EGU26-6437, updated on 13 Mar 2026
https://doi.org/10.5194/egusphere-egu26-6437
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Monday, 04 May, 17:40–17:50 (CEST)
 
Room 1.15/16
A Cloud-Based DataFabric for Multi-Hazard Nowcasting and Near-Real-Time Disaster Risk Management: The Emilia-Romagna Case Study within the DIRECTED Project
Stefano Bagli1, Paolo Mazzoli1, Valerio Luzzi1, Francesca Renzi1, Marco Renzi1, Tommaso Redaelli1, Debora Cocchi1, Lydia Cumiskey2, Benedikt Gräler3, Clarissa Dondi4, Valeria Pancioli4, Christian Morollli4, Antonio Pesaresi4, Mirco Carlini4, Paolo Pedron4, AnnaMaria Pangalli4, Edoardo Lazzari4, and Max Steinhausen5
Stefano Bagli et al.
  • 1GECOsistema srl, Rimini, Italy (stefano.bagli@gecosistema.it)
  • 2Environmental Research Institute, Beaufort Building University College Cork (LCumiskey@ucc.ie)
  • 352°North Spatial Information Research GmbH (b.graeler@52north.org)
  • 4Agenzia regionale per la sicurezza territoriale e la protezione civile Regione Emilia-Romagna
  • 5Technische Universität Braunschweig

The increasing frequency and intensity of compound hydro-meteorological and wildfire events require advanced, operational, integrated tools capable of supporting early warning and near-real-time Disaster Risk Management (DRM). Within the framework of the EU-funded DIRECTED project, we present the development and operational implementation of a Data Fabric designed for a Real-World Lab in the Emilia-Romagna region (Italy).

The proposed Data Fabric is a cloud-native, serverless web application specifically designed to support nowcasting and short-term forecasting of pluvial and coastal flood hazards as well as wildfire propagation. The system has been co-designed in close collaboration with civil protection authorities (ARPAE) and first emergency responders (firefighters) to ensure operational relevance, usability, and direct integration into emergency workflows.

The platform integrates interoperable real-time observations provided by the ARPAE monitoring network, including weather radar, rainfall intensity, sea level, waves, tides, and wind measurements, together with meteorological and marine forecast models. These heterogeneous data streams are ingested into a scalable processing pipeline that feeds multi-hazard impact models, including high-resolution flood hazard models developed by SaferPlaces and wildfire spread models. The system produces near-real-time hazard maps at building-level resolution, enabling rapid identification of exposed and vulnerable receptors such as population, critical infrastructure, and strategic assets.

Beyond hazard mapping, the Data Fabric supports impact-based decision-making, facilitating the rapid assessment of potential consequences and the design of mitigation, such as flood barriers, and Disaster Risk Reduction (DRR) measures during evolving events. This contribution demonstrates how cloud technologies, interoperable data infrastructures, and stakeholder-driven co-design can be effectively combined to enhance preparedness, response, and resilience in complex multi-hazard contexts. Lessons learned highlight both the opportunities and challenges of deploying advanced digital solutions for operational DRM at regional scale.

How to cite: Bagli, S., Mazzoli, P., Luzzi, V., Renzi, F., Renzi, M., Redaelli, T., Cocchi, D., Cumiskey, L., Gräler, B., Dondi, C., Pancioli, V., Morollli, C., Pesaresi, A., Carlini, M., Pedron, P., Pangalli, A., Lazzari, E., and Steinhausen, M.: A Cloud-Based DataFabric for Multi-Hazard Nowcasting and Near-Real-Time Disaster Risk Management: The Emilia-Romagna Case Study within the DIRECTED Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6437, https://doi.org/10.5194/egusphere-egu26-6437, 2026.