The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau

Journal Pre-proof The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau

Yiding Bao, Shijie Zhai, Jianping Chen, Peihua Xu, Xiaohui Sun, Jiewei Zhan, Wen Zhang, Xin Zhou PII:

S0169-555X(19)30461-1

DOI:

https://doi.org/10.1016/j.geomorph.2019.106970

Reference:

GEOMOR 106970

To appear in:

Geomorphology

Received date:

15 September 2019

Revised date:

20 November 2019

Accepted date:

20 November 2019

Please cite this article as: Y. Bao, S. Zhai, J. Chen, et al., The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau, Geomorphology(2019), https://doi.org/10.1016/j.geomorph.2019.106970

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© 2019 Published by Elsevier.

Journal Pre-proof The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau Yiding Baoa • Shijie Zhai a • Jianping Chen*, a • Peihua Xu a • Xiaohui Sun a • Jiewei Zhan a • Wen Zhang a • Xin Zhou b a College of Construction Engineering, Jilin University, Changchun, 130026, China b School of River and Ocean Engineering, Chongqing Jiaotong University, 400074, Chongqing, China * Corresponding author. Tel.:+86 13843047952

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* Email address: [email protected]

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Abstract

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A large number of landslides have occurred in the upstream reaches of the Jinsha River, Tibetan

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Plateau due to the intensity of tectonic movement in the area. Remote sensing and field investigation indicate that one of them, the Samaoding paleolandslide, previously blocked the river. Various

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river-blocking phenomena are well preserved, including the old landslide dam and deposits, fluvial

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sediments, and hydrostatic sandy sediment. To better understand the evolution of the Samaoding

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landslide, the authors carried out thermoluminescence (TL) dating and numerical simulations. The TL analysis shows that the landslide occurred at 10.6 ± 0.5 Ka BP. Discrete element method (DEM) simulation of the landslide based on landform restoration provided results that are consistent with field observations. The simulation indicates that the entire landslide process lasted for 80 s, and the sliding mass reached a maximum velocity of 64 m/s. The landslide formed a landslide dam with a length of 1900 m, a width of 600 m, and a depth of 200 m. The simulation results show that the level of the riverbed at that the time of the landslide was at least 25 m higher than it is today. On the combined basis of the simulation results and field observations, the authors propose explanation that the

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following valley evolution sequence occurred after river blocking. The landslide dam experienced flood overtopping and then was eroded until it had mostly had been transported away by river flow, and the river then rapidly incised the bedrock to form the present-day landform. Based on the field investigations, the authors summarize the failure mechanism of steep-inclined antidip rockslides and found that tectonics play an important role in the formation of landslide dams (or trigger of landslides)

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and the failure of landslide dams in an active tectonic environment of Tibetan Plateau.

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Introduction

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1.

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reconstruction, river valley evolution, antidip rockslide

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Keywords: Landslide river blocking, Numerical simulation, TL dating, Topography

The Tibetan Plateau, which has an average elevation of over 4000 m, is the most extensive highland

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on earth. It contains a large number of water sources and steep mountains, making it the source of many

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great rivers such as the Yangtze River and the Yellow River, and it is thus an ideal laboratory for research

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into river valley evolution. The Jinsha River, which is the name given to the upper reaches of the Yangtze River, is located at the southeastern margin of the Tibetan Plateau. It flows through the area where the eastern Tibetan block is rapidly converging with the western Sichuan block from west to east (Chen et al., 1998). Strong extrusion has caused considerable regional tectonic activity, in turn resulting in a large number of geological disasters such as landslides. Many studies have proven that large tectonics such as earthquakes not only directly triggers landslides forming dammed lakes (Chigira et al., 2010; Mazzanti and Bozzano, 2011; Zhang et al., 2019), but also generates many cracks inside the slope, thus decreasing the strength and increasing the possibility of landslides (Fan et al., 2019). Landslides in the Jinsha River usually cause river blocking and the generation of a dammed lake. 2

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Besides landslide dams, there are some other types of natural dams including fluviatile dams, eolian dams, coastal dams, organic dams, moraine dams, glacier dams, and volcanic dams (Costa and Schuster, 1988; Chen et al., 2018). These natural dams frequently have obvious differences in many aspects including formation geomorphologic region, composition, size and shape, longevity, failure mechanism, and outburst flood (Kataoka et al., 2008; Korup and Montgomery, 2008; Kataoka, 2011; Chen et al., 2013;

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Liu et al., 2015; Guo et al., 2016; Wu et al., 2016). Formation and failure of natural dams are the result of

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internal and external geological processes and reflect the characteristics and evolution of geological

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environment. Among them, three types of natural dams including landslide dams, glacier-ice dams, and

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late-neoglacial-age moraine dams are most catastrophic for human beings. A clear understanding of the

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processes including the formation and breaching of landslide dams is crucial for hazard mitigation and landscape evolution (Korup, 2002). Old landslide dams and lacustrine sediments may record the events

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that occurred during deposition (Korup and Clague, 2009), so they have become a key data source for

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research into paleogeology and the paleoenvironment (Hancox and Perrin, 2009; Zhang et al., 2011;

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Chen et al., 2013; Wang et al., 2014; Guo et al., 2016; Chen et al., 2018; Liu et al., 2018b; Ma et al., 2018; Wang et al., 2018; Sun et al., 2019a, 2019b). The Samaoding paleolandslide is located in the Deqin–Derong reach of the upper Jinsha River, at the southeastern margin of the Tibetan Plateau. It is typical of rockslides along the Jinsha River and has a well-preserved scar. The elevation of the top and bottom of the scar are 817 m and 222 m higher than the current river surface, respectively. A pile of old landslide deposits is also present on the other bank of the river; the base of these deposits is 50 m higher than the present river surface. Several questions arise: How did the rockslide occur and how large an area was affected? Does the old landslide dam on the opposite bank belong to the Samaoding paleolandslide or is it authigenic? When did the Samaoding 3

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paleolandslide occur, and how did it evolve to the present-day landform? A detailed study of the evolution of the Samaoding paleolandslide is necessary to explore these questions. Reproducing the evolutionary process associated with a geological event can be very challenging because the sequence often spans hundreds to millions of years. Researchers can only propose explanation on evolution on the basis of unique geological phenomena, and they can only propose

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explanation on a long-term geological process on the basis of short-term geological processes. Early

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research into the evolution of geological events relied heavily on field investigation; corresponding

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qualitative descriptions and proposed explanations were then made on the basis of the data gathered.

