Crop simulation models are frequently used to estimate the impact of climate change on crop production.
However, few studies have evaluated the model performance in ways that most researchers practiced in
climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain
sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios,
namely in years with normal or extreme temperature and precipitation. We also investigated model
uncertainties introduced by input data that are not site-specific but commonly used or available for
climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were
used for model evaluations. The results showed that overall model reliability was about 56%. The mean
absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate classes
and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = 25%) and the most
unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability
that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the
application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts
are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen stressed
conditions.