Background
Hydrological drought hazard results from extreme low flows in rivers, reducing water supplies and thus the capacity for abstraction causing water shortages. Currently, the UK’s vulnerability to drought hazard has reached the warning threshold (20%) on the Water Exploitation Index (water abstraction as a percentage of the freshwater resource); it is thus defined by the European Environment Agency as a water-stressed country (EEA, 2019 ). Recent research (Collet et al., 2018 , Visser-Quinn et al., 2019 ; (Kay et al., 2018 , Rudd et al., 2019 ),suggests that climate change may represent an additional stressor, with hydroclimatological projections indicating an increase in the frequency and intensity of hydrological droughts in the coming decades.
It is clear that drought hazard represents a major threat to water security globally, and the UK is no different. However, these hazards are subject to spatial variation, which may change in the future. With regional variations in these hazards, as well as regional population patterns, it is crucial to study such phenomena at a large geographical scale (e.g. country level). In addition to spatial considerations, temporal analyses are needed, using flow or precipitation time series. Projections of future river flows (runoff) are the product of a long and complex modelling chain: emissions scenarios force General Circulation Models (GCMs), the outputs of which are downscaled to force hydrological models. Uncertainties in terms of model input, structure, and parameters, cascade through the modelling chain (Clark et al., 2016 ). Looking forward to future climate projections, any analyses require to consider ensemble projections, thus posing questions around probabilistic analyses.
Aims and Objectives
Droughts can be explored in many ways, one of which is categorising by severity and exploring the transition between severity states. Markov chains are a powerful tool which allow us to explore patterns as an alternative to traditional hydrological models by utilising flows projections either directly from regional climate models (Aitken et al 2022) or through modelling chains such as EFLaG (Aitken et al, 2023). The aim of this PhD is to explore the regional variation in drought severity transitions regionally across the UK. The research will include developing novel ways to establish the probability of different events occurring, as well as grappling with large datasets to detect patterns of transition or occurrence.