Multi-hazard and risk informed system for Enhanced local and regional Disaster risk management

该项目将开发一个灾害风险管理决策支持系统（DSS），通过使用一种新的弹性信息和面向服务的方法，考虑多种相互作用的自然灾害和级联影响，该方法考虑了灾害（如气候变化）、脆弱性/弹性（如结构和人口老龄化）和暴露（如人口减少/增加）的预测变化。medium的主要交付成果将是一个面向服务的网络工具形式的决策支持框架和附带的灾害风险管理框架，为最终用户（地方当局、企业等）提供构建准确情景的能力，以模拟其缓解和适应风险管理行动的潜在影响。这些情景可以根据当地的条件和需要（例如人口、贫困、自然资源等）进行定制，这些情景将基于历史记录和未来气候变化预测的结合，以预测与气候有关的灾害事件的地点和强度，并预测其影响，包括对当地自然、经济和社会系统脆弱性的级联影响。这些情景将允许最终用户评估不同风险管理策略的潜在影响，以减少脆弱性并增强社区复原力。该项目将包括分析相关数据，并与决策支持系统的试验台决策者共同开发一个决策支持系统，以便进行更可靠的复原力评估，考虑风险缓解和适应能力，从而减少未来气候相关灾害和地球物理灾害造成的（人力、财力、环境等）损失。该项目将涉及一个由地球物理和气象科学家、风险工程师、社会科学家、信息技术专家和最终用户组成的多学科团队，共同努力确保该系统由用户主导并得到适当技术的支持。

This project will develop a decision-support system (DSS) for disaster risk management by considering multiple interacting natural hazards and cascading impacts using a novel resilient-informed and service-oriented approach that accounts for forecasted modifications in the hazard (e.g., climate change), vulnerability/resilience (e.g., aging structures and populations) and exposure (e.g., population decrease/increase). The primary deliverable from MEDiate will be a decision support framework in the form of service-orientated web tool and accompanying disaster risk management framework providing end users (local authorities, businesses etc) with the ability to build accurate scenarios to model the potential impact of their mitigation and adaptation risk management actions. The scenarios, which can be customised to reflect local conditions and needs (e.g., demographics, deprivation, natural resources etc), will be based on a combination of the historical record and future climate change projections to forecast the location and intensity of climate related disaster events and to predict their impacts, including cascading impacts, on the vulnerability of the local physical, economic and social systems. The scenarios will allow end users to evaluate the potential impact of different risk management strategies to reduce vulnerability and enhance community resilience. The project will consist of analysis of relevant data and co-development with testbed decision-makers of a DSS to enable more reliable resilience assessments, accounting for risk mitigation and adaptive capabilities, to be made, therefore reducing losses (human, financial, environmental etc) from future climate-related and geophysical disasters. The project will involve a multi-disciplinary team of geophysical and meteorological scientists, risk engineers, social scientists, information technologists and end users, working together to ensure that the system is user-led and supported by appropriate technology.