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Cited by 57

The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.

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

Hill, Bartholomew, Liang, Qiuhua, Bosher, Lee, Chen, Huili, Nicholson, Alex·2023·Journal of Flood Risk Management
DOI 10.1111/jfr3.12899
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Abstract

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.

Overview

Integrity signals

Registry

Crossref · 10.1111/jfr3.12899

Cites

135 of 135 references verified0 citation errors · 0 not checkable

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Citations

Cites

1 retracted

Research works printed but not linked: 21

  1. ARUP, 2020, River Hull natural flood management study – Synthesis report
  2. Burgess‐Gamble L., 2017, Working with natural processes–evidence directory
  3. CRED, 2020, Disaster year in review 2020, global trends and perspectives
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  5. Fitton S. L.(2015).Social value in practice: A case of flood alleviation schemes. (Doctoral dissertation). University of Cambridge.
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  7. Higgins J. P. T., 2011, Cochrane handbook for systematic reviews of interventions version 5.1.0
  8. Iacob O.(2015).Natural flood management: An ecosystem based adaptation response for climate change(Doctoral dissertation). University of Dundee.
  9. JBA Consulting, 2015, High level assessment of flood storage options in Debenham: Phase 1 – Natural Flood Management
  10. Metcalfe P., 2017, Case study 2: Brompton runoff attenuation modelling – North Yorkshire
  11. Moore R. D., 2005, Slug injection using salt in solution, Streamline Watershed Management Bulletin, 8, 1
  12. Pearson C.(2016).Modelling the potential impact of spatially targeted natural flood management at the landscape scale for a rural UK catchment(MSc by research Dissertation). Durham University.
  13. Pitt M.(2008).Learning lessons from the 2007 floods. Pitt Review.
  14. POSTNOTE, 2016, Green space and health
  15. Rogers M.(2017).Can structure from motion determine the efficacy of river re‐meandering as a natural flood management measure. (Doctoral dissertation MSc thesis). University of Cambridge.
  16. SEPA, 2016, Natural flood management handbook
  17. Sisson J., 2017, Case study 9 – River Elwy runoff attenuation modelling – Denbighshire, 5
  18. Smith K. L.(2017).Investigating the potential of 3D visualisation to enhance stakeholder engagement in natural flood management. (Doctoral dissertation). University of Gloucestershire.
  19. Welton P., 2017, Case study 13: Lustrum Beck runoff attenuation modelling – Stockton on Tees
  20. Wilkinson M., 2017, Case study 1 – Tarland burn runoff attenuation modelling – Aberdeenshire
  21. Yan Y. &Ryu Y.(2019).Google street view and deep learning: A new ground truthing approach for crop mapping. arXiv preprint arXiv:1912.05024. · arXiv

Cited by

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Metadata

Authors
Hill, B., Liang, Q., Bosher, L., Chen, H., & Nicholson, A.
Affiliations
  • School of Architecture, Building and Civil Engineering Loughborough University Loughborough LE11 3TU UK
  • Newcastle Office Arup Group Ltd 5 Forth St, Newcastle Upon Tyne NE1 3PL Tyne and Wear UK
ORCID
Hill, Bartholomew
Venue
Journal of Flood Risk Management
Publisher
Wiley
Published
2023-04-03
Volume
16
Issue
3
ISSN
1753-318X
DOI
10.1111/jfr3.12899
Cited by
57
References
135
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.