About the Project
This project is one of a number in competition for a studentship from the Faculty of Engineering and Design at the University of Bath. If successful, this studentship is expected to commence 28 September 2026.
An alternative start date may be possible if agreed with your intended supervisors and the Doctoral College.
Project Background:
Urban communities worldwide are facing increasing risks of flooding, with devastating social, environmental, and economic impacts. These risks are being amplified by climate change, rapid urbanisation. In many cities, waterways are further compromised by debris and waste from human activity, which increases the likelihood of sudden blockages and localised flooding. Traditional flood warning systems typically rely on networks of in-river sensors and monitoring stations. These systems are expensive to install and maintain, which prevents widespread use and makes them inaccessible to many communities where the risks are most severe. There is an urgent need for affordable, scalable alternatives that can provide timely warnings and improve resilience, especially in developing countries.
Based on a successful pilot project using CCTV images for real-time monitoring of debris accumulation in urban rivers (Smith et al., 2025) this project will explore a novel solution: combining low-cost camera technologies with machine learning and computer vision to create real-time flood monitoring systems. By “watching” rivers and streams, the system will automatically detect rising water levels and debris blockages in surveillance images. These observations will be combined with rainfall forecasts and open-source hydraulic modelling systems to generate early-warning signals, offering a powerful and inexpensive tool for flood risk management. The project will initially focus on a case study in the UK, with possible additional testing in selected international locations to assess transferability to diverse urban environments to test scalability.
The student will be given freedom to steer the project towards their main interest, but topics may include statistical analysis of extreme hydro-meteorological events, both historical and forecasts, and development of machine-learning based computer vision algorithms applicable to urban flooding problems. The outcome of this project will be solutions that allows flood managers to better manage flood risk across urban areas using low-cost technologies.
Candidate requirements:
Applicants must have, or be about to obtain, a UK Honours degree 1st or 2.1, or international equivalent. A master’s level qualification would also be advantageous.
Non-UK applicants, who are not currently studying in the UK, must meet the programme’s English language requirement before the application deadline – no exceptions will be considered.
The project sits at the interface of civil engineering, computer science, and environmental management, making it an ideal challenge for a student motivated by interdisciplinary research. Interest and experience in hydrology, python programming, and image analysis will be an advantage.
Enquiries:
Informal enquiries are encouraged! Direct these to Dr Thomas Kjeldsen
Application Instructions
Please follow the below instructions carefully.
You must make a formal application via the University of Bath’s online application form for a PhD in Civil Engineering
Please note that you can apply for a maximum of two PhD projects on this programme.
In the ‘Funding Your Studies’ section, you must select ‘University of Bath URSA’ from one of the drop-down menus.
In the ‘Your PhD project’ section, you must quote the project title in the PhD project title field, and you must quote the lead supervisor’s name in the field ‘Name of intended supervisor at University of Bath.’
If you are applying for two projects, you must quote the project title for your second choice project in the field ‘Project 2 Title’ and the lead supervisor’s name in ‘Name of intended supervisor for 2nd choice project at University of Bath.
You must ensure that you follow the above steps correctly. Failure to complete these steps will cause errors in the automated processing of your application and may mean that you are not considered for a particular project.
Equality, Diversity and Inclusion
We value a diverse research environment and strive to be an inclusive university, where difference is celebrated and respected. We encourage applications from under-represented groups.
If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.
The Disability Service ensures that individuals with disabilities are provided the support that they need. If you state if your application that you have a disability, the Disability Service will contact you as part of this process to discuss your needs.
Keywords
Urban flooding, Extreme rainfall, Machine learning, AI, Image analysis, Forecasting
Funding Notes
Applicants will be considered for a studentship. The Faculty of Engineering and Design at the University of Bath has studentships available for Home and Overseas students. However, in line with UKRI policy, the number of studentships available to Overseas students are capped. Studentships cover tuition fees, provide a £1k per annum training support fee, and a maintenance stipend (£20,780 2025/26 rate). International students will be required to cover the cost of a Student visa and Immigration Health Surcharge from personal funds.
References
Smith, R.C., Barnes, A.P., Wang, J., Dooley, S., Rowlatt, C. and Kjeldsen, T.R., 2025. CCTV image‐based classification of blocked trash screens. Journal of Flood Risk Management, 18(1), p.e13038.
