Uncertainty in crop model predictions: What is the role of users?

Crop models are used to estimate crop productivity under future climate projections, and modellers manage uncertainty by considering different scenarios and GCMs, using a range of crop simulators. Five crop models and 20 users were arranged in a randomized block design with four replicates. Parameters for maize (well studied by modellers) and rapeseed (almost ignored) were calibrated. While all models were accurate for maize (RRMSE from 16.5% to 25.9%), they were, to some extent, unsuitable for rapeseed. Although differences between biomass simulated by the models were generally significant for rapeseed, they were significant only in 30% of the cases for maize. This could suggest that in case of
models well suited to a crop, user subjectivity (which explained 14% of total variance in maize outputs) can hide differences in model algorithms and, consequently, the uncertainty due to parameterization should be better investigated.