About the Project
This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water quality following contamination events associated with Combined Sewer Overflows (CSOs). Such events present increasing risks to public health, ecosystems and urban water environments, particularly under pressures from climate change, urbanisation and ageing infrastructure. Although high-fidelity numerical models can simulate hydrodynamic and pollutant transport processes, their computational cost limits their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics-based modelling with data driven surrogate approaches.
The first stage of the project will involve the development of a multi-layer hydrodynamic model capable of representing key three-dimensional flow processes in riverine and estuarine systems. This model will be coupled with advection–diffusion–reaction equations to simulate pollutant transport, mixing and biochemical processes.
To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained using datasets generated by the high-fidelity numerical solver. The surrogate will emulate key hydrodynamic and water quality responses while providing robust uncertainty quantification to support reliable decision-making. Evolutionary algorithms will be employed to efficiently explore the parameter space and undertake sensitivity analyses.
The integrated framework will be validated using analytical test cases, laboratory experiments, and field measurements. It will then be applied to a real-world case study on the Ouseburn in Newcastle upon Tyne to demonstrate its capability for real time water quality forecasting and its ability to support decision-making aimed at protecting river users from health risks.
This 4 year PhD studentship provides a tax-free annual living allowance of ÂŁ25,726 plus a research training support grant of ÂŁ20,000 and 100% fees paid as part of the Water Infrastructure and Resilience CDT (WIRe) funded by EPSRC & Reece Foundation
Please apply here Postgraduate Funding Search | Newcastle University
Funding Notes
Home and international applicants (inc. EU) are welcome to apply and if successful will receive a full studentship. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills.
International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.
