Evolution characteristics of the Huangtupo landslide based on in situ tunneling and monitoring

Tang, Huiming; Li, Changdong; Hu, Xinli; Su, Aijun; Wang, Liangqing; Wu, Yiping; Criss, Robert E.; Xiong, Chengren; Li, Yunan

doi:10.1007/s10346-014-0500-2

Cited by 118 publications

(52 citation statements)

References 14 publications

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“…Riverside Slumping Mass I# and II#, which due to their location on the riverside are expected to be highly affected by the river water level, show a clear in-phase relationship indicating that both the landslides displacement and the reservoir groundwater level are in phase, in agreement with Xie (2009), Tomás et al (2014) and Tang et al (2014).…”

Section: Xwt and Wtc Of Reservoir Water Level And The Landslide Displsupporting

confidence: 83%

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

et al. 2015

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Synthetic Aperture Radar Interferometry (InSAR) has proven to be a powerful tool for monitoring landslide movements with a wide spatial and temporal coverage.Interpreting landslide displacement time-series derived from InSAR techniques is a major challenge for understanding relationships between triggering factors and slope displacements. In this study, we propose the use of various wavelet tools, namely Continuous Wavelet Transform (CWT), Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) for interpreting InSAR time-series information for a landslide. CWT enables time-series records to be analysed in time-frequency space, with the aim of identifying localized intermittent periodicities. Similarly, XWT and WTC help identify the common power and relative phase between two time-series records in time-frequency space, respectively. Statistically significant coherence and confidence levels against red noise (also known as brown noise or random walk noise) can be calculated. Taking the Huangtupo landslide (China) as an example, we demonstrate the capabilities of these tools for interpreting InSAR time-series information. The results show the Huangtupo slope is affected by an annual displacement periodicity controlled by rainfall and This paper has to be cited as: Tomás, R., Li, Z., Lopez-Sanchez, J.M., Liu, P. & Singleton, A. 2016. Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide. Landslides, 13, 437-450, The final publication is available at Springer via: https://link.springer.com/article/10.1007%2Fs10346-015-0589-y reservoir water level. Reservoir water level, which is completely regulated by the dam activity, is mainly in 'anti-phase' with natural rainfall, due to flood control in the Three Gorges project. The seasonal displacements of the Huangtupo landslide is found to be 'in-phase' with respect to reservoir water level and the rainfall towards the front edge of the slope and to rainfall at the higher rear of the slope away from the reservoir.

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Section: Xwt and Wtc Of Reservoir Water Level And The Landslide Displsupporting

confidence: 83%

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

et al. 2015

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“…The geological formations from which this landslide developed are known locally as the Badong Formation (T 2 b 2 and T 2 b 3 ). The landslide mainly consists of irregular alternations of mudstone, pelitic siltstone, argillaceous limestone, and limestone (Deng et al 2000;Tang et al 2015a;Wang et al 2014 Original Paper landslide is located at approximately 600 m.a.s.l., while the toe ranges from 50 to 90 m.a.s.l.. The toe is submerged in the Yangtze River with water levels varying from 145 to 175 m as regulated by the Three Gorges Dam.…”

Section: Patterns Of Movement In the Huangtupo Landslidementioning

confidence: 99%

“…The tunnel excavation exposed two main landslide shear zones consisting of three lithologies, namely brown-yellow gravel soil in the slide mass, yellow and light-grey clay with gravel along the shear zone, and bluish-brown and brownish-yellow argillaceous limestone formed in the subjacent stable bedrock (Tang et al 2015a). Intact samples were collected from the upper shear zone (see Fig.…”

Section: Test Materialsmentioning

confidence: 99%

Residual-state creep of clastic soil in a reactivated slow-moving landslide in the Three Gorges Reservoir Region, China

Wang

et al. 2018

Landslides

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We study the creep properties of clastic soil in residual state. The intact samples are taken from a reactivated slow-moving landslide in the Three Gorges Reservoir Region, China. Firstly, the patterns of the landslide movement are analysed based on recent monitoring data, which indicate that the soil within the shear zone is undergoing two deformation processes: a creep phase, characterised by different creep rates, and a dormant phase. We then study the creep behaviour of the soil samples through a series of ring shear creep tests under various shear stress conditions. The creep response depends strongly on the ratio of the shear stress to the residual strength, and the normal effective stress, whereas the creep rate decreases due to strength regain. The long-term strength of the clastic soil is close to the residual strength. Therefore, the residual strength obtained from conventional shear test, which is less time consuming than creep test, can be used in longterm stability analyses of creeping landslides.

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“…In addition, the most dangerous geological section is used to calculate the seepage field and stability coefficient [41]. Two different materials mainly comprise the geomechanical model: silty clay and fragmented rubble contained in the slide mass and interbedded sandstone and mudstone contained in the ledge rock.…”

Section: Geomechanical Model Of the Sifangbei Landslidementioning

confidence: 99%

“…Furthermore, to explore the seepage field when the reservoir water level increases from 145 m to 175 m, the stable landslide saturation line of the 145 m reservoir water level is regarded as the initial saturation line. to calculate the seepage field and stability coefficient [41]. Two different materials mainly comprise the geomechanical model: silty clay and fragmented rubble contained in the slide mass and interbedded sandstone and mudstone contained in the ledge rock.…”

Section: Geomechanical Model Of the Sifangbei Landslidementioning

confidence: 99%

Stability Analysis of Hydrodynamic Pressure Landslides with Different Permeability Coefficients Affected by Reservoir Water Level Fluctuations and Rainstorms

Huang

Luo

Liu

2017

Water

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Abstract:It is significant to study the variations in the stability coefficients of hydrodynamic pressure landslides with different permeability coefficients affected by reservoir water level fluctuations and rainstorms. The Sifangbei landslide in Three Gorges Reservoir area is used as case study. Its stability coefficients are simulated based on saturated-unsaturated seepage theory and finite element analysis. The operating conditions of stability coefficients calculation are reservoir water level variations between 175 m and 145 m, different rates of reservoir water level fluctuations, and a three-day continuous rainstorm. Results show that the stability coefficient of the hydrodynamic pressure landslide decreases with the drawdown of the reservoir water level, and a rapid drawdown rate leads to a small stability coefficient when the permeability coefficient ranges from 1.16 × 10 −6 m/s to 4.64 × 10 −5 m/s. Additionally, the landslide stability coefficient increases as the reservoir water level increases, and a rapid increase in the water level leads to a high stability coefficient when the permeability coefficient ranges from 1.16 × 10 −6 m/s to 4.64 × 10 −5 m/s. The landslide stability coefficient initially decreases and then increases as the reservoir water level declines when the permeability coefficient is greater than 4.64 × 10 −5 m/s. Moreover, for structures with the same landslide, the landslide stability coefficient is most sensitive to the change in the rate of reservoir water level drawdown when the permeability coefficient increases from 1.16 × 10 −6 m/s to 1.16 × 10 −4 m/s. Additionally, the rate of decrease in the stability coefficient increases as the permeability coefficient increases. Finally, the three-day rainstorm leads to a significant reduction in landslide stability, and the rate of decrease in the stability coefficient initially increases and then decreases as the permeability coefficient increases.

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Evolution characteristics of the Huangtupo landslide based on in situ tunneling and monitoring

Cited by 118 publications

References 14 publications

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

Residual-state creep of clastic soil in a reactivated slow-moving landslide in the Three Gorges Reservoir Region, China

Stability Analysis of Hydrodynamic Pressure Landslides with Different Permeability Coefficients Affected by Reservoir Water Level Fluctuations and Rainstorms

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