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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Introduction to Environmental Modelling (PGGE11250)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryComputer based models are widely used in many areas of science, especially in environmental sciences. The emphasis of this course will be on the application and development of models in the context of ecosystem and environmental management. The concepts of model development, model calibration, uncertainty analysis and validation will be introduced through lectures and practical classes. The strengths and weaknesses of different modelling approaches will be examined. The course is designed for students with relatively little mathematical experience and it is an ideal opportunity to develop those skills required to apply computer models to complex environmental systems.
Course description This course is designed to enable students to critically assess and apply alternative modelling approaches for given systems, with a focus on environmental and ecosystem management. After lectures on the basics of modelling, the course will be practical focussed, typically with a short introductory lecture followed by modelling exercises. A range of examples will be utilised (but including some repeat scenarios for implementation in different approaches). The final sessions introduce a range of topics, and will allow students to explore the different approaches as appropriate.

1) Introduction to modelling 1
2) Introduction to modelling 2 and intro to OpenRefine for data management (practical)
3) Modelling (simple risk models) and data summary using Excel (practical)
4) Modelling using OpenModel 1 (practical)
5) Modelling using OpenModel 2 (uncertainty analysis) (practical)
6) Modelling using Simile (practical)
7) Monte Carlo simulation and modelling for Carbon auditing (practical)
8) Social network modelling using R (practical)
9) Case studies- spatial modelling (practical)
10) Case studies- predator-prey modelling (practical)
11) Case studies- pollution modelling (practical)
Please note that in light of possible COVID issues, the above topics are subject to change. Although the course can be run completely remotely, if possible we will have additional on-campus classes (repeated online).
One of the aims of the course is to expose students to a variety of software tools (so students can judge how different tools may be better or worse in different situations, or can find out what tools they prefer to use). The teaching materials and practical sessions will use the following software:
¿ Excel
¿ OpenModel ( free for PC, if you have a Mac you will need Bootcamp ( to install
¿ Simile ( free for PC, Mac and Linux
¿ R/R Studio ( free for PC, Mac, Ubuntu etc
¿ OpenRefine ( free for PC, Mac and Linux
¿ HEC-RAS ( PC only (but as we use this software as a practical example of parameterising existing software to build a model, and not model building from scratch, this is the least essential download. I am working to get the class access to this software through SRUC virtual desktop though)

Although teaching will focus on the above tools (primarily OpenModel and Simile), students are free to use any of the software as appropriate for their assessments if they wish (including software not included here, such as MatLab, or programming in Python etc).

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed:
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2024/25, Not available to visiting students (SS1) Quota:  0
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 44, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 152 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework, with the marks split as follows:

Data modelling exercise (15%)
Modelling uncertainty report (35%)
Case study report (50%)

Feedback Feedback will be provided that enables students to apply as relevant to other assessments in this course. In addition, generic feedback on core academic skills (writing, critical appraisal) will be given that can be applied more widely.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. understand the role and nature of modelling environmental systems
  2. understand the basic principles of model building using both empirical and mechanistic modelling approaches
  3. have a clearer understanding of the challenges and decisions associated with model implementation and validation of model outputs
  4. have an awareness of the strengths and limitations of different types of model
Reading List
Additional Information
Course URL
Graduate Attributes and Skills - General data analysis and information technology
- Organisation skills to plan, execute and report on scientific investigations
- To participate in individual and team activities towards the completion of a set of objectives
- Critical thinking necessary for the evaluation of information
KeywordsEnvironmental Modelling
Course organiserDr Alistair Hamilton
Tel: 0131 535 4417
Course secretaryMs Jennifer Gumbrell
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