SPLASH: digital approaches to predict wave hazards

SPLASH：预测海浪灾害的数字方法

• 批准号: NE/Z503423/1
• 负责人: Nieves Garcia Valiente
• 金额: $ 24.3万
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FZ503423%2F1
• 关键词: SPLASH; digital; approaches; predict; wave

With sea level rise accelerating and coastal populations increasing, the requirement of accurate tools to predict natural hazards and mitigate damages to infrastructure, property and human life is ever more urgent. Our project sits in the frame of assessing impacts of changing environmental conditions, particularly extremes, on the state of the natural world, affected by both natural variability and impact of human activity. Coastal flooding is normally caused by wave overtopping that occurs when water is discharged by waves over a coastal structure such as a breakwater. There are multiple methods to forecast coastal overtopping, and most of them demonstrate a lack of precision and large dependency to local processes. Statistical analysis of Earth Observations (EO) will provide a method to assess wave fields to better understand how processes (winds, tides, coastal sheltering, swell and wind waves) interact across a coastal area to change the coastal wave hazard through, for example, (depth and current) refraction, wind shadowing and bimodal wave contributions. From March 2021-2022 monitoring of the wave overtopping at Dawlish and Penzance provided in-situ hazard alerts, indicating when overtopping starts and stops, along with a measure of the severity (WireWall data). Such observations can be used alongside national monitoring networks of waves, water levels and Earth Observations (EO) data to develop an environmental digital twin pilot, and ultimately, improve operational hazard management and increase UK resilience to natural hazards. The principal aim of this proposal is to build a deployable coastal overtopping warning tool (SPLASH) with the vision of transforming weather and climate research and services through transformative technologies. The main outcomes of the proposal will be (1) a method to analyse coastal wave fields from EO to determine regular asymmetries in hazards conditions, (2) a digital twin of wave overtopping in which machine learning has been applied to produce a warning tool using model predictions of wind, waves and water level, and (3) coastal overtopping projections to assess future changes in hazard frequency. The proposed project will use: (i) overtopping Dawlish/Penzance WireWall data (observations) to train and validate machine learning algorithms based on model predictions (wind, waves and water levels); (ii) camera images for calibration and validation; and (iii) satellite images to study variability in wave field indicators. Met Office reanalysis and analysis model data will be obtained from freely available data portals (e.g., Copernicus Marine Service) and through the UK Marine and Climate Advisory Service. Furthermore, case studies will be used as a demo and the approach will be tested in other wave hazard hotspot locations along the UK coastline where there are CCTV cameras or webcams (e.g., Chesil, Teignmouth). Reliable warning tools such as SPLASH provide essential information to those coastal communities that are currently experiencing wave related hazards. The combined application of SPLASH as a forecasting and a projection tool will facilitate coastal practitioners' decision making, helping mitigate the effects of climate change in already vulnerable locations.

随着海平面上升的加速和沿海人口的增加，对准确预测自然灾害和减轻对基础设施、财产和人类生命的损害的工具的需求变得更加迫切。我们的项目是在评估不断变化的环境条件，特别是极端环境，对自然世界状态的影响的框架内，受到自然变化和人类活动的影响。沿海洪水通常是由波浪漫过引起的，当波浪将水排出到海岸结构（如防波堤）上时，就会发生这种情况。有多种方法可以预测沿海过顶，但大多数方法都缺乏精度，而且很大程度上依赖于当地过程。地球观测（EO）的统计分析将提供一种评估波场的方法，以更好地了解过程（风、潮汐、海岸庇护、膨胀和风浪）如何在沿海地区相互作用，通过（深度和电流）折射、风阴影和双峰波贡献等方式改变沿海波的危害。从2021年3月到2022年3月，对Dawlish和Penzance的波浪过顶的监测提供了现场危险警报，表明何时开始和停止过顶，以及严重程度的测量（WireWall数据）。这些观测结果可以与国家波浪、水位和地球观测（EO）数据监测网络一起使用，以开发环境数字孪生试点，最终改善业务风险管理，提高英国对自然灾害的抵御能力。该提案的主要目的是建立一个可部署的沿海漫顶预警工具（SPLASH），通过变革性技术改变天气和气候研究和服务的愿景。该提案的主要成果将是：(1)一种从EO分析海岸波场的方法，以确定危险条件下的规则不对称；(2)海浪漫过的数字孪生，其中机器学习已被应用于使用风、波和水位模型预测产生警告工具；(3)沿海漫过预测，以评估未来灾害频率的变化。拟议的项目将使用：(i) overtopping Dawlish/Penzance WireWall数据（观测）来训练和验证基于模型预测（风、波浪和水位）的机器学习算法；（ii）用于校准和验证的相机图像；（三）利用卫星图像研究波场指标的变异性。气象局的再分析和分析模型数据将从免费的数据门户（例如，哥白尼海洋服务）和英国海洋和气候咨询服务获得。此外，案例研究将被用作演示，该方法将在英国海岸线上其他有闭路电视摄像机或网络摄像头的波浪危险热点地区（例如，切西尔，泰格茅斯）进行测试。可靠的预警工具，如SPLASH，为那些目前正遭受海浪相关危害的沿海社区提供了必要的信息。将SPLASH作为预测和投影工具的结合应用将促进沿海从业者的决策，帮助减轻气候变化对已经脆弱的地区的影响。