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However, relying solely on field investigations is severely limiting, as some areas are difficult for

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humans to reach and research results are sometimes qualitative. Later, remote sensing techniques and digital terrain models (DTMs) were widely applied to the study of landform evolution (Philip, 1994;

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Hanamgond and Mitra, 2008; Chuang and Shiu, 2018) to help researchers monitor landform changes

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from a broader perspective and transform research into landform evolution from the qualitative to the

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quantitative. Elemental geochemical analysis, which enables the sedimentary environment to be inferred on the basis of measurements of the amounts of sensitive chemical elements such as Mg, Ca and Fe, is also an important approach to researching geological event evolution (Khalifa et al., 2009; Cuven et al., 2013). In addition, methods of radiometric dating such as optically stimulated luminescence (OSL), thermoluminescence (TL), and carbon-14 dating (14C) have become popular for acquiring the age of geological events (Wang et al., 2014; Chen et al., 2018; Liu et al., 2018b; Ma et al., 2018); radiometric dating can also be used to derive other time-related information such as the sediment deposition rate or channel incision rate. Although some useful information can be acquired with the above methods, it remains difficult to directly and vividly re-create the evolution of a geological event. In recent years, 4

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improvements in computing power have led to the use of various numerical simulation methods to simulate geological phenomena. Numeric models of landslides can be divided into two main types. One is based on the continuum method and describes landslide motion via a macroscopic stress–strain constitutive equation or through flow behavior. It can be based on the finite element method (FEM), which relies on a macroscopic stress–strain constitutive relationship and is able to analyze fine-scale

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deformation (Zheng et al., 2005; Bao et al., 2019a; Farah et al., 2011). Smoothed particle

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hydrodynamics (SPH), which is a purely Lagrangian, mesh-free method and describes motion via the

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interaction of mass points, is another popular continuum method for describing landslide movement

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(Pastor et al., 2009a; Dai and Huang, 2016). Depth-integrated continuum mechanics, which is based on

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the shallow-water flow model, is well-able to describe the physical properties of fluid flow with a large spatial scale and is not computing resource-intensive (Han et al., 2017a, 2017b; Ouyang et al., 2017;

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Bao et al., 2019c). The other type of model uses the discrete element method (DEM), which is based on

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Newton's second law and the force-displacement law and utilizes interactions between particles to

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reflect macroscopic mass behavior. (Tang et al., 2009; Lo et al., 2011; Lu et al., 2014; Lin and Lin, 2015; Zhou et al., 2015; Liu et al., 2018a; Bao et al., 2019b). The discrete element method is more suitable for analyzing landslides than is the continuum method, not only because more relevant and detailed information can be acquired but also because it can clearly simulate mass separation behavior. This paper aims to reproduce the entire Samaoding landslide process and illustrate its evolution, and make it a reference for other similar river blocking events. To this end, a detailed field investigation was conducted in October 2015, and the old landslide dam was sampled for TL testing to assess the age of the landslide. Data from field investigation and remote sensing were then combined in ArcGIS 10.2 to restore the pre-failure landform. A DEM-based landslide simulation was conducted 5

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based on this analysis to enable detailed description and discussion of the landslide. Finally, an evolutionary sequence for the Samaoding landslide was developed based on the above work. The flowchart of this paper is shown in Fig. 1.

Insert Fig.1 Here 2.

Study area

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2.1. Background The study area is in the upper reaches of the Jinsha River, at the border between Sichuan Province

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and Yunnan Province at the southeastern margin of the Tibetan Plateau (Fig. 2a). The Jinsha River

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flows through the area from north to south through mountainous terrain, which has given the river the

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symmetrical V-shaped valley characteristic of rapid downward erosion. The elevation of the area is from 1912 m to 5000 m, and slopes are steep, mostly larger than 40° (Fig. 2b). As well as narrow

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valleys, broad valleys are also distributed within the study area and retain terrace landforms.

Insert Fig.2 Here

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The study area is located in one of the plate sutures associated with the Indo-Asian collision, giving it a complex geological structure and stratigraphic lithology. This is the Jinshajiang suture zone, which lies between the Zhongza-Zhongdian and Qamado blocks and formed in the Paleo-Jinshajiang orogenic belt after the closure of the Jinshajiang Ocean. Suture belts are large-scale crustal discontinuities that form belts of weakness in the lithosphere where endogenic geological processes are extremely active. The Jinshajiang suture zone includes two main tectonostratigraphic units: the Jinshajiang ophiolitic mélange belt (Paleozoic) and the Gajinxueshan group (Mesoproterozoic). The representative lithology of the study area is ophiolitic, and granite, basalt, limestone, marble, and other volcanic and metamorphic rocks are widely distributed (Fig. 3). The main active faults in the study area 6

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are deep-seated faults that are active constituents of the north–south trending Jinshajiang fault zone. Significant fault activity has occurred in the study area in the Quaternary, such as a Ms 5.9 earthquake on 31 August, 2013.

Insert Fig.3 Here The study area is geographically located in a subtropical climatic zone and is comprised of dry-hot

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valleys with distinct rainy and dry seasons. The average precipitation is 354 mm/year, but the average

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evaporation is 1747.7 mm/year. Notably, approximately 60% of the annual rainfall is concentrated

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between June and August. Additionally, the lowest temperature is about -8.6 °C, but the highest

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temperature can reach 35 °C. Due to the high altitude and the complicated topography, there is a strong

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altitudinal climatic gradient in the area, and the climate is arid and hot on valley floors. Due to its location at the margin of the Tibetan Plateau, the study area is subject to strong

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compressive stress (4.0–16.3 MPa) (Chen and Li, 2016) in the east–west direction, and stress

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concentration is particularly evident in valley floors and at the foots of slopes (Gong et al., 2010). It is

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affected by neotectonic activity, with very frequent earthquakes. As a consequence, rocks along the valleys have experienced extremely intense deformation, which leads to various, numerous mass movements such as rock falls, debris flows, and rockslides (Zhan et al., 2018). These mass movements have usually caused river blocking, as demonstrated by several phenomena related to river blocking that were discovered in the study area during the field investigations. For example, in the upper reaches of the study area, old landslide deposits from the Zhisishan rockslide were found on the right bank of the Jinsha River. The slip surface of the rockslide was a fault plane, and fissure water had intensely eroded the fault to take some part of the soft interlayer away and generate holes; these may have been the reason for failure (Fig. 4a). There is an old landslide dam near Benzilan town (Fig. 4b) (Zhang et al., 7

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2011), and an old landslide dam can be observed along the Dingqu River (Fig. 4c). Additionally, lacustrine deposits (Fig. 4d) formed due to river blocking are widely distributed in the study area. It can be seen that there have been many river blocking events in the study area, and research into landslide-dammed lakes is of great significance to better understanding the paleoenvironment and river valley evolution in the study area.

