A systematic review of natural flood management modelling: Approaches, limitations, and potential solutions
A systematic review of natural flood management modelling: Approaches, limitations, and potential solutions
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DOI：
10.1111/jfr3.12899
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发表时间：
2023-04
影响因子：
4.1
通讯作者：
Bartholomew Hill;Qiuhua Liang;L. Bosher;Huili Chen;A. Nicholson
中科院分区：
文献类型：
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作者：
Bartholomew Hill;Qiuhua Liang;L. Bosher;Huili Chen;A. Nicholson
2008年出版的英国2007年夏季洪水的皮特评论赞扬了自然洪水管理（NFM）在减少洪水风险方面的潜力。NFM是一种基于自然的方法，已经引起了从业者和学者的极大兴趣。该审查进一步强调了基于流域的洪水管理（CBFM）的必要性，通过将NFM和更广泛的基于自然的解决方案纳入硬防洪系统，以提高对洪水和气候变化的抵御能力。这种综合方法被认为比传统的硬工程措施更具可持续性和适应性。最近，欧盟委员会的欧洲绿色协议也强调了更多地使用基于自然的解决方案的必要性，包括管理洪水风险的NFM。虽然已经有许多尝试，以量化的影响，NFM通过水力和水文模型，仍然没有系统的审查进行这些模拟工作。本文旨在总结当前的NFM建模方法，并讨论其与数据，模型方法和真实的世界应用相关的关键限制。然后，本文进一步强调了其中一些挑战的潜在解决方案，并提供指导，以协助建模人员改进未来的建模和数据收集过程。
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.