Duration
15h Th, 15h Pr
Number of credits
| Master of Science (MSc) in Data Science | 3 crédits | |||
| Master of Science (MSc) in Data Science and Engineering | 3 crédits | |||
| Master in oceanography (120 ECTS) | 3 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
CHAPTER 1 Introduction
- What is a model?
- Why do we need models?
- Conceptual model
- Mathematical model formulation
- Formulation of ecological interactions
- Chemical reactions
- Inhibition
- Coupled model equations
- Impact of physical conditions
- Taonomy of spatial models
- Spatial boundary conditions
- Example: competitive interactions in a lattice model
- In situ measurement
- Literature-Derived parameters
- Calib_ters.43
- Initial conditions
- Analytical solutions of differential equations
- Numerical solution of differential equations
- Steady-state and stability analysis
- Dimensional homogeneity and consistency of units
- Conservation of energy and mass
- Testing the correctness of the model solution
- Testing the internal logic of the model
- Model verification
- Model validity
- Model sensitivity
- Example_74
- Example of the conservation principle: a mass budget of a marine bay
- Strategic versus tactic models
- Continuous and discrete time models
- Deterministic and stochastic models
- Density-biomass specific models
- Physiological - individual-based - population - ecosystem models
- Example: growth of a Daphnia individual
- Taxonomy of differential equations
- Solving difference equations
Learning outcomes of the learning unit
The main aim of this course is to learn how to conceptualize, parameterize and implement mathematical models of marine biogeochemical and ecological processes
Prerequisite knowledge and skills
None. The mathematics used will be quiet elementary
Planned learning activities and teaching methods
The half part of the time will be devoted to the implementation of very simple examples in order to get familliar with models implementation
Mode of delivery (face to face, distance learning, hybrid learning)
1.5 ECTS : theory
1.5 ECTS : Exercises
Recommended or required readings
Lecture notes (theory, exercices) are available via eCampus. Each lecture is podcasted to allow the student to revise the lecture at his own pace.
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions )
Written work / report
Additional information:
A written, in-person, examination will be organized in January. This exam will not require the use of a computer. It will involve questions on the theory, practicals and homework.
A homework is due for January 7th at midnight. Description of the homework will be given during the lecture and will be made available via eCampus. Students will have to develop, implement and analyze a simple biogeochemical model to solve an environmental problem. This homework has to be realized by group of 3-4 students. A written report of ~10 pages describing the results and answering a list of questions has to be provided as well as the Rmd file describing the model code. Questions on the homework will be part of the written exam.
For those who failed in January, a second session exam will be planned in August/September. This second session exam will be similar to that organized in January.
All the exams are exclusevely in person.
Work placement(s)
Organisational remarks and main changes to the course
None
Contacts
Prof. Marilaure Grégoire,
MAST research group
Department of Astrophysics, Geophysics and Oceanography (AGO)
e-mail : mgregoire@uliege.be