地形-测深和海洋学数据集对沿海洪水研究的启示:法国圣马洛洪水预防行动方案

IF 11.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Léo Seyfried, Laurie Biscara, H. Michaud, F. Leckler, Audrey Pasquet, M. Pezerat, Clément Gicquel
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引用次数: 0

摘要

摘要法国圣马洛防洪行动方案要求评估沿海洪水风险并开发当地洪水预警系统。首要前提是了解圣马洛海湾的地形和水深情况;2018 年和 2019 年采集了新的多波束测深数据,以提高现有地形-水深数据集的分辨率,并制作了两个高分辨率(20 米和 5 米)地形-水深数字地形模型。其次,通过 2018-2019 年冬季开展的密集而广泛的海洋学实地试验,对与沿岸洪水相关的水动力进行了调查,使用了由 22 个锚系设备和 37 个传感器组成的网络:该网络包括 2 个定向浮标、2 个压力验潮仪、18 个波浪压力计、4 个单点海流计、7 个海流剖面仪和 4 个声波海流剖面仪,从中层深度(25 米)一直到上层海滩和堤坝系统。因此,海洋学数据集提供了圣马洛海湾从海岸到洪水泛滥和过顶区的水动力和波浪过程的全貌。该数据集有助于确定沿海洪水的物理驱动因素,并对其各自的作用进行量化。特别是,可以观察到保护结构脚下的波浪过程:在这一宏观潮汐环境中,春潮涨潮时,短波和次重力波会传播到保护结构,而波浪的设置仍然可以忽略不计,海包会造成过顶。结合高分辨率地形测深和海洋学数据集,可以构建、校准和验证一个波浪和水动力耦合模型,用于更深入地研究洪水过程,并可能通过圣马洛社区间的方式纳入未来的地方预警系统。地形测深和海洋学数据集可在 https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84、https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 和 https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO 免费获取(Shom,2020a,b,2021)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Insights from a topo-bathymetric and oceanographic dataset for coastal flooding studies: the French Flooding Prevention Action Program of Saint-Malo
Abstract. The French Flooding Prevention Action Program of Saint-Malo, France, requires the assessment of coastal flooding risks and the development of a local flood warning system. The first prerequisite is knowledge of the topography and bathymetry of the bay of Saint-Malo; the acquisition of new multibeam bathymetric data was performed in 2018 and 2019 to increase the resolution of the existing topo-bathymetric datasets and to produce two high-resolution (20 and 5 m) topo-bathymetric digital terrain models. Second, the hydrodynamics associated with coastal flooding were investigated through a dense and extensive oceanographic field experiment conducted during winter 2018–2019 using a network of 22 moorings with 37 sensors: the network included 2 directional buoys, 2 pressure tide gauges, 18 wave pressure gauges, 4 single-point current meters, 7 current profilers, and 4 acoustic wave current profilers from mid-depth (25 m) up to the upper beach and the dike system. The oceanographic dataset thus provides an extended overview of the hydrodynamics and wave processes in the bay of Saint-Malo from the coast up to over-flooding and over-topping areas. This dataset helps to identify the physical drivers of the coastal flooding and provides a quantification of their respective contributions. In particular, the wave processes at the foot of the protection structures can be observed: in this macro-tidal environment, during high spring tides, short and infragravity waves propagate up to the protection structures, while the wave set-up remains negligible, and over-topping by sea packs can occur. The combination of high-resolution topo-bathymetric and oceanographic datasets allows the construction, calibration and validation of a wave and hydrodynamic coupled model that is used to investigate flooding processes more deeply and might be integrated into a future local warning system by means of Saint-Malo inter-communality. The topo-bathymetric and oceanographic datasets are available freely at https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84, https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 and https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO (Shom, 2020a, b, 2021).
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来源期刊
Earth System Science Data
Earth System Science Data GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍: Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.
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