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A systematic review of natural flood management modelling: approaches, limitations, and potential solutions

journal contribution
posted on 2023-03-17, 09:14 authored by Bartholomew Hill, Qiuhua LiangQiuhua Liang, Lee BosherLee Bosher, Huili ChenHuili Chen, Alex Nicholson

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), as well as making systems more resilient 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 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 provide 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

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History

School

  • Architecture, Building and Civil Engineering

Published in

Journal of Flood Risk Management

Publisher

Wiley

Version

AM (Accepted Manuscript)

Publisher statement

This is an Open Access Article.

Acceptance date

2023-03-05

ISSN

1753-318X

eISSN

1753-318X

Language

en

Depositor

Prof Lee Bosher. Deposit date: 16 March 2023