Engineering with Nature: combining Artificial intelligence, Remote sensing and computer Models for the optimum design of coastal protection schemes

目前，41%的发电站、17.9%的铁路、14.3%的火车站、33%的污水处理设施和50万处房产面临沿海洪水的威胁。每年的平均财产损失超过2.6亿英镑。由于建设、维护和适应海平面和风暴变化的高成本，硬工程解决方案在经济上变得不可行。出于这个原因，人们对自然工程（包括盐沼、海草床、海滩营养和超级营养的创造）的兴趣越来越大，这提供了一个更经济可行的替代方案，也支持净零碳排放和当地设施价值，这一点在英格兰、苏格兰和威尔士的25年政府改善环境计划、FCERM战略中得到了强调。然而，尽管越来越多的人认识到有必要转向这种更环保的海岸保护选择，但很少有关于实施自然工程的指导。没有定量的和基于过程的决策工具和指导方针来帮助工程师、规划者和政府选择适合他们独特的当地环境的海岸管理策略。与自然工程的建立和寿命最大化有关的条件以及与自然工程的有效性有关的条件仍然存在许多不确定性。该奖学金将通过广泛采用与自然相关的工程来发展对保护沿海基础设施和沿海社区所必需的新理解。该研究金将利用遥感、人工智能和计算机模型的新颖组合，首次提供海岸保护的设计标准，利用具有自然和知识的工程，选择最持久和最有效的海岸管理类型和地点。研究结果将汇总成一个交互式决策支持工具，分发给利益相关者和政府机构，以便对不同海岸管理干预措施的利弊进行一致的评估，包括在不同海平面上升和风暴情景下其有效性的不确定性。

Currently, 41% of power stations, 17.9% of railway track, 14.3% of railway stations, 33% of wastewater treatment and half a million of properties are at risk of coastal flooding. The average damage to properties is over £260million each year. Hard engineering solutions are becoming economically unviable due to the high costs of construction, maintenance and adaptation to changes in sea level and storms. For this reason, there is a growing interest in engineering with nature (including the creation of salt marshes, seagrass beds, beach nourishment and mega-nourishment) which offers a more economically viable alternative and also support net Zero-Carbon emissions and local amenities value as highlighted into the 25 years Government plan to improve the environment, FCERM strategies for England, Scotland and Wales. However, despite the growing recognition about the necessity to move towards this greener alternative for coastal protection, there is little to no guidance on the implementation on engineering with nature. There are no quantitative and process-based decision-making tools and guidelines to aid engineers, planners, and governments to select coastal management strategies fit for their unique local environment. There are still many uncertainties in relation to conditions maximizing the establishment and longevity of engineering with nature and uncertainties in relation to their effectiveness. This fellowship will develop novel understanding necessary to protect coastal infrastructures and coastal communities through widespread adoption of engineering with nature. The fellowship will use a novel combination of remote sensing, artificial intelligence and computer models to provide -for the first-time- design criteria for coastal protection using engineering with nature and knowledge necessary for the choice of the most durable and efficient coastal management type and location. Results will be summarized into an interactive decision support tool which will be distributed to stakeholders and government agencies for a consistent evaluation of pros- and cons of different coastal management interventions including uncertainties in relation to their effectiveness under different sea level rise and storms scenarios.