Project start: 01.09.2022
Duration: 28 Monate
Lead: Harald Kunstmann
Involved scientists: Maximilian Graf, Christian Chwala (KIT, Campus Alpin)
Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, Dresden (Verbundkoordinator)
Deutscher Wetterdienst, Offenbach
Technische Universität Dresden
Landesbetrieb Straßen, Brücken und Gewässer Hamburg
Landesamt für Umwelt Bayern, Hochwassernachrichtendienst
Landesamt für Umwelt Rheinland-Pfalz, Hochwassermeldedienst
Landesamt für Umwelt, Bergbau und Naturschutz des Freistaats Thüringen
Ericsson GmbH, Hamburg
The goal of this project is to develop a demonstrator for an "information platform on meteorological-hydrological forecasts and warnings in small catchments" that also evaluates and communicates the uncertainties in the forecasts of precipitation and runoff. The demonstrator links a scalable hydrologic ensemble forecasting system with user-specific visualization and analysis in a web-based dashboard. Furthermore, modules for education and training of users in the use of probability-based warnings and forecasts are planned. In doing so, it integrates novel methods of precipitation estimation using commercial microwave links (CMLs) with a radar multisensor calibration and ensemble-based precipitation forecasts to achieve seamless forecasts with shorter update cycles for the short-term range for flash floods. The demonstrator will undergo extensive, multi-stage validation and demonstration to best support iterative, user-driven development. This will be done in close cooperation with the associated partners for different regions in Germany.
The starting point of the proposed project is the joint project HoWa-innovativ "Early flood warning for small catchments with innovative methods of precipitation measurement and prediction". The solutions developed in HoWa-innovativ, the radar CML adjustment and the web-based demonstrator for early flood warning, show the current state of research. However, for a transfer into practice, further progress in research and development has to be achieved, especially in the fields of radar CML adjustment, the prediction of small-scale heavy rain events and flash floods, the robustness of the data flows as well as the user-specific result communication and system validation.