Pluvial flooding caused by heavy rainfall poses an increasing challenge for cities and municipalities. For emergency services, local decision-makers, and infrastructure operators in particular, managing these sudden floods is demanding, as forecasts are still limited. Thus, comprehensive heavy rainfall management is essential. The key challenge lies in the early detection of endangered areas, rapid response during events, and systematic analysis to optimize protective measures.

FloodPrep addresses exactly these issues and aims to support decision-makers and emergency services before, during, and after heavy rainfall events. At the same time, it strengthens the link between science and practice by aligning simulation tools more closely with the requirements of real-world crisis situations.

Core Objectives of the Project

• Experimental real-time simulation of heavy rainfall events for operational support
  Within FloodPrep, two hydrodynamic 1D/2D simulation models will be experimentally tested for the case studies in Graz and Innsbruck. The aim is to evaluate computation times for real-time application during heavy rainfall events. The coupling of surface runoff and drainage system models will be further developed to provide realistic representations of flood hotspots.

• Optimization of operational coordination and decision support
  The models will be tested to assist emergency services and crisis management teams through user-friendly visualization of simulation results. Real-time situational analyses will be evaluated to facilitate decision-making under time pressure. Simulation-based assessments will identify particularly vulnerable urban areas, enabling the prioritization of preventive measures.

• AI-supported model improvement using operational documentation
  Simulation validation will be based on operational data, photos, and video recordings from fire brigades and disaster management authorities. Using artificial intelligence and machine learning, the project investigates how models can be continuously improved based on past event data. Long-term analyses and climate scenarios will also be evaluated to identify future flood risks at an early stage.

• Sustainable integration into urban planning and flood management
  The experimental results will contribute to the assessment of existing flood protection measures to identify potential improvements. The models will also be used to support long-term drainage planning and the development of urban flood management strategies.

Within the project, DCNA is responsible for public relations, dissemination, and the analysis of user requirements and usability.

Project partners besides DCNA

• University of Innsbruck (coordinator)
• Graz University of TechnologysafeREACH GmbH
• KAWUMMS Naturgefahrenmanagement GmbH
• ÖSTAP Engineering & Consulting GmbH
• Innsbrucker Kommunalbetriebe AG
• City of Graz
• City of Innsbruck

The project is financed through the KIRAS funding program of the Austrian Federal Ministry of Finance.