This is an Honours Pathway Course. It emphasises a sophisticated and critical analysis of environmental models and offered in association with Fenner School.

Focus of the course will be on critical assessment of models used in published papers and one or more models will be coded and analysed to document their performance, limitations and potential improvements. This will include:

• critical reviewing of papers
• analytical exploration of the models described in the papers
• coding models used in the papers and testing against actual or synthetic data
• developing potentially improved model structures

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.

Note: This course will have shared lectures with MATH6102 but will have different tutorials and assessment which will emphasise a more sophisticated approach to the evaluation of the models.

On satisfying the requirements of this course, students will have the knowledge and skills to:

1. Describe the basic processes and behaviours of different environmental systems and the major methods of modelling these (e.g. model family selection, model structure identification, parameter estimation, sensitivity assessment, optimisation)
2. Appreciate 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
3. 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
4. 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
5. Build a model of a system, drawing on an existing understanding of the typical behaviour of the system and available data.
6. Be able to critically evaluate the limitations of a model, and identify potential 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)

36 lectures and regular tutorials

Prerequisite:  MATH3501

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.