Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2567-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-2567-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Oct 2020
Research article |
| 01 Oct 2020
| 01 Oct 2020
A risk-based network analysis of distributed in-stream leaky barriers for flood risk management
Lancaster Environment Centre, Lancaster University, Lancaster, UK
JBA Consulting, Skipton, UK
Ian Hewitt
Mathematical Institute, Oxford University, Oxford, UK
Graham Sander
School of Civil and Building Engineering, Loughborough University, Loughborough, UK
Federico Danieli
Mathematical Institute, Oxford University, Oxford, UK
Giuseppe Formetta
Department of Civil, Environmental and Mechanical Engineering,
University of Trento, Trento, Italy
Alissa Kamilova
Mathematical Institute, Oxford University, Oxford, UK
Ann Kretzschmar
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Kris Kiradjiev
Mathematical Institute, Oxford University, Oxford, UK
Clint Wong
Mathematical Institute, Oxford University, Oxford, UK
Sam Pegler
School of Mathematics, University of Leeds, Leeds, UK
Director, JBA Trust, Skipton, UK
Lancaster Environment Centre, Lancaster University, Lancaster, UK
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Short summary
With growing support for nature-based solutions to reduce flooding by local communities, government authorities and international organisations, it is still important to improve how we assess risk reduction. We demonstrate an efficient, simplified 1D network model that allows us to explore the
whole-systemresponse of numerous leaky barriers placed in different stream networks, whilst considering utilisation, synchronisation effects and cascade failure, and we provide advice on their siting.
With growing support for nature-based solutions to reduce flooding by local communities,...
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