The accurate estimation of reference evapotranspiration (ET_ref) is a crucial component for modeling hydrological and ecological cycles. The goal of this study was the calibration of 32 empirical equations used to determine ET_ref in the three classes of temperature-based, solar radiation–based, and mass transfer–based evapotranspiration. The calibration was based on measurements taken between the years 1990 and 2019 at 41 synoptic stations located in very dry, dry, semidry, and humid climates of Iran. The performance of the original and calibrated empirical equations compared to the PM-FAO₅₆ equation was evaluated based on model evaluation techniques including the coefficient of determination (R²), the root mean square error (RMSE), the average percentage error (APE), the mean bias error (MBE), the index of agreement (D), and the scatter index (SI). The results show that the calibrated Baier and Robertson equation for temperature-based models, the Jensen and Haise equation for solar radiation–based models, and the Penman equation for mass transfer–based models performed better than the original empirical equations. The calibrated equations had, respectively, an average R² = 0.73, 0.67, and 0.78; RMSE = 35.14, 35.02, and 30.20 mm year^-1; and MBE = − 5.6, − 3.89, and 2.57 mm year^-1. The original empirical equations had values of average R² = 0.60, 0.37, and 0.65; RMSE = 68.34, 66.98, and 52.62 mm year^-1; and MBE = − 5.75, 4.26, and 8.99 mm year^-1, respectively. The calibrated empirical equations for very dry climate (e.g., Zabol, Zahedan, Bam, Iranshahr, and Chabahar stations) also significantly reduced the SI value from SI > 0.3 (poor class) to SI < 0.1 (excellent class). Therefore, the calibrated empirical equations are highly recommended for estimating ET_ref in different climates.

参考蒸散量 (ET _ref )的准确估计是模拟水文和生态循环的关键组成部分。本研究的目标是校准 32 个经验方程，用于确定基于温度、基于太阳辐射和基于传质的蒸散三类中的ET _ref。校准基于 1990 年至 2019 年间在位于伊朗非常干燥、干燥、半干燥和潮湿气候的 41 个天气站进行的测量。与 PM-FAO ₅₆方程相比，原始和校准经验方程的性能是基于模型评估技术，包括决定系数 (R ²)、均方根误差 (RMSE)、平均百分比误差 (APE)、平均偏差误差 (MBE)、一致性指数 (D) 和分散指数 (SI)。结果表明，基于温度的模型的校准 Baier 和 Robertson 方程、基于太阳辐射的模型的 Jensen 和 Haise 方程以及基于传质模型的 Penman 方程的性能优于原始经验方程。校准方程的平均值分别为 R ² = 0.73、0.67 和 0.78；RMSE = 35.14、35.02 和 30.20 毫米年^-1；和 MBE = − 5.6、− 3.89 和 2.57 mm 年^-1。原始经验方程的平均值 R ² = 0.60、0.37 和 0.65；RMSE = 68.34、66.98 和 52.62 毫米年^-1; 和 MBE = − 5.75, 4.26, 和 8.99 mm year ^-1，分别。针对非常干燥气候（例如 Zabol、Zahedan、Bam、Iranshahr 和 Chabahar 站）的校准经验方程也将 SI 值从 SI > 0.3（差级）显着降低到 SI < 0.1（优级）。因此，强烈建议使用校准的经验方程来估计不同气候下的ET _ref。