- 1National Research Council, Research Institute for Geo-hydrological Protection, Perugia, Italy
- 2RSS-Hydro, Luxembourg
- 3DHI A/S, Denmark
- *A full list of authors appears at the end of the abstract
Floods are among the most destructive natural disasters, causing severe damage to human health, the environment, cultural heritage, and economies. Over the past 50 years, Europe alone has experienced approximately 4,000 fatalities and $274 billion in economic losses due to floods. The situation is even more severe in developing regions, where the lack of infrastructure and resources intensifies the impacts of such disasters. As climate change exacerbates the frequency and intensity of flood events, there is an urgent need for innovative approaches to improve flood forecasting and reduce societal impacts.
EO4FLOOD is a project funded by ESA demonstrating the potential of advanced satellite data in enhancing the accuracy and timeliness of flood forecasting systems. The project focuses on integrating state-of-the-art satellite technologies and hydrological and hydraulic models to deliver reliable flood predictions up to seven days in advance.
EO4FLOOD is structured around three main objectives:
- Development of an Advanced EO Dataset: The EO4FLOOD dataset integrates high-resolution satellite products from ESA and non-ESA missions, providing global coverage of critical variables such as precipitation, soil moisture, snow, flood extent, water level and river discharge.
- Integration into Flood Forecasting Models: By combining these datasets with machine learning-enhanced hydrological and hydraulic models, the project achieves more accurate flood predictions while quantifying uncertainty.
- Demonstration for Science and Society: EO4FLOOD showcases the application of these tools in flood risk management and explores the influence of human activities, such as land-use changes and dam construction, on flood dynamics.
By leveraging cutting-edge algorithms and satellite products, EO4FLOOD provides a robust framework for advancing flood forecasting and supporting effective disaster preparedness and response, highlight its broader implications for global flood risk management.
Angelica Tarpanelli, Guy Schumann, Cecile Kittel, Jafet Andersson, Silvia Barbetta, Peter Bauer-Gottwein, Elia Cantoni Igomez, Connor Chewning, Luca Ciabatta, Denise Dettmering, Omid Elmi, Paolo Filippucci, Laetitia Gal, Miguel González-Jiménez, David Gustafsson, Yeshewatesfa Hundecha, Gilles Larnicol, Kevin Larnier, Christian Massari, Alexandra Murray, Vanessa Pedinotti, Karina Nielsen, Rocco Palmitessa, Adrien Paris, Claus Bjoern Pedersen, Beatriz Revilla Romero, Malak Sadki, Peyman Saemian, Daniel Scherer, Paolo Tamagnone, Christian Toettrup, Marta Toro Bermejo, Mohammad Javad Tourian, Jérôme Benveniste, Karim Douch, Espen Volden
How to cite: Tarpanelli, A., Schumann, G., and Kittel, C. and the EO4FLOOD team: Earth Observation data for Advancing Flood Forecasting: EO4FLOOD project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6671, https://doi.org/10.5194/egusphere-egu25-6671, 2025.
