H2020
Europeo
ExpectedOutcome:Projects’ results are expected to contribute to some of the following outcomes:
Innovative exposure and vulnerability analysis methods, including those that take a systemic perspective by integrating sectoral expertise (e.g. social science, human health, cultural heritage, environment and biodiversity, public financial management and key economic sectors) and identifying key vulnerable groups and assets.Maximising usability through a service-oriented approach, including through the optimisation and tailoring recommended practices, scientific models and scenarios for the intended users to support technical policy improvements and implementation of actions.Enhanced exploitation of monitoring data and satellite/remote sensing information as well as artificial intelligence to improve high-level assessment from international to local levels, identifying the major sources of uncertainty in hazard assessment and ways to reduce them. Evaluation of existing disaster risk and resilience assessment and scenarios (at national and local levels), taking into account historical / geological data, monitoring, risk and forecasting data, and based on the evaluation, seri...
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ExpectedOutcome:Projects’ results are expected to contribute to some of the following outcomes:
Innovative exposure and vulnerability analysis methods, including those that take a systemic perspective by integrating sectoral expertise (e.g. social science, human health, cultural heritage, environment and biodiversity, public financial management and key economic sectors) and identifying key vulnerable groups and assets.Maximising usability through a service-oriented approach, including through the optimisation and tailoring recommended practices, scientific models and scenarios for the intended users to support technical policy improvements and implementation of actions.Enhanced exploitation of monitoring data and satellite/remote sensing information as well as artificial intelligence to improve high-level assessment from international to local levels, identifying the major sources of uncertainty in hazard assessment and ways to reduce them. Evaluation of existing disaster risk and resilience assessment and scenarios (at national and local levels), taking into account historical / geological data, monitoring, risk and forecasting data, and based on the evaluation, serious games, modelling of future scenarios accounting for current and future impacts of diverse extreme events and disasters.
Scope:The assessment of disaster risks requires different types of actions ranging from soft measures to technologies. Simulation-based risk and impact assessments represent an effective approach to make science understandable to decision makers and streamline national to local mitigation/adaptation actions. This is especially the case if they are integrated with evaluation tools for cost-benefit/effectiveness and multi-criteria analyses, data-farming experiments, serious games, and are tailored to meet end-user’s needs, to assess the effectiveness of alternative options in different phases of the Disaster Risk Management cycle.
Specific risk assessments should be decision- or demand-driven and informed by scientific evidence, and there is a clear need to translate the results to ensure they are relevant, usable, legitimate and credible from the perspectives of the users. Co-design, co-development, co-dissemination and co-evaluation engaging the intended end users represent in this sense key features of improved risk, resilience and impact assessments.
In a first place, the acquisition of data is an essential feature and this requires innovative solutions for faster risk assessment and reduction. This includes the identification of precursors for different types of threats, supporting the design or improvement of risk-targeted monitoring programmes. In addition, risk assessments themselves are primarily designed to predict the likelihood of a specific event, whereas what is of primary concern is the impact of that event on society, infrastructure, governance, etc. Numerous experiences gathered in the natural hazards area showed that an enhanced assessment of risks and scenario building may be improved by taking into account reliable data (both quantitative and qualitative) and historical occurrences, when available, including disaster loss data (studies of past events in particular low-probability / long-time recurrence events). This includes for example a higher completeness of the historical-geological records of volcanic eruptions, major earthquakes, tsunamis etc.
In the case of extreme climate events such as storms and related storm surges, or health crises (outbreaks, pandemics) the analysis should draw on the outputs of state-of-the-art climate projections, including by taking into account the uncertainties brought on by climate change and our state of knowledge of the key processes underpinning the functioning of the Earth system.In cases where there are not be enough historical data and a high level of uncertainty, assessments and decision making will have to rely on qualitative data.
The action should take into account disaster loss databases and risk data repositories in Member States and relevant hubs. This topic requires the effective contribution of SSH disciplines and the involvement of SSH experts, institutions as well as the inclusion of relevant SSH expertise, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities. In order to achieve the expected outcomes, international cooperation is encouraged.
Where possible and relevant, synergy-building and clustering initiatives with successful proposals in the same area should be considered, including the organisation of international conferences in close coordination with the Community for European Research and Innovation for Security (CERIS) activities and/or other international events.
Cross-cutting Priorities:International CooperationSocio-economic science and humanities
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