Real-Time Prediction of Pluvial Floods and Induced Water Contamination in Urban Areas (EVUS)
Pluvial floods in urban areas are caused by local, fast storm events with very high rainfall rates that lead to failure of the drainage system of a city. Such events have a high potential for damage and will, with expected increase of extreme events, become more important in the future. A cascading potential damage during pluvial flooding is the accidental release of hazardous substances. During flooding, transport times to critical points in the urban water system and to leakage points into the deeper subsurface are fast, which may endanger groundwater and surface water quality. Early warning systems for such cases require forecast of rainfall and related flow and transport scenarios. Due to the required long lead time, such forecast modeling scenarios are challenging. In this project, we plan to develop a pluvial forecast model for the city of Hannover, which contains rainfall forecast, forecast of flow and paths and times of contaminant transport in the sewer system, on the surface and the subsurface of the city and rapid damage estimation. Two models for flow will be set up with different levels of complexity. First, a so-called physically based model that captures the physics of flow will be used to calculate possible scenarios. Due to its complexity, prediction of flow cannot be calculated in real-time with such a model. Second, from the scenarios with the physically based flow model, a simplified database meta model will be derived that is fast enough for forecast with a calculation time of minutes. The flow model will be combined with a flood damage model in order to identify critical spots, where the flood should be captured particularly well. A survey will be carried out for damage model development and validation. We will make use of crowd sourcing in order to integrate as much information as possible for calibration, validation and potentially steering of a forecast of flow and transport and possibly for rainfall prediction. For this purpose, devices will be developed that send information on flooding via smart phones. A web-interface will be generated that allows for visualization of predictions and to directly update observations.
Kick-Off Meeting in July 2015