The Potential of EO Data for Enhanced Flood Monitoring and Forecasting: A Consortium Assessment
Abstract The monitoring and modeling of riverine floods have been covered extensively in the scientific literature with a substantial number of scientific contributions related to calibration/validation of hydraulic and hydrological models and assimilation of Earth Observation (EO) data into them. These models, when used for flood forecasting purposes, rely heavily on ground-based hydrological networks along with numerical weather models which, particularly in data-scarce regions, are often challenged by data sparsity. In these situations, EO data offer a viable solution to enhance the skill of these flood forecasting systems by providing global-scale observations of key hydrological variables such as precipitation, soil moisture, river discharge, water levels, and flood extent. This manuscript reviews and discusses the capability of these EO data in enhancing flood forecasting systems, by analyzing their accuracy, lead time, and reliability, while at the same time highlighting key challenges such as data latency, spatial–temporal resolution trade-offs, and model assimilation constraints. By leveraging recent advancements in remote sensing, data assimilation techniques, and artificial intelligence, EO-based flood forecasting has the potential to bridge existing observational gaps, particularly in vulnerable regions. The paper also outlines future research directions and technological developments needed to maximize the impact of satellite data in operational flood forecasting systems.
Authors
- Adrien Paris (ORCID: https://orcid.org/0000-0003-2304-5132)
- Peter Bauer‐Gottwein (ORCID: https://orcid.org/0000-0002-9861-4240)
- Peyman Saemian (ORCID: https://orcid.org/0000-0003-2612-8718)
- Denise Dettmering (ORCID: https://orcid.org/0000-0002-8940-4639)
- Espen Volden
- Laëtitia Gal (ORCID: https://orcid.org/0000-0002-5054-4992)
- Luca Ciabatta (ORCID: https://orcid.org/0000-0003-4600-6320)
- Kévin Larnier (ORCID: https://orcid.org/0000-0002-4350-6285)
- Vanessa Pedinotti (ORCID: https://orcid.org/0000-0002-6155-7342)
- Silvia Barbetta (ORCID: https://orcid.org/0000-0002-3221-3209)
- Beatriz Revilla-Romero (ORCID: https://orcid.org/0000-0001-5120-4095)
- Yeshewatesfa Hundecha (ORCID: https://orcid.org/0000-0002-9225-1485)
- Èlia Cantoni
- Paolo Tamagnone (ORCID: https://orcid.org/0000-0002-0485-2169)
- Angelica Tarpanelli (ORCID: https://orcid.org/0000-0003-3487-1659)
- Daniel Scherer (ORCID: https://orcid.org/0000-0001-6210-5869)
- Cécile Marie Margaretha Kittel (ORCID: https://orcid.org/0000-0002-7711-9726)
- Malak Sadki (ORCID: https://orcid.org/0009-0000-3140-8170)
- Gilles Larnicol
- Guy J.-P. Schumann
- Connor Chewning (ORCID: https://orcid.org/0000-0001-9963-4668)
- Christian Schwatke
- Paolo Filippucci (ORCID: https://orcid.org/0000-0003-4243-589X)
- Karim Douch
- Jafet Andersson
- Jérôme Benveniste
- Mohammad J. Tourian
- Christian Massari
- Omid Elmi
- David Gustafsson
- Artemis Vrettou
- Karina Nielsen
Institutions
- University of Stuttgart (DE)
- University of Copenhagen (DK)
- Swedish Meteorological and Hydrological Institute (SE)
- Norsk Hydro (Germany) (DE)
- Serco (United Kingdom) (GB)
- Centre National d'Études Spatiales (FR)
- Research Institute for Geo-Hydrological Protection (IT)
- Laboratoire d'Hydrodynamique de l'École polytechnique (FR)
- DHI (DK)
- Magellium (France) (FR)
- European Space Research Institute (IT)
- GMV Innovating Solutions (Spain) (ES)
- Technical University of Denmark (DK)
Publication Details
- Journal
- Surveys in Geophysics
- Published
- 2026-02-15
- DOI
- https://doi.org/10.1007/s10712-026-09935-w
- Citations
- 2
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 73.25
Funders
- European Space Agency
- Consiglio Nazionale delle Ricerche