[S-SS07] Environmental Seismology: from deep earth to surface process

[SSS07-12] Real-time Landslide and Rockfall Monitoring Method Based on Distributed Acoustic Sensing

*Peng Wu¹, Chen Gu¹, Yichen Zhong¹, Zhi Yuan¹, Zhuoyu Chen¹, Jiawei He¹ (1.Tsinghua University)

Keywords:Distributed acoustic sensing, Ambient noise cross-correlation, Rainfall-induced slope instability, Landslides, Rockfalls

Rainfall is a critical triggering factor for landslides and rockfalls, as it increases soil saturation and reduces slope stability. Understanding how rainfall influences slope stability is essential for developing effective monitoring and early warning systems. In this study, we utilize Distributed Acoustic Sensing (DAS) to monitoring rainfall-induced slope instability by analyzing ambient seismic noise cross-correlation applied to DAS data recorded via subsurface fiber-optic cables. A one-month field experiment was conducted on a slope in Yunnan province, China, where optical fibers were deployed to capture high-resolution acoustic data. Through ambient noise cross-coreelation, we observed variation in the shallow subsurface velocity model, revealing a clear response to rainfall events and an indication fo slope instability. Additionally, benchmark rockfall experiments were performed to observe the acoustic signals generated by rolling stones, enabling real-time trajectory tracking and energy estimation. By establishing a quantitative link between rainfall, seismic velocity changes, and slope stability, this study advances the development of a comprehensive, real-time landslide and rockfall monitoring system. Our findings highlight the potential of DAS as a scalable and cost-effictive tool for geohazard assessment in landslide-prone regions.