从感知到建模:以自然为基础的解决方案作为沿海风险管理工具
Marina d'Avdeew1,2,3, Louis Janin1,4, Lydie Goeldner-Gianella2,3
1Artelia, 16, rue Simone Veil, 93400 Saint-Ouen-sur-Seine, France.
Cambridge prisms. Coastal futures
|November 3, 2025
概括
沿海基于自然的解决方案 (NBS) 提供了防洪的好处. 这项研究发现,通过漏洞重新安置堤是NBS在Authie Bay最有效的策略,弥合了公众认知和科学数据之间的差距.
科学领域:
- 沿海工程的工程.
- 环境科学环境科学
- 风险管理 风险管理
背景情况:
- 沿海以自然为基础的解决方案 (NBS) 在法国越来越受欢迎,用于防洪.
- 这些项目面临技术和社会接受性的挑战.
- 关于NBS有效性的公众认知和科学数据之间存在差距.
研究的目的:
- 将公众感知数据与Authie Bay的NBS场景的数值建模结果进行比较.
- 评估NBS感知和实际防洪保护之间的差距.
- 评估堤搬迁作为NBS战略的有效性.
主要方法:
- 利用了DIGUES研究计划2021年感知调查的数据.
- 采用数值模型来评估NBS场景的防洪效率.
- 将调查场景翻译成数值模型进行交叉比较.
主要成果:
- 通过漏洞的Dyke搬迁显示出与奥西湾的其他NBS场景相比,有显著的好处.
- 该研究发现了感知和实际保护水平之间的差异.
- 根据规模,NBS的有效性有所不同,堤搬迁被证明是最有利的.
结论:
- 通过漏洞重新安置Dyke是NBS对Authie Bay的一个非常有益的策略.
- 解决公众认知和科学数据之间的差距对于成功实施NBS至关重要.
- 数字建模为沿海洪水风险管理的NBS有效性提供了客观的见解.
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