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

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.

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