ET₀ forecast precision is observed and is hardly accurate for the purpose of water distribution management in an irrigation district. The RMSE, RE, and MAE of the T_max forecast decrease by 2.0–3.0°C, 0.1–0.2, and 2.0–2.8°C, respectively, and those of the corresponding ET₀ forecast decrease by 0.7–0.9, 0.2–0.3, and 0.6–0.7 mm/day, respectively, after T_max correction. Compared with the decaying-average method, the improved decaying-average method can correct T_max better and improve the ET₀ prediction accuracy.

中文翻译：

---

基于主控因子修正的参考作物蒸散量中长期预报

本研究选择温度Penman-Monteith（PMT）模型来解决由于气象数据不完整导致的参考作物蒸散量（ET ₀）预测困难。然后，使用多个指标确定 PMT 模型的主控制因素。结果表明，T _max与ET ₀的年平均相关系数和敏感性系数最高。因此，在这些因素中，T _{max是对ET 0}贡献比例和金额的最大贡献者，也是PMT模型的主要控制因素。_{预测 ET 0}的均方根误差 (RMSE)、相对误差 (RE) 和平均绝对误差 (MAE)与第 15 天相比，第 16 天后分别增加 0.7、0.2 和 0.6 毫米/天。_{因此，观察到 ET 0}预测精度显着下降，对于灌区的配水管理而言几乎不准确。T _max预报的 RMSE、RE 和 MAE 分别下降 2.0–3.0°C、0.1–0.2 和 2.0–2.8°C，对应的 ET ₀预报下降 0.7–0.9、0.2–0.3 ，和 0.6-0.7 毫米/天，分别在T _max校正后。与衰减平均法相比，改进衰减平均法可以更好地修正T _max，提高ET ₀预测精度。