Evaluation of the Environmental Policy Integrated Climate model on predicting crop yield in the Canadian Prairies: a case study

被引:5
|
作者
Lychuk, Taras E. [1 ]
Moulin, Alan P. [1 ]
Johnson, Eric N. [2 ]
Olfert, Owen O. [3 ]
Brandt, Stewart A. [4 ]
Izaurralde, Roberto C. [5 ]
机构
[1] Agr & Agri Food Canada, Brandon Res & Dev Ctr, 2701 Grand Valley Rd, Brandon, MB R7A 5Y3, Canada
[2] Univ Saskatchewan, Dept Plant Sci, 51 Campus Dr, Saskatoon, SK S7N 5A8, Canada
[3] Agr & Agri Food Canada, Saskatoon Res & Dev Ctr, 107 Sci Pl, Saskatoon, SK S7N 0X2, Canada
[4] Northeast Agr Res Fdn, POB 1240, Melfort, SK S0E 1A0, Canada
[5] Univ Maryland, Dept Geog, 2181 LeFrak Hall, College Pk, MD 20740 USA
关键词
EPIC model; agricultural inputs; cropping diversity; modeling; Canadian Prairies; CARBON SEQUESTRATION; LONG-TERM; SOIL; WHEAT; DIVERSITY; DYNAMICS; CORN;
D O I
10.1139/cjss-2017-0044
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
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 (R-2), 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 R-2, RMSE, and the d index values on long-term yield were R-2 = 0.74, RMSE = 205 kg ha(-1), and d = 0.75 for wheat; R-2 = 0.90, RMSE = 226 kg ha(-1), and d = 0.73 for barley; R-2 = 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.
引用
收藏
页码:692 / 702
页数:11
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