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%的铁轨、14.3%的火车站、33%的废水处理和50万处房产面临着沿海洪水的风险。平均每年造成的财产损失超过2.6亿GB。由于建造、维护和适应海平面变化和风暴的高昂成本，硬工程解决方案在经济上正变得不可行。因此，人们对利用自然工程(包括创建盐沼、海草床、海滩营养和巨型营养)越来越感兴趣，因为这提供了一种更经济可行的替代方案，还支持净零碳排放和当地便利设施价值，如政府改善环境的25年计划、英格兰、苏格兰和威尔士的FCERM战略所强调的那样。然而，尽管越来越多的人认识到有必要转向这种更绿色的海岸保护替代方案，但很少或根本没有关于利用自然工程实施的指导意见。没有量化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其独特的当地环境的沿海管理战略。在使工程的建立和寿命最大化的条件方面，仍有许多不确定因素，与其有效性有关的不确定因素也很多。这一奖学金将通过广泛采用工程学与自然相结合的方式，发展保护沿海基础设施和沿海社区所需的新的理解。该研究金将使用遥感、人工智能和计算机模型的新组合，首次利用工程学为海岸保护提供设计标准，并利用选择最持久和最有效的海岸管理类型和地点所需的自然和知识。结果将被汇总成一个交互式决策支持工具，分发给利益攸关方和政府机构，以便对不同沿海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与其有效性有关的不确定性。

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.