Near Real-time Flood Risk Modelling in Response to Increasing Uncertainties in Flood Predictions

In the face of increasing uncertainties and the expected rise in flood events worldwide, this technical note presents an innovative approach for enhancing rapid response capabilities, exemplified during the Kakhovka Dam breach in Ukraine. Utilizing the Tygron Model, our methodology combines open-source data with high performance computing for swift hydrodynamic simulations—a departure from traditional flood risk management techniques. Central to this approach is the strategic use of social media to gather crowd-sourced feedback during the emergency, enhancing the precision and relevance of flood risk information. During the Kakhovka Dam event, our model processed extensive datasets, enabling effective predictions of flood impacts, including extents, velocities, depths, and arrival times. The near real-time modeling capability allowed for dynamic updates using social media inputs, which were of value for emergency responders to optimize response strategies for relief coordination. While the underlying technology is used for flood simulations, its application in emergency response is novel and promising for more adequate disaster response coordination. However, further research and applications are necessary to refine the approach that can ensure real-time flood risk information during a emergency situations.