DERISC: Deep learning based Extreme Rainfall and flood warnIngs through Seamless foreCasting​

The project will lead to several peer-reviewed publications in open-access journals. We will also present our research findings at international conferences and during a final workshop. These findings will also be presented in a more accessible way during science shows, podcasts or other outreach events for the general public.

By improving the RMI's seamless prediction system, this project is expected to have a substantial societal and economic impact. More accurate operational weather forecasts and warnings delivered by the RMI will directly benefit all its users including the general public through media, the RMI App and website, as well as economic actors such as agriculture, transport and the renewable energy sector.

We will share a minimum viable seamless forecast product for hydrological models early in the project. For other test users, we will provide an interactive dashboard. After thorough validation, these forecasts will be made available through the RMI's open data portal, in accordance with the EU's Open Data Directive.

Providing accurate precipitation forecasts from long to short lead times allows stakeholders to issue early warnings, reduce impact by managing flood control reservoirs by controllable weirs and other hydraulic infrastructure, and warn local authorities in case of a flash flood. This will help prevent deaths, injuries or damages due to extreme precipitation events.

In order to maximize the impact of this project, stakeholders are involved early in workshops and surveys through which they identify their needs and contribute to the design of the forecasting system.