DEVELOPMENT AND VALIDATION OF A REMOTE BED-LEVEL SENSOR FOR IMPROVED OPERATIONAL COASTAL FLOOD WARNINGS
DEVELOPMENT AND VALIDATION OF A REMOTE BED-LEVEL SENSOR FOR IMPROVED OPERATIONAL COASTAL FLOOD WARNINGS
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开发和验证远程床位传感器以改进沿海洪水预警业务
DOI：
10.1142/9789811275135_0093
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
POATE T
中科院分区：
文献类型：
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作者：
POATE T
波浪越顶和海滩降低是动态关联的过程，并且对于海防基础设施的管理和设计至关重要。然而，这些相互作用知之甚少，因此没有很好地代表现有的越浪工具，如EurOtop，沿海管理人员使用。在海岸结构前，关于海滩动力学的高分辨率（现场）数据很少。在这里，我们演示了如何低成本，可靠，独立的床级传感器（B扫描）能够捕捉日常海滩配置文件的反应，可以支持运营管理决策。从四个站点的结果表明，一个强大的系统，可用于提高业务越浪预测和资产管理的准确性。该系统表现出了弹性、可靠性和准确性，赢得了其他利益攸关方的支持，这些利益攸关方渴望在更多地点改进监测工作。B扫描传感器的可靠范围为12-15 m，可以很好地代表海堤前海滩对强迫条件的响应，可用于资产管理和沿海洪水预报。该系统可用于广泛的设置减轻需要现场访问，以了解海滩状态，以帮助在沿海管理。改进的时间分辨率的数据可以明显地提高漫顶预报的准确性，这对沿海洪水管理很重要，并有助于提高沿海洪水预报系统的信心。
Wave overtopping and beach lowering are dynamically linked processes, and vital to the management and design of sea defence infrastructure. However, these interactions are poorly understood and therefore not well represented in existing overtopping tools, such as EurOtop, used by coastal managers. There is a paucity of high resolution (field) data on beach dynamics in front of coastal structures. Here we demonstrate how a low cost, reliable, standalone bed-level sensor (B-Scan) capable of capturing daily beach profile response can support operational management decisions. Results from four sites demonstrate a robust system that can be used to improve the accuracy of operational overtopping forecasts and asset management. The system has exhibited resilience, reliability and accuracy earning support from additional stakeholders keen to improve the monitoring at further locations. With a reliable range of 12-15 m the B-Scan sensor can provide a good representation of beach response to forcing conditions, in front of sea walls, that can be used for asset management and coastal flood forecast. The system can be used in a wide range of settings mitigating the need for site visits to understand beach state to aid in coastal management. The improved temporal resolution of the data can demonstrably improve the accuracy of overtopping forecasts important for coastal flood management and help to generate greater confidence in coastal flood forecast systems.