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Insert Fig.4 Here

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2.2. Samaoding paleolandslide

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Samaoding paleolandslide is located about 3 km upriver from Maoding Township. The

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post-failure scar on the left bank of the Jinsha River is well preserved (Fig. 5a). The scar ranges from

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an elevation of 2917 m down to 2322 m, with 1130 m in length and 890 m in width (Fig. 5b), and the dip angle of head scarp can reach 60 ° (Fig. 6). The surface of scar is generally clean and smooth, and it

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is mainly composed of fine material, which indicates that the paleolandslide might have high speed during the sliding process. Additionally, some old landslide deposits are hosted on the toe of scar, and

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the scar can be approximately treated as the slip surface without these landslide deposits. The bedrock exposed behind the scar is mainly sub-vertically dipping greenschist, and its strata attitude is 65°/∠83° (Fig. 5c). The rock mass is relatively intact, but with well-developed horizontal fissures. A pile of old landslide deposits is present on the opposite bank of the river (Fig. 5d), and it is mainly composed of gravels and sands with some boulders in it. The body of this old landslide dam is 300 m long from east to west and 1132 m wide from north to south. Its top lies at an elevation of 2330 m, and its base is at an elevation of 2150 m, which is 50 m above the river surface (2100 m). The old landslide dam is mainly composed of greenschist and is inconsistent with the lithology of the bedrock

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on the right bank of the river, which is mainly granite and gneiss. Meanwhile, there is no obvious scar on the right bank of the Jinsha River. Thus, the authors propose the explanation that the old landslide dam on the right bank of the river was from the Samaoding landslide and that the landslide caused river blocking. Other strands of evidence besides the material composition also support the occurrence of a river-blocking event. Firstly, the old landslide dam forms a bulge in the terrain on the right bank of the

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river, and the front edge has clearly been eroded by the river. Additionally, the direction of the Jinsha

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River is deflected here, and this may be because the current channel is a new channel that formed after

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river blocking. Secondly, well-consolidated pebbles and gravel, which are characteristic of fluvial

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sediments (Fig. 5e), were observed on the top of the old landslide dam (2330 m). From the extent of

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consolidation, the authors conclude that these pebbles and gravel were deposited a long time ago. These may have been deposited due to the Jinsha River flowing over the landslide dam in the flood

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season. Thirdly, a layer of well-distributed coarse sand (average grain diameter = 2 mm) was observed

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on the right bank of the river (Fig. 5f) that is consistent with deposition in a lacustrine environment.

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The authors found the surface of the bedrock of the landslide scar to be severely weathered and to feature well-developed fissures. The apertures of the fissures reach up to 30 cm, and there are clearly visible signs of erosion in marble (Fig. 5g). Erosion and suffosion by fissure-water hollow out fissures, resulting in the formation of a discontinuous structural surface with extremely low shear strength.

Insert Fig.5 Here Insert Fig.6 Here In the study area, many antidip rock slopes are present with their stratum dipping inwards the slope surface. Although, this type of slope is usually considered stable and difficult to generate rockslides (more likely to generate toppling or falls), there are still lots of such slope failures. How does this 9

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phenomenon occur? The authors think that the crucial factor is the tectonics. Because of intense tectonics, the layered rock mass is fragment and broken. For steep-inclined antidip rock slopes, the part that is bent under gravity is easily broken under tectonics, because stress easily accumulates in this part (Fig. 7a). Meanwhile, because of tectonics, many discontinuous planes are formed in the slope. Fig. 7b shows a discontinuous plane in the hard rock mass. The plane surface is smooth and straight, indicating that it is

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generated by vertical shear action of tectonics. Under intense tectonics, two types of rockslides are

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commonly observed in antidip rock slopes. The first type of rockslide frequently occurs in soft rock

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slopes with extremely fractured rock structure (Fig. 7c). Because of extreme fragmentation, the rock

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mass can be approximately treated as homogeneous from a macro perspective. Mass slides occur along

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the internal cylindrical slip surface, and this type of slide belongs to rotational slides. The second type of rockslide frequently occurs in hard rock slopes with relatively intact structure compared to the first type

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of rockslide and discontinuous planes in it (Fig. 7d). The rock is fractured under tectonics, and the

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fractured rock fragments increase the load on the lower rock mass. Because of self-gravity and extra

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loads, the rock mass is continuously deformed downwards, making discontinuous planes continuously expand and connect with others and finally generating a penetrating slip surface. Slip surface of this type of slides is determined by controlled structure planes, and mass moves along these planes. This type of slides belongs to translational slides. Similar failure phenomena of antidip rock slopes can be found on physical modeling in Li’s study (Li et al., 2019).

Insert Fig.7 Here According to the field investigation, the bedrock of Samaoding landslide is relatively intact but with many discontinuous planes present in it. The longitudinal profile (Fig. 6) shows that the landslide belongs to translational rockslides (Varnes, 1978). Therefore, it belongs to the second type of slides, and 10

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the gradual progress of failure is shown in Fig. 8. Fig. 8a shows the initial state of the slope. Because of long terms of tectonics, many discontinuous planes were formed in the slope, and some of them were almost parallel to the slope surface. The steep-inclined antidip strata bent towards the free surface under gravity, and cracks are formed at the bent part. The bent parts of strata are easily fractured under tectonics, generating rock fragments, increasing loads, and thrusting the lower strata (Fig. 8b). Under self-gravity

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and extra loads, the lower strata are gradually fractured and slid (or crept) along the controlled structure

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planes. Meanwhile, the discontinuous planes continuously expanded and connected with others under the

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action of suffosion by fissure-water and upper load (Fig. 8c). Finally, when the slope suffering from an

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earthquake, or the lower strata cannot withstand the load of upper fragmented rock mass, the controlled

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structure planes penetrated to form a complete slip surface, thus triggering a landslide (Fig. 8d).

