with Andrej Ceglar, Raúl López and Simona Bassu (Joint Research Centre). Work in progress.
The purpose of this research project is to improve winter wheat crop model calibration by better simulating crop yields using actual field-level yield data, which will eventually improve MARS crop yield forecasting tools and will help to estimate crop water requirements (implications for irrigation).
Materials and Methods
WOFOST is a deterministic, dynamic crop model used for the quantitative analysis of the growth and production of annual field crops. As a mathematical model of agricultural production, WOFOST only considers ecological factors under the assumption that optimum management practices are applied. In WOFOST, systems analysis and simulation are applied to agricultural production. This approach is characterised by the terms: systems, models and simulations. In WOFOST, the system considered is an annual crop, growing in a specific physical environment.
WOFOST simulates crop growth with time steps of one day, based on knowledge of processes at a lower level of integration. The state-rate approach is used, based on the assumption that the state of the system can be quantified at any moment, and that changes in the system can be described by mathematical equations. State variables are quantities, such as biomass or the amount of water in the soil. Driving variables (or forcing functions) characterise the influence of external factors on the system, but are not influenced by the processes within the system. Examples are macro-meteorological variables, such as radiation, air temperature and precipitation. Rate variables indicate the rate at which the state variables change over a certain time step. In WOFOST, crop growth is simulated based on eco-physiological processes. The major processes are CO2 assimilation, respiration, phenological development, transpiration, partitioning of assimilates to the various organ, and dry matter formation.