Coastal urban flood risk management: Challenges and opportunities - A systematic review

被引:2
|
作者
Aziz, Farhan [1 ,2 ]
Wang, Xiuquan [1 ,2 ]
Mahmood, Muhammad Qasim [1 ,2 ]
Awais, Muhammad [1 ,2 ]
Trenouth, Bill [3 ]
机构
[1] Univ Prince Edward Island, Canadian Ctr Climate Change & Adaptat, Prince Edward Island, PE C0A 2A0, Canada
[2] Univ Prince Edward Island, Sch Climate Change & Adaptat, Prince Edward Island, PE C1A 4P3, Canada
[3] AECOM Canada Ltd, 250 York St Citi Plaza Suite 410, London, ON N6A6K2, Canada
基金
加拿大创新基金会;
关键词
Coastal urban flood risk management; Urbanization; Climate change; Artificial intelligence; Green funding; Nature-based solutions; Participatory planning and governance; CLIMATE-CHANGE; REDUCTION; AREAS; RESILIENCE; GOVERNANCE; VULNERABILITY; IMPACTS; BOND;
D O I
10.1016/j.jhydrol.2024.132271
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Generational mechanisms and spatio-temporal evolution patterns of coastal urban flood risk involve complex interactions between climate change, sea level rise and human-induced factors, necessitating integrated adaptive flood management strategies to mitigate evolving vulnerabilities. This systematic review offers a thorough assessment of the challenges and strategic opportunities for sustainable adaptation in managing flood risk in coastal urban areas. It integrates emerging innovative technologies and financial solutions to identify promising approaches to implement mitigation strategies and improve coastal urban flood resilience. Enhancing governance and policy frameworks is crucial for the successful implementation of coastal urban flood risk management (CUFRM) plans. An innovative participatory planning framework is developed to promote flood management practices which are socially inclusive and equitable. Funding for green infrastructure and nature-based solutions and the strategic use of public-private partnerships are effective methods for advancing sustainable flood risk management (FRM). The advancements in emerging technologies, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), social media and digital twin technologies, provide dynamic and collaborative platforms for simulating flood scenarios and have potential to significantly improve CUFRM practices. In the end, a cross-country comparison of current practices in Australia, China, the Netherlands, the UK and the USA reveals a diverse range of approaches and valuable insights derived from regional experiences. The review provides a comprehensive analysis for researchers, policymakers and practitioners aiming to improve flood resilience in coastal metropolitan regions by learning from effective UFRM approaches that enhance governance structures, infrastructure resilience and funding mechanisms.
引用
收藏
页数:18
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