Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain

TLDR

Floods are the most common natural risk in the UK, causing over £1 billion in annual damage, and climate projections predict that flood risk will rise, making assessment of extreme flows urgent. This study evaluates how climate change will alter 1:100‑year extreme runoff across Great Britain using the Future Flows Hydrology database. We fit Generalised Extreme Value and Generalised Pareto models to 11‑member ensemble flow series for baseline and 2080s, then quantify uncertainty from extreme‑value and climate‑model parameters. Both GEV and GP yield similar runoff estimates, but uncertainties increase in east England, with GEV’s climate‑model uncertainty contributing about 60 % versus 40 % for GP, underscoring the need to account for parameter uncertainty when assessing extreme runoffs.

Abstract

Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11‐member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs.