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

该项目通过与主要利益攸关方合作，确保研究符合目的，大大有助于提高联合王国对气候变异和变化的适应能力。这一进步将通过在EDF中嵌入一名高素质的研究人员来实现，以应用新的建模技术来检查其发电站对洪水和极端降雨侵蚀的脆弱性。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。通过嵌入EDF，研究人员将建立对日常工作，驱动程序，决策环境，知识和信息需求以及实施监管要求的良好理解。研究人员将建立一个良好的理解洪水风险评估的业务和规划要求，并从地表水流侵蚀的相关危害的脆弱性阈值。研究人员还将确定通过规划、管理和执行必要的缓解措施将这种改进的评估付诸实践的组织机制。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，以了解如何最好地预测和传达这些与气候相关的灾害。研究人员将与EDF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，“合作产生新知识，综合和交流发现，以促进相关科学和商业领域的学习。“风险模型包括洪水和侵蚀危害（影响概率和范围）和损害（经济损失）模型，其产品是面临风险的建筑物和结构的概率图。将使用水力侵蚀模型制作这些地图，以便评估极端降雨事件对核能发电和退役的风险。该模型预测有多少降雨成为径流，径流如何根据坡度和地形进行路由，以及由此产生的水流如何能够侵蚀，运输和存款沉积物。模型输出的洪水，侵蚀和沉积，更新的坡度和救济，并通过time.To提供一个不断变化的事件强度和频率的侵蚀危害评估细比例尺地图，英国气候变化预测将用于生成降雨深度持续时间频率曲线和河流流量时间序列，为未来60年。为了量化极端降雨对业务的影响和资产的脆弱性，该项目将预测物理破坏造成的经济损失，判断缓解措施的成本与相关的经济效益。项目成果将通过研讨会、会议和网络研讨会传播给能源行业的利益相关者，展示与决策相关的风险数据如何优化资源部署和降低运营成本。这种传播提供了一个机会，为风暴相关风险的沟通提供了一种“共同语言”，并在使用基于风险的分析为业务决策提供信息方面树立了最佳做法的榜样。- 对气候预测导致的核电站不断变化的洪水和侵蚀风险的科学见解-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、有弹性的决策提供急需的强有力证据基础-深化能源部门科学家和利益攸关方之间的接触

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