Toolkit to improve resilience of critical ports and dependent national supply chain systems against extreme sea level rise (storm surge) events

作为英国港口基础设施和供应链运营风暴潮风险分析的第一阶段，该项目旨在提高明汉港及其与发电站的关键生物质/煤炭运输环节的弹性。该项目包括以下三个活动：WF1：完善和运行一个创新的人工神经网络（ANN）极端海平面预测模型（NE/M008150/1），用于在明汉应用（潜在应用于其他英国港口，特别是河口内）。WF2：通过利益相关者的参与，将预测的浪涌高度和持续时间转化为对基础设施（设备、设施）和运营的风险（即对生物质/煤炭流量的影响）。WF3：将铁路基础设施和货运列车运动纳入UCL的MARS模型（用于NE/M008150/1），以预测对电力部门的级联影响。

As a first stage in the analysis of storm surge risks to UK port infrastructure and supply chain operation, this project aims to improve the resilience of the port of Immingham and its critical biomass/coal transport link to power stations. The project includes the following three activities: WF1: To refine and operationalize an innovative artificial neural network (ANN) extreme sea-level prediction model (NE/M008150/1) for application at Immingham (with potential application for other UK ports, especially within estuaries). WF2: To translate predicted surge height and duration to risks to infrastructure (equipment, facilities) and operations (i.e. impacts on biomass/coal flows) through stakeholder engagement. WF3: Incorporate railway infrastructure and freight train movements to UCL's MARS model (used in NE/M008150/1) to predict the cascading impacts on the power sector.