This session concentrates on extreme rainfall events, surface water dynamics, and flood events, exploring innovative remote sensing, AI, and digital twin technologies for real-time monitoring, risk assessment, and mitigation. It invites submissions on advanced data integration, modeling approaches, early warning systems, and decision-support tools to improve understanding, forecasting, and management of flooding and related surface water hazards.

The integration of AI with digital twin improves the analytical and operational capabilities of geospatial systems, which through the analysis of historical data and the integration of real-time information (IoT) are able to highlight even “hidden patterns” in the data, identifying new models capable of improving forecasts with greater control over the quantification of uncertainty and the variability of the phenomenon analysed.

This session aims to focus on flood hazard and risk assessment, monitoring, and management. This Topic invites the submission of articles focused on, but not limited to, the following areas:
• Monitoring of extreme rainfall events and flood hazards for risk assessment and communication.
• Digital twins (DTs)/prototypes of DTs in flood hazard forecasting, early warning, monitoring, and supporting tools for urban governance.
• DSSs to extract meaningful information in the artificial intelligence era, eventually serving to reduce risk and provide support tools to mitigate flood hazards.
• The role of AI and digital twins to assess the economic impacts of flood hazards and the cost-effectiveness of various mitigation strategies.
• Novel techniques to analyse big data coming from Earth observation platforms, drones, and other geospatial data in order to provide timely information related to the extend, exposure, and impacts of flood hazards.