Deadline: 05-Nov-2026
The European Commission is accepting grant applications to develop next-generation systems for predicting and managing cascading and cumulative disaster impacts. The initiative aims to unify single-hazard models into integrated frameworks capable of analysing complex interactions between meteorological, geophysical, and technological hazards. It supports improved forecasting, resilience planning, and coordinated disaster response across Europe and beyond.
Programme Objective
The primary objective is to build advanced predictive systems that can model cascading disaster effects across interconnected hazards. These systems should improve understanding of how multiple hazards interact and compound risks across societies, economies, and critical infrastructure. The goal is to strengthen anticipatory action, early warning capabilities, and resilience planning at all governance levels.
Funding Information
The total funding available for this topic is €8,000,000. Individual project contributions are expected to be around €4,000,000. The funding supports research, system development, validation, and deployment of integrated disaster risk modelling solutions.
Key Focus Areas
The programme focuses on several interconnected technical and policy areas, including multi-hazard risk assessment, cascading and cumulative impact modelling, predictive modelling systems, hazard forecasting, and scenario-based stress testing. It also emphasizes AI-driven analytics, digital twins, early warning systems, data interoperability, and disaster risk governance frameworks.
Multi-Hazard and Cascading Risk Modelling
A central priority is developing systems that integrate multiple hazard models into a unified framework. These systems must analyse cascading effects where one hazard triggers or amplifies another. This includes interactions between climate-related events, geological hazards, and technological or infrastructure failures, with attention to compound and long-term impacts.
Predictive Modelling and AI Integration
The programme supports the use of advanced predictive models powered by artificial intelligence and machine learning. These models should incorporate real-time data, remote sensing inputs, and historical datasets to improve forecasting accuracy. AI-driven analytics are expected to enhance early warning systems and decision-support capabilities.
Early Warning and Anticipatory Action Systems
Projects should strengthen early warning systems and enable anticipatory disaster response. This includes improving detection speed, prediction accuracy, and communication of risk information to decision-makers and the public. The goal is to support timely interventions that reduce loss of life and economic damage.
Interoperability and Data Sharing
A key requirement is improving interoperability between hazard monitoring systems across local, national, and global levels. Systems must enable seamless data exchange and integration across platforms and institutions. The initiative also promotes standardized data sharing practices to enhance coordination and collaboration during emergencies.
Risk and Resilience Metrics
The programme emphasizes the development of holistic risk and resilience metrics that incorporate physical, economic, and social dimensions. These metrics are intended to support policymakers in evaluating vulnerability and designing effective adaptation and prevention strategies for complex disaster environments.
Digital Twins and Advanced Simulation Tools
Projects are encouraged to use digital twins, simulation models, and stress testing methodologies to replicate real-world infrastructure and environmental systems. These tools help assess the combined effects of multiple hazards and support scenario-based planning for disaster preparedness and response.
Cascading and Long-Term Impact Assessment
Proposals must address cascading effects of disasters on infrastructure systems, supply chains, and communities. They should also consider long-term vulnerabilities influenced by climate change, environmental degradation, and socio-economic conditions. The focus is on systemic risk rather than isolated hazard events.
Governance and Policy Integration
The initiative promotes a cross-cutting approach that integrates scientific research, operational response, and governance frameworks. Projects should align with EU resilience policies and international disaster risk reduction frameworks. Citizen-generated data and community-level inputs are also encouraged to improve inclusivity.
System Requirements
Proposed solutions must be adaptable, scalable, and capable of operating across different geographic and institutional contexts. They should support real-time analytics, interoperability, and integration with existing emergency management systems. Flexibility to evolve with emerging risks is a key requirement.
Eligibility Criteria
Any legal entity may participate in the programme, including organisations from non-associated third countries and international organisations. Participation is subject to Horizon Europe eligibility conditions. The programme encourages collaboration among research institutions, public authorities, technology developers, and private sector actors.
Why This Programme Matters
This initiative addresses the increasing complexity of disaster risk in a changing climate and interconnected world. By focusing on cascading impacts and multi-hazard interactions, it helps improve preparedness, reduce systemic vulnerabilities, and strengthen resilience. It supports smarter decision-making for governments and emergency agencies dealing with large-scale crises.
Common Mistakes to Avoid
Applicants often fail by treating hazards independently instead of modelling cascading interactions. Some proposals lack strong interoperability or real-time data integration components. Others underestimate the importance of governance alignment or fail to include scalable, cross-border solutions. Weak incorporation of AI, digital twins, or validation frameworks can also reduce competitiveness.
Tips for a Strong Application
Successful proposals should integrate multi-hazard modelling with AI-driven analytics and real-time data systems. They should clearly demonstrate interoperability across platforms and governance levels. Strong use of digital twins and scenario-based stress testing is highly recommended. Projects should also include clear pathways for operational adoption and alignment with EU disaster risk reduction strategies.
Frequently Asked Questions
- What is the main goal of this EU programme?
It aims to develop advanced systems for predicting and managing cascading and multi-hazard disaster impacts. - How much funding is available?
The total funding is €8,000,000, with about €4,000,000 per project expected. - What types of hazards are included?
Meteorological, geophysical, technological, and cascading multi-hazard events. - What technologies are encouraged?
AI analytics, digital twins, predictive modelling, early warning systems, and interoperable platforms. - Who can apply?
Any legal entity, including organisations from non-associated third countries and international organisations, under Horizon Europe rules. - What is meant by cascading disasters?
Disasters where one hazard triggers or intensifies another, creating compound impacts across systems. - Why is interoperability important?
It ensures seamless data sharing and coordination between different monitoring and response systems.
Conclusion
The European Commission’s cascading disaster risk modelling programme aims to transform how Europe predicts and responds to complex, multi-hazard events. By integrating AI, digital twins, and interoperable systems, it enables more accurate forecasting and stronger resilience planning. The initiative supports a systemic approach to disaster risk management that improves preparedness, coordination, and long-term societal resilience.
For more information, visit European Commission.
