An improved numerical model for landslide-induced waves and its application to the Huangtian landslide in the XW reservoir, China
Abstract Landslides are one of the most common types of geological disasters. However, the waves generated by landslides often cause more severe damage than the landslides themselves. This paper proposes an improved numerical model for landslide-induced waves. The model’s governing equations are der...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11959-y |
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| Summary: | Abstract Landslides are one of the most common types of geological disasters. However, the waves generated by landslides often cause more severe damage than the landslides themselves. This paper proposes an improved numerical model for landslide-induced waves. The model’s governing equations are derived from the equilibrium of forces acting on columns and principles of fluid dynamics. It can rapidly and effectively simulate the entire process of landslide-induced wave generation. Moreover, the model improves computational efficiency through the use of fixed computational cells, particularly in mountainous regions. The model was validated using a case study by Fernández-Nieto and then applied to simulate the Huangtian landslide-induced waves in the XW reservoir, China. The simulated landslide deposit closely matches the digital surface model obtained from unmanned aerial vehicle surveys. Simulated results showed a maximum wave height of 40.85 m, a maximum run-up height on the opposite bank of 34.1 m, and a wave height of 3.75 m near the dam. The fixed computational cells, which accounted for approximately 22% of the total cells, led to a four-fold improvement in computational efficiency over a full grid approach. Even with the additional cost of the preliminary simulation, the overall method still achieved a 3.7-fold improvement in computational efficiency over a full grid approach. |
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| ISSN: | 2045-2322 |