A comparison of the performance of the CSM-CERES-Maize and EPIC models using maize variety trial data

Yawen Bao, Gerrit Hoogenboom, Ron McClendon and George Vellidis

Agricultural Systems, 2017, vol. 150, issue C, 109-119

Abstract: Multiple crop models are now being used in climate change impact studies. However, calibration of these models with local data is still important, but often this information is not available. This study determined the feasibility of using maize variety trial data for the evaluation of the CSM-CERES-Maize and EPIC models. The models were calibrated using observed grain yield from variety trials conducted in Blairsville, Calhoun, Griffin, Midville, Plains, and Tifton, Georgia, USA. The software program GenCALC was used to calibrate the yield component coefficients of CSM-CERES-Maize, while the coefficients for EPIC were manually adjusted. The criteria for evaluating the performance of the two crop models included the slope of linear regression, R2, d-stat, and RMSE. Following model calibration and evaluation, both models were used to simulate rainfed and irrigated grain yield during 1958 to 2012 for the same six locations that were used for model evaluation. The differences between the simulations of CSM-CERES-Maize and observations were no more than 3% for calibration and no more than 8% for evaluation. However, the differences between the simulations of EPIC and observations ranged from 2% to 23% for calibration and evaluation, which was larger than for the CSM-CERES-Maize model. This analysis showed that calibration of CSM-CERES-Maize was slightly superior than EPIC for some cultivars. Although this study only used observed grain yield for calibration and evaluation, the results showed that both calibrated models can provide fairly accurate simulations. Therefore, it can be concluded that limited data sets from maize variety trials can be used for model calibration when detailed data from growth analysis studies are not readily available.

Keywords: Yield; Calibration; Evaluation; Climate change; Decision support system (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0308521X16306588
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:150:y:2017:i:c:p:109-119

DOI: 10.1016/j.agsy.2016.10.006

Access Statistics for this article

Agricultural Systems is currently edited by J.W. Hansen, P.K. Thornton and P.B.M. Berentsen

More articles in Agricultural Systems from Elsevier
Bibliographic data for series maintained by Catherine Liu ().