The Kangjiapo landslide in Wanzhou district, Chongqing city: reactivation of a deep-seated colluvial landslide in the Three Gorges Reservoir

doi:10.21203/rs.3.rs-2006217/v1

Download PDF

Research Article

The Kangjiapo landslide in Wanzhou district, Chongqing city: reactivation of a deep-seated colluvial landslide in the Three Gorges Reservoir

https://doi.org/10.21203/rs.3.rs-2006217/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

How to reduce landslide risk economically and effectively is a very meaningful and challenging research topic. In particular, it is difficult and expensive to completely control deep-seated colluvial landslides. Taking the Kangjiapo landslide in Wanzhou district, Chongqing city, China as a case, this study focuses on measures to prevent and control the risks of deep-seated colluvial landslides through detailed investigation and monitoring. The Kangjiapo landslide is located in the Three Gorges Reservoir area, and it is part of a famous ancient landslide named the Pipaping landslide. The steep sliding surface in the rear was not found during the first treatment, the Kangjiapo landslide has been reactivated since 2015. Field investigations, monitoring, borehole and related test were conduct to identify the landslide characteristics and mechanisms. The landslide deformation was not spatially or temporally uniform according to monitoring data analysis. The landslide is less likely to fail in general because the sliding surface in the front is very gentle. The reasons for Kangjiapo landslide reactivation could include the decline of the reservoir water level, a steep sliding surface in the rear, the existence of a sliding zone with low strength due to a long period of reservoir immersion. Landslide risk mitigation measures are proposed for the deep-seated landslide, including stabilizing piles nearby the road, and a BeiDou Navigation Satellite System and MEMS inclinometers in the platform.

Deep-seated landslide

Deformation characteristics

Landslide mechanisms

Landslide mitigation

Deep-seated landslides are one of the most dangerous geological disasters, and often cause significant loss of lives and property damage (Guo et al. 2020). Deep-seated landslides are frequently observed in the Three Gorges Reservoir, the volume of which is usually larger than 10⁶ m³ and the depth is usually up to several tens of meters, such as the Huangtupo landslide (Cojean and Cai, 2011) and the Baishuihe landslide (Li et al. 2010). Deep-seated landsides are triggered by human activities and by change in hydrologic processes, such as fluctuation of reservoir water levels or heavy rainfall (Lo. 2017; Li et al. 2010). Their surface velocities range from a few millimeters per year to several meters per second. Deep-seated landslides remain a serious challenge due to complex subsurface geological conditions coupled with several interrelated triggering factors (Kaunda, 2010).

For purpose of reducing the deep-seated landslides risk, it is essential to investigate the landslide movement characteristics, movement mechanisms, long-term factors, and hydrologic processes that influence their movement (Kaunda, 2010; Lo, 2017). The evolution of deep-seated landslides could be revealed by field investigation, remote sensing and field monitoring. Aerial image interpretation, together with geophysical investigations and borehole logging, are the most commonly used methods for landslide investigation (Van Westen et al. 1999; Van Den Eeckhaut et al. 2005). The surface features used in interpreting landscapes were investigated to identify deep-seated landslides, using detailed images from airborne LiDAR data (Glenn et al. 2006; Schultz, 2007; Kasai et al. 2009; Lo, 2017). Photogrammetric surveys and GPS monitoring are usually used to observe the kinematics of deep-seated landslides (Brückl et al. 2006; Tang et al. 2019; Li et al. 2019).

In the Wanzhou district in the middle Yangtze River, is seriously threatened by deep-seated landslides. It is in eastern Chongqing city, covers an area of about 3459 km², and is about 280 km upstream of the Three Gorges Dam (Gui et al. 2016). Wanzhou has a monsoon-humid subtropical climate with four distinct seasons. The temperature extremes range from − 3.7 to 42.1°C, and the average annual temperature is 18.1°C. Mean annual precipitation amounts to 1191 mm, and Most rainfall is concentrated in summer. Around 70% of its total annual rainfall falls between May and September. During the operation phase of the Three Gorges Dam, the reservoir water levels have fluctuated between 145m and 175m. Based on the regional geological hazards inventories, there are about 780 geological hazards in Wanzhou District, mainly including slides and rock falls. There are several large deep-seated ancient landslides with a total volume of several million m³, that are often slow-moving and show a complex kinetic progress. The heavy rainfall, fluctuations of the reservoir water level and some human construction activities, for example roads and houses, are main landslide triggers.

