English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. By showing the uncertainty surrounding a prediction,probabilistic forecasts can give an earlier indication of potential upcomingfloods, increasing the amount of time available to prepare. However, makinga decision based on probabilistic information is challenging. As part of theUK-wide policy's move towards forecast-based flood risk management, theEnvironment Agency (EA), responsible for managing risks of flooding inEngland, is transitioning towards the use of probabilistic fluvial forecastsfor flood early warning. While science and decision-making are bothindividually 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 designof scientific practice. To address this, interviews were carried out with EAdecision-makers (i.e. Duty Officers), key players in the EA's flood warningdecision-making process, to understand how they perceive this transitionmight impact on their decision-making. The interviews highlight the complexlandscape in which EA Duty Officers operate and the breadth of factors thatinform their decisions, in addition to the forecast. Although EA Duty Officers already account for uncertainty and communicate their confidence inthe forecast they currently use, the interviews revealed a decision-makingprocess which is still very binary and linear to an extent, which appears atodds with probabilistic forecasting. Based on the interview results, we makerecommendations to support a successful transition to probabilisticforecasting 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 beused for decision-making in practice, EA communication with all players in the decision-making chain (internal and external) that this transitionwill become operational practice and the documentation of this transition tohelp other institutes yet to face a similar challenge. We believe that this paper is of wide interest for a range of sectors at theintersection between geoscience and society. A glossary of technical termsis highlighted by asterisks in the text and included in Appendix A.

geoscience communication

“Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England