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，准确的工具需要预测自然危害并减轻对基础设施的损害，财产和人类生活的损害越来越紧迫。我们的项目位于评估不断变化的环境条件的影响的框架中，尤其是极端对自然世界状态的影响，受到人类活动的自然变异性和影响的影响。沿海洪水通常是由于波浪上的波浪造成的，当水通过沿海结构（例如防波堤）排出时发生。有多种方法可以预测沿海的超越，其中大多数表明缺乏精确性和对本地过程的依赖性。地球观测值（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，沿海庇护所，膨胀和风波）如何在沿海地区相互作用，以通过（例如（DEPTH和电流）折射，风阴影和Bimodal波浪贡献来改变沿海波浪的危害。从2021 - 2022年3月，对Dawlish和Penzance的波动上的波动的监视提供了现场危害警报，表明何时超过上下开始和停止，以及一定程度的严重性（WireWall Data）。这些观察结果可以与国家监测网络，水位和地球观测（EO）数据一起使用，以开发环境数字双胞胎飞行员，并最终改善运营危险管理并提高英国对自然危害的弹性。该提案的主要目的是建立可部署的沿海高度警告工具（Splash），其愿景是通过变革性技术改变天气和气候研究和服务。该提案的主要结果将是（1）一种分析来自EO的沿海波场以确定危险条件下的规则不对称的方法，（2）数字双波超过，在其中应用机器学习来使用风，波和水位的模型预测来制作警告工具，以及（3）沿海超级超过的投射，以评估未来的变化率较大的危险频率。拟议的项目将使用：（i）基于模型预测（风，波和水位），将Dawlish/Penzance Wirewall数据（观察值）置于训练和验证机器学习算法； （ii）用于校准和验证的相机图像； （iii）卫星图像以研究波场指标的变异性。 MET办公室的重新分析和分析模型数据将从免费可用的数据门户（例如哥白尼海洋服务）以及英国海洋和气候咨询服务中获得。此外，案例研究将被用作演示，该方法将在英国海岸线的其他波浪危害热点位置进行测试，那里有CCTV摄像头或网络摄像头（例如Chesil，Teignmouth）。可靠的警告工具（例如Splash）为那些目前遇到与波浪相关的危害的沿海社区提供了必不可少的信息。飞溅作为预测和投影工具的联合应用将促进沿海实践者的决策，从而减轻已经脆弱的地点气候变化的影响。