The purpose of this paper is to determine the movement characteristics of the Kangjiapo landslide, a deep-seated landslide, in the Wanzhou district, using field investigation, and surface and sub-surface monitoring. The monitoring data is used to detect the sliding surface and examine the relations between triggering factors and landslide movement. By quantifying the landslide features and estimating future landslide behavior, several landslide risk control measures, including engineering treatment measures and improved monitoring, are presented to lower the risk of large deep-seated landslides.

2.1 The Pipaping landslide

The Pipaping landslide is a famous large-scale ancient landslide in the Three Gorges Reservoir, which is situated on the northern bank of the Yangtze River in Wanzhou. The Pipaping landslide is approximately 850–960 m in length, 1610–2200 m in width, and 1.8 ×10⁶ m² in area (Fig. 1). The Kangjiapo landslide is a small part of this landslide. The complex landslide is characterized by an ancient rockslide upslope and three colluvial landslides downslope. Based on the ancient rockslide upslope and internal structures, the landslide can be divided into four units: an ancient rockslide (U1), Huangnibao landslide (U2), Kangjiapo landslide (U3) and Juyutuo landslide (U4). The four genetically linked landslide units are identified from field investigation and boreholes. Except for the ancient rockslide (U1), the other three sub-landslides are in the front of the landslide.

(1) Ancient rockslide (U1):

The ancient rockslide is around 500–750 m in length, 1900 m in width, 1.3×10⁶ m² in area, 36.7 m in average thickness, and 4.9 ×10⁷ m³ in volume (Fig. 1). The elevation of the ancient landslide ranges from 220 to 300 m. The slope is about 10°, except for a relatively steep rear region where the slope angle is larger than 25°. The rockslide is a translational type from a geomorphological point of view. The Schematic geological profile indicates a gentler lower slope and steeper upper slope, and the thickness decreases toward the toe (Fig. 2). The main sliding surface of the rockslide has a very gentle dip angle of about 3°. The bedrock is mainly sandstone interbedded with thin layers of mudstone. The mobilized material consists of Quaternary deposits, fractured sandstone and fractured mudstone. The ancient rockslide landslide has two sliding surfaces. The shallow sliding surface is located in the contact zone between the Quaternary deposit and the bedrock. The sliding zone is located in the contact zone between the fragmented rock and the bedrock. It is a weathered mudstone layer with a lower shear strength. Based on the landslide stability analysis, the rockslide is stable in general. Therefore, it was chosen as a resettlement area after local engineering treatment, which was carried out before the first reservoir impoundment in 2003. The residential quarters are concentrated here due to a limited supply of urban land.

(2) Huangnibao landslide (U2):

The Huangnibao landslide is a colluvial landslide, which covers an area of 3.2 ×10⁵ m² and has a volume of about 6 ×10⁶ m³. The landslide is shaped like a chair with a width of 500 m and a length of 650 m. Its average thickness is 18 m. The landslide elevation ranges between 132 and 500 m. The Huangnibao landslide has a steeper upper slope and gentler lower slope with two flat platforms. The bedrock consists of sandstone and mudstone. The mobilized material was composed of artificial fill and silty clay with rubble. The landslide has been treated by the construction of piles which were finished in June 2003.

(3) Kangjiapo landslide (U3):

The Kangjiapo landslide is also a large colluvial landslide with a volume of 4.7 ×10⁶ m³ (Fig. 1). It is around 400 m in length, 530 m in width, and 1.8 ×10⁵ m² in area. The landslide elevation ranges from 132 to 215 m. The Kangjiapo landslide has been reactivated since 1996, which damaged the school buildings and gas pipelines. A local failure of 2×10⁴ m³ in volume occurred in the northeastern part in January 2002. In order to protect the school, engineering treatments with stabilizing piles were carried out in the rear in November 2002. Figure 3 shows the location of the stabilizing pipes.

(4) Juyutuo landslide (U4):

The Juyutuo landslide is a large-scale colluvial landslide, which has a volume of 2.4 × 10⁶ m³ and an area of 1.9×10⁵ m². It is around 350 m in length and 540 m in width. Its depth ranges between 2 and 22 m. The landslide elevation ranges from 120 to 235 m. The landslide deformation started in 1992 due to heavy rainfall. The maximum crack width was 0.6 m with a length of 10 m. The landslide was treated in 2003 using piles with anchors and by cutting the slope.

