The C2IMPRESS project has achieved significant milestones in several technical and scientific domains, primarily focused on enhancing disaster and crisis simulations, risk and resilience assessment, and advanced data management for early warning systems. The project established a centralized database for data storage, sharing, and accessibility, alongside the development of an ontology-based knowledge graph for seamless interoperability and efficient data management. This infrastructure enables the integration of diverse datasets, facilitating comprehensive analysis and simulation of multi-hazard scenarios. Additionally, big data analytics tools were employed for social media analysis, extracting valuable insights for decision-making processes. Expanded data visualization tools were also developed to improve the presentation and understanding of analytics. Furthermore, the project created simulation models incorporating human behavior and community response to hazards, such as the Human Behavior Model (HBM) and Agent-Based Model (ABM) in WP2. These models incorporate cognitive reasoning and novel approaches to provide a comprehensive understanding of individual and community responses to hazards. In terms of risk and resilience assessment, the project successfully developed and operationalized the C2IMPRESS Multi-Hazard Risk Management, Exposure, and Resilience Framework. This framework enables comprehensive risk and resilience assessments across various dimensions, reaching even the most vulnerable segments of the community. By integrating data from diverse sources and conducting dynamic vulnerability assessments, decision-makers are empowered with critical insights into vulnerabilities, facilitating informed decision-making and prioritization of mitigation efforts. Moreover, the project led to significant advancements in advanced data management and early warning systems. Existing climatic forecasting and early warning systems were improved for more accurate and timely alerts and forecasts. New Early Warning Systems (EWS) were developed in Turkish, Greek, and Spanish case study areas. Simulation models across various domains such as river basin, groundwater, wildfire, earthquake, and coastal flooding were enhanced to provide a robust framework for understanding hydrologic and hydro-meteorologic dynamics at different scales. The operational deployment of the SoS4MHRIN framework enabled nowcasting, hindcasting, and forecasting simulations for effective detection and prediction of extremes. Decision Support Tools (DST) for Policy Management and HazardActionEye, a real-time automated and interactive decision support tool, were developed to facilitate improved public understanding and decision-making in multi-hazard preparedness policy and planning. Additionally, sophisticated data management tools and techniques were deployed for timely information updates and effective communication of forecasts and early warnings.