Artificial Intelligence-assisted decadal scale beach change forecasting

英国每年因洪水和海岸侵蚀造成的损失估计为5.4亿英磅。海平面上升和与气候变化相关的极端天气迅速增加了海岸侵蚀和洪水，以及经济影响。英国政府的弹性国家繁荣成果认识到需要实施气候适应、安全和可持续的沿海管理，重点放在自然过程上。规划和实施可持续适应需要新的、有效的工具来预测十年尺度的沿海变化。沿海行为固有的不确定性意味着，这些行为必须建立在人工智能(AI)等先进技术的基础上，以便能够针对多种情况进行高效和可靠的测试。该项目将为应对这一挑战做出重大贡献，并通过采用顺序学习人工智能仿真框架来训练和验证一个有效的人工智能工具，以模拟依赖时间的、十年尺度的海岸地貌动态变化。一个经过良好验证的基于高保真过程的海岸计算模型，由使用蒙特卡洛方法生成的多个十年尺度的连续随机海况时间序列驱动，将为人工智能仿真器的培训和验证提供合成的海滩变化数据，并解决广泛接受的数据稀缺问题。该模拟器将成为计算成本高昂的传统建模方法的强大替代品，用于预测局部和全球范围内十年尺度的海滩变化，并成为发现基于自然的、耐气候的沿海管理干预措施的工具。

Annual UK cost of flood and coastal erosion damage is estimated at £540 million. Sea level rise and extreme weathers associated with climate change rapidly increases coastal erosion and flooding, and economic impacts. The UK Government's Resilient Nation prosperity outcome recognises the need to implement climate-adaptive, safe, and sustainable coastal management, focusing on natural processes. Planning and implementation of sustainable adaptation requires new, efficient tools to predict decadal-scale coastal change. The uncertainty that is inherent in coastal behaviour means that these must be built on advanced technologies such as Artificial Intelligence (AI) to allow efficient and robust testing against multiple scenarios. This project will make a major contribution to tackle this challenge and train and validate an efficient AI tool to emulate time-dependent, decadal-scale coastal morphodynamic change by adopting a sequential learning AI emulation framework. A well-validated high-fidelity process-based coastal computational model, driven by multiple decadal-scale continuous stochastic time series of sea states, generated using a Monte Carlo approach, will provide synthetic beach change data for training and validation of the AI emulator and address the widely accepted data-scarcity issue. The emulator will be a powerful surrogate to computationally costly conventional modelling approaches for predicting decadal-scale beach change at local and global scale, and a tool to discover nature-based, climate-resistant coastal management interventions.