2.2 The Kangjiapo landslide

Other sub-landslides (U1, U2 U4) did not undergo obvious deformation after treatment. Engineering piles were set in the middle of the Kangjiapo landslide (U3) in 2002, several cracks formed and settlement started to occur on the Binhe road due to heavy rainfall in 2015. The front part of the landslide became active and the deformed part was renamed the Middle school landslide, as shown in Figs. 3 and 4. Because the Middle school landslide was not treated with engineering works, obvious surface deformation occurred here. It is approximately 230–310 m in length, 400–540 m in width, 1.4×10⁵ m² in area, 30.9 m in average thickness, and 4.3×10⁶ m³ in volume. Kangjiapo landslide elevation ranges from 134 to 188 m. The landslide profile shows a gentle slope of 5°-10°, except the steeper front which has a slope of 10°-25°, as shown in Fig. 4.

The landslide geological conditions were determined by surveys and borehole. Sliding body consists of artificial fill and landslide deposits. The artificial fill consisted of rubble soil. The coarse particle percentage of the soil varied from 25 to 55%, based on its grain size distribution. Its thickness varies from 0.5 to 12 m. The landslide deposit below the artificial fill was silty clay with gravel and its thickness varies from 10 to 28 m. The bedrock is Jurassic mudstone and sandstone. The Kangjiapo landslide has two sliding surfaces. The shallow sliding zone was located in the old landslide deposit and was silty clay. The deep sliding zone was buried in the interface zone between the bedrock and landslide deposit. The sliding surface with a low strength was in the interface, showing distinct slickensides in the layer. Its thickness varies from 0.1 to 0.3 m and it is clay with high content of kaolin, as shown in Fig. 5.

The landslide risk is focused in the Middle school landslide now. More serious surface deformation in the Middle school landslide has occurred since May 2017. The road crack continued to propagate, stone railings of the road began to topple and new cracks appeared in the park. The obvious ground cracks mainly occurred in the rear in the middle part of the Kangjiapo landslide. There is no obvious deformation in the front. According to the landslide deformation features, the Kangjiapo landslide can be spanided into two regions: Ⅰ and Ⅱ (see Fig. 6).

(1) Strong deformation zone, which occurred in the middle of the landslide (I). Based on field investigation, ground cracks and road subsidence are mainly distributed at about 178m to 185m above sea level, as shown in Fig. 7. These cracks in the Binhe road were about 100–500 cm long and 1–12 cm wide. Several trees on the road side were tilted 15° in the sliding direction. The road subsidence was up to 55 cm in August 2020, which caused the road closure. The toppled stone railings, with a length of 5 m, were caused by the landslide. The railings were damaged in September 2019. The toppled direction of the railings was about 160° and is basically the same as that of the landslide direction. Although the railings were repaired in December 2019, they were found deformed again in July 2020, as shown in Fig. 8. The horizontal and vertical displacements of a curbstone were respectively 7 cm and 5 cm. Compared to road deformation, there was a slight deformation at the park. Three ground cracks started to occur in 2019. These cracks, with a strike direction of 70°, were about 12–15 m long and 0.5-2 cm wide.

(2) Weak deformation zone (II), which was divided into two sub-regions by the strong deformation zone. There is slight deformation on left slide of the landslide (II₁). A few ground cracks occurred at approximate elevations of 185 m in the rear. Compared to the left side, no obvious cracks were found on the right side of Kangjiapo landslide (II₂). It is more stable.

3.1 Landslide monitoring system

Landslide monitoring has been carried out since June 2019 to find out the landslide deformation features and identify the sliding surfaces. The BeiDou Navigation Satellite System (BDS), a leveling instrument and simple crack measurement were used to monitor the surface displacement. A total of 3 BDS survey points and 19 settlement monitoring points using the leveling instrument were positioned for measuring landslide surface deformation. Two flexile tilt sensors based on a micro-electromechanical system (MEMS) and one traditional artificial inclinometer were monitored for landslide subsurface deformation. The MEMS multi-axis accelerometer device is used to measure a high-precision tilt angle of an object using the force of gravity. Figure 6 shows that the MEMS sensor, composed of rigid pipe units and flexible joints, was used to measure large subsurface deformation. A MEMS sensor is placed every meter in the rigid pipe unit from the borehole bottom to the surface. The sensor in the tube can detect the change when the landslide is deformed. The horizontal displacement at different depth was calculated based on the tilt angle of each sensor. The MEMS inclinometer can measure large landslide deformation and obtain the landslide change in a timely fashion.

