KIWA - Artificial Intelligence for flood warning
The management of natural disasters, especially heavy rainfall and flooding, places special demands on the emergency services because it is not possible to predict the exact temporal and spatial distribution of precipitation over time and space. Thus, the locations and measures of disaster prevention can change quickly. Therefore, it is desirable to have a sufficient warning time to "get in front of the situation" and to better assess and evaluate options for action. In the event of flooding, observations of the flowing waters are necessary for accurate pictures of the situation, so that suitable flood defence measures can be taken and their effectiveness checked. The project aims are the development and demonstration of AI-based tools for flood warning and observation, in order to support disaster control and management to cope with large-scale emergencies caused by heavy rain and floods. These tools include data-driven rainfall-runoff models that emulate the behavior of the catchment areas and rainfall from different data sources (ensemble forecasts, short-range forecasts, etc.) for early runoff prediction and warning. Furthermore, AI-based algorithms are developed for image-based, robust quantification of water levels and flow velocities using cameras, which will allow for a remote and mobile operation. The AIs will be integrated into an operations command demonstrator. Through collaboration with associated partners from the field, the requirements for the AI-based demonstrator will be ascertained and its acceptance tested. The project is a joint project with the Chair of Hydrology at the TU Dresden and the Frauenhofer Institute.
More informationen: http://kiwa.hydro.tu-dresden.de/
