C and N models Intercomparison – benchmark and ensemble model estimates for grassland production

Much of the uncertainty in crop and grassland model predictions of how arable and grassland systems respond to changes in management and environmental drivers can be attributed to differences in the structure of biophysical models. This has created an urgent need for international benchmarking of models, in which uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty in model predictions. Simulations of C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions and complicated by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects to benchmark and compare simulation models that estimate C–N related outputs from arable crop and grassland systems. In this study substantial differences in the outputs of 12 grassland models were obtained, indicating uncertainty in simulated grassland processes. Uncertainties for some outputs (e.g. biomass yield) reduced after calibration with detailed production and phenology data. The multi-model approach also allowed for improved performance, as reflected by standardized residuals. Locally calibrated models more reliably assess mitigation options at the studied sites than uncalibrated models.