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

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.

Decision‐Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment

“…The changes highlighted in Figure 3a are consistent with that reported by Collet et al (2017), which used both the generalized Pareto method (fitting to Peak over Threshold data) and the GEV method (fitting to Annual Maxima series) to analyze changes in extreme flows. Large increases in multiday and extreme precipitations are expected as a result of climate change in the north and west of the United Kingdom (Wilby et al, 2008), which translates into rising peak flows in Scotland as shown in Figure 3a.…”

“…Some limits of this study are related to the use of the future flow database. As reported by Collet et al (2017), some catchments were calibrated with an emphasis on the representation of the water balance, and low flows and the extreme high flows might thus be underestimated. A validation exercise was undertaken where the FFH data set was used to determine the 1:200-year RP event for each station for the hydrological period 1981-2010.…”

“…Recent research (e.g., Collet et al, 2017) has recognized the need to understand climate model projection uncertainty and quantify the impact this may have on flood hazards across the United Kingdom. The UKCP09 provide climatic projections for a perturbed physics ensemble for various emission scenarios and are used to project potential changes to temperature and precipitation across the United Kingdom (Murphy et al, 2009).…”

“…This way the results are more adequate for end-user needs (see, e.g., Jahn et al, 2012;Lang et al, 2012). Therefore, the aim of this study was to take an inclusive approach to the transfer of recent research (Collet et al, 2017) by working with flood risk practitioners to investigate how to use climate change projections and the associated uncertainties in a meaningful manner. It aimed to answer, in a manner that is clear to decision makers, three questions which were dictated through discussion with practitioners:…”

“…In answering the final question, this paper explores how the uncertainties associated with predictions of future flows can be expressed in a manner that can assist flood management practitioners to make decisions in the face of uncertainty. Collet et al (2017) concluded it was crucial that the uncertainty arising from the climate change impact modeling chain was considered for flood risk planning. However, transferring these results to industry implies a change of practice in flood risk management (e.g., moving from a deterministic to a probabilistic approach) and collaboration with practitioners is essential to ensure the practical use of research outputs.…”