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

工程与自然：结合人工智能、遥感和计算机模型，优化海岸保护方案设计

基本信息

批准号：
EP/V056042/1
负责人：
Nicoletta Leonardi
金额：
$ 96.99万
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FV056042%2F1
关键词：
Engineering Nature combining Artificial intelligence

项目摘要

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.

目前，有41％的电力站，铁路轨道的17.9％，火车站的14.3％的沿海洪水风险每年对财产的平均损害超过26000万英镑。由于这个原因，对自然海滩营养和大型养育的工程越来越兴趣）敌人重视了25个Youars政府计划，尽管对英格兰，苏格兰和威尔士的FCERM策略，但人们对朝鲜的策略越来越多。这种用于自然工程的沿海保护植物没有定量和基于过程的工具和指南，以帮助工程师，策略和政府选择适合适合拟合适合您的选择。适合适合适合适合适合适合适合适合拟合适合适合适合适合适合适合适合适合适合适合适合适合适合适合适合拟合适合适合适合适合适合适合适合适合合身的适合效果，以最大化自然不确定性的工程寿命。 ELOP通过广泛采用遥感，人工智能和模型来保护沿海基础设施和社区所必需的理解。位置。将分配给利益相关者机构，以始终如一地评估不同的沿海管理企业的利弊，包括在不同的海平面上升和风暴场景下与其有效性有关的不确定性。