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March 3, 2026
Integrating machine learning and numerical methods for enhanced landslide susceptibility and hazard mapping in the Bhotekoshi watershed, central Nepal
BG
Bishal Gurung
NC
Ningsheng Chen
GH
Guisheng Hu
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Key Points
Enhanced prediction accuracy of landslide susceptibility using machine learning algorithms allows for better hazard mitigation.
Landscapes in the Bhotekoshi watershed were analyzed, revealing critical zones prone to landslides and natural hazards.
The approach involved a combination of machine learning techniques and numerical modeling to assess risks effectively.
Implications suggest that this integrated strategy can significantly improve land management practices and disaster preparedness.
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Cite This Study
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Gurung et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761f4c6e9836116a300b5
https://doi.org/https://doi.org/10.1007/s11629-025-9951-2
Integrating machine learning and numerical methods for enhanced landslide susceptibility and hazard mapping in the Bhotekoshi watershed, central Nepal | Synapse