Proposals should aim to develop and validate integrated forecasting models, that enhance the prediction and management of multi-hazard scenarios, supports flexibility and extensibility, and coordination of responses by incorporating real-time data, AI-driven analytics, and remote sensing technologies. These models should facilitate improved hazard forecasting by addressing challenges in platform interoperability and data exchange, ensuring that diverse hazard monitoring systems at local, national, and global levels can effectively communicate and operate in synergy.

Efforts should also explore the interoperability of regional and national hazard warning systems, enhancing global forecasting capabilities for hazards such as landslides triggered by extreme weather events, or cumulative damage modelling for earthquakes and their aftershocks. Research should address gaps in loss estimation models by considering the cascading and long-term impacts of disasters on infrastructure, the built environment, supply chains, and diverse needs of communities. Furthermore, proposals should contribute to the development of advanced tools and methodologies to assess the combined effects of multiple hazards on critical infrastructure, ensuring that disaster risk management strategies account for interdependencies across sectors This should include scenario-based stress testing, digital twins for risk modelling, and AI-powered decision-support systems, taking into account existing biases, to enhance resilience planning for lifeline services such as energy, water, transport and telecommunications.

A holistic, systemic, and cross-cutting approach should be applied to disaster risk management, taking into consideration climate change trends, environmental degradation, and vulnerabilities such as gender, age, disabilities and others social factors. The topic should lead to the creation of comprehensive Risk and Resilience Metrics, integrating physical, economic, and social dimensions to support decision-makers in designing effective prevention and adaptation strategies. Considering building on and leveraging from existing systems, such as the Copernicus Emergency Management Service (CEMS) the Destination Earth Platform or Risk Data Hub, could be beneficial.

Projects should conduct a stakeholder or market analysis and a roadmap or plan for uptake of the developed methodologies, findings, and technologies to the industry, the research and innovation community, and/or the relevant authorities.

Projects may take into account the assets but also particular challenges faced by the European outermost regions and may include entities from these regions in the consortium’s composition.

Projects should contribute to strengthening risk governance at multiple levels by fostering collaboration between scientific communities, policymakers, emergency responders, and infrastructure operators. Efforts should be made in leveraging citizens-generated content in social media and decentralised digital platforms for citizen-driven early warning and situational awareness. Alignment with EU policies, international risk reduction frameworks, and best practices in resilience planning should be ensured, maximizing the applicability and impact of the developed solutions. The Preparedness Union Strategy is a key document in this regard and includes a key action on developing an EU comprehensive risks and threats assessment. Finding synergies with projects from operational grants, such as the Knowledge for Action in Prevention & Preparedness (KAPP), is recommended.

Where applicable, proposals should leverage the data and services available through European Research Infrastructures federated under the European Open Science Cloud, as well as data from relevant Data Spaces. Particular efforts should be made to ensure that the data produced in the context of this topic is FAIR (Findable, Accessible, Interoperable and Re-usable).

Technology Readiness Level – Technology readiness level expected from completed projects