Insert Fig.8 Here

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TL testing was carried out to date the occurrence of the Samaoding paleolandslide. TL is the light

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emitted by a crystalline or glassy material when it is heated after being exposed to ionizing radiation.

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The burial time of sediments (T) can be calculated from the radiation accumulated by the mineral particles (N) since the time of burial and the rate at which the mineral particles received it (B), which is calculated from the content of radioactive elements like U, Th, and K; T =B/N. The sample was taken from the old landslide dam body and consisted of cobble, gravel, and sand (Fig. 9). The sample was not illuminated during the collection process, and then it was sent to the Groundwater Mineral Water and Environmental Monitoring Center of the Ministry of Land and Resources, where it was first treated with 40% H2O2 and 30% HCl to remove organic matter and carbonates and then treated with 40% H2SiF6 for 5 days. After being washed in distilled water, grains between 4 μm and 11 μm were selected by the water sedimentation method. The dating result shows the Samaoding paleolandslide occurred at 11

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10.6 ± 0.5 Ka BP.

Insert Fig.9 Here Although the field investigation provided some evidence indicating that the Samaoding landslide originally blocked the river, the specific process of river blocking, as well as the post-failure scale of the landslide, remained unknown. Determining these is very important for clarifying the overall process

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of paleolandslides and may enable proposed explanations about the evolution of the Jinsha River. To

Methodology

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3.

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solve this problem, the authors used the DEM to reproduce the landslide.

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3.1. Discrete element method

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The discrete element method was first developed by Cundall (1979) for the analysis of rock mechanics. In the method, the rigid body is composed of two basic types of elements, i.e., balls and walls.

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Each element is permitted to overlap with adjacent elements to trigger a normal and a tangential force.

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The interparticle contacts are usually represented by elastic springs and viscous dampers, and the

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magnitude of the force is determined by the magnitude of overlap at contact points. Displacement and velocity are calculated from the original location and force and then updated according to Newton’s second law of movement in every time step. This method reflects the macroscopic physical–mechanical behavior of material through microscopic granular interaction. Today, many researchers use the method to simulate landslides, and the results show it to be effective (Lo et al., 2011, 2014; Lin and Lin, 2015). In the DEM, various aspects of granular contact mechanics (Mindlin and Deresiewicz, 1953; Derjaguin et al., 1975; Thornton, 1991; Maugis, 1992) are simplified to mechanical models to reflect different granular properties, and the choice of calculative model is of great importance. Here, the authors have chosen to describe the behavior of a rockslide with the ―Hertz-Mindlin with Bonding‖ 12

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model in the software package EDEM (John, 2013), because the bonded particle model (BPM) (Potyondy and Cundall, 2004) has been most widely used for rock avalanches (Lo et al., 2011; Lu et al., 2014; Lin et al., 2015; Zhou et al., 2015). BPM is conceptually based on bonding together a packed group of spheres to form a breakable body (Fig. 10a). The bond can transfer force and moment at the same time and ruptures when the tensile stress or shear stress exceeds the tensile strength or shear

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strength (Fig. 10b). After bond breakage, the particles interact according to the Hertz-Mindlin no-slip

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contact model (Fig. 10c), and no further bonds will be generated. In Hertz-Mindlin no-slip contact

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model, the normal force component is based on Hertzian contact theory (Hertz, 1882). The tangential

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force model is based on Mindlin-Deresiewicz work (Mindlin and Deresiewicz, 1953). Both normal and

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tangential forces have damping components where the damping coefficient is related to the restitution coefficient (Tsuji et al., 1992). The tangential friction force follows the Coulomb law of friction model

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(Cundall and Strack, 1979). The rolling friction is implemented as the contact-independent directional

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constant torque model (Sakaguchi et al., 1993). The Hertz-Mindlin no-slip contact model can well

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illustrate granular interactions between cohesionless particles.

Insert Fig.10 Here

Certain micro-parameters are essential to the model, including the parameters μ (friction coefficient), E (Young's modulus), and ν (Poisson’s radio) between particles, and the bonding parameters ̅̅̅ 𝜎𝑐 (tensile strength of bonding), ̅̅̅ 𝜏𝑐 (shear strength of bonding), 𝑘̅𝑛 (normal bond stiffness of bonding), and 𝑘̅𝑠 (tangential bond stiffness of bonding). However, microscopic parameters cannot be measured easily, and a robust theoretical basis has not yet been established for ensuring that the magnitude of the relationship between macroscopic parameters and microscopic parameters is correct. Therefore, numerical parameter calibration experiments are usually performed. If the results of 13

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numerical experiments are not consistent with laboratory tests, a new group of microscopic parameter values will be provided for the numerical experiment to be recalibrated. By repeating numerical experiments with different microscopic parameters until the outcomes of numerical experiments are consistent with laboratory tests, the microscopic parameters can be considered appropriate. To acquire and calibrate the micro-parameters of greenschist material, the authors refer to Zhang’s laboratory test

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(Zhang et al., 2012) of uniaxial compression test for greenschist, and adopt a numerical uniaxial

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compression test imitating it. This test enables macro-parameters including the uniaxial compression

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strength (UCS), Young’s modulus, and Poisson’s ratio to be calibrated. Fig. 11 shows numerical tests

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for deriving the micro-parameters of the EDEM model and shows that the outcome of numerical

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uniaxial compression after repeated calculations is consistent with that from laboratory tests. To improve the calculative efficiency, the radius of particles in the landslide simulation will be many times

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greater than in the numerical test. This leads to a change in the stiffness of bonding, as the magnitude

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of the bond stiffness is inversely proportional to the particle radius. This relationship can be expressed 𝐸𝑐 as: 𝑘̅𝑛 = 𝑅 +𝑅 (Potyondy and Cundall, 2004), where R is the radius of the particles and 𝐸𝑐 is the 2

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1

Young's modulus of the bond. The corresponding micro-parameters are shown in Table 1.

Insert Fig.11 Here Insert Table.1 Here

3.2. Construction of a 3D model

The definition of the pre-failure topography is essential for reproducing the landsliding process. However, no topographic data are available for 10.6 ± 0.5 Ka BP. The only way to acquire the pre-failure topography is to restore it on the basis of the present-day terrain. The restoration relies on DTM data with an accuracy of 15 m and comprises the following three main aspects: repairing the 14

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terrain in the sliding area to its pre-slide morphology, removing the old landslide dam on the right bank of the river, and restoring the riverbed topography in consideration of channel incision. The principle guiding repair of the topography in the slide area and old landslide dam area is to restore the ground surface to the natural angle of repose, because the authors found in the field investigations that slopes along the Jinsha River are mostly at the natural angle of repose, and slopes at the natural angle of

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repose can remain stable for a long time. First, terrain raster data in the DTM are converted to point

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cloud data using the Conversion Tools in ArcGIS software to allow for more convenient modification;

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point cloud data in the relevant area are then deleted, and characteristic terrain points are added.