Figures 6 and 9 show the locations of the monitoring devices. The settlement monitoring and subsurface deformation monitoring were measured by traditional inclinometer every 15 days or 30 days, depending on the landslide deformation situation. The surface deformation by BDS were measured every hour. The MEMS inclinometer was measured every day. The drilling depths of A1 and A2 boreholes for the MEMS tilt sensor were respectively 42.7 m and 42.8 m, and the depth of M1 manual inclinometer borehole was 30.5 m.

3.2 Monitoring results

Figure 10 shows the evolution of landslide surface displacement over time based on BDS. In order to highlight the relationship between landslide displacement and triggering factors, daily rainfall and reservoir water level are also shown in Fig. 10. Cumulative displacement of the BDS monitoring points G1, G2 and G3 were respectively 50.7 mm, 27.5 m and 48.8 m. Figures 11 and 12 show the subsurface displacement versus depth at different time for A1 and A2 MEMS monitoring points and the M1 inclinometer point. The main features shown by the monitoring data are as follows :

(1) The subsurface monitoring results show the locations of the landslide sliding surface. The A1 horizontal displacement at the depth of 41 m increased sharply, which indicated the sliding surface in the landslide platform point was 41 m. It can be deduced that the depths of A2 and M1 sliding surfaces were 35 and 23 m. This was consistent with borehole records. The sliding surface at point A1 is located at the interface between the bedrock and landslide deposit. The cumulative displacement of the A1 sliding surface was up to 120 mm on October 14, 2020. The A2 cumulative displacement at the sliding surface reached 38 mm on June 3, 2020. The M1 inclinometer borehole was broken at the depth of 23 m due to landslide shearing. Its cumulative displacement was 13 mm at the sliding surface.

(2) The Kangjiapo landslide deformation varied spatially. The maximum landslide surface deformation occurred in the Binhe road and locally on the landslide platform. The larger deformation corresponds to the steeper sliding surface, as shown in Figs. 4 and 9. There was no obvious deformation at the locations of the gentle sliding surfaces. In a word, the deformation in the rear of the Kangjiapo landslide was greater than that in the front.

(3) The Kangjiapo landslide deformation which fluctuated with rainfall and reservoir water level varied temporally. The temporal variability is embodied in the change in displacement rate corresponding to different periods. From November 2019 to March 2020, the landslide was relatively stable by analyzing the monitoring data. During this period the displacement rate registered 0.01–0.2 mm/day, but increased to 1.0-4.2 mm/day from mid-March to mid-September 2020. Kangjiapo landslide tended to be stable in the winter when the reservoir level was higher than 170 m. However, when the water level started to draw down from 160 m to 145 m, the landslide became active and accelerated heavy rainfall in summer.

4.1 Triggering factors

The mechanism and cause of the Kangjiapo landslide were determined by field investigation and monitoring data analysis. The likely landslide cause was a combination of heavy rainfall, fluctuations in reservoir water level, the steeper sliding surface in the rear and the existence of a soft layer in the interface. Figure 10 shows rainfall and daily cumulative displacement. When the reservoir water level was constant at the level of about 146m, the cumulative rainfall totaled 65.0mm from 28 August to 1 September 2019. The cumulative displacement of the G1 monitoring point was 4.4mm. This indicates that the displacement of Kangjiapo landsldie during this period was caused by rainfall.

