Simulation Models

This sub-section has chapters on dynamic crop simulation models. The term dynamic refers to the fact that these models simulate a process over time. That is, the model computes values for many time steps where the output of the time step (t) becomes input to model for the next time step (t+1). In the models we use here, the time step is always one day.

Simulation models provide a quantitative description of the mechanisms that cause the behavior of a system of interest (a system is a limited part of reality that contains interrelated elements). They are often referred to as mechanistic and explanatory. These terms refer to the idea that the model developer uses known mechanisms sub-system processes, such as leaf-level photosynthesis, to construct a model of the system of interest, such as crop growth.

A prime benefit of these models is that we can use them to learn about (explain) the processes of interest. They can also be particularly useful to as what-if questions. For example to investigate the potential benefit of a new variety with a particular trait. These models can be used to refine our thinking before venturing into expensive breeding programs and field experiments. They are also used to estimate things that are hard to observe, such as crop yield potential and the effect of future climate change.

Currently we have one chapter in this section, explaining how to use the WOFOST model. But stay tuned for updates on LINTUL, APSIM, and other models.