Course Title: Resource Modelling
Part A: Course Overview
Course Title: Resource Modelling
Credit Points: 12.00
145H Mathematical & Geospatial Sciences
|Sem 2 2006,
Sem 2 2007,
Sem 2 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011,
Sem 2 2012,
Sem 2 2014,
Sem 2 2015
Course Coordinator: Lynne McArthur
Course Coordinator Phone: +61 3 9925 3122
Course Coordinator Email: email@example.com
Course Coordinator Location: 8.9.39
Pre-requisite Courses and Assumed Knowledge and Capabilities
You will be expected to have achieved a pass in
- Calculus 1
- Calculus 2
This course will explore the concepts, theory and key issues underpinning sustainable development and resource management, including the practical application of advanced geospatial technologies to address nationally and internationally significant resource management problems. The focus of this subject is the biophysical dimensions of resource management.
Natural Resource Modelling comprises two basic components: Ecosystem Modelling and Water Resource Management. The first component includes the study of population models as applied to wildlife, fisheries and natural resources. The second component includes the study of hydrological systems in terms of streamflow modelling, water consumption, operational flood forecasting and linear and non-linear programming.
Objectives/Learning Outcomes/Capability Development
You will gain an enhanced appreciation and understanding of key human-environment linkages and the implications of these linkages for natural resource management, with emphasis on the Australian situation.
When you have completed this course, you will be able to:
- Distinguish between empirical, conceptual and physically based models.
- Apply spatial modelling to physical systems.
- Use data-handling techniques for a wide range of hydrological, climatic and socio-economic data.
- Use data sources typically used in Australia’s resource management.
- Construct mathematically valid models to describe how populations and systems behave.
- Use the models to assess population and system dynamics.
- Use the models to predict outcomes under given scenarios.
- Apply appropriate validation techniques to the models.
- Apply techniques of time series analysis for prediction.
- Understand the concept of risk management .
- Understand the principles of team work.
- Produce a group report.
- Produce a written report.
- Communicate ideas to other group members.
- Present outcomes of research to class.
- Present results of analyses with all caveats declared.
- Access data banks managed by the federal and state wide resource management authorities.
- Access international journal data bases and retrieve relevant material.
This course contributes to the development of the following Program Learning Outcomes:
Personal and professional awareness
- The ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
- The ability to reflect on experience and improve your own future practice
- The ability to apply the principles of lifelong learning to any new challenge.
Knowledge and technical competence
- The ability to use the appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.
- The ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
- An understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.
Teamwork and project management
- The ability to contribute to professional work settings through effective participation in teams and organisation of project tasks
- The ability to constructively engage with other team members and resolve conflict.
- The ability to communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral) and to tailor the style and means of communication to different audiences. Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.
- The ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.
Overview of Learning Activities
During this course you will attend lectures where the underlying theory will be presented. You will also participate in scheduled labs and or practice classes.
Overview of Learning Resources
Teaching staff will supply printed notes where appropriate.
Overview of Assessment
You will be assessed on individual and group project work, assignments and exams.