AI-assisted design of nature-based solutions for integrated flood and pollution management NERC DLA TREES STUDENTSHIP

Flood risk and water pollution are escalating challenges under climate change and rapid urbanisation. Conventional grey infrastructure provides limited flexibility and sustainability, while nature-based solutions (NbS)—such as wetlands, riparian buffers, and urban green corridors—offer multiple co-benefits by reducing flood hazards, improving water quality, and supporting biodiversity. Yet, designing NbS remains challenging due to diverse local conditions, competing objectives, and deep uncertainties.

This project will develop an AI-assisted framework for NbS design and evaluation, combining advanced predictive modelling with multi-objective optimisation. Methodological approaches include:

• Data integration of remote sensing, hydrological, water quality, and land-use datasets.
• AI-based modelling, leveraging LSTMs, Transformers, and graph neural networks to predict flood and pollution dynamics, coupled with process-based models such as SWAT and HEC-HMS.
• Multi-objective optimisation using evolutionary algorithms and reinforcement learning to balance flood risk reduction, pollution mitigation, and ecological co-benefits.
• Uncertainty quantification through Bayesian inference and factorial analysis to ensure robustness under future climate scenarios.

Potential research directions include scaling NbS design from local to basin levels, evaluating socio-economic trade-offs, and exploring adaptive pathways under climate change. The project will deliver a transferable decision-support tool for policymakers and planners, advancing AI applications in sustainability science and contributing to resilient, cost-effective solutions for water security.

As the PhD candidate, you will receive comprehensive training through Brunel’s Graduate School Research Development Programme (e.g., literature review, academic writing, presentation skills, statistics) and tailored one-to-one guidance from the supervisory team. Technical training will include advanced GIS, spatial data analytics, and decision-support tool development. Project-specific AI training will cover time-series forecasting (e.g., LSTM), deep learning (Transformers, GNNs), reinforcement learning, and evolutionary optimisation, delivered via workshops, coding sessions, and external platforms (e.g., LinkedIn Learning, Coursera). Additional professional development will be available through Brunel’s CIWEM-accredited CPD e-Learning courses on flood risk and resilience, ensuring broad expertise and transferable skills.

Eligibility

You must hold, or be expected to achieve, a first or high upper second-class undergraduate honours degree or equivalent (for example BA, BSc, MSci) or a Master's degree in a relevant subject (e.g. Biosciences, Analytical Science, Ecotoxicology etc). Prior experience in data analysis/visualisation, machine learning and/or analytical chemistry would be beneficial for this project. Candidates that have a relevant background in maths and/or data analytics that would like to develop biological knowledge, and analytical chemistry skills will also be suitable for this position. For further information on eligibility please refer to the TREES website.

How to apply

Enquiries email name and address:

TREES.Admissions@ucl.ac.uk

Application Web Page:

https://www.trees-dla.ac.uk/apply

Meet the Supervisor(s)

Yurui Fan - Led/participated in research projects supported by industrial, governmental, and international organizations (e.g. Royal Society, Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, Environment and Climate Change Canada, Saskatchewan Ministry of the Environment, Ontario Ministry of the Environment and Climate Change, Mitacs) Produced high-quality peer-reviewed papers published on Water Resources Research, Earth's Future, Hydrology and Earth System Sciences, Journal of Hydrology, Advances in Water Resources Areas of research interests include water and environmental systems analysis, hydroclimatic extremes, hydroinformatics, climate change impacts.
Abiy Kebede - Dr Kebede is a Senior Lecturer (Associate Professor) in Flood and Coastal Engineering and the PGR Director in the Department of Civil and Environmental Engineering (CEE), College of Engineering, Design and Physical Sciences (CEDPS) at Brunel University of London. He is also a founding member and Deputy Director of one of Brunel's interdisciplinary Research Centres, the Centre for Flood Risk and Resilience (CFR2). He also leads the Department's Flood, Coastal and Water Engineering (FCWE) Research Group. Prior to joining Brunel, Abiy worked as a Researcher at the University of Southampton, where he also completed his PhD and part of his MSc studies. His current research interests span from integrated assessment of the food-water-land-ecosystems nexus interactions and implications for sustainability and the Sustainable Development Goals (SDGs), to investigating the potential impacts of climate change, sea-level rise and climate extremes and risks of hydro-geo-meteorological hazards (e.g., flooding and coastal erosion), and quantifying the costs and benefits of engineered- and nature-based solutions to climate and environmental risks and sustainability challenges at different spatial (local to global) and temporal (short- to long-term) scales for informing robust climate adaptation and risk management policies. His work explores the following key research questions: What are the physical, socio-economic and environmental impacts of climate change, sea-level rise and climate extremes in coastal areas and river deltas? What are the long-term implications of historic coastal landfills on shoreline management and engineering solutions to coastal risks? What are the direct and indirect impacts and key uncertainties of future changes in climate and socio-economic conditions on the built and natural environment? How can we devise robust adaptation policies across multiple sectors, scales, and scenarios to tackle environmental and sustainability challenges?

Related Research Group(s)

Engineering Management and Sustainability

Engineering Management and Sustainability -

Geotechnical and Environmental Engineering

Geotechnical and Environmental Engineering - Delivering a new understanding of our geo-environment and critical infrastructure in diverse ecosystems, for predicting and preventing catastrophic failure and responding to the need for decarbonisation and energy security.

Flood, Coastal and Water Engineering

Flood, Coastal and Water Engineering - The Flood, Coastal and Water Engineering Group addresses the challenges of water scarcity, aging water infrastructures and flood management in the UK and worldwide. The group also concentrates on providing research solutions for recycling water and offering sustainable water resources for domestic and industrial uses.