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Secondly, natural neighbor interpolation, which can scientifically solve ground surface construction

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(Anton, 2001; Dinis et al., 2007; 2008), is used to conduct point cloud interpolation in the sliding area. Additionally, the valley lies in an area undergoing rapid uplift (Li and Fang, 1999; Harris, 2006; Li et

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al., 2015), which has usually been accompanied by rapid fluvial incision during the Cenozoic. Previous

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research (Huang et al., 2010; Luo et al., 2010; Dong et al., 2018) has shown the relative incision rate of

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the Jinsha River to be between 117 cm/ka and 465 cm/ka in the last 20 ka, generally higher in the upstream section than in the downstream section. It is therefore necessary to consider the elevation of the riverbed at 10.6 ± 0.5 Ka BP in the simulation. Thirdly, the revised point cloud data are converted to terrain raster data, and 3D contour lines are extracted from those data. Finally, a solid slope model is constructed based on 3D contour lines via the CAD software Rhino, and the model is then used in the DEM simulation. The process of model construction is shown in Fig. 12. The topography of slip surface can be approximately treated as the residue chair-shaped topography in the simulation (Ventisette et al., 2015; Ibañez and Hatzor, 2018) with old landslide deposits removed. The sliding mass is determined on the basis of the difference between the pre-failure topography and post-failure 15

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topography in the sliding area; topographic analysis gives a volume of about 33×106 m3. In this study, a ball-wall model using ball elements to compose a landslide body and wall elements to compose a bedrock was used for the landslide simulation. To prevent excessive calculations while ensuring the accuracy of the calculation, up to 108878 balls are used to form the landslide body, and the radius of the ball-elements is limited to between 3.5 m and 7 m. The internal friction between balls is usually set

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at the friction value for rock blocks, which is 0.5 in the simulation. Whereas this mainly influences the

oo

final landslide configuration and has little effect on the run-out distance, the friction between the

pr

sliding mass and the slip surface can strongly influence both. However, the frictional mechanism that

e-

operates as the sliding mass moves at high speed on the slip surface is complicated and cannot be

Pr

simply reflected by the friction. Many landslide events (Aaron and Hungr, 2016; McDougall, 2017; Ibañez and Hatzor, 2018; Aaron and McDougall, 2019; Hu et al., 2019) and laboratory tests (Ditoro et

al

al., 2004; Han et al., 2007) have proved that a rockslide moving over a slip surface will greatly reduce

rn

friction at the slip surface. Some mobility theories have been proposed to illustrate the phenomenon

Jo u

including high pore-air pressures leading to enhanced mobility (Shreve, 1968; Manzanal et al., 2016), dynamic fragmentation (Davies et al., 1999; Bowman et al., 2012), flash heating (Erismann, 1979; Hu et al., 2019), and acoustic fluidization (Melosh, 1979; Johnson and Campbell, 2017). To determine the friction value, the authors refer to parts of the literature reporting back analysis of 3D DEM landslide simulations (Table. 2). It could be found that compared to a soil slide, friction coefficient in a rockslide is generally smaller, which mainly ranges from 0.05 to 0.15 (Table.2). Therefore, the friction coefficient between the sliding mass and slip surface is set to 0.1 preliminarily, and, for river resistance, that at the riverbed surface is set as 0.25 (Lu et al., 2014). The run-out process is started by reducing the friction coefficient on slip surface (Lin and Lin, 2015). 16

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Insert Fig.12 Here Insert Table.2 Here 4.

Numerical simulation results

In addition to measuring parameters in the field or laboratory, an alternative approach for selecting parameters is to calibrate values through numerical back-analysis of past landslides

oo

f

(McDougall, 2017, Aaron et al., 2019). In fact, in the landslide simulation using DEM, back-analysis is the most important way to calibrate a simulation result (Tang et al., 2009; Lo et al., 2011, 2014; Lin and

pr

Lin, 2015), because some parameters such as friction coefficient of the slip surface cannot be easily

e-

calculated or acquired from a test. And considering the mobility of rock avalanche is complex (Aaron

Pr

and McDougall, 2019), a back-analysis for the Samaoding landslide is essential. In this section, the

al

authors carried out a sensitive analysis of main parameters including friction coefficient of the slip

Jo u

investigation.

rn

surface, bond strength and riverbed elevation, to acquire the most suitable result with the field

4.1. Influence of the friction coefficient of the slip surface Theoretically speaking, friction between particles and the slip surface can strongly influence both the velocity and run-out distance of a sliding mass. To explore the influence of friction on mass movement, four simulations were run with the friction coefficient set to 0.1, 0.2, 0.3, and 0.4, respectively; the results are shown in Fig. 13. It can be seen that with an increase in the friction coefficient, the volume of the sliding mass and the corresponding run-out distance will decrease. More and more mass will remain on the slip surface, and there will be a decrease in the thickness of the landslide deposit on the riverbed. The maximum velocity reached by the sliding mass during the

17

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process is 48 m/s, 51 m/s, 57 m/s, and 64 m/s for the values u=0.4, u=0.3, u=0.2, and u=0.1, respectively. When u is greater than 0.2, the scale of the mass remaining on the slip surface is not consistent with the scale of the landslide deposits on the scar, and the deposit in the river channel does not reach the observed location of the old landslide dam. These simulations show that 0.1 is an appropriate friction coefficient value for Samaoding landslide and that friction between the particles

f

and the slip surface does indeed play an important role in mass movement and in the area affected.

oo

Insert Fig.13 Here

pr

4.2. Influence of bond strength

e-

The strength of the rocky material in the field is lower than the values obtained in laboratory tests

Pr

because of the existence of joints and cracks and due to weathering. Thus, it is necessary to consider the effect of rock strength on the rockslide. The authors explored this effect by running simulations

al

with four bond strength values 𝜎 ̅̅̅=0 MPa, 8 MPa, 80 MPa, and 200 MPa, keeping the total number of 𝑐

rn

bonds at 430948 under every condition. The simulation results (Fig. 14) indicate that the number of