The relationship between the Kangjiapo landslide displacement and variations in the reservoir water level is illustrated in Fig. 10. The graph demonstrates that the Kangjiapo landslide deformation was significantly affected by the fluctuation of the reservoir water level. When the reservoir water level dropped rapidly, the Kangjiapo landslide underwent greater deformation. A typical example is that the water level dropped by 2.2m without rain from June 3 to June 7, 2020, and the maximum displacement reached 7.9mm. The same phenomenon also occurred in 2019. The maximum displacement was 11.7mm after the water level dropped by 2.4m for 10 days. Conversely, when the reservoir water level rose sharply, the Kangjiapo landslide deformation decreased or was virtually negligible. A typical example is that the landslide displacement decreased by 2–11 mm from September to November 2019, when the reservoir water level rose rapidly from 163.6 m to 170.7 m. This might be ascribed to rising water increasing normal stress on the landslide front below the water level. In consideration of the fact that the displacement of Kangjiapo landslide changes with the fluctuation of the reservoir water level, it can be concluded that the cyclic decline of the reservoir water level induced the Kangjiapo landslide.

4.2 Landslide mechanisms

The landslide has a long history of deformation and its movement fluctuated with triggering factors. Through the on-site investigation and the analysis of monitoring data, the landslide mechanisms are obtained as follows.

(1) The landslide deformation depended on the shape of the sliding surface and its geotechnical parameters. Based on borehole records and field investigation, the slop of the deep sliding surface in the front is flat, but which in the rear is steep. The slope of the sliding surface in the rear varied from 25° to 48°. The very steep sliding surface can generate great gravitational force and cause landslide movement.

(2) Since the water level of the Three Gorges Reservoir rose sharply after the impoundment, the elevations of the deep sliding surface at G1 and G3 was about 140 m and 145 m, which was already lower than that of reservoir water. The reservoir water may have affected the structure of the sliding zone and resulted in its loss of strength due to the long period of immersion. The result of field shearing test show the internal friction angle of the saturated sliding soil in the deep sliding zone varied from 7.5° to 9.7°. Its cohesion varied from 9.3 to 13.5. The loss of strength of the sliding soil affected the landslide movement.

(3) The seepage process of slope depended on water head difference and the property of the landslide body. The landslide has deformed after the reservoir water drops. During the monitoring period, the maximum drop rate of the water level reached 1.6 m/day. The permeability coefficient of the landslide body varied 0.024 to 0.033 m/d. By reason of the low permeability of the Slideing Material of Kangjiapo Landslide, groundwater dissipated slowly and groundwater remained high within the landslide while the reservoir water declined rapidly. Therefore, these might increase dynamic water pressure, which resulted in the landslide deformation (Chen et al. 2018; Li et al. 2019).

4.3 Stability analysis of Kangjiapo Landslide

The soil parameters, geological and hydrological data of Kanjiapo landslide were obtained through the above survey and investigation. The soils parameters in the numerical simulation are shown in Table 1. The Geostudio12 was used to calculate the daily stability of landslide from June 15, 2019 to October 24, 2020. First of all, the daily seepage field of Kangjiap landslide during the monitoring period was simulated using hydrological data (including reservoir water level and rainfall). Then, daily factors of safety were calculated by coupling gravitational field and seepage field, as shown in Fig. 13.

In addition to rainfall, the reservoir water lever is the most important factor controlling the stability of the Kangjiapo landslide. When the water level rises, the factor of safety increases, and its maximum is 1.65; When the water level drops, the factor of safety decreases, and its minimum is 0.98. There are 21days of the factor of safety less than 1 in the 497 days of the simulation. So the Kangjiapo landslide is in a potentially unstable state.

Table 1

Parameters of the Slideing Material of Kangjiapo Landslide
Slideing Material	Density (kN/m³)	Cohesion (kPa)	Internal friction angle(°)	Saturated permeability (cm/s)
Artificial fill	20.5	21	19.7	7.26x10^− 4
Silty clay with gravel	22.35	22.64	22.27	5.12x10^− 4
Sliding zone soils	20.0	10.0	7.6	4.57x10^− 4

Based on the results of stability analysis and monitoring data analysis, it is less likely that the Kangjiapo landslide accidents would occur in general. However, local landslide deformation would mainly occur in the rear. Local landslide deformation could damage Binhe Road which is the main road in Wanzhou District, and block traffic, which would cause huge economic and social risks. Landslide front risk is low because there is little or no deformation in the landslide front and residents have been relocated. Therefore, the authors propose to use engineering measures and enhance landslide monitoring for landslide risk mitigation.

