Abstract
Abstract. By showing the uncertainty surrounding a prediction, probabilistic forecasts can give an earlier indication of potential upcoming floods, increasing the amount of time available to prepare. However, making a decision based on probabilistic information is challenging. As part of the UK-wide policy's move towards forecast-based flood risk management, the Environment Agency (EA), responsible for managing risks of flooding in England, is transitioning towards the use of probabilistic fluvial forecasts for flood early warning. While science and decision-making are both individually progressing, there is still a lack of an ideal framework for the incorporation of new and probabilistic science into decision-making practices, and, respectively, the uptake of decision-makers' perspectives in the design of scientific practice. To address this, interviews were carried out with EA decision-makers (i.e. Duty Officers), key players in the EA's flood warning decision-making process, to understand how they perceive this transition might impact on their decision-making. The interviews highlight the complex landscape in which EA Duty Officers operate and the breadth of factors that inform their decisions, in addition to the forecast. Although EA Duty Officers already account for uncertainty and communicate their confidence in the forecast they currently use, the interviews revealed a decision-making process which is still very binary and linear to an extent, which appears at odds with probabilistic forecasting. Based on the interview results, we make recommendations to support a successful transition to probabilistic forecasting for flood early warning in England. These recommendations include the new system's co-design together with Duty Officers, the preparation of clear guidelines on how probabilistic forecast should be used for decision-making in practice, EA communication with all players in the decision-making chain (internal and external) that this transition will become operational practice and the documentation of this transition to help other institutes yet to face a similar challenge. We believe that this paper is of wide interest for a range of sectors at the intersection between geoscience and society. A glossary of technical terms is highlighted by asterisks in the text and included in Appendix A.
Highlights
The ongoing shift in UK policy from “flood defence” towards a forecast-based “flood risk∗ management” approach to better anticipate floods (Dale et al, 2012; McEwen et al, 2012) has shaped a series of developments in the uptake of flood forecasting science in practice, often implemented in the wake of significant flood events
The two Environment Agency (EA) flood scenarios are an intermediate step between deterministic and probabilistic fluvial flood forecasting (n.b. probabilistic coastal flood forecasts are already operational and this paper focuses on fluvial flood forecasting), as outlined as essential by the National Flood Resilience Review (NFRR)
There is currently a lack of clarity about how probabilistic forecasts should be used for flood incident management and how this transition will affect decision-makers’ roles at the EA
Summary
The ongoing shift in UK policy from “flood defence” towards a forecast-based “flood risk∗ management” approach to better anticipate floods (Dale et al, 2012; McEwen et al, 2012) has shaped a series of developments in the uptake of flood forecasting science in practice, often implemented in the wake of significant flood events. The winter 2013/14 UK floods illustrated the value of these institutional changes to flood forecasting as well as the value in using new forecasting techniques, such as ensemble∗ surge forecasts∗, for flood preparedness∗ (Flowerdew et al, 2009; Stephens and Cloke, 2014) It was during the 2013/14 floods that the EA moved from using a single prediction of upcoming floods (known as a deterministic forecast∗) to using two fluvial (river) flood scenarios∗, a “best estimate”∗ and a “reasonable worst case”∗ (see more information below), for flood incident management in England (FFC, 2020). The recent floods exposed a limitation in our forecasting approach by only running flood models with a Best Estimate and Reasonable Worst Case meteorological inputs Whilst this approach is fine at providing a high level general meteorological input to flood forecast models small variances in rainfall profiles within and across catchments makes a big difference in river response and flood risk. Modelling the impacts of snow accumulation and melting was a particular problem [...] Being able to run meteorological ensembles through our flood forecasting models to determine the probability of different magnitudes of flood impacts within and across catchments would in my view have given us a better understanding of river response and allowed for clearer communication of risk from forecasters to responders. [...] There was a lot we did well but a lot we can do better
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