1. Handbook
  2. Subjects
  3. Quantitative Environmental Modelling

Quantitative Environmental Modelling (ENEN90031)

Graduate courseworkPoints: 12.5On Campus (Parkville)

You’re viewing the 2017 Handbook:
Or view archived Handbooks
You’re currently viewing the 2017 version of this subject


Year of offer2017
Subject levelGraduate coursework
Subject codeENEN90031
Semester 1
FeesSubject EFTSL, Level, Discipline & Census Date


Environmental problems are highly complex and challenging to analyse and are often addressed through modelling. Being skilled at environmental modelling is a core professional requirement for an Environmental Engineer. This subject focuses on environmental modelling methodology including the steps of model conceptualisation, model construction, model evaluation and model application using a range of energy, water and waste models in Matlab. The subject complements ENEN90032 Environmental Analysis Tools and ENEN90028 Monitoring Environmental Impacts which provide other core environmental engineering skills. It provides modelling skills for a wide range of discipline based subjects such as ENEN90006 Solid Wastes, ENEN90034 Environmental Applied Hydrology and ENEN90027 Energy for Sustainable Development. The subject is of particular relevance to all Environmental Engineers but is also of relevance to a range of engineering and environmental analysis disciplines that require advanced modelling skills.


The relationship between theoretical and empirical understanding and their use in model conceptualisation and construction will be explored. This subject introduces a range of environmental modelling techniques applicable to different environmental problems. In this subject students will conceptualise and construct, evaluate and utilise their own model to undertake a technical evaluation of a specified range of potential solutions to an environmental problem. Students will also develop professional judgement skills to critically evaluate models and model results.

Specific topic areas:

  • System conceptualisation
  • Model construction and validation (computational accuracy)
  • Model evaluation
  • Calibration and optimisation
  • Model uncertainty assessment techniques
  • Issues of appropriate model complexity
  • Students will have an opportunity to review a modelling topic of their choice.

Students will use MatLab to undertake modelling tasks and will be required to learn some MatLab programming skills in the subject.

Intended learning outcomes


On completion of this subject the sstudent expected to:

  1. Select an appropriate approach to quantitative modelling of problems, given existing knowledge and data
  2. Develop a conceptual model designed to investigate and solve engineering problems
  3. Apply, calibrate and evaluate a quantitative model of the problem using generic modelling software in a MATLAB programming environment
  4. Apply models to investigate problems and synthesise recommendations based on the modelling
  5. Write and present engineering reports of modelling studies.

Generic skills

  • Ability to undertake problem identification, formulation, and solution
  • Ability to utilise a systems approach to complex problems and to design and operational performance
  • Capacity for lifelong learning and professional development.

Last updated: 22 August 2019