Dynamic system models are now widely used in agronomic research and extension. These models consist of differential or difference equations that represent the dynamics of the different components of the system (soil, plant, pathogens, etc). One then solves the equations on a computer to simulate the dynamics of the real system. Such models can thus be used to explore the effects that changes in the environment or in management would have on the system that is modelled. They are used in impact assessment, in evaluating innovative management practices, as decision aids, as diagnostic tools or to aid in planning experiments.
Developing such models and interpreting the results requires detailed domain knowledge concerning the behaviour of the real system. However, this domain knowledge is in general not sufficient. There are also mathematical, statistical and computer considerations which are equally important, but are seldom considered by agricultural modelers. This has led to difficulties in working with such models: modellers are usually researchers in the area being modelled, and they often lack expertise in the methods for working with models. The purpose of this course is to provide agronomic researchers the information and tools that are necessary to work effectively with dynamic models.
Current PhD students and established agronomic researchers who are interested in applications of agricultural models in their research programs should apply. The course will include lectures, demonstrations of models and software for working with the models as well as hands-on practical exercises. Participants will learn how to estimate parameters for dynamic agricultural models, how to evaluate them, and how to conduct sensitivity and uncertainty analyses using modern techniques. Substantial time will be devoted to exercises. At the end of the course, the students should be able to apply the methods on their own.
The material will be based on the text book, “Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization and Applications”
Edited by D. Wallach, D. Makowski, and J. W. Jones.