ENN575 Artificial Intelligence in Water Modelling
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | ENN575 |
|---|---|
| Prerequisite(s): | Admission to (EV51 OR EN51 OR EN56 OR EN65 OR EN71 OR EN75 OR EN80) |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,192 |
| Domestic tuition unit fee | $4,368 |
| International unit fee | $6,216 |
Unit Outline: Semester 2 2026, Gardens Point, Internal
| Unit code: | ENN575 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | Admission to (EV51 OR EN51 OR EN56 OR EN65 OR EN71 OR EN75 OR EN80) |
| Coordinator: | Maziar Gholami Korzani | m.korzani@qut.edu.au |
Overview
The goal of modelling water systems (flood and water quality) is to understand their behaviour and predict future changes, investigate their environmental and socio-economic impacts, and support policy development in the water sector. Recent advancements in AI and technology provide new avenues to smartly achieve the above-mentioned goals. This unit will introduce you to fundamentals of AI and how AI enables the future of flood and water quality prediction. You will also grow your skills in techniques for advanced flood and water quality data analytics that can be applied to develop predictive models for water systems in line with contemporary engineering practice.
Learning Outcomes
On successful completion of this unit you will be able to:
- Apply advanced knowledge on artificial intelligence (AI) to solve complex water engineering problems
- Implement AI algorithms using appropriate tools and libraries
- Apply systematic approaches to manage water infrastructures using AI based solutions
- Communicate complex AI based water modelling to diverse audiences in oral and written forms
Content
This unit introduces students to artificial intelligence (AI) and machine learning (ML) through a strongly applied, Python-based curriculum. The content progresses from foundational skills to advanced AI applications relevant to water engineering and environmental systems.
Key Content Areas
- Programming Foundations
- Python fundamentals for data-driven applications
- Data analysis and visualisation using scientific Python libraries
- Core Artificial Intelligence Concepts
- Overview of AI, ML, and deep learning
- Problem formulation and data-driven modelling approaches
- Applied Geospatial Analysis
- Building and road footprint mapping
- Handling and analysing spatial datasets using Python
- Classical Machine Learning
- Supervised and unsupervised learning techniques
- Feature selection, model training, and performance evaluation
- Neural Networks and Deep Learning
- Fundamentals of artificial neural networks
- Multi-layer networks, training strategies, and optimisation
- Use of Generative AI to support neural network code development
- Computer Vision
- Image representation and basic image processing
- Introduction to computer vision techniques for real-world applications
- Ethics and Responsible AI
- Ethical issues in AI and ML, including bias, fairness, and transparency
- Responsible use of AI in engineering and environmental contexts
Learning Approaches
In this unit you can expect to experience the following activities:
- Videos explaining key concepts, released at the beginning of each week
- 2 hour lecture, where you can engage with experienced engineers in working though problem sets, applying the concepts learned in the videos
- 1 to 2 hour of tutorials/workshops where you will be guided through applied design and data analytics problems, working with experienced engineers and your peers to deepen your skills
- Follow up formative quizzes, readings and online discussions to help you review your learning for the week and clarify any areas of misunderstanding
Feedback on Learning and Assessment
Feedback in this unit will be provided in the following ways:
- Formative oral feedback will be offered by the lecturer and tutors during the semester to assist you in the development of your skills.
- Formative written feedback through criteria sheet grading.
- In addition to CRA (criteria sheet), comments on summative assessment will be provided.
- Generic comments will be provided to the cohort through the Canvas.
Assessment
Overview
Assessment items in this unit have been designed to give you the opportunity to show your learning against the unit learning outcomes. You will work individually to present a complex research article in the context of AI. You will work as a member of an effective group to prepare and submit an applied design project report and a presentation, addressing a complex problem in water modelling using AI.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Buildings and roads footprints mapping
This assignment requires you to apply AI techniques to map building and road footprints within a selected catchment. Students will use real-world DEM and spatial data to generate footprint maps and compare them with satellite imagery to assess spatial accuracy.
The task includes catchment selection, data collection, footprint mapping, and basic land cover analysis. Students submit a concise technical report with mapped outputs, brief analysis, and well-documented code, demonstrating practical application of AI in geospatial analysis.
- This assignment is eligible for the 48-hour late submission period and assignment extensions.
- The ethical and responsible use of generative artificial intelligence (GenAI) tools is authorised in this assessment. See the relevant assessment details in Canvas for specific guidelines.
Assessment: AI Paper Presentation
In this assessment, students select and present a peer-reviewed journal paper that applies machine learning, deep learning, or computer vision to water engineering and modelling. The task focuses on critically analysing state-of-the-art AI methods and clearly communicating their methodology, performance, and relevance.
- This is a verified identity assessment where students will complete and submit their work in class.
- The use of generative artificial intelligence (GenAI) tools is prohibited in this assessment.
- Attendance is compulsory in this assessment. In case of non-attendance, zero marks will be awarded for this assessment. If the attendance is missed due to unforeseen personal circumstances, you can apply for special consideration with the required documentation.