Jo u

intact bonds is 0, 0, 5697, and 21238 under the conditions ̅̅̅=0 𝜎𝑐 MPa, 8 MPa, 80 MPa, and 200 MPa, respectively. It is apparent that when the strength of the bonds is less than a certain value, almost all bonds will be broken during the mass movement process, but when the bond strength exceeds that value, the number of intact bonds will increase with an increase in bond strength. Affected by the movement distance, intact bonds are mainly distributed at the back part of the deposit. This dynamic fragmentation is one of the reasons which can lead to greater runout or spreading (Davies et al., 1999; Bowman et al., 2012). Additionally, the phenomenon of almost total bond breakage indicates that the internal interactions between particles and the collisions between the particles and the slip surface are very severe. The authors conclude high-impact collision can produce a large amount of heat, which can 18

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lubricate the slip surface (Erismann, 1979; Hu et al., 2019), and lead to greater runout path. This illustrates why friction coefficient of the slip surface is lower than the natural friction angle of material. The simulation result is consistent with the field observation that the sliding mass is almost powdered after having moved such a long distance at high speed (Fig. 9), with some boulders left (Fig.14). Additionally, the authors find that the bond strength of the rock has little effect on the landslide scale in

f

the condition when most of the bonds are broken. However, the areal extent of the landslide will

oo

decrease significantly when a large number of bonds remain intact (Lo et al., 2011, 2016; Lin et al.,

pr

2015).

Pr

4.3. Influence of riverbed elevation

e-

Insert Fig.14 Here

To investigate the elevation of the riverbed at 10.6 ± 0.5 Ka BP and assess the rate of channel

al

incision, the authors designed four elevation values for the riverbed (2070 m, 2080 m, 2095 m, and

rn

2110 m), which correspond to incision rates in the riverbed of 0 cm/ka, 100 cm/ka, 250 cm/ka, and 400

Jo u

cm/ka, respectively. The simulation results (Fig. 15) show that an increase in the riverbed elevation significantly increases the height of the top of the landslide deposit. When the elevation of the riverbed is less than 2095 m, the sliding mass cannot reach its present-day level. Furthermore, the simulation results for a riverbed at an elevation of 2095 m are also the most consistent with the actual situation. This gives a lower bound for the original elevation of the deposits, given that some non-fluvial erosion will also have occurred. Thus, it can be concluded that the rate of fluvial incision has been at least 250 cm/ka in the last 11 ka, making this period one of rapid incision.

Insert Fig.15 Here 4.4. Characteristics of the sliding process 19

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The above simulations show that a good fit is achieved between the simulation results and the actual conditions with a friction coefficient of 0.1, parallel bond strength of 85 MPa, contact stiffness of 4 × 108 kN/m, and riverbed level of 2095 m. The simulation results indicate that the Samaoding landslide process took 80 s, and corresponding landslide process is shown in Fig. 16. To know the detailed information of run-out behavior, seven groups of balls were set to trace and record positions and velocities in every step

f

(Fig.17a). All the balls started moving simultaneously, initially slowly except for ball group 7 which was

oo

pushed out over the edge of the lower part of scar and accelerated unconstrained down to the river.

pr

Monitoring groups 6 and 5 were initially a bit slower until they too went over the lower part of scar and

e-

accelerated downslope. The maximum velocity of sliding mass could reach 64 m/s. The lower half of

Pr

failing mass will decelerate because of friction and collision with the riverbed after reaching the riverway. The upper half of failing mass appears to have been left behind by the lower half, due to being impeded

al

by the lower half of failing mass (Fig. 17b). The maximum runout distance is about 1500 m.

rn

In general, the whole sliding process can be divided into two stages. Initially, the sliding mass

Jo u

accelerates continuously before reaching the riverbed, reaching a maximum velocity of 64 m/s; after the leading edge has reached the riverbed, the sliding mass begins to decelerate rapidly because of friction and collision with the riverbed, and its leading edge decelerates continuously after the sliding mass runs up onto the opposite bank until it comes to a standstill. During the period from the initiation of failure to the halting of the leading edge, the sliding mass generally moves in the direction of the main slide line. After the front part stops moving, the back part begins to move along the riverbed and gradually piles up due to confinement by the front part. In this period, the direction of movement is perpendicular to the main slide line. The landslide finally forms a landslide dam with a length of 1800 m, a width of 600 m, and a depth of 200 m. Due to the large vertical drop undergone by the slide, the sliding mass has a large 20

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amount of kinetic energy before reaching the riverbed and can rush up to a relatively high level on the opposite bank.

Insert Fig.16 Here Insert Fig.17 Here 5.

Discussion

oo

f

The findings above can be used to propose a reasonable evolutionary sequence for the river-blocking event of the Samaoding paleolandslide. Before 10.6 ± 0.5 Ka BP, a large number of cracks

pr

and discontinuous interfaces will have been present in the bedrock due to slope creep towards the free

e-

face as well as the intense regional tectonic activity, making rock slopes unstable (Fig. 18a). Meanwhile,

Pr

the large amount of fissure water in the slope may have reduced the strength of the discontinuous

al

interfaces. Under such conditions, landslides can easily be triggered by various events and processes,

rn

including earthquakes, rainfall, long-term creep at the free face, or rock burst (Ren et al., 2019) due to

Jo u

high tectonic stress. Upon the occurrence of such a trigger, a volume of 33×106 m3 of material failed and slid along the slip surface. The sliding mass blocked the Jinsha River, and the leading edge ran forward through the river to pile up on the opposite bank. The landslide dam is estimated to have been 1900 m long, 600 m wide, and 200 m deep (Fig. 18b). The landslide dam was not destroyed in a short time, and river flow occurred over the top of it (Fig. 18c). Flow was slow over the dam and had weak carrying capacity, leading to the deposition of early-period fluvial sediments on the top of the dam (Fig. 5e) and sand deposition downstream of the dam (Fig. 5f). The dam was then continuously washed over and eroded by the river so that a flood-relief channel formed (Fig. 18d). After the dam was broken, the main body of the dam was rapidly taken away by water flows because the water flows during the dam

21

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break outbursts achieved high magnitudes and were extremely erosive (Kehew and Lord, 1986). Under the rapid uplift of the valley, the river incised downwards rapidly with a rate of fluvial incision of at least 250 cm/ka. During this process, lateral erosion was weaker than downward incision on the right bank due to the influence of the curve in the river, which led to the retention of a partial old landslide dam on the right bank (Fig. 18e). Then under long-term river incision, the river removed most of the

f

landslide dam and incised through a certain thickness of bedrock (Fig. 5d), forming the current

oo

landform (Fig. 18f).

