Chen Yulong, Irfan Muhammad, Uchimura Taro, Zhang Ke
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China.
Department of Civil Engineering, The University of Tokyo, Tokyo 113-8656, Japan.
Sensors (Basel). 2018 Mar 27;18(4):997. doi: 10.3390/s18040997.
Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate.
降雨引发的山体滑坡是全球范围内最普遍的边坡失稳现象之一,对公共安全构成严重威胁,因此其时间预测对于建立有效的预警系统至关重要。本研究的目的是确定边坡表层弹性波速度在滑坡监测、预测和预警中的有效性。进行了小规模的固定和可变以及大规模的边坡模型试验。结果分析表明,弹性波速度随含水量和变形的变化而持续降低,在破坏开始时波速降低率有明显激增。基于该分析的初步结果,利用弹性波速度变化的方法在滑坡预警方面表现出色,并建议在波速降低率发生变化时发出预警。