Articles | Volume 25, issue 7
https://doi.org/10.5194/nhess-25-2271-2025
https://doi.org/10.5194/nhess-25-2271-2025
Research article
 | 
08 Jul 2025
Research article |  | 08 Jul 2025

Improving pluvial flood simulations with a multi-source digital elevation model super-resolution method

Yue Zhu, Paolo Burlando, Puay Yok Tan, Christian Geiß, and Simone Fatichi

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Short summary
This study addresses the challenge of accurately predicting floods in regions with limited terrain data. By utilising a deep learning model, we developed a method that improves the resolution of digital elevation data by fusing low-resolution elevation data with high-resolution satellite imagery. This approach not only substantially enhances flood prediction accuracy, but also holds potential for broader applications in simulating natural hazards that require terrain information.
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