Evaluation of the Integrated Canadian Crop Yield Forecaster (ICCYF) model for in-season prediction of crop yield across the Canadian agricultural landscape

© 2015 . Early warning information on crop yield and production are very crucial for both farmers and decision-makers. In this study, we assess the skill and the reliability of the Integrated Canadian Crop Yield Forecaster (ICCYF), a regional crop yield forecasting tool, at different temporal (i.e. 1-3 months before harvest) and spatial (i.e. census agricultural region - CAR, provincial and national) scales across Canada. A distinct feature of the ICCYF is that it generates in-season yield forecasts well before the end of the growing season and provides a probability distribution of the forecasted yields. The ICCYF integrates climate, remote sensing derived vegetation indices, soil and crop information through a physical process-based soil water budget model and statistical algorithms. The model was evaluated against yield survey data of spring wheat, barley and canola during the 1987-2012 period. Our results showed that the ICCYF performance exhibited a strong spatial pattern at both CAR and provincial scales. Model performance was better from regions with a good coverage of climate stations and a high percentage of cropped area. On average, the model coefficient of determination at CAR level was 66%, 51% and 67%, for spring wheat, barley and canola, respectively. Skilful forecasts (i.e. model efficiency index. >. 0) were achieved in 70% of the CARs for spring wheat and canola, and 43% for barley (low values observed in CAR with small harvested area). At the provincial scale, the mean absolute percentage errors (MAPE) of the September forecasts ranged from 7% to 16%, 7% to14%, and 6% to 14% for spring wheat, barley and canola, respectively. For forecasts at the national scale, MAPE values (i.e. 8%, 5% and 9% for the three respective crops) were considerably smaller than the corresponding historical coefficients of variation (i.e. 17%, 10% and 17% for the three crops). Overall, the ICCYF performed better for spring wheat than for canola and barley at all the three spatial scales. Skilful forecasts were achieved by mid-August, giving a lead time of about 1 month before harvest and about 3-4 months before the final release of official survey results. As such, the ICCYF could be used as a complementary tool for the traditional survey method, especially in areas where it is not practical to conduct such surveys.