Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 23, issue 2
Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-809-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-809-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 2
Research article
 | 
24 Feb 2023
Research article |  | 24 Feb 2023

Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany

Omar Seleem, Georgy Ayzel, Axel Bronstert, and Maik Heistermann

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Short summary
Data-driven models are becoming more of a surrogate that overcomes the limitations of the computationally expensive 2D hydrodynamic models to map urban flood hazards. However, the model's ability to generalize outside the training domain is still a major challenge. We evaluate the performance of random forest and convolutional neural networks to predict urban floodwater depth and investigate their transferability outside the training domain.
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Advances in pluvial and fluvial flood forecasting and assessment...
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