Evaluation of the environmental policy integrated climate model on predicting crop yield in the canadian prairies: A case study
Lychuk, T.E., Moulin, A.P., Johnson, E.N., Olfert, O.O., Brandt, S.A., Izaurralde, R.C. (2017). Evaluation of the environmental policy integrated climate model on predicting crop yield in the canadian prairies: A case study, 97(4), 692-702. http://dx.doi.org/10.1139/cjss-2017-0044
© Her Majesty the Queen in right of Canada 2017. The Environmental Policy Integrated Climate (EPIC) model was updated with relevant weather, tillage, and crop management operations from the 1994 to 2013 Alternative Cropping Systems study to assess simulations of annual and long-term yield of wheat, barley, and canola. Linear regression and coefficients of determination (R2), root mean square error of prediction (RMSE), the d index, and paired sample t-test were used to assess the relationship between simulated and experimental values. Simulations indicated that the model captured long-term yield trends but was less accurate at predicting annual variations. These variations were due to variability of soil properties at the research field, terrain attributes, extreme weather events, and the model’s overestimation of available nitrogen (N) under low-N input systems. The R2, RMSE, and the d index values on long-term yield were R2 = 0.74, RMSE = 205 kg ha-1, and d = 0.75 for wheat; R2 = 0.90, RMSE = 226 kg ha-1, and d = 0.73 for barley; R2 = 0.98, RMSE = 238 kg ha-1, and d = 0.76 for canola, indicating good model performance. The EPIC model effectively simulated crop yields affected by agricultural inputs and cropping diversity, and may be used to assess future cropping decisions and agronomic management.
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