The SEED-FD project is advancing global flood and drought forecasting by developing hydrometeorological datasets that integrate satellite technology with innovative methods. These datasets aim to improve early warning systems, with a focus on vulnerable regions in the Global South, where enhanced forecasts can significantly improve disaster preparedness. By bridging gaps in hydrological modelling, SEED-FD contributes to a safer and more resilient future, addressing the growing challenges of climate-induced disasters.
Building a Reliable Data Basis for Hydrological Models
The development of precise and reliable datasets for precipitation, river discharge, water levels, and soil moisture is a fundamental aspect of SEED-FD, forming the basis for further research and advancements in flood and drought prediction.
For precipitation, the project combines classical satellite data from the Global Precipitation Measurement (GPM) mission, a collaboration between NASA (the United States’ National Aeronautics and Space Administration) and JAXA (the Japan Aerospace Exploration Agency). This integration, alongside innovative bottom-up methodologies obtaining precipitation from soil moisture data (SM2RAIN), developed within the project, enhances the accuracy of rainfall data, making it applicable to regions around the globe.
River discharge and water level, which are closely related, are challenging to measure directly from space. SEED-FD addresses this by developing proxy datasets that estimate variables correlating with river flow. This combines classical satellite altimetry, which measures water elevation over time, with innovative optical data methods developed within the project. The result is improved temporal resolution, up to one to two days. Current datasets already support hydrological models in critical use case river basins such as the Danube, Niger, and Paraná.
Soil moisture datasets, provided by the Copernicus program, play a vital role in drought monitoring and assessment. As these datasets are globally available, SEED-FD is working to identify the most suitable data for specific project needs. This careful selection ensures that the datasets align with spatial and temporal requirements, making them ready for integration into hydrological models. By leveraging these tailored datasets, SEED-FD enhances advancing drought forecasts in diverse use case regions.
Animation: Global precipitation patterns. This animation visualizes global monthly precipitation using the SM2RAIN-ASCAT dataset, derived by converting EUMETSAT ASCAT satellite soil moisture data into rainfall estimates. In SEED-FD, this dataset complements direct measurements from the Global Precipitation Measurement (GPM) Mission, filling gaps in regions with limited observations. Together, these datasets enhance hydrological models and improve global flood and drought forecasting. Access the dataset here: SM2RAIN-ASCAT.
Ensuring Quality and Sharing Knowledge
The reliability of SEED-FD’s datasets is ensured through rigorous validation processes. Each dataset is compared against ground-based measurements, such as rain gauges for precipitation and micro-stations for water levels. These in-situ tools provide essential benchmarks, ensuring that the satellite-derived data meets the highest accuracy standards.
While precipitation data is ready for immediate use, other datasets, like river discharge, are further processed by normalizing the data in the same data range to make them comparable. This step ensures smooth integration of the datasets into workflows within the project.
Collaboration is a key pillar of the project. SEED-FD relies on a centralised repository, which allows all partners to access the datasets efficiently. This shared platform not only ensures seamless data exchange but also fosters a spirit of collaboration across the consortium.
Validating Innovations Through Real-World Use Cases
SEED-FD is currently in the development phase, focusing on advancing hydrological models, refining algorithms, and improving predictions for a wider range of extreme weather events. While this phase is dedicated to these developments, the datasets for precipitation, river discharge and water levels, as well as soil moisture, are particularly important in the subsequent validation phase. Use case regions, such as the Juba-Shebelle, Niger, and Paraná river basins, play a key role in testing the applicability and accuracy of SEED-FD’s new developments. Through the integration of these datasets into flood and drought models, SEED-FD ensures that its innovations are thoroughly validated, paving the way for enhanced forecasting systems.
The Impact of SEED-FD’s Innovations on Disaster Resilience
One important innovation of SEED-FD is the use and testing of satellite-based precipitation datasets for global flood forecasting for the first time. This effort contributes to enhancing the accuracy and capabilities of early warning models used within the Copernicus Emergency Management Service (CEMS). By improving the hydrological models that underpin these operational forecasting systems, SEED-FD advances both scientific knowledge and practical outcomes, directly benefiting at-risk populations.
SEED-FD is dedicated to delivering tangible benefits for stakeholders, including governments, humanitarian organizations, and local communities. By integrating satellite datasets into operational early warning systems, the project improves both the accuracy and timeliness of flood and drought predictions, providing crucial support for disaster preparedness and response. In regions with limited access to ground-based monitoring infrastructure, these datasets offer a reliable foundation for building resilience. They equip communities and decision-makers with the tools to act proactively in the face of extreme weather events, reducing risks and mitigating potential impacts.
Creating New Datasets – Conclusion and Next Steps
In the coming months, SEED-FD will focus on tailoring its datasets, ensuring they align with the needs of diverse hydrological models and use cases. This includes refining spatial and temporal resolutions – for example, providing precipitation data with daily or sub-daily updates and river discharge data over varying timeframes. These adjustments ensure that the datasets are optimized for effective integration into forecasting systems.
Through ongoing collaboration and refinement, SEED-FD is set to play a critical role in shaping a safer, more resilient world. The integration of satellite technology into disaster management represents a significant step forward in addressing the challenges posed by climate change.
Stay tuned for updates on SEED-FD’s progress and discover how its work is transforming disaster preparedness for communities around the globe.