Real-time methods for short and medium-term evapotranspiration forecasting using dynamic crop coefficient and historical threshold

Crop evapotranspiration (ETc) plays a fundamental role in agronomic and water resource management. Accurate forecasting of ETc is a major challenge for agricultural researchers and experts. Based on the measured ETc of the Eddy Covariance system and weather forecast data (1-15 d: short and medium-term) in North China, the realtime short (1-7 d) and medium (8-15 d) term ETc forecast models were developed by coupling with the dynamic crop coefficient and modifying the historical threshold. The results demonstrated that compared with the single crop coefficient model recommended by the Food and Agricultural Organization (FAO-56, M1), the M2 model (a modification of the M1 model developed using the dynamic crop coefficient) accurately forecasted the winter wheat and summer maize ETc, with an increased accuracy of 11%. Moreover, the ETc forecasting accuracy using the M2 model for short and medium-term was over 77%, of which the short-term accuracy was higher (greater than84%). The ETc forecasting accuracy increased with the decrease in the forecast period at different growth stages. Further, the short and medium-term accuracies of M3 model (a modification of the M2 model developed by incorporating the historical threshold) were over 81%, of which the accuracy of the 1 d forecast period was approximately 95%, which was 6% higher than that of the M2 model; the root mean square error and the mean absolute error were reduced by 0.1 mm d(-1) and 0.11 mm d(-1), respectively. Thus, these results indicated that the M3 model, which was developed by integrating the dynamic crop coefficient and the historical empirical threshold, can predict short and medium-term ETc more accurately.

Automated summary

Crop evapotranspiration (ETc) is crucial for agronomic and water resource management, but accurate forecasting has been a challenge. In this study, real-time short and medium-term ETc forecast models were developed based on dynamic crop coefficient and historical threshold modification. The results showed that the new models accurately predicted ETc for different crops, with higher accuracy in shorter forecast periods. The study also found that integrating historical empirical threshold further improved the accuracy of short and medium-term ETc forecast.