Building flexibility into long-term water resources system planning and management strategies

About the Project

Sustainable water resources planning, and management policies need to consider the impact of future changes due to factors like geomorphologic processes, aging infrastructure, demand shifts or variability of water supplies. However, whilst change over time is certain, the extent to which it will affect the physical and social dimensions of the water resource systems is uncertain. Under ‘deep’ uncertainty where predictions are highly unreliable (Timbadiya, Singh and Sharma, 2023; Roach, Kapelan and Ledbetter, 2018), responsible decision makers should avoid irreversible actions and anticipate the need to adapt their policies as information about the future unfolds (Plummer and Armitage, 2007; Folke et al., 2005). This is particularly crucial for the water sector, which relies on a capital-intensive infrastructure legacy requiring long-term investments. Failing to embed flexibility and adaptable planning into system’s design could result in significant consequences. Since it is not possible to ‘disinvest’ should conditions change adversely, long-lived infrastructure with high irreversible sunk costs may have to be replaced or expensively retrofitted before the end of the design life (Ranger, Reeder and Lowe, 2013). This could also expose society to higher risks than initially planned for and lead to bad adaptation decisions, which can be proved to be far from optimal (Hall and Borgomeo, 2013). Hence in such situations, adaptive strategies can reveal insights to avoid maladaptation and reduce the effect of erroneous decisions.

This project aims to develop a capacity expansion optimization model to help water planners select the most appropriate schedule for future infrastructure upgrades and investments, incorporating flexible and adaptive strategies. This will be achieved by building on current advancements in the literature (Ihm, Seo and Kim, 2019; Pachos et al., 2022; Timbadiya, Singh and Sharma, 2023). This initiative is timely, given the significant infrastructure investments that countries, including the UK, plan to make over the next decade to ensure water security (UKWIR, 2020b; HM Treasury, 2020). UKWIR guidelines (UKWIR, 2016; UKWIR, 2020a) and recent government guidance (Ofwat, 2022) also emphasise the importance of integrating flexibility into water resource system designs.

We welcome applications from individuals with strong backgrounds in civil and environmental engineering, or mathematical and computer science. Ideal candidates should have proficiency in mathematical optimisation, data science for handling large datasets, and Python programming.

The project will be co-supervised by Professor Jean-Christophe Nebel, a leading expert in computer science with over 20 years of research experience in AI, pattern recognition, and game theory. His work bridges academic excellence and real-world impact, with a strong record in knowledge exchange through consultancy, contract research, and technology transfer. Notable achievements include technology foresight for UK digital health SMEs (2018–19), an ‘Outstanding’-rated double KTP (2019–22), and a successful AKT project in 2024, recognised by Innovate UK for pioneering affordable AI-powered air quality sensors. As Director of Kingston University's Knowledge Exchange & Research Institute for Cyber, Engineering & Digital Technologies, Prof. Nebel brings deep technical insight and robust industry, government, and community connections.

Funding Notes

there is no funding for this project