Climate change is causing significant impacts, including floods and droughts, which necessitate early warning systems to save lives. However, one third of the global population in least developed countries lacks coverage from these systems.
The EU-funded SEED-FD project aims to address this gap by improving flood and drought detection and predictions globally, particularly in lower and middle-income countries.
Using advanced science, Earth Observation (EO), and non-EO technologies, the project aims to enhance the accuracy and reliability of hydrological simulations and extreme events forecasts.
SEED-FD will collaborate with the Copernicus Emergency Management Service (CEMS) to provide skilful forecasts, thereby improving all aspects of the CEMS Hydrological Forecasting Modelling Chain (HFMC). By integrating state-of-the-art science with new data, the project seeks to transform new observational information into high-quality hydro meteorological extreme event forecast products.
SEED-FD will invest in better representing hydrological processes and parameterization techniques of the CEMS core hydrological engine (LISFLOOD) and combine the model enhancements with innovative techniques to integrate EO and non-EO data with the near real-time hydrological processing chain for reducing hydrological forecasting errors, hence breaking the current limitations of hydrological simulation accuracy where there are no or few in situ data available and make skillful forecasts available anywhere in the world. The enhancements will also drastically improve the monitoring capacity of hydrological status and extreme events worldwide. Using Artificial Intelligence-based event-detection algorithms, SEED-FD will create a new global flash flood forecast product for better anticipation of high-impact events and will create global drought forecast indicators for anticipating food, water, and energy shortages. The evolutions developed in SEED-FD will be domain-agnostic and could be applied to both European or Global domains. However, the benefits are expected to be largest in the global south for lower and middle-income countries, typically the most impacted by extreme hydrological events but also where the current knowledge gap in hydrological simulation and forecasting is highest.
