Learn more about The Art of Modelling in this Wageningen Summer School for PhD candidates and other academics.
Registration closed, course started.
Modelling is a crucial part of today's science. Particularly in agronomy, ecology and environmental sciences, where models are used for assessing sensitivity of systems to disturbances or changes in external factors, and for predictions of future system states. This course provides an introduction to modelling.
In the course modelling concepts will be dealt with in detail, going through the basic steps to be taken.
The main themes of this course are:
- Modelling concepts
- Model design
- Model use
- Calibration and validation
- Sensitivity and uncertainty
- Linearity and complexity
- Reporting on model studies
What you will learn
Upon successful completion of this course, participants are expected to be able to:
- Understand and evaluate scientific literature where models are used;
- Choose appropriate modelling methods for their own research;
- Plan and report on a modelling study in their own research;
- Follow advanced modelling courses.
Meet the lecturers
The main part of the course focuses on systems analysis using dynamic simulation models. Systems approaches are widely used in studies of ecological systems for the purpose of increasing our understanding of ecosystems functioning and improving systems management. This course introduces the participants to the study of the behaviour of ecological systems.
The course comprises four blocks:
- Systems dynamics with examples from crop production & population ecology
- Partial differential equations & modelling in space
- Model performance & model evaluation
- Reflection & reporting
The course comprises a) lectures, b) practicals in which exercises are solved using paper and pencil and by means of a computer, c) application of the subject matter in case studies elaborated in small groups, d) reflection on own study and model(s) using the concepts and applications used, and e) presentations of how modelling is used in the participants' own work.
No previous PE&RC postgraduate courses are required. However, basic knowledge of mathematics (in particular basic algebra, vector and matrix algebra, differentiation, integration and differential equations) is required.