About the Project
One of the greatest risks facing society is water unavailability, referred to as hydrological drought. Ensuring continued water availability requires both assessing and managing the risk of drought – a risk that may be changing with the climate.
Water managers generally assess risk in two ways. The first involves setting standards to ensure resilience to specific events defined by their return periods. For example, a 1-in-20 year event is considered “moderate”, while a 1-in-200 year event is “severe”. The second is “stress testing”: developing plausible worst-case scenarios and strategies to cope with them.
Return periods for hydrological drought are particularly difficult to define because drought is a complex phenomenon. Droughts may be rapid or slow-onset, can last days to decades, and are affected by many land and atmospheric drivers. As a result, managers generally construct stress tests using physical climate storylines, defined as physically self-consistent, causal explanations of an event. But storylines do not necessarily have a probability attached to them; they just need to be plausible. The goal of this project is to reconcile these two approaches to serve the goals of water risk management, with a focus on the most severe cases.
The student will develop a set of plausible worst-case scenarios for UK hydrological drought, expressing drought risk in terms of specific configurations of various drivers of drought (e.g. back-to-back dry winters), drawing from historical events enriched with downward counterfactuals (i.e. imagined events which would have been worse than the actual event if conditions had been different in a specific way). The probability of these driver configurations will be assessed within a rigorous Bayesian framework, and their response to climate change explored. As a final step, this framework will be connected to decision-making tools within the sector.
The MFC CDT programme provides comprehensive training in the theory of climate science, physical sciences, scientific computing, statistics and data analysis to address pressing problems and challenges posed by climate change. The CDT programme also affords extensive opportunities for personal and professional development training, and for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners.
For this project, the student will spend time at Anglian Water, working with staff and undergoing training including hydrological modelling, water resources system modelling, and drought risk assessment. The student will also gain experience in water resources planning and drought planning including technical and regulatory requirements. The student will be part of a group of PhD students sponsored by Anglian Water, offering opportunities to broaden knowledge and develop complementary research opportunities.
Funding Notes
A full UKRI stipend plus home-level PhD tuition fees, details are found below:
References
Shepherd, T. G. (2019) Storyline approach to the construction of regional climate change information, https://doi.org/10.1098/rspa.2019.0013
Chan, W. C. H., et al. (2024) Added value of seasonal hindcasts to create UK hydrological drought storylines, https://doi.org/10.5194/nhess-24-1065-2024
Wilby, R. L. and Darch, G. (2025) Uncertainty in Hydrologic and Water Resources Modelling, https://doi.org/10.1007/978-3-031-85542-9_9