Assessment: Streamflow Forecast Project
The Streamflow Forecast Project consists of a group report and an individual oral presentation. In groups, students develop an artificial neural network (ANN) to predict daily streamflow from rainfall data using time series modelling, building on classical machine learning, neural networks, and Generative AI (GenAI). The group report presents the modelling approach, results, and evaluation under dry and wet conditions.
Following the group submission, each student delivers an individual presentation demonstrating their understanding of the project and reflecting on their code by comparing it with a provided benchmark solution. This assessment develops practical AI modelling skills, critical evaluation, and the ability to clearly communicate and reflect on technical work.
- The group report component is eligible for the 48-hour late submission period and assignment extensions.
- The ethical and responsible use of generative artificial intelligence (GenAI) tools is authorised in this assessment. See the relevant assessment details in Canvas for specific guidelines.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no required text book. Contents from latest publications in top-tier water journals will be used and referenced during the lectures.
Risk Assessment Statement
You will undertake lectures and tutorials in the traditional classrooms and lecture theatres. As such, there are no extraordinary workplace health and safety issues associated with these components of the unit.
You will be required to undertake practical sessions in the laboratory under the supervision of the lecturer and technical staff of the School. In any laboratory practicals you will be advised of the requirements of safe and responsible behaviour and will be required to wear appropriate protective items (e.g. closed shoes).
You will undergo a health and safety induction before the commencement of the practical sessions and will be issued with a safety induction card. If you do not have a safety induction card you will be denied access to laboratories.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN51 Master of Sustainable Infrastructure
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices as they relate to contemporary practice in Sustainable Infrastructure
Relates to: Buildings and roads footprints mapping - Analyse and evaluate Sustainable Infrastructure problems using technical approaches informed by contemporary practice and leading edge research to achieve innovative, critically informed solutions
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage projects in Sustainable Infrastructure in a way that assures sustainable outcomes over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate Sustainable Infrastructure problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability and reflective practice when working in individual and collaborative modes
Relates to: AI Paper Presentation
EN56 Master of Engineering Technology
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices as they relate to contemporary practice in Engineering Technology
Relates to: Buildings and roads footprints mapping - Analyse and evaluate Engineering Technology problems using technical approaches informed by contemporary practice and leading edge research to achieve innovative, critically informed solutions
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage projects in Engineering Technology in a way that assures sustainable outcomes over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate Engineering Technology problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability and reflective practice when working in individual and collaborative modes
Relates to: AI Paper Presentation
EN65 Graduate Certificate in Water Modelling
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices as they relate to contemporary practice in Water Modelling
Relates to: Buildings and roads footprints mapping, AI Paper Presentation - Analyse and evaluate Water Modelling problems using technical approaches informed by contemporary practice to achieve innovative, critically informed solutions
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage projects in Water Modelling in a way that assures sustainable outcomes over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate Water Modelling problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability and reflective practice when working in individual and collaborative modes
Relates to: AI Paper Presentation
EN71 Master of Sustainable Infrastructure with Project Management
- Demonstrate and apply advanced and specialist discipline knowledge, concepts, methods and practices as they relate to contemporary practice in Sustainable Infrastructure and Project Management domains
Relates to: Buildings and roads footprints mapping - Analyse and evaluate problems in Sustainable Infrastructure and Project Management domains using technical approaches informed by contemporary practice and leading-edge research to achieve evidence based, innovative, critically informed solutions and outcomes
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage projects in Sustainable Infrastructure and Project Management domains in a way that assures sustainable outcomes and strategic objectives over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate problems in Sustainable Infrastructure and Project Management domains, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability, reflective practice, risk-informed judgements, and leadership
Relates to: AI Paper Presentation
EN75 Master of Sustainable Infrastructure with Data Analytics
- Demonstrate and apply advanced and specialist discipline knowledge, concepts, methods and practices as they relate to contemporary practice in Sustainable Infrastructure and Data Analytics domains
Relates to: Buildings and roads footprints mapping - Analyse and evaluate problems in Sustainable Infrastructure and Data Analytics domains using technical approaches informed by contemporary practice and leading-edge research to achieve evidence based, innovative, critically informed solutions and outcomes
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage projects in Sustainable Infrastructure and Data Analytics domains in a way that assures sustainable outcomes and strategic objectives over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate problems in Sustainable Infrastructure and Data Analytics domains, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability, reflective practice, risk-informed judgements, and leadership
Relates to: AI Paper Presentation
EN79 Graduate Diploma in Engineering Studies
- Demonstrate and apply advanced discipline knowledge, concepts and practices as they relate to contemporary Engineering practice
Relates to: Buildings and roads footprints mapping - Analyse and evaluate Engineering problems using technical approaches informed by contemporary practice and leading edge research to achieve innovative, critically informed solutions
Relates to: Buildings and roads footprints mapping - Apply innovative, systematic approaches to plan, design, deliver and manage Engineering projects in a way that assures sustainable outcomes over their whole lifecycle
Relates to: AI Paper Presentation - Effectively communicate Engineering problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: AI Paper Presentation - Demonstrate ethically and socially responsible practice, recognising the importance of personal accountability and reflective practice when working in individual and collaborative modes
Relates to: AI Paper Presentation