A Multi-Source Early Warning System of MEMS Based Wireless Monitoring for Rainfall-Induced Landslides

Abstract

Landslide monitoring and early warning systems are the most successful countermeasures to reduce fatalities and economic losses from landslide hazards. The traditional strategies such as GPS and extensometers are relatively expensive and difficult to be installed in steep, high mountains. In this study, a MEMS (Micro Electro Mechanical Systems) based multivariate wireless monitoring sensor unit was used to build a monitoring and early warning system for rainfall-triggered landslides, as one of the most practical and cost-effective countermeasures for hard-reached mountains. The multi-source wireless monitoring system and its well-developed equipment were tested in a landslide-prone slope to monitor the triggering of landslides and debris flows in the Wenchuan earthquake region, China. The variations of several state variables were observed, including the soil moisture content, soil matric suction, rainfall, inclination and ground vibration. The results of a slope stability analysis were benchmarked with the in situ measurements to identify the multivariate early warning parameters for rainfall-induced landslides. The proposed early warning system for the slope stability analysis can provide a more accurate prediction for rainfall-induced landslides and debris flows in earthquake hit regions.

Application and verification of a multivariate real-time early warning method for rainfall-induced landslides: implication for evolution of landslide-generated debris flows

“…Based on previous studies by the authors (Yang et al 2017a;Shao et al 2018;Cai et al 2019;, and through on-site monitoring of the landslide in Yindongzi Gully (Yang et al 2017b), the hydro-mechanical parameters based on 5 years of monitoring were calculated and analyzed to construct a multivariate early warning system for rainfall-induced landslides. This method was based on the unsaturated hydro-mechanical coupling analysis of the measured data.…”

“…1a and can monitor the process, deformation characteristics, and related hydraulic parameters of landslides, thereby providing data for the analysis of landslide processes and the development of early warning systems. The self-developed micro-electromechanical systems (MEMS)-based wireless real-time monitoring system can collect parameters such as precipitation, surface displacement, and soil moisture data in real time (Yang et al 2017b). The data collected in real time are wirelessly sent to the data logger, which is convenient for the remote analysis and management of data from various monitoring sites.…”

“…The I-P model is developed based on the ratio of landslide to rainfall events recorded within each rainfall amount category, and the threshold is defined as the corresponding minimum amount of rainfall in each category that would trigger a landslide (Supplementary material). Considering the great heterogeneity of the landslide deposit, a unified standard for the early warning practice could not be established by using the original soil water content index (Yang et al 2017b(Yang et al , 2019. Hence, in this study the saturation index S i was updated as a uniform parameter for real-time soil moisture and is calculated as follows:…”

An Experimental Study on the Hydromechanical Behaviours of the Evolution of Postearthquake Landslide Deposits

“…The type of pore water pressure sensors was PGM-1KG lowpressure transducer by KYOWA, Japan, which can measure the pore water pressure and soil suction with the installation of a customized porcelain component. The wireless surface tiltmeters were developed by the Chuo Kaihatsu Corporation, Japan, and were compatible with the SCA100T-D01 series 2-axis MEMS tiltmeter module made by Murata [12,38], Japan, with an accuracy of 0.0025°. The type of soil moisture sensors was EC-5 by Decagon, USA; the measurement accuracy of this sensor for the gravelly soil used in this test is ±3%, and its resolution is 0.25%.…”

“…Understanding the evolution mechanism of shallow headward failure and rill erosion of earthquake-induced landslide deposits in the headwater valleys caused by heavy rainfall is key to developing an early warning system of postseismic debris flow disasters [12,13]. The study of rainfall-induced landslides is a fairly complex topic involving a multidisciplinary technology [14].…”