pr

Insert Fig.18 Here

e-

Notably, most landslide dams failed in a short time: 27% of the dams failed within one day of

Pr

formation; 41% failed within one week; and 80% failed within six months (Costa and Schuster, 1988). Most of the collapses coincide with the first dam overtopping (Ermini and Casagli, 2003). However,

al

the Samaoding landslide will probably not fail in a very short time because of the presence of

rn

early-period fluvial sediments on the top of dam and sand deposition. Some cases show that the

Jo u

landslide dam will probably not completely fail immediately after overtopping (Korup and Tweed, 2007). For example, the landslide dam formed on 6 October 1999 in South Westland lasted six days after overtopping (Hancox et al., 1999). Lacustrine sedimentary sections (clayey silt layer) (Fig. 4d) indicate that some landslide dams in the study area can exist for a very long time. Other studies (Wang et al., 2014; Liu et al., 2018; Ma et al., 2018; Chen et al., 2018) also show that the landslide dams in the southeastern margin of Tibetan Plateau can exist for several thousand years. Why can these landslide dams last for such a long time? In Costa’s (Costa and Schuster, 1988) and Chen’ studies (Chen et al., 2018), three factors are the most relevant to the longevity of a landslide dam: (1) rate of inflow to the impoundment; (2) size and shape of the dam, and (3) geotechnical characteristics of the dam. In the 22

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southeastern Tibetan Plateau, mountainous topography provides conditions for huge landslides (Delaney and Evans, 2015), leading to large-volume of landslide dams. They are very difficult to fail in a very short time, and consolidation increases the stability of dam. For rockslide dams, some large rock fragments will be generated after slope failure, and these large particles well resist failure (Costa and Schuster, 1988). In Evans’s study (Evans et al., 2011), only 20% of major rockslide dams fail with 75

f

days of formation. Although rivers at the southeastern Tibetan Plateau have strong downward incision

oo

effect, their inflow is too small as the river upstream. Another fact is that in the southeastern Tibetan

pr

Plateau, multiple dammed lakes may be close to each other to form lake clusters in a period (Chen et al.,

e-

2013; Wang et al., 2014; Chen et al., 2018), reducing the discharge of river flow. The reason for the

Pr

formation of dammed-lake clusters is that intensive tectonics (such as earthquakes) lead to many landslides, thus blocking the river in a short period. Therefore, the landslide dam is difficult to fail in a

al

short time. Previous study (Vilimek et al., 2005) suggests that seepage and overtopping are among the

rn

less frequent causes of sudden failure. Therefore, how does the barrier lake existing for thousands of

Jo u

years suddenly fail? The authors think tectonics plays an important role. The landslide dam will suddenly fail under a large earthquake or gradually becomes weak under long-terms tectonic movement.

6.

Conclusions

The developmental process of the Samaoding paleolandslide and the evolution of the upstream reaches of the Jinsha River were studied through a series of investigations including fieldwork, TL testing, topographic analysis, and numerical simulation. Field investigation shows that a large rockslide occurred on the left bank of the Jinsha River and caused river blockage. An old landslide dam is still

23

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preserved on the opposite bank of the river and preserves clear evidence for river blocking phenomena. Failure mechanism of the Samaoding landslide was analyzed, and the failure mechanism of steep-inclined antidip rockslides is also summarized. TL dating indicates that the landslide occurred at 10.6 ± 0.5 Ka BP. A numerical simulation was also carried out based on the restored topography and showed that the landslide occurred in about 80 s when a rock mass of about 33×106 m3 failed and slid

f

downwards. Because of the large drop undergone by the slide and resulting self-lubrication at the slip

oo

surface, the maximum velocity of the sliding mass reached 64 m/s, and the landslide finally formed a

pr

900 m long, 600 m wide and 200 m deep landslide dam. Rapid fluvial incision eroded away most of the

e-

landslide dam material and incised 25 m into the bedrock. The significance of this study is that is

Pr

shows how an integrated approach (field investigation, TL testing, topographical analysis, and numerical simulation) can provide reasonable, quantitative detail on a paleolandslide and allow

al

proposed explanations to be made on the evolution of landforms in the upstream reaches of the Jinsha

rn

River. This work can serve as a reference for other river blocking events. In addition, we found that

Jo u

tectonics plays an important role in the formation of landslide dams (or trigger landslides) and the failure of landslide dams in an active tectonic environment. This study proves that DEM can be well applied to the simulation of land surface processes such as rockslides, and various numerical models probably play important roles in the future work of landform evolution. However, in the landslide river-blocking simulation, there are still limitations that can be improved in the future. For example, the river resistance is taken into consideration in the DEM simulation by increasing the value of the friction coefficient. This is acceptable when the main concern is the mass movement and the scale of the landslide is much larger than that of the river. However, it is difficult to estimate the scale of the dammed lake after the landslide blocks the river and to reflect the 24

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erosional effect of river flow on the dam. Future work should consider using coupled DEM-CFD (computational fluid dynamics) (Zhao et al., 2017), which can precisely reflect the interaction between particles and flow at a micro-level, or smoothed particle hydrodynamics (SPH) (Pastor et al., 2009b; Shi et al., 2015; Wang et al., 2017), which can reflect the interaction between particles and flow at a macro-level. It is worth noting that CFD-DEM coupling requires very high-quality meshes. Also,

f

because its use is limited by computational capacity, the diameters of particles would need to be

oo

enlarged by many times, which would significantly affect the movement of particles in fluids and cause

pr

the numerical simulation to differ substantially from reality. For example, if the minimum diameter of

e-

particles were 5 m in a river-blocking simulation, that would correspond to a 5-m boulder in reality,

Pr

which is difficult for a river to transport. Therefore, applying it to a real example in 3D would be both interesting and challenging.

al

Acknowledgements

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This work was supported by the National Natural Science Foundation - Yunnan joint fund key support project (Grant No. U1702241), and the National Key Research and Development

Jo u

Program of China (2017YFC1501004).

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List of figure captions: Fig. 1. Flowchart of this work. Fig. 2. Location maps and overview of the study area. (a) Location of the study area; (b) geomorphological conditions of the study area (The photograph of the study area is taken in March 2014); (c) overview of Samaoding paleolandslide. Fig. 3. Geological map of the study area. Fig. 4. River-blocking phenomena of river blocking observed during the field investigations. (a) Post-failure condition of Zhisishan landslide; (b) relict landslide near Benzilan town; (c) old landslide 36

Journal Pre-proof deposits from the opposite bank along the Dingqu River; (d) lacustrine deposits in the study area (see Fig.2b for locations). Fig. 5. Geological conditions of the Samaoding paleolandslide. (a) Overview of the Samaoding paleolandslide; (b) old landslide deposits on the residual slip surface; (c) green schist bedrock on the left bank of the river; (d) sedimentary relationship on the right bank of the river; (e) early-period fluvial sediments on the top of the old landslide dam; (f) hydrostatic sandy sediment; (g) fissures and erosion. Fig. 6. Longitudinal profile of Samaoding paleolandslide in Fig. 5. Fig. 7. Antidip rock slopes in the study area. (a) Flexural-toppling phenomenon in slates; (b) a

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shear-type discontinuous plane caused by tectonics; (c) a potential rotational slide in a very broken antidip rock mass; (d) a translational rockslide in an antidip rock mass.

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Fig. 8. Failure mechanism of Samaoding landslide (Red lines represent controlled structure planes). Fig. 9. Location for sampling site (see Fig.5 for the location).

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Fig. 10. Scheme of Hertz-Mindlin with bonding model (a) Schematic representation of BPM (modified

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from Potyondy, 2004); (b) schematic force-displacement behavior on a bond beam (modified from Cho et al., 2007); (c) the simplified mechanic model of Hertz-Mindlin no slip contact model.

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Fig. 11. Numerical uniaxial test and the outcome consistent with laboratory experiment. (a) Numerical uniaxial test sketch; (b) stress-strain curve obtained from the numerical experiment; (c) axial strain -

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transverse strain curve obtained from the numerical experiment; (d) comparison of the

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macro-parameters between the numerical model and the laboratory experiment. Fig. 12. Process of the construction of a 3D DEM model. Fig. 13. Simulation of various friction coefficient values between particles and slip surface. Fig. 14. Simulation of various bonding strengths (red color denotes the intact bonds between particles). Fig. 15. Simulation of various riverbed levels. (a) An example of 3D simulation result (Riverbed level=2070 m); (b) vertical profiles of deposit mass; (c) plane graph of deposit mass. Fig.16. Dynamic mass movement process of Samaoding landslide. Fig.17. Run out behavior in different parts of sliding mass. (a) Position of the monitoring balls and corresponding traces; (b) velocity of monitoring balls in the whole sliding process. Fig.18. The evolution of the Samaoding landslide river-blocking event. (a) Pre-failure landform; (b) the landslide blocks the river; (c) river flow through the top of the dam; (d) a flood-relief channel forms under river erosion; (e) different extents of lateral erosion cause left-bank landslide dam deposits to be 37

Journal Pre-proof transported by the river while a partial old landslide dam remains on the right bank of the river; (f) rapid river flow incises into the bedrock and forms the present-day landform.

Table.1 DEM modeling numerical parameter values Numerical

Numerical

parameters of the

parameters of the

compression test

landslide modeling

3

-4

3300×104

Simulation volume (m )

1.97×10

Number of particles

15713

Radius (m)

0.01-0.016

Particle density (kg/m3)

2600

2600

Friction between balls

0.5

0.25

Friction between balls and slip surface

0.5

38.7

38.7

0.1-0.4

0.25

0.25

8.5e7

8.5e7

4.2e7

4.2e7

1.4e12

4e8

7e11

2e8

e-

E (GPa) ν

𝜏𝑐 ̅̅̅(Pa) 𝑘̅𝑛 (N/m ) 3

rn

al

𝑘̅𝑠 (N/m3)

Pr

𝜎 ̅̅̅(Pa) 𝑐

3.5-7

pr

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f

108878

Table.2 Micro-parameters for 3D landslides simulation from back analysis in other studies

Jiweishan, China Butangbunasi River, Taiwan

type Rock slide

Lime stone

Rock

Sandstone

avalanches

and shale

Debris slide

Hsiaolin,Taiwan

material

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area

with rock avalanche

Sandstone with shale

μ

𝜎𝑐 ̅̅̅(MPa)

𝜏𝑐 ̅̅̅(MPa)

𝑘̅𝑛 (N/m3)

𝑘̅𝑠 (N/m3)

0.05

200-250

200-250

\

\

0.06

6

6

2.18e9

2.18e9

0.1

16

8

4e8–4.8e8

0.1

30

15

1.5e9-6.0e9

0.15

100

50

2e9

reference Zhang et al., 2012 Lin et al., 2015

2e8–

Lo et al.,

2.4e8

2011

7.5e8–

Lo et al.,

3.0e9

2014

Colluvium SuHuaHighway, Taiwan

Rock debris

and weathered rock

Xinmo, China

Rock avalanches

Sandstone Limestone

Wenjiagou, China

Rock slide

Hungtsaiping,

Colluvium

Colluvial

Taiwan

slide

deposits

and shale

0.2

2

0.3

5.2

38

2

2.6

2e8

2.71e7

1e9

2e8

1.35e7

Gianvito et al., 2018 Liu et al., 2018a Lo et al., 2016

Journal Pre-proof Bayi, China

μ

Debris

Soils and

avalanches

rock blocks

3e-3-1e-2

0.5

3e-3-1e-2

3e6–1e7

3e6–1e7

Zhou et al., 2015

denotes the friction coefficient between sliding mass and slip surface, ̅̅̅ 𝜎𝑐 denotes the tensile strength of bonding, ̅̅̅ 𝜏𝑐 denotes

shear strength of bonding, 𝑘̅𝑛 denotes the normal bond stiffness of bonding, 𝑘̅𝑠 denotes the tangential bond stiffness of bonding.

Highlights 1) The Samaoding paleolandslide occurred at 10.6 ± 0.5 Ka BP according to TL analysis.

oo

f

2) Detailed run out process of the Samaoding paleolandslide was well

pr

reproduced by DEM simulation.

e-

3) The relative incision rate of the study area is at least 250 cm/ka in the past 10000 years.

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4) The evolution of the Samaoding paleolandslide is proposed.

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summarized.

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5) Failure mechanism of steep-inclined antidip rockslides is

39

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Figure 16

Figure 17

Figure 18