NETWORK FOR EVALUATING AND IMPROVING SOYBEAN CROP MODELS AND THEIR ROLE IN ENVIRONMENTAL IMPACT AND SUSTAINABILITY OF AGRONOMIC SYSTEMS

The long-term goal of this project is to develop an ensemble of soybean models that reduces the uncertainty in prediction of water, C, and N balances when used in the design of sustainable agronomic systems that include this major grain legume. We will address this goal by providing a network across crop model developers and data experimentalists and designing protocols for data testing, synthesis, and generation of new knowledge that target bottleneck areas necessary for an accelerated improvement and applicability of soybean models.The specific objectives that we will address will be the model testing and improvement for the four main bottleneck areas listed below. Within each objective, we will evaluate the uncertainties in projected environmental impacts from an ensemble of models and discuss challenges and opportunities for increasing ecosystems services.Objective 1: Simulation of soybean model responses under different CO2 levels with data from Free-Air Concentration Enrichment (FACE) experiments.Objective 2: Simulation of evapotranspiration in soybean with data from eddy covariance water vapor flux sites.Objective 3: Simulation of N2-fixation processes with experimental data under variable water stress. Evaluate the potential impact of soybean rotations on water dynamics and C / N cycling.Objective 4: Simulation of sowing date and cultivar maturity group (MG) effect with regional and detailed in-season data.Evaluate the potential impact of management adaptation on water dynamics and C / N cycling.