Rainfall-induced landslides occur commonly in mountainous areas around the world and cause severe human and infrastructural damage. An early warning system can help people safely escape from a dangerous area and is an economical and effective method to prevent and mitigate rainfall-induced landslides. This paper proposes a method to evaluate soil moisture and shear deformation by compression wave velocities in a shallow slope surface layer. A new type of exciter and new receivers have been developed using a combination of micro electro-mechanical systems (MEMS) accelerometers and the Akaike’s information criterion (AIC) algorithm, which can automatically calculate the elastic wave travel time with accuracy and reliability. Laboratory experiments using a multi-layer shear model were conducted to reproduce the slope failure. The relationships between wave velocities and soil moisture were found to be dependent on the saturation path (rain or drain); in other words, hysteresis was observed. The wave velocity ratio reduced by 0.1–0.2 when the volumetric water content (VWC) increased from 0.1 to 0.27 m3/m3. When loading the shear stress corresponding to slope angles of 24, 27, 29, or 31 degrees, a drop of 0.2–0.3 in wave velocity ratio was observed at the middle layer, and near 0.5 at the bottom layer. After setting the shear stress to correspond to a slope angle of 33 degrees, the displacement started increasing and finally, slope failure occurred. With increasing displacement, the wave velocities also decreased rapidly. The wave velocity ratio dropped by 0.2 after a displacement of 3 mm. Monitoring long-term elastic wave velocities in a slope surface layer allows one to observe the behavior of the slope, understand its stability, and then apply an early warning system to predict slope failure.
An Early Warning System to Detect At-Risk Students in Online Higher Education
