Emergency flood planning and management using unmanned aerial systems

在英格兰和威尔士，约有500万人生活在洪水风险地区，每六个家庭中就有一个面临洪水风险。在印度，也存在类似的风险：超过4000万公顷（占印度陆地面积的12%）容易遭受洪水和河流侵蚀。在本世纪，洪水造成的经济损失远远超过其他自然灾害造成的损失（英国27起洪水造成210亿美元损失，印度128起洪水造成390亿美元损失）。此外，随着时间的推移，由于气候变化，洪水和河流洪水的频率和强度预计将增加-增加洪水风险，经济损失和（人）死亡。英国有完善的应急规划流程和程序，但最近发生了一些洪水事件，紧急疏散流程已经延伸到极限甚至更远（例如科克茅斯和卡莱尔）。今年早些时候，印度议会根据《灾害管理法》提出了一项国家行动计划，目的是通过改进我国的救灾工作，大幅度减少生命、生计和资产损失。该计划强调迫切需要改进（预测性）警报、风险和威胁识别及政策评估、疏散规划、数据收集、信息传播、合作和有效管理救济行动。管理这些问题的核心是在关键时刻，特别是在洪水事件发生和发展期间，充分了解基本社区及其基础设施以及这些濒危系统的状况。无人驾驶航空系统的部署和管理（垂直起飞和着陆的四旋翼或小型固定翼飞机）及其数据产品与先进的模型预测能力的结合，似乎是一种具有挑战性但有前途的支持应急规划和管理以及测试政策决定的预测和实际影响的方法。收集和整理有关洪水灾害的相关信息。无人机可以相对容易地部署（通常是手动发射）来评估大面积的损害，这为应急响应人员提供了快速评估情况的机会，从而可以优先考虑资源并在需要时有效部署。研究的一个方面将集中在解决与在这种（非理想）情况下飞行UAS相关的挑战：例如在恶劣天气条件下保持性能，在与基站的间歇性通信丢失期间，克服操作员视觉损失，提供在没有跑道的情况下恢复车辆的能力，并避免与飞行区域内的意外障碍物发生潜在碰撞。该项目还将考虑如何将这些数据与加速洪水淹没模型相结合，以生成详细的疏散计划，并预测洪水的性质和进展，以改善应急资源的分配，建立社区洪水复原力，拯救生命并减少经济损失。该战略将考虑到洪水事件本身的物理性质和受洪水影响的社会结构。这些概念将通过创建一个原型决策支持系统来实现，该系统将使英国和印度应急协调小组或政府机构的实地决策者能够更好地了解洪水的后果，以帮助他们做出及时和更明智的决策。我们还将专注于印度和英国的用户参与和能力建设，以结构化的方式将UAS的使用有效地整合到当前的洪水响应框架中，以最大限度地发挥其所能提供的效益。

Some 5 million people live in flood risk areas in England and Wales, with one in six homes at risk of flooding. In India, similar risks are present: over 40 million hectares (12% of India's land mass) are prone to flooding and river erosion. In this century, the economic losses resulting from damage caused by flooding far outweigh the costs associated with other natural disasters ($21bn in losses from 27 instances in the UK, and $39bn in losses from 128 instances in India). Furthermore, both the frequency and intensity of pluvial and fluvial flooding is expected to increase over time due to climate change - increasing flood risk, financial loss and (human) fatalities. The UK has well-developed emergency planning processes and procedures, and yet there have been a number of recent cases of flooding where the emergency evacuation process has been stretched to its limits and beyond (e.g. Cockermouth and Carlisle). Earlier this year, the Indian Parliament put forward a national action plan under the Disaster Management Act with the aim of substantially decreasing the loss of life, livelihoods and assets, by improving the country's response to disasters. The plan highlights the urgent need for improved (predictive) warning, risk and threat identification and policy assessment, evacuation planning, data collection, information dissemination, cooperation and effective management of the relief operation. At the heart of the management of these issues is developing a good knowledge of the underlying communities and their infrastructure and the state of these endangered systems at critical times, particularly during the onset and development of the flooding event. The deployment and management of unmanned aerial systems (either vertical take-off and landing quad-rotors or small fixed wing aircraft) and of their data product coupled with advanced model prediction capabilities would seem to be a challenging but promising way of supporting emergency planning and management and testing the predicted and actual effects of policy decisions.The project focuses on using instrumented unmanned aerial systems (UASs) to collect and collate pertinent information about an unfolding flooding disaster. The relative ease with which UASs can be deployed (often hand launched) to assess damage across large areas provides emergency responders with the opportunity to assess the situation quickly, allowing the prioritisation of resources and their effective deployment where they are required. One aspect of the research will focus on addressing the challenges associated with flying UASs in such (non-ideal) situations: for example maintaining performance during adverse weather conditions, during intermittent loss of communication with the base station, overcoming the loss of operator visuals, providing the ability to recover the vehicle without a runway and avoiding potential collisions with unexpected obstacles within the flight domain. The project will also consider how the data can be combined with accelerated flood inundation models to generate detailed evacuation plans, and to predict the nature and progress of the flooding to improve allocation of emergency resources, build community flood resilience, save lives and reduce economic damage. The strategy will take into account both the physicality of the flood event itself and the social structures which are subject to the flooding. The concepts will be practically realised by the creation of a prototype decision support system to allow on-the-ground decision makers in the UK and India emergency coordination teams, or government agencies, to better understand the consequences of flooding to help them make timely and better informed decisions. We will also focus on engaging users and building capacity in India and the UK to integrate the use of UASs effectively into current flood response frameworks in a structured way to maximise the benefits they can provide.