Optimization and evaluation of the ANTHRO-BGC model for winter crops in Europe

Climate change and agricultural development are interrelated processes, both of which take place on the global scale. An accurate representation of crop phenology and physiology in ecosystem models is important in order to investigate the interactive processes between atmosphere and biosphere. A new phenological model for crops has been recently incorporated into the ecosystem model BIOME-BGC. Fruit compartments as well as a module for harvest were added to the original model. Here we explore whether eddy flux measurements of agricultural ecosystems are helpful to identify the spatially generalized ecophysiological parameters of the ANTHRO-BGC model (updated BIOME-BGC model) for croplands. The maximum, minimum, and reference values of the ANTHRO-BGC parameters were derived from a literature review. The sensitive parameters of the model were detected by using global sensitivity analysis. The spatially generalized values of ecophysiological parameters for wheat, barley, and rape within a typical temperature and precipitation range in western and central Europe were identified with the help of optimization algorithms and eddy covariance measurements of carbon and water fluxes of agricultural ecosystems as observational constraints. Gross primary productivity (GPP) provided the best constraint on the model parameters for all the three crop types. The validity range of the parameter values defined by the literature review was proved to be reliable. The predictive ability of the optimized model has been improved for GPP and net ecosystem exchange (NEE), but not for evapotranspiration (ET). The performance of the ANTHRO-BGC model was comparable to the performances of other crop models such as DNDC, CERES-EGC, ORCHIDEE-STICS, and SPA model, tested on multiple sites. The optimized ANTHRO-BGC model was relatively stable in response to the variation of the parameters on multiple sites and years.

► The BIOME-BGC model was updated for agricultural ecosystems (named as ANTHRO-BGC). ► Eddy flux measurements were used as constraints to optimize ANTHRO-BGC model using optimization algorithm. ► The spatially generalized ecophysiological parameters of ANTHRO-BGC model were identified for different crops. ► The performance of optimized ANTHRO-BGC model was similar to other ecosystem models. ► Sensitivity and uncertainty analysis were adopted to explore reliable parameters for ANTHRO-BGC.