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Title Failure Mechanism and Its Induced Movement Simulation of Large-scaleSlope

Author(s) 史, 嘯

Citation Nagasaki University (長崎大学), 博士(工学) (2017-03-21)

Issue Date 2017-03-21

URL http://hdl.handle.net/10069/37312

Right

NAOSITE: Nagasaki University's Academic Output SITE

http://naosite.lb.nagasaki-u.ac.jp

Doctoral Thesis

Failure Mechanism and Its Induced Movement

Simulation of Large-scale Slope

March 2017

Graduate School of Engineering

Nagasaki University

Xiao Shi

I

ACKNOWLEDGEMENTS

I would like to express my gratitude to all those who helped me during the writing of this

thesis. My deepest gratitude goes first and foremost to Prof. Yujing Jiang, my supervisor,

in the faculty of civil engineering, Nagasaki University, for his constant encouragement

and guidