A systematic review of natural flood management modelling: approaches, limitations, and potential solutions
The Pitt Review of the 2007 summer floods in the UK, published in 2008, commended the potential of natural flood management (NFM) for reducing flood risk. NFM is a nature-based approach that has since gained substantial interest from both practitioners and academics. The review further highlighted the need for catchment-based flood management (CBFM) to enhance resilience to flooding and climate change by incorporating NFM and wider nature-based solutions into hard flood protection systems. Such integrated approaches are considered to be more sustainable and adaptable than the traditional hard-engineered measures. More recently, the European Commission's European Green Deal also highlighted the need for greater use of nature-based solutions including NFM for managing flood risk. Whilst there have been many attempts to quantify the effects of NFM through hydraulic and hydrological modelling, there is still no systematic review conducted for these modelling works. This review aims to summarise the current NFM modelling approaches, as well as discussing their key limitations related to data, model methods, and real-world applications. This paper then goes further to highlight potential solutions to some of these challenges and provides guidance to assist modellers to improve future modelling and data collection process.
Funding
EPSRC Centre for Doctoral Training in Water and Waste Infrastructure Systems Engineered for Resilience (Water-WISER)
Engineering and Physical Sciences Research Council
Find out more...History
School
- Architecture, Building and Civil Engineering
Published in
Journal of Flood Risk ManagementVolume
16Issue
3Publisher
WileyVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This is an Open Access Article. It is published by Wiley under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2023-03-05Publication date
2023-04-03Copyright date
2023ISSN
1753-318XeISSN
1753-318XPublisher version
Language
- en