Influence of trenches and subway system on pluvial flood forecast

The FURBAS project (Forecasting urban floods and strong rainfall events, 2022-2025) aims at establishing a real-time pluvial flood forecast system for the city of Hanover in Germany with a total catchment area of 260km. The forecast system consists of radar rainfall with nowcasting and an Artificial Neuronal Network (ANN) to forecast the dynamical evolution of surface water levels in the city with a spatial resolution of 5x5meter and a temporal resolution of 5 minutes (Berkhahn Neuweiler, 2023). The ANN is trained based on results of a physically based hydrodynamic model (HYSTEM EXTRAN 2D) with bi-directional coupled storm-sewer (1d) to surface (2d) domain.The terrain has a slight gradient which causes a long travel time in the sewer system. The pipe network is partially built as combined sewer and separate sewer system. In the latter, rainfall is partially routed via trenches that are modelled as part of the 2d surface. These trenches are required to get an impression of the overall extent of the flooding and the interaction with the sewer system. In classical modelling approaches the drainage volume vanishes when reaching the outlets of the pipe network which leads to an underestimation of the flood level. We show the effects of modelling trenches as elements of the surface and provide tips for the correct arrangement of trenches.The underground transport tunnels of a city are a rarely modelled factor in the flooding of a city. The underground stations are connected to the public drainage system where it can lead to a drainage delay, due to underground storage tanks. Flooding or overload of the drainage pipes along the underground tunnels have an important influence on the operability of the trains because the inflowing water is pumped into the regular drainage network. The fill level of the pipes is therefore the decisive limit value. We show the effects of station entrances and tunnel ramps to the water level at the surface and how the precipitation intensity is decisive for the operation of the trains.Funding:The FURBAS research project is a cooperation of the Institute for Technical and Scientific Hydrology (itwh) GmbH, the Institute of Fluid Mechanics and Environmental Physics in Civil Engineering, Leibniz University of Hanover, and the municipal operation for Hanover city drainage. The project is funded by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection under grand number 67DAS224.Literature: Berkhahn, S., Neuweiler, I. (2023). Data driven real-time prediction of urban floods with spatial and temporal distribution. Journal of Hydrology X, 100167.