Birch, C orcid.org/0000-0001-9384-2810, Rabb, B, Böing, S et al. (8 more authors) (2021) Enhanced surface water flood forecasts: User-led development and testing. Journal of Flood Risk Management, 14 (2). e12691. ISSN 1753-318X
Abstract
The risk of surface water flooding (SWF) in England is already high and its frequency and severity is projected to increase in the future. SWF generally occurs due to intense, highly localised rainfall, which is challenging to forecast with sufficient accuracy to take proactive action ahead of flood events. Being able to manage the risk effectively lies in improved rainfall and flood forecast products, better communication of uncertainty and building the capacity of local responders. This study utilises state-of-the-art high-resolution ensemble rainfall forecasts and hydraulic modelling tools alongside a novel post-processing method to develop and trial new SWF forecast products within an incident workshop attended by forecast producers and regional forecast users. Twenty-two of 24 workshop participants reported that the new information would be useful to their organisation but more product development and training in its interpretation is required. Specific recommendations to improve SWF forecast provision include increased support for local government through a single government organisation responsible for SWF, making more use of existing static SWF mapping in a real-time context and employing the process of user-based consultation, as outlined in this study, to guide the future development of future SWF forecast information and processes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Journal of Flood Risk Management published by Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | convective rainfall, engagement, ensemble forecasting, flood forecasting, intense rainfall, pluvialflooding, surface water flooding, user-led testing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Institute for Applied Geosciences (IAG) (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/P011160/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Dec 2020 13:10 |
Last Modified: | 25 Jun 2023 22:32 |
Status: | Published |
Publisher: | Wiley Open Access |
Identification Number: | 10.1111/jfr3.12691 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169181 |