- Code MATH6102
- Unit Value 6 units
Offered in association with Fenner School.
In this course the major model types used to represent environmental systems are studied. Mathematical emphasis on how they are constructed will use the theory of inverse problems while the practical emphasis uses systems methodology. The focus will be on hydrological systems and their basic processes, combined with the constraints imposed by the limitations of real observational data.
It will be assumed that students have a reasonable grasp of different model types (time series, PDE/ODE-based models, frequency domain models) as well as understanding of the issue of uncertainty in model inputs, structure and observed outputs.
The assessment of the course will be based on written reports on selected papers, as well as a project exploring a particular paper/model in more detail. The key component of the project will be proposing potential improvements in the work done, and doing at least some initial work on evaluating these improvements. This will include components of:
analytical evaluation of model behaviour
coding the original and improved versions of the model and conducting sensitivity analysis
exploration of structure of uncertainty in model inputs.
Propagating uncertainty in inputs through the model
Note: Graduate students attend joint classes with undergraduates but are assessed separately.
Upon successful completion, students will have the knowledge and skills to:
On satisfying the requirements of this course, students will have the knowledge and skills to:
Describe the basic processes and behaviour of different environmental systems and the major methods of modelling these (e.g. model family selection, model structure identification, parameter estimation, sensitivity assessment, optimisation).
Be able to apply the concept of tradeoffs and uncertainty sources in decision-making and optimisation through critical evaluation of case studies referring to hydrology, ecology, water quality and socioeconomics.
Evaluate the issues in building and evaluating models; formulate treatment of complex real-world problems (not just environmental problems); and select appropriate frameworks and methods to solve these, including using computer platforms and the statistical R package.
Communicate and engage with interest groups involved in a problem; and appreciate how integrated assessment can be used for managing our environment more sustainably, and the valuable role played by modelling.
Build a model of a system, drawing on an existing understanding of the typical behaviour of the system and available data.
Be able to critically evaluate the limitations of a model, and identify and conduct research that will enable improvements in the model.
Assessment will be based on:
• Five reviews of selected papers (50%; LO 1, 2)
• Two presentations (10%; LO 3, 4)
• Project (40%; LO 5 and 6)
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36 lectures and regular tutorials
Requisite and Incompatibility
You will need to contact the Mathematical Sciences Institute to request a permission code to enrol in this course.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings, Dates and Class Summary Links
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|10080||24 Jul 2017||31 Jul 2017||31 Aug 2017||27 Oct 2017||In Person||N/A|