Project details
Project Rationale
Flooding – the most wide-spread natural hazard – affects every country and region of the world. Flood risk is expected to increase due to climate change, as evidenced by recent recurring UK summer and winter floods.
The UK climate projections (UKCP18) suggest a >10% increase in heavy rainfall by 2050, with much of this “very likely” to fall in a short period of time [1], causing more severe surface water flooding. This type of flooding threatens more UK people and properties than any other; 3.2 million properties in England alone.
Reliable forecasting and early warning can improve preparations, response and recovery, but rapid onset and localised extent make observing and predicting surface water flooding from intense rainfall technically challenging, and our ability to provide reliable, detailed forecasts remains limited [2].
We recently made a significant contribution by developing a new high-performance hydrodynamic system to forecast surface water flooding across an entire catchment at unprecedented resolution [3].
But the latest developments in AI and data analytics technologies have not yet sufficiently exploited to advance operational surface water flood forecasting; uncertainties in different components a forecasting system, e.g. numerical weather predictions and flood dynamics modelling, need to be better understood, quantified and minimised.
Methodology
The aim of this exciting PhD project is to harness the latest developments in high-performance computing and deep learning (DL) technologies to address some of the key technical challenges, and finally demonstrate a DL-enabled system for mapping, risk assessment and real-time forecasting of surface water flooding from intense rainfall. The project will deliver the following key research tasks:
- Develop physis-informed DL models to integrate rainfall observations from different sources and identify conditions associated with very extreme rainfall from the outputs of convection-permitting numerical weather models, and then emulate such numerical weather predictions to create reliable real time forecasts or large ensembles.
- Integrate the improved weather forecasts with the Loughborough in-house High-Performance Integrated hydrodynamic Modelling System (HiPIMS) to forecast in real time the surface water flooding process at a meter-level resolution for assessing flood impact/risk on individual buildings/objects. HiPIMS will be ML-enabled to support rapid ensemble forecasting.
- Design and perform systematic numerical experiments to better understand and quantify the uncertainties in different steps, their interaction and propagation through the entire flood forecasting procedure, and interpret their implication on the final flood forecasting and risk products.
- Demonstrate the system for real-time flood mapping, risk assessment and probability forecasting in a selected case study site.
Supervisors
Primary Supervisor: Professor Qiuhua Liang
Secondary supervisor: Jinghua Jiang
Entry requirements
Our entry requirements are listed using standard UK undergraduate degree classifications i.e. first-class honours, upper second-class honours and lower second-class honours. To learn the equivalent for your country, please choose it from the drop-down below.
Entry requirements for United Kingdom
Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in a relevant subject such as geography, economics, or engineering. A relevant master’s degree and/or experience is desirable.
EU and Overseas applicants should achieve an IELTS score of 6.5 with at least 6.0 in each competency.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Fees and funding
Tuition fees for 2024-25 entry
UK fee
Fully funded Full-time degree per annum
International fee
£27,500 Full-time degree per annum
Tuition fees for 2025-26 entry
UK fee
Fully funded Full-time degree per annum
International fee
£28,600 Full-time degree per annum
Fees for the 2024-25 academic year apply to projects starting in October 2024, January 2025, April 2025 and July 2025.Fees for the 2025-26 academic year apply to projects starting in October 2025.
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.
Additional information
Studentship type – UKRI through Flood-CDT.
The studentship is for 3.5 years and provides a tax-free stipend of £19,237 per annum plus tuition fees at the UK rate. Excellent International candidates are eligible for a full international fee waiver however due to UKRI funding rules, no more than 30% of the studentships funded by this grant can be awarded to International candidates.
How to apply
All applications should be made online.
Under programme name, select Architecture, Building and Civil Engineering. Please quote the advertised reference number: FCDT-25-LU7 in your application.
This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be found here. Please note, that your application will be assessed upon:
- Motivation and Career Aspirations;
- Potential & Intellectual Excellence;
- Suitability for specific project and
- Fit to FLOOD-CDT.
So please familiarise yourselves with FLOOD-CDT before applying. During the application process candidates will need to upload:
- a one-page statement of your research interests in flooding and FLOOD-CDT and your rationale for your choice of project
- a curriculum vitae giving details of your academic record and stating your research interests
- academic transcripts and degree certificates (translated if not in English)
- a IELTS/TOEFL certificate, if applicable.
You are encouraged to contact potential supervisors by email to discuss project specific aspects of the proposed prior to submitting your application. If you have any general questions, please contact floodcdt@soton.ac.uk.
