Short–term forecasting of daily evapotranspiration from rice using a modified Priestley–Taylor model and public weather forecasts

Reliable crop evapotranspiration (ET) forecasting is critical for water resource management and allocation. However, most estimation models cannot be directly used for ET forecasting with public weather forecasting information. Here, we propose a modified Priestley–Taylor (PT) model using only solar radiation (Rs) and air temperature (Ta) as inputs that can be easily obtained from public weather forecasts. The commonly used generalized sunshine– and temperature–based Rs models using forecasted weather types (transferred to sunshine duration) and Ta data as inputs were compared to identify the more suitable model for forecasting daily Rs. Results showed that the modified PT model using measured Rs and Ta data provided a reasonable accuracy to estimate daily rice ET across three energy flux sites. The regression coefficient (m), correlation coefficient (R), root mean squared error (RMSE), and index of agreement (dIA) were in the range of 0.949–1.044, 0.916–0.964, 0.396–0.645 mm d–1, and 0.954–0.980, respectively. The generalized temperature–based Rs model is more suitable for forecasting daily Rs for a 1–7 day lead time during the growth period of rice at present as indicated by its superior performance to sunshine–based model at 70% of 30 sites. The forecasted accuracy of rice ET was acceptable and decreased gradually as lead time increased. The mean values of m, R, RMSE, and dIA were decreased from 0.887 to 0.981, 0.641–0.782, 1.160–1.243 mm d–1, and 0.783–0.870 in 1–day lead time to 0.834–0.941, 0.376–0.563, 1.406–1.740 mm d–1, and 0.639–0.743, respectively, in 7–day lead time during 2018–2020 at Nanjing when Rs was forecasted based on the generalized temperature–based model. This study provides an important approach for short–term prediction of rice ET using public weather forecasting information.