A new prediction method for the occurrence of landslides based on the time history of tilting of the slope surface

Xie, Jun; Uchimura, Taro; Wang, Gonghui; Shen, Qian; Maqsood, Zain; Xie, Canrong; Liu, Jiapeng; Lei, Weikai; Tao, Shangning; Chen, Pan; Dong, Hongyuan; Mei, Guoxiong; Qiao, Shan

doi:10.1007/s10346-019-01283-8

Cited by 31 publications

(23 citation statements)

References 27 publications

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“…The direction of the tilt angles can also predict the possible failure plane, as the sensors placed above the failure plane tilts backward with the sliding slope, while the sensors reaching the slip surface are expected to tilt forward in the failure process. Tilt sensors placed at the lower part of the sliding masses can be used to detect the initiation of slope failure [23]. MEMS sensors are conventionally used to foresee the rapid shallow failures using this concept, but in this study, the displacements are found to be slow movements.…”

Section: Tilting Rate and Slope Failurementioning

confidence: 85%

“…This does not always hold true, so LEWS should consider the effect of real-time site conditions. When thresholds are developed on a regional scale, the effect of the local site conditions and material heterogeneity is neglected [23]. In addition, the empirical thresholds are statistically based and do not take the complex hydrological processes and failure mechanisms into account when deriving the thresholds.…”

Section: Introductionmentioning

confidence: 99%

“…It is an extensively accepted fact that slope failures are often preceded by cracks due to slope deformations. If the minor movements of the slopes can be monitored effectively, this can be correlated with the potential occurrence of displacement [23] in the locale. The authorities can make a better judgment about the warning that should be given to the public based on real-time monitoring.…”

Section: Introductionmentioning

confidence: 99%

“…Tilting Rate and Slope FailureXie et al (2019)[23] conducted laboratory and field-scale experiments to predict possible slope failures by analyzing the tilting behavior of MEMS sensors. Artificial rainfall was used to trigger slope failure along a slip surface, which was pre-defined.…”

mentioning

confidence: 99%

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IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas

Abraham

Satyam

Pradhan

et al. 2020

Sensors

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In hilly areas across the world, landslides have been an increasing menace, causing loss of lives and properties. The damages instigated by landslides in the recent past call for attention from authorities for disaster risk reduction measures. Development of an effective landslide early warning system (LEWS) is an important risk reduction approach by which the authorities and public in general can be presaged about future landslide events. The Indian Himalayas are among the most landslide-prone areas in the world, and attempts have been made to determine the rainfall thresholds for possible occurrence of landslides in the region. The established thresholds proved to be effective in predicting most of the landslide events and the major drawback observed is the increased number of false alarms. For an LEWS to be successfully operational, it is obligatory to reduce the number of false alarms using physical monitoring. Therefore, to improve the efficiency of the LEWS and to make the thresholds serviceable, the slopes are monitored using a sensor network. In this study, micro-electro-mechanical systems (MEMS)-based tilt sensors and volumetric water content sensors were used to monitor the active slopes in Chibo, in the Darjeeling Himalayas. The Internet of Things (IoT)-based network uses wireless modules for communication between individual sensors to the data logger and from the data logger to an internet database. The slopes are on the banks of mountain rivulets (jhoras) known as the sinking zones of Kalimpong. The locality is highly affected by surface displacements in the monsoon season due to incessant rains and improper drainage. Real-time field monitoring for the study area is being conducted for the first time to evaluate the applicability of tilt sensors in the region. The sensors are embedded within the soil to measure the tilting angles and moisture content at shallow depths. The slopes were monitored continuously during three monsoon seasons (2017–2019), and the data from the sensors were compared with the field observations and rainfall data for the evaluation. The relationship between change in tilt rate, volumetric water content, and rainfall are explored in the study, and the records prove the significance of considering long-term rainfall conditions rather than immediate rainfall events in developing rainfall thresholds for the region.

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Section: Tilting Rate and Slope Failurementioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas

Abraham

Satyam

Pradhan

et al. 2020

Sensors

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show abstract

“…In recent years, with the development of microelectronic techniques, early warning systems utilizing MEMS (microelectromechanical systems) technology have been proposed to monitor and estimate the risk of slope failure [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]. Compared to conventional instruments used to monitor landslides, MEMS sensors, such as accelerometer sensors [30][31][32] and tilt sensors [33][34][35][36][37][38][39], are small, inexpensive and sophisticated, which also greatly reduces the cost of building early warning systems.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

Qiao

Feng

et al. 2020

Sensors

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In recent decades, early warning systems to predict the occurrence of landslides using tilt sensors have been developed and employed in slope monitoring due to their low cost and simple installation. Although many studies have been carried out to validate the efficiency of these early warning systems, few studies have been carried out to investigate the tilting direction of tilt sensors at the slope surface, which have revealed controversial results in field monitoring. In this paper, the tilting direction and the pre-failure tilting behavior of slopes were studied by performing a series of model tests as well as two field tests. These tests were conducted under various testing conditions. Tilt sensors with different rod lengths were employed to investigate the mechanism of surface tilting. The test results show that the surface tilting measured by the tilt sensors with no rods and those with short rods located above the slip surface are consistent, while the tilting monitored by the tilt sensors with long rods implies an opposite rotational direction. These results are important references to understand the controversial surface tilting behavior in in situ landslide monitoring cases and imply the correlation between the depth of the slip surface of the slope and the surface tilting in in situ landslide monitoring cases, which can be used as the standard for tilt sensor installation in field monitoring.

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A novel wireless underground transceiver for landslide internal parameter monitoring based on magnetic induction

Wang

Zhuo

Zhong

et al. 2021

Circuit Theory & Apps

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This article introduces a magnetic induction communication transceiver MI-S125-III, which can be buried in a landslide body and can be used to transmit the internal characteristic parameters of landslide mass (such as inclination angle). The device is based on the Manchester code, and the working frequency is 125 kHz. Its data transmission distance can reach 5.28 m in the soil. We built a physical landslide model, in which three MI-S125-III nodes with a tilting sensor were embedded, and the angle monitoring curve was obtained by human triggering. The angle monitoring curve can reflect the sliding process, indicating that MI-S125-III can be used for landslide monitoring and early warning in the future.

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A new prediction method for the occurrence of landslides based on the time history of tilting of the slope surface

Cited by 31 publications

References 27 publications

IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas

IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

A novel wireless underground transceiver for landslide internal parameter monitoring based on magnetic induction

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