· Identify and characterize a model and understand the mathematics of a process-based model;
· Translate a physical, environmental and/or spatial process into mathematical language;
· Grasp all steps of a modelling process, from the statement of a question to the validation of results;
· Start engaging with professionals of environmental modelling and management in various settings.
Contribution to the acquisition and evaluation of the following learning outcomes of the programme in geography (general and climatology):
· AA 1.1, AA 1.2, AA 1.4, AA 1.6, and particularly AA.1.7 and AA 1.8
· AA 3.3, AA 3.4
· AA 4.1, AA 4.2
· AA 5.5
· AA 6.1, 6.2
Most importantly, these learning outcomes are central to this course:
· AA 4.3, AA 4.4, AA 4.5
The following topics are dealt with:
· How to model? The various steps of modelling;
· Typology of models;
· Differential models: linear ordinary differential problems (e.g. first order decay);
· Differential models: non-linear ordinary differential problems (e.g. population modelling, prey-predator populations, epidemiological model);
· Differential models: space-time dependency;
· Spatial models: making space explicit, self-organising systems (e.g. epidemic diffusion, erosion processes);
· Spatial models: interacting, spatially-explicit objects: agent-based models (e.g. land use change)
How to model? Model validation.
Due to the COVID-19 crisis, the information in this section is particularly likely to change.Classroom lectures and practical sessions, involving active learning methods.
All lectures are in English. The course material and practical notes are in English and French.
Due to the COVID-19 crisis, the information in this section is particularly likely to change.Part 1 (differential models): 50%, continuous assessment of knowledge through homework assignments and a written exam
Part 2 (spatial models): 50%, written exam and 2 practical reports.