Associated with climate change are the rising frequency, probability, and intensity of natural hazards, as stated by IPCC (2014). To contribute to the evaluation of climate change consequences, we study the impact of river floods caused by torrential rain periods, which are supposed to become and already are one of the major future challenges. Since subsequent flood and adaptation measures are usually interdependent, identifying causal effects is the main challenge. Therefore we investigate a sequence of river floods and subsequent adaption measures in a natural experiment setting. Our study area is the city of Dresden, Germany in the time period from 2000 until 2017. Remarkable in this setting is the exogeneity of the first flood event in 2002 that hit the city unexpectedly after 60 years without considerable flood events. We use a complete set of lot transactions from 2000 until 2017 to study the effect of these events on lot prices. The basis of our identification strategy is a Difference-in-Differences design in which we control for an unstable assignment to treatment and control group. Additionally we consider the heterogeneity of the treatment, which is caused by the varying intensity levels during a flood. It shows that flood risk is incorporated into lot prices only after awareness is risen due to a sudden flood event and that a higher expected intensity increases discounts. A long-term effect can be verified once we control for adaption, such as public protection measures.