The characteristics of this model is that, in this model, certain model parameters were estimated using Bayesian statistics with a Markov-Chain Monte Carlo (MCMC) method based on field observation data. This process allows for the model parameters to be calibrated to fit any region or scale. The model repeatedly performs hundreds of thousands of calculation steps in the MCMC process. Therefore, although the model must be sufficiently complex to describe the response of soybean production to increased atmospheric CO2, it should be relatively simple and include the fewest parameters possible to shorten the calculation time for each MCMC step. The model incorporates the big-leaf model and has a simple structure. The dynamics of mineral nutrients, such as nitrogen, are not considered. The daily partitioning of the photosynthate to each organ is estimated allometrically: the ratio of leaf biomass to total biomass is related to the degree of development of the crop, which is determined only by cumulative temperature. To calculate photosynthetic carbon assimilation, we used the enzyme kinetics model developed by Farquhar et al. (1980). To calculate soil water balance, we used a two-layer sub-model of the Soil & Water Assessment Tool (SWAT) model (Neitsch et al. 2005) but did not include lateral transport.
PRYSBI2 is one of the 14 models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a agricultural sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Agricultural Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.006
