Evapotranspiration is a key component of water and energy balance. An accurate estimate of reference evapotranspiration (ET_o) is important for determining the water demand of field crops, water management, and hydrological modelling. The FAO-PM ET_o equation is the standard equation for estimating ET_o. Its use is limited by the requirement for too many observed inputs that are not always available in most weather stations. Empirical models requiring readily available inputs have been developed as an alternative. However, their performance is location-specific. Therefore, this study assesses the performance of the FAO-PM ET_o computed with limited data and fourteen empirical ET_o models. Meteorological data (2012–2019) was analyzed under the semi-arid climate conditions in southern Manitoba. Model performance was assessed using statistical indices, including R², RMSE, NSE, MPE, and MAE. Results showed that ET_o estimates under missing wind speed, relative humidity, or solar radiation were acceptable, although model performance decreased with increased missing data yielding average to poor performance. Based on R², RMSE, and NSE values, among the 14 models compared, the best performing models are Valiantzas-1, Valiantzas-3, Irmak, Valiantzas-2, and Priestly-Taylor models. New empirical coefficients were developed, requiring one or two climatic inputs to improve empirical models. Results showed that the calibrated models performed better than the original equation. The sensitivity analysis showed that ET_o is most sensitive to maximum temperature (T_max) and solar radiation (R_s), followed by vapour pressure deficit (VPD), wind speed (U₂), and minimum temperature (T_min). Therefore, it is recommended to ensure accurate measurements of temperature and solar radiation for accurate ET_o estimates. This study provides alternative ET_o models with reasonable and accurate ET_o estimates for southern Manitoba and other areas with similar climate characteristics.

蒸散作用是水和能量平衡的关键组成部分。对参考蒸散量（ET _o）的准确估算对于确定大田作物的需水量，水管理和水文模型很重要。FAO-PM ET _o方程是估算ET _o的标准方程。它的使用受限于对大多数气象站中并不总是可用的太多观测输入的需求。已经开发了需要随时可用的输入的经验模型作为替代方案。但是，它们的性能是特定于位置的。因此，本研究评估了FAO-PM ET的性能_Ø数据有限十四经验ET计算_Ø楷模。在曼尼托巴省南部半干旱气候条件下分析了气象数据（2012-2019年）。使用统计指标（包括R ²，RMSE，NSE，MPE和MAE ）评估模型性能。结果表明，在缺失风速，相对湿度或太阳辐射下的ET _o估计值是可以接受的，尽管模型性能随着缺失数据的增加而降低，从而导致平均表现不佳。基于R ²，RMSE和NSE值，在比较的14个模型中，性能最好的模型是Valiantzas-1，Valiantzas-3，Irmak，Valiantzas-2和Priestly-Taylor模型。开发了新的经验系数，需要一个或两个气候输入来改进经验模型。结果表明，校正后的模型的性能优于原始方程。敏感性分析表明，ET _o对最高温度（T _max）和太阳辐射（R _s）最为敏感，其次是蒸气压赤字（VPD），风速（U ₂）和最低温度（T _min）。因此，建议确保准确测量温度和太阳辐射，以进行准确的ET _o估算。这项研究为马尼托巴南部和具有类似气候特征的其他地区提供了具有合理和准确的ET _o估计值的替代ET _o模型。