Assessing forecasting performance of daily reference evapotranspiration: A comparative analysis of updated temperature penman-monteith and penman-monteith forecast models

• Published in: Journal of hydrology (Amsterdam) Vol. 626; p. 130317
• Main Authors: Lin, En, Qiu, Rangjian, Chen, Mengting, Xie, Hua, Khurshid, Bushra, Ma, Xinjuan, Quzhen, Suolang, Zheng, Shizong, Cui, Yuanlai, Luo, Yufeng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2023
• Subjects: Air temperature; China; continental climates; evapotranspiration; irrigation; monsoon season; Reference crop evapotranspiration; Solar radiation; temperature; water management; weather forecasting; Weather forecasts; China; Weather forecasts; Solar radiation; Reference crop evapotranspiration; Air temperature
• DOI: 10.1016/j.jhydrol.2023.130317
• ISSN: 0022-1694

•Updated PM model with temperature and sunshine duration-based solar radiation forecast methods for ET0 forecasting.•The most accurate method of ET0 forecasting was recommended for each climate region.•Using a temperature-based method to forecast solar radiation can greatly improve ET0 forecasting.•The updated PMT models outperformed than the PMF model in multiple climatic zones, but slightly less accurate in SMZ. Accurate forecast of reference evapotranspiration (ET0) is essential for effective water resource management and efficient irrigation scheduling. The Penman-Monteith model (PM) recommended by FAO56 is widely used as the standard method for ET0 forecasting, but PM model application is often limited by the absence of forecasted meteorological variables, especially solar radiation (Rs). Previous studies have proposed two types of models based on temperature and sunshine duration to estimate Rs. However, there is currently a lack of comprehensive comparative analysis research to evaluate the performance and applicability of these two types of models combined with weather forecast data for ET0 forecasting using the PM model. To address this issue, we selected China as the research area, which has complex climate zones and an uneven distribution of water resources. The forecasting results of Rs from temperature-based models (M1–M8) and a sunshine duration-based model (M9) are input independently into the PM model for ET0 forecasting. The updated PM model is named PMTM1–PMTM8 and PMF, respectively. We conducted a comprehensive and analytical assessment of the updated PMTM1–PMTM8 model, the PMF model and the Hargreaves-Samani (HS) model in different climate zones of China. The results showed that the accuracy of the M1–M8 and the M9 for forecasting Rs decreased as the forecasting period increased. The accuracy of the M9 was higher than that of M1–M8 in the overall accuracy in the subtropical monsoon climate (SMZ). Both the updated PMTM1–PMTM8 and PMF models were utilized to evaluate the ET0 forecasting performance in all five zones. The PMTM3 model exhibited the highest accuracy, with RMSE and MAE ranges of 0.671–1.572 mm d−1 and 0.532–1.365 mm d−1, respectively. In contrast, the PMF model displayed RMSE and MAE ranges of 0.690–1.590 mm d−1 and 0.641–1.437 mm d−1, respectively. Compared to the PMF model, the updated PMTM1–PMTM5 model showed higher accuracy in forecasting ET0 in the plateau mountain climate, temperate continental climate, temperate monsoon climate, and tropical monsoon climatic zones, but was slightly less accurate in the SMZ. Moreover, both models outperformed the Hargreaves-Samani (HS) model in terms of ET0 forecasting accuracy. Specifically, the updated PMTM1–PMTM5 model demonstrated improved accuracy compared to the temperature-based model HS model across various climate zones, with reductions in RMSE and MAE ranging from 0.117 mm d−1 to 0.616 mm d−1and 0.012 mm d−1 to 0.450 mm d−1, respectively. Overall, the updated PMTM3 model was better than the PMF and thus this model was recommended for daily ET0 forecasting for the near-future at all climate regions across China.