5.1 Engineering control measures

Due to the landslide sliding force generated by the very steep sliding surface in the rear, stabilizing piles are suggested to reduce the landslide force. On the basis of the depth of the sliding surface and landslide design results, two different pile types should be arranged as shown in Fig. 13. In areas where the landslide deformation is relatively small or the sliding surface is relatively flat, 63 A-type stabilizing piles are proposed. In areas with strong deformation or a steep sliding surface, 22 B-type piles are suggested. The length of all stabilizing piles is 34 m. The A-type pile has an anchorage length of 11 m, while the anchorage length of the B-type pile is 10 m. The size of the A-type piles is 2.0 m × 3.0 m. B-type piles have a larger sectional area of 2.5 m × 3.0 m to resist a greater sliding force. The engineering measure could strength the landslide safety in order to protect Binhe road. Through the simulation calculation, it is found that the landslide stability has been significantly improved after the engineering treatment. The factors of safety during the monitoring period after landslide control are 1.20–2.13, and they are increased by 20%-36% as a whole. The change trend of the factor of safety is the same as before treatment. The increase in the safety factor is also related to the landslide stability. When Kangjiapo landslide is in the safe period, the greater the improvement of the safety factor after treatment. When the landslide is in an unstable period, the improvement of the safety factor after treatment is relatively small (Fig. 13).

5.2 Enhance landslide monitoring

Although installation of the piles is suggested to strength landslide stability, the residual landslide risk would remain. Therefore, another landslide mitigation measure that would enhance landslide monitoring was proposed to reduce the landslide risk in the front. The main monitoring measures, including a MEMS inclinometer and BDS was suggested. The arrangement position is shown in Figs. 13 and 14. The A3 MEMS inclinometer would monitor the sliding surface and landslide subsurface deformation in the landslide front. Therefore, landslide mitigation measures, including stabilizing piles in the rear and more detailed landslide monitoring in the front, could reduce the major landslide risk.

The Pipaping landslide is a complex large deep-seated landslide. After several engineering measures were carried out in different landslide zones, the landslide risk mainly occurs in the Kangjiapo landslide, which is a part of the Pipaping landslide and located in its front. In order to propose some appropriate landslide risk mitigation measures for the Kangjiapo landslide, triggering factors, deformation feature and mechanism of the Kangjiapo landslide were studied on basis of field investigation and monitoring work. The conclusions were drawn below:

(1) The Kangjiapo landslide has two sliding surfaces. The shallow sliding surface was in the landslide deposit and the deep sliding surface was located in the interface zone between bedrock and landslide deposit. Due to the very gentle sliding surface in the front with a slope that ranged from 1° to 6°, the landslide should not fail in general and move quickly.

(2) Landslide deformation did not behave in a spatially or temporally uniform fashion. The serious landslide deformation occurred nearby the Binhe Road in the middle part. However, there was no obvious deformation in the front in comparison. The torrential rain and drawdown of the reservoir were the triggering factors for landslide reactivation, and when the reservoir water declined rapidly or heavy rainfall occurred, the Kangjiapo landslide became active. Other possible factors affecting the Kangjiapo landslide deformation were the steep sliding surface in the rear and the existence of a soft sliding zone with a low friction angle and small cohesion.

(3) For purpose of reducing the landslide risk and protect the middle school and the road, landslide mitigation measures are suggested, including engineering control measures with stabilizing piles and enhancing monitoring work. Based on landslide deformation characteristics, the piles should be arranged near the road and the MEMS inclinometers and BDS are designed to be installed on the landslide platform.

Acknowledgements

The authors would like to thank Jiang Wu, Yingchun Li and Qingli Liu from Wanzhou Station of Geo-Environment Monitoring for providing the landslide material.

Funding

This study was financially supported by The Natural Science Foundation of China (41772310, 42007267)

Declaration

The authors declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence this stuy.

Brückl E, Brunner FK, Kraus K (2006) Kinematics of a deep-seated landslide derived from photogrammetric, GPS and geophysical data. Engineering Geology 88(3-4):149–159. https://doi.org/10.1016/j.enggeo.2006.09.004
Chen M, Lv P, Zhang S, Chen X, Zhou J (2018) Time evolution and spatial accumulation of progressive failure for Xinhua slope in the Dagangshan reservoir, Southwest China. Landslides 15:565–580. https://doi.org/10.1007/s10346-018-0946-8
Cojean R, Cai YJ (2011) Analysis and modeling of slope stability in the Three-Gorges Dam reservoir (China) – The case of Huangtupo landside. Journal of Mountain Science 8(2):166-175. https://doi.org/10.1007/s11629-011-2100-0
Glenn NF, Streutker DR, Chadwick DJ, Thackray GD, Dorsch SJ (2006) Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity. Geomorphology 73:131–148. https://doi.org/10.1016/j.geomorph.2005.07.006
Gui L, Yin K, Glade T (2016) Landslide displacement analysis based on fractal theory, in Wanzhou District, Three Gorges Reservoir, China. Geomatics, Natural Hazards and Risk 7(5):1707–1725. https://doi.org/10.1080/19475705.2015.1137241
Guo Z, Chen L, Yin K, Shrestha DP, Zhang L (2020) Quantitative risk assessment of slow-moving landslides from the viewpoint of decision-making: a case study of the Three Gorges Reservoir in China. Engineering Geology 273:105667. https://doi.org/10.1016/j.enggeo.2020.105667
Huang F, Chen L, Yin K, Huang J, Gui L (2018) Object‑oriented change detection and damage assessment using high‑resolution remote sensing images, Tangjiao Landslide, Three Gorges Reservoir, China. Environmental Earth Sciences 77(5):183. https://doi.org/10.1007/s12665-018-7334-5
Li D, Yin K, Leo C (2010) Analysis of Baishuihe landslide influenced by the effects of reservoir water and rainfall. Environ Earth Science 60:677–687. https://doi.org/10.1007/s12665-009-0206-2
Li D, Yan L, Wu L, Yin K, Leo C (2019) The Hejiapingzi landslide in Weining County, Guizhou Province, Southwest China: a recent slow-moving landslide triggered by reservoir drawdown. Landslides 16:1353–1365. https://doi.org/10.1007/s10346-019-01189-5
Lo CM (2017) Evolution of deep-seated landslide at Putanpunas stream, Taiwan. Geomatics, Natural Hazards and Risk 8(2):1204–1224. https://doi.org/10.1080/19475705.2017.1309462
Kasai M, Ikeda M, Asahina T, Fujisawa K (2009) LiDAR-derived DEM evaluation of deep-seated landslides in a steep and rocky region of Japan. Geomorphology 113:57–69. https://doi.org/10.1016/j.geomorph.2009.06.004
Kaunda R. (2010) A linear regression framework for predicting subsurface geometries and displacement rates in deep-seated, slow-moving landslides. Engineering Geology 114:1–9. https://doi.org/10.1016/j.enggeo.2010.03.004
Schulz W (2007) Landslide susceptibility revealed by LIDAR imagery and historical records, Seattle, Washington. Engineering Geology 89:67–87. https://doi.org/10.1016/j.enggeo.2006.09.019
Tang H, Wasowski J, Juang C (2019) Geohazards in the three Gorges Reservoir Area China–lessons learned from decades of research. Engineering Geology 261:105267. https://doi.org/10.1016/j.enggeo.2019.105267
Van Den Eeckhaut M, Poesen J, Verstraeten G, Vanacker V, Moeyersons J, Nyssen J, van Beek LPH (2005) The effectiveness of hillshade maps and expert knowledge in mapping old deep-seated landslides. Geomorphology 670(3–4):351–363. https://doi.org/10.1016/j.geomorph.2004.11.001
Van Westen CJ, Seijmonsbergen AC, Mantovani F (1999) Comparing landslide hazard maps. Nature Hazards 20:137–158. https://doi.org/10.1023/A:1008036810401

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

The Kangjiapo landslide in Wanzhou district, Chongqing city: reactivation of a deep-seated colluvial landslide in the Three Gorges Reservoir

Status:

Version 1

Abstract

Figures

1. Introduction

2. Landslide Features

2.1 The Pipaping landslide

2.2 The Kangjiapo landslide

3. Landslide Deformation Characteristics

3.1 Landslide monitoring system

3.2 Monitoring results

4. Triggering Factors And Landslide Mechanisms

4.1 Triggering factors

4.2 Landslide mechanisms

4.3 Stability analysis of Kangjiapo Landslide

5. Landslide Risk Mitigation Measures

5.1 Engineering control measures

5.2 Enhance landslide monitoring

6. Conclusions

Declarations

References

Additional Declarations

Status:

Version 1