Climate Resilience of EDF's Current Fleet: Impact of Flooding and Erosion from Extreme Rainfall

法国电力公司现有机队的气候适应能力：洪水和极端降雨侵蚀的影响

• 批准号: NE/W006960/1
• 负责人: James Cooper
• 金额: $ 8.93万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FW006960%2F1
• 关键词: Climate; Resilience; EDF; Current; Fleet

This project contributes substantially to enhancing the UK's resilience to climate variability and change through working with key stakeholders to ensure research is fit for purpose. This advance will be achieved by embedding a high qualified researcher in EDF to apply new modelling techniques that examine the vulnerability of their power stations to flooding and erosion from extreme rainfall.Embedded researchers play an important role in connecting businesses and environmental managers to current state-of-the-art in research approaches and techniques. By being embedded in EDF, the researcher will establish a good understanding of day-to-day working, drivers, decision-making contexts, and knowledge and information needs as well as the regulatory requirements for implementation. The researcher will establish an excellent understanding of both operational and planning requirements of flood risk assessment, and vulnerability thresholds for the associated hazard of erosion from surface water flows. The researcher will also identify the organizational mechanisms whereby this improved assessment is put into practice through planning, management and the implementation of the necessary mitigation measures. The researcher will, therefore, develop an intrinsic understanding of the problems due to flooding and erosion from extreme rainfall events, and then bring appropriate knowledge and innovative tools to bear on how these climate-related hazards are best predicted and communicated. Working with both EDF colleagues and University of Liverpool academics, the researcher will undertake assessments of flood and erosion risk that provide useful and usable information, "working collaboratively to generate new knowledge, synthesize and communicate findings to promote learning across relevant science and business domains."The risk modelling comprises models of flood and erosion hazard (probability of impact and extent) and damage (economic loss), the product of which are probability maps of buildings and structures at risk. A hydro-erosion model will be used to produce these maps, allowing the risk to nuclear power generation and decommissioning from extreme rainfall events to be assessed. This model predicts how much rainfall becomes runoff, how runoff is routed according to slope and relief, and how the resulting flows are then able to erode, transport and deposit sediment. Model outputs are fine scale maps of flooding, erosion and deposition, updated slope and relief, and runoff through time.To provide an assessment of erosion hazard from changing event intensity and frequency, UK Climate Change Projections will be used to generate rainfall depth duration frequency curves and river discharge time series for the next 60 years. To quantify the business impact of extreme rainfall and the vulnerability of assets, the project will forecast the economic loss caused by physical damage, judging the cost of mitigation measures against the associated economic benefits.Project outputs will be disseminated to energy sector stakeholders through workshops, conferences and webinars, showcasing how decision-relevant risk data can optimise the deployment of resources and reduce operational costs. This dissemination provides an opportunity to deliver a 'common language' for the communication of storm-related risk, and set an example of best practice in using risk-based analysis to inform operational decision-making.The outputs will include:- Scientific insights into the changing flood and erosion risk to nuclear power stations as a result of climate projections- How erosion hazards influence the vulnerability and resilience of these safety-critical assets to a changing climate- An integrated quantitative predictive modelling framework and decision-support tool that provides the much needed strong evidence base for sustainable, resilient decision making- Deepened engagement between scientists and stakeholders in the energy sector

该项目通过与主要利益相关者合作，确保研究符合目的，大大提高了英国对气候变率和变化的适应能力。这一进步将通过在法国电力公司中嵌入一名高素质的研究人员来实现，该研究人员将应用新的建模技术来检查他们的发电站对极端降雨造成的洪水和侵蚀的脆弱性。嵌入式研究人员在将企业和环境管理人员与当前最先进的研究方法和技术联系起来方面发挥着重要作用。通过加入EDF，研究人员将对日常工作、驱动因素、决策环境、知识和信息需求以及实施的监管要求建立良好的理解。研究人员将建立对洪水风险评估的操作和规划要求以及地表水流侵蚀相关危害的脆弱性阈值的良好理解。研究人员还将确定组织机制，通过规划、管理和实施必要的缓解措施，将这种改进后的评估付诸实践。因此，研究人员将对极端降雨事件造成的洪水和侵蚀问题有一个内在的理解，然后带来适当的知识和创新工具，以承担如何最好地预测和传播这些与气候有关的危害。研究人员将与EDF的同事和利物浦大学的学者合作，对洪水和侵蚀风险进行评估，提供有用和可用的信息，“协同工作，产生新知识，综合和交流发现，促进相关科学和商业领域的学习。”风险建模包括洪水和侵蚀危害（影响的概率和范围）和损害（经济损失）的模型，这些模型的产物是处于危险中的建筑物和结构的概率图。水文侵蚀模型将用于绘制这些地图，从而评估极端降雨事件对核能发电和退役的风险。该模型预测了有多少降雨成为径流，径流如何根据坡度和地形走向，以及由此产生的水流如何侵蚀、运输和沉积沉积物。模型输出是洪水、侵蚀和沉积、更新的坡度和地形以及随时间变化的径流的精细比例尺地图。为了从事件强度和频率的变化中评估侵蚀危害，英国气候变化预测将用于生成未来60年的降雨深度、持续时间、频率曲线和河流流量时间序列。为了量化极端降雨对业务的影响和资产的脆弱性，该项目将预测物理损害造成的经济损失，根据相关的经济效益判断缓解措施的成本。项目成果将通过研讨会、会议和网络研讨会传播给能源部门的利益相关者，展示与决策相关的风险数据如何优化资源部署并降低运营成本。这种传播提供了一个机会，为传播与风暴有关的风险提供了一种“共同语言”，并树立了利用基于风险的分析为业务决策提供信息的最佳实践范例。产出将包括：-对气候预测导致的核电站洪水和侵蚀风险变化的科学见解-侵蚀危害如何影响这些安全关键资产对气候变化的脆弱性和复原力-综合定量预测建模框架和决策支持工具，为可持续、弹性决策——深化能源领域科学家和利益相关者之间的接触