Author(s): Simon Berkhahn; Insa Neuweiler; Lothar Fuchs; Stefan Krämer; Robert Sämann

Linked Author(s):

Keywords: No keywords

Abstract: Urban areas are prone to occurrence of pluvial flooding, which has the potential to inflict significant damage on urban infrastructure. At the same time, the real-time prediction of such events remains challenging. Therefore, there is a necessity for the development of advanced predictive models to mitigate potential risks and enhance urban resilience. In the present study, we show a test case for a model chain for predicting urban flooding in the city of Hanover, Germany. The model chain consists of a radar-based rainfall nowcasting model and a data-driven water level prediction model. The training data base for the water level prediction model was generated with a detailed hydrodynamic model. The objective of this study is to evaluate the predictive capabilities of the entire model chain, rather than merely those of its constituent parts. Therefore, we have utilised a historical event from 2021 to evaluate the model chain.

DOI: https://doi.org/10.71573/dr9zby76

Year: 2025