Spatiotemporal deformation characteristics and triggering factors of Baijiabao landslide in Three Gorges Reservoir region, China

Yao, Wenmin; Li, Changdong; Zuo, Qingjun; Zhan, Hongbin; Criss, Robert E.

doi:10.1016/j.geomorph.2019.06.024

Cited by 92 publications

(18 citation statements)

References 30 publications

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“…Therefore, the deformation in this stage mainly occurred with the decline of the reservoir water level (Figure 8). The relationship between the stability of the Ganjingzi landslide and the reservoir water level was similar to many other colluvial landslides in the TGR area [7,26,30,35,46]. Such as the Shuping and Baishuihe landslides [26,46], the GNSS data show that the accelerated deformation of these landslides is also related to the reservoir water drawdown.…”

Section: Characterizing the Development Pattern Of The Landslidesupporting

confidence: 61%

“…In recent literature, some authors have applied the correlation and sensitivity analysis methods to explain the triggering mechanism of landslides [28][29][30], while others have proposed kinematic models on the basis of movement identification to predict landslide risks [31,32]. However, few studies use integrated in situ data to uncover the time-variable patterns of slow-moving colluvial landslides in the TGR area.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

et al. 2021

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Since the impoundment of the Three Gorges Reservoir (TGR) in June 2003, the fluctuation of the reservoir water level coupled with rainfall has resulted in more than 2500 landslides in this region. Among these instability problems, most colluvial landslides exhibit slow-moving patterns and pose a significant threat to local people and channel navigation. Advanced monitoring techniques are therefore implemented to investigate landslide deformation and provide insights for the subsequent countermeasures. In this study, the development pattern of a large colluvial landslide, locally named the Ganjingzi landslide, is analyzed on the basis of long-term monitoring. To understand the kinematic characteristics of the landslide, an integrated analysis based on real-time and multi-source monitoring, including the global navigation satellite system (GNSS), crackmeters, inclinometers, and piezometers, was conducted. The results indicate that the Ganjingzi landslide exhibits a time-variable response to the reservoir water fluctuation and rainfall. According to the supplement of community-based monitoring, the evolution of the landslide consists of three stages, namely the stable stage before reservoir impoundment, the initial movement stage of retrogressive failure, and the shallow movement stage with stepwise acceleration. The latter two stages are sensitive to the drawdown of reservoir water level and rainfall infiltration, respectively. All of the monitoring approaches used in this study are significant for understanding the time-variable pattern of colluvial landslides and are essential for landslide mechanism analysis and early warning for risk mitigation.

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Section: Characterizing the Development Pattern Of The Landslidesupporting

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

et al. 2021

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“…An alternative approach needs to be developed due to the limitation of susceptibility assessment of landslides. Researchers tend to pay attention to the factor combination prone to landslides (Pourghasemi, Kariminejad, et al 2020;Yao et al 2019), which requires the methods to extract useful information from large amounts of data quickly and accurately. Data mining is an effective method to extract knowledge from complicated data (Ouyang et al 2011;Witten et al 2011;Sameen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Analysis of secondary-factor combinations of landslides using improved association rule algorithms: a case study of Kitakyushu in Japan

Wang

Han

Chen

2021

Geomatics, Natural Hazards and Risk

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Landslide analysis prevents landslides from threatening resident safety and property, and the predominant method is susceptibility assessment which is cumbersome and time-consuming. The association rule algorithm (ARA) is proposed to mine the correlation between the factors and landslides simply and rapidly. The original ARA cannot reflect the scope of landslides which is nonnegligible for landslide analysis and is thus improved to mine the frequent secondary-factor combinations (SFCs). Firstly, eight factors are selected using the out-of-bag error and chi-squared (v 2 ) test. The accuracy of the factor selection is further verified employing landslide susceptibility assessment which is predicted using 30% of study grid data selected randomly as the training data. The improved ARA employs the area of historical landslides to mine the frequent SFCs, and the results are then verified by the frequency ratio and v 2 test. It is concluded that the frequent SFCs are: (21, 41), (21, 74), (34, 41), (34, 74), (41, 74), (21, 41, 74), and (34, 41, 74), and the area with the SFCs needs special protection. The present study provides a valuable reference for the primary prevention of landslides.

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“…However, a high-speed failure landslide is a large deformation landslide occurring within a short time. Due to the limitations of monitoring technology at present, the deformation of landslides is monitored for a long time, e.g., from the identification to the failure of a landslide [ 28 ]. Nevertheless, the deformation always stays at a creep state with a velocity of cm/year for general landslides, and the differential result implies that the acceleration is so small that the variation cannot be monitored.…”

Section: Introduction Of Inertial Measurement In Landslide Displacmentioning

confidence: 99%

Design and Testing of Inertial System for Landslide Displacement Distribution Measurement

Zhang

Tang

et al. 2020

Sensors

Self Cite

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Landslide displacement monitoring plays a fundamental role in the study of landslide evolution mechanisms, forecasting, risk assessment, prevention, and control. To fill the deficiencies of traditional instrumentation for measuring landslide displacement distributed along lateral direction, a landslide displacement measurement method based on deformation-coupled pipeline trajectory measurement is proposed, and a pipeline trajectory inertial measurement instrument is developed. The developed instrument, primarily comprised of a single shaft gyro, two axis accelerometers, and an external roller encoder, is designed as an axial half strapdown-radial half platform structure combined with a mechanical gravity platform. This structure avoids the singularity of pitch angle and roll angle and can expediently calculate a pipeline trajectory with an Eulerian transformation when obtaining several basic physical variables, e.g., the axial linear velocity, pitch angle, roll angle, and azimuth angle. Additionally, the pipeline trajectory, measured at different times, possesses the ability to reflect the displacement evolution feature of landslides. The results of prototype simulation tests imply a single measurement accuracy of a 12 cm/100 m span and a singly periodic multiple (more than five times) measurement accuracy of a 3 cm/100 m span, which meets medium-precision displacement measurement requirements for a landslide. Additionally, the finished instrument has been successfully applied to the deformation monitoring of the Majiagou I# landslide, which further verifies its feasibility and offers a reference for similar landslides.

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Spatiotemporal deformation characteristics and triggering factors of Baijiabao landslide in Three Gorges Reservoir region, China

Cited by 92 publications

References 30 publications

Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

Analysis of secondary-factor combinations of landslides using improved association rule algorithms: a case study of Kitakyushu in Japan

Design and Testing of Inertial System for Landslide Displacement Distribution Measurement

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