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Environmental Modelling (EVSC90020)
Graduate courseworkPoints: 12.5Online
Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 - Online |
---|---|
Fees | Look up fees |
Modelling is a fundamental component of Environmental Science, being used for prediction, monitoring, auditing, evaluation, and assessment. This subject introduces students to a wide range of models used by environmental scientists including models of climate change, population dynamics, pollution, hydrology, habitat and species distributions. Both deterministic and stochastic models are used as examples. The subject explains how to develop conceptual models that can then be quantified and analysed using mathematical and statistical methods. Topics covered include development of the basic model structure, estimation of parameters and calibration, methods of analysis, sensitivity analysis, model evaluation and model refinement. The subject teaches students how to simplify apparently complex problems.
Intended learning outcomes
The subject aims to provide students with the ability to:
- Articulate the role of modelling in environmental science;
- Describe and evaluate a range of environmental models in use and choose an appropriate modelling framework for a particular environmental problem; and
- Analyse models of environmental systems and processes.
Generic skills
Generic skills gained from this subject include:
- Synthesis of information from a range of sources;
- Appropriate simplification of complex problems to make them amenable to analysis;
- High level written communication and presentation skills;
- High level oral communication and presentation skills;
- The ability to exercise critical judgement, think rigorously and independently, account for decisions, and solve problems; and
- Application of advanced analytical methods.
Last updated: 31 October 2023
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST90044 | Thinking and Reasoning with Data | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
OR
600-615 Thinking and Reasoning with Data or equivalent statistical subject
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 October 2023
Assessment
Description | Timing | Percentage |
---|---|---|
Report on a practical exercise
| Week 3-5 | 15% |
Report on a case study model
| Week 6 | 30% |
Oral presentation on case study model
| From Week 8 to Week 12 | 10% |
Take home written exam
| During the examination period | 45% |
Last updated: 31 October 2023
Dates & times
- Semester 1 - Online
Coordinator Michael McCarthy Mode of delivery Online Contact hours 2 x 1-hour lectures each week and 6 x 3-hour practical (computer laboratory) classes (42 hours in total) Total time commitment 170 hours Teaching period 1 March 2021 to 30 May 2021 Last self-enrol date 12 March 2021 Census date 31 March 2021 Last date to withdraw without fail 7 May 2021 Assessment period ends 25 June 2021 Semester 1 contact information
Time commitment details
170 hours
Last updated: 31 October 2023
Further information
- Texts
Prescribed texts
Recommended texts and other resources
Environmental Modelling: Finding Simplicity in Complexity (Wainwright and Mulligan)
Bayesian Methods for Ecology (McCarthy)
- Related Handbook entries
This subject contributes to the following:
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 October 2023