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%的铁路轨道，14.3%的火车站，33%的废水处理和50万财产面临沿海洪水的风险。平均每年财产损失超过2.6亿英镑。由于建造、维护和适应海平面和风暴变化的成本很高，硬工程解决方案在经济上变得不可行。出于这个原因，人们对利用自然进行工程的兴趣越来越大（包括创造盐沼、海草床、海滩营养和超级营养），这提供了一种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，正如25年政府改善环境计划、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沿海保护替代方案，但在实施自然工程方面几乎没有指导。没有定量和基于过程的决策工具和指导方针，以帮助工程师，规划师和政府选择适合其独特的当地环境的沿海管理战略。在最大限度地建立和使用自然工程的条件方面仍然存在许多不确定性，在其有效性方面也存在许多不确定性。该奖学金将通过广泛采用自然工程来开发保护沿海基础设施和沿海社区所需的新理解。该研究金将使用遥感、人工智能和计算机模型的一种新的组合，首次提供沿海保护的设计标准，利用具有自然和知识的工程，选择最持久和有效的沿海管理类型和地点。结果将汇总成一个互动式决策支持工具，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价，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.