ABSTRACT
With crop development models there exists a hierarchy of approaches, which operate at varying levels of complexity, both in terms how component processes are addressed and in the way these processes are represented mathematically and within software products. The complexity of a model is partly determined by the nature of the issue that motivated model development, and partly by the data available to run the model. Nevertheless, crop simulation models generally simulate the changing state of a crop-soil system given initial system conditions, management interventions to the system, and values for the environmental variables that drive the system. Timesteps for data input and output are generally daily, although shorter durations are sometimes used for component processes. While crop yield is a primary output of such models, changes in other state variables, such as soil water or fertility status, are also often of interest. There are a number of reviews of crop simulation models and their make-up (e.g., Ref.[1]).
