The Challenge
Sudden, intense downpours are one of the most damaging and least predictable climate risks facing cities. When a convective storm drops more rain than the ground and drainage can absorb, water concentrates into flash floods that are not tied to any river or stream, damaging homes, roads, and rail lines in places no conventional flood map anticipated. As the climate warms and cities grow denser, this pluvial flood risk keeps rising.
Managing it well means joining up hazard analysis, forecasting, early warning, and risk communication. In practice those pieces rarely connect: municipalities run standalone tools that don't share data, and the impact side, who and what is actually at risk when a storm hits, is often the weakest link.
InnoMAUS (Innovative Instruments for the Management of Urban Heavy-Rain Risk) is a three-year research consortium funded by Germany's Federal Ministry of Education and Research (BMBF) to close those gaps. It brings together the University of Potsdam, the Technical University of Munich, and KISTERS, with the cities of Berlin and Würzburg as real-world testbeds. Mapular joined as the SME partner responsible for the impact side of the problem.
The Solution
Mapular leads Work Package 4.2: modeling the consequences of extreme rainfall and flash floods on people, buildings, and infrastructure, and making those consequences legible to the people who have to act on them.
The damage and exposure models combine two data sources that are available nationwide, so the approach scales well beyond any single city. The Basic European Assets Map (BEAM) supplies high-resolution information on the value of assets and the number of people per unit area, and OpenStreetMap is used to estimate damage to the road and rail network. Fed with the flood footprints produced by the consortium's rainfall and runoff models, these turn a storm into an estimate of who and what it affects.
Numbers alone rarely drive decisions, though. Mapular builds the results into target-group "storylines": narrative, map-driven infographics that pair quantitative estimates with qualitative context and tailor the same underlying analysis to different audiences, from city planners to emergency responders. The outputs are designed to plug into partners' existing municipal systems through open, standards-based interfaces rather than becoming yet another standalone tool.
Results & Impact
- Damage modeling that transfers. Because the models rely on nationally available data (BEAM and OpenStreetMap), the method carries over from Berlin and Würzburg to other municipalities instead of being hand-built for each one.
- Risk made communicable. The storyline approach turns technical flood-impact output into something planners, authorities, and responders can act on, which is where most hazard data stalls.
- Integrated, not siloed. The work is built to connect into partners' existing infrastructure, supporting early warning as well as long-term planning and prevention.
Key Takeaways
- The impact layer is where flood data becomes useful. Predicting where the water goes matters only if you can say who and what it harms; the exposure and damage model is what turns hydrology into decisions.
- Build on data that exists everywhere. Anchoring the models in nationally available datasets is what makes the approach transferable rather than a one-off.
- Communication is part of the engineering. Target-group storylines are treated as a deliverable in their own right, because analysis that stakeholders can't interpret rarely changes what they do.