Groundwater Flooding: Developing an approach to risk assessment and communication

The increasing frequency of extreme weather events is drawing attention to groundwater flooding, which is caused by rising groundwater levels and can result in significant damage to infrastructure, buildings, and the environment. Unlike fluvial or pluvial flooding, groundwater flooding is difficult to detect and not easily managed with traditional protective measures. Numerical models—particularly probabilistic approaches such as Bayesian inference—help to better quantify uncertainties in modeling and forecasting. Flood risk maps are essential for managing groundwater flooding; however, precise uncertainty analyses are often lacking. Citizen science and low-cost sensors can also contribute by bridging data gaps and encouraging public participation. This study presents a framework for assessing vulnerability to groundwater flooding that accounts for uncertainties and generates probabilistic maps. Using a case study from Garching in 2023, it demonstrates how modeling tools can be effectively utilized. Finally, the study suggests expanding monitoring tools and citizen engagement to strengthen risk communication, raise awareness, and better integrate groundwater flood protection measures.