Characterising Historical and Future Transitions in UK Hydrological Extremes

Rapid transitions between droughts and floods can exacerbate the impacts of the individual events and present a complex challenge for water resource management: sudden or frequent transitions between dry and wet conditions can negatively impact water quality, agricultural productivity, and cause damage to water infrastructure. Despite these potentially severe impacts, such transitions are less comprehensively studied than their component extremes.  

Transitions can be defined multiple ways, here we identify transition events as the period between consecutive yet opposite extremes. Firstly, we use a threshold method to demarcate extreme wet and dry events in both streamflow and precipitation to allow for understanding of both hydrological and meteorological transitions. Transitions are then derived from the extreme wet and dry events in pairs, to extract both wet-to-dry and dry-to-wet transitions. The transition events can then be characterised and quantified by transition metrics, namely magnitude, duration, intensity, and frequency. We apply these methods to analyse both historical and future transitions over the UK using national river flow and precipitation projections from the enhanced future Flows and Groundwater (eFLaG) dataset for 1989-2079. We also use the associated physical catchment characteristics to evaluate their influence on transitions. 

This work aims to characterise the spatial distribution of transitions in the UK, with a view to identifying any ‘hotspots’ of transitions, as well as assess projected changes in transitions across the UK. We find a difference in transition characteristics between the north-west and south-east UK, a pattern which persists under future projections, and an increase in the frequency of transitions in the north-west into the future.  

Our findings will provide valuable insights to support water resource managers in drought and flood preparedness in making informed, sustainable decisions to mitigate the impacts of extreme wet and dry events; and potentially enable improved prediction of hydrological extremes.