The result “Early warning monitoring solutions for flood defence system” features a digital early warning system that processes and visualises spatially distributed measurement data from fibre-optic sensors at flood defences, enabling continuous risk assessment and early warnings through automated data integration, anomaly detection and correlation with climatic factors such as precipitation. 

The digital solution addresses the need to efficiently post-process, store, interpret and dispaly the large volumes of spatially distributed monitoring data produced by fiber optic monitoring systems installed in flood defence assets. While the monitoring infrastructure generates high-resolution temperature and strain measurements, this raw data alone cannot support operational decision-making. The tool therefore provides a dedicated digital layer that retrieves data from existing cloud services, performs automated processing and integration, and transforms measurements into actionable early-warning information. By linking monitoring outputs with climatic drivers such as rainfall and environmental conditions, the system enables continuous assessment of flood defence state and early identification of anomalous behaviour. This supports timely interventions and risk-informed management, bridging the gap between data acquisition and practical early-warning capabilities required by infrastructure managers. 

The tool is a digital Early Warning System (EWS) designed to process and visualize spatially distributed monitoring data from flood defence infrastructure. It follows a three-layer architecture: sensor layer (data acquisition), integration layer (data processing and modelling), and presentation layer (dashboard interface). The system retrieves data from existing cloud services via API, performs preprocessing and post-processing, and stores harmonized datasets for analysis. Key functions include data aggregation, anomaly detection, threshold-based alerts, forecasting support, and visualization of levee and movable barrier conditions. The dashboard provides geospatial views, time-series analysis, risk indicators, and reporting tools tailored to both technical and non-technical users. Overall, the solution converts raw distributed sensing data into clear early-warning information supporting operational and strategic decision-making. 

The digital solution has been implemented and tested within the MULTICLIMACT project and is currently accessible to project partners on request and authorized users through cloud-connected interfaces from the cloud service of fibristerre. Data retrieval is enabled through APIs linked to existing cloud storage systems, allowing remote access and centralized data management. While operational within demonstrator environments, broader accessibility will require further standardization and user-oriented deployment plus additional development. Future improvements include simplified user onboarding, surrogate model coupling, expanded web access, role-based interfaces (manager vs leyman’s), and potential mobile compatibility for field operations. Interoperability through APIs already facilitates integration with external platforms, supporting scalability beyond the project context. These developments will enable wider adoption by public authorities and infrastructure operators while maintaining data integrity and security.

The user group includes infrastructure managers, water authorities, engineers, emergency responders, and public stakeholders involved in flood risk management. Engineers and technical experts use detailed datasets, processed outputs, and modelling tools for analysis and interpretation. Decision-makers benefit from high-level risk indicators, alerts, and forecasts supporting operational and strategic actions. Field inspectors use georeferenced visualizations to identify critical locations for targeted inspections. The system is designed to accommodate multiple levels of expertise, ensuring that complex monitoring data can be understood and applied by both technical and non-technical users. Within MULTICLIMACT, the tool supports authorities responsible for monitoring, preparedness, and resilience planning of flood defence systems.

The solution contributes by transforming distributed monitoring data into actionable early-warning information through automated processing, storage, and interpretation workflows. By continuously retrieving data from cloud services, the system ensures reliable data availability and supports real-time analysis. It integrates climatic drivers such as rainfall forecasts with monitoring data to detect evolving risk conditions and generate warning signals. Visualization tools and alert thresholds help users quickly interpret infrastructure status and prioritize interventions. This reduces dependency on manual data analysis and enables faster, evidence-based decision-making. The tool therefore bridges the gap between monitoring technology and operational management, enhancing preparedness, reducing risk, and improving resilience of flood defence infrastructure. 

The digital solution has been tested within MULTICLIMACT demonstrator environments, including the Leidschendam levee and Flood Proof Holland experiments. Testing validated automated cloud data retrieval, processing workflows, dashboard performance, and early-warning functionalities. The system demonstrated reliable ingestion and handling of large spatial datasets, effective visualization, and real-time alert generation based on processed indicators. Feedback from engineers and infrastructure stakeholders supported refinement of interface design, alert visualization, and data interpretation functions to better match operational needs. Movable barrier experiments confirmed the platform’s capability to identify strain anomalies and support rapid decision-making. Continued testing in demo sites will focus on long-term usability, robustness, and operational integration under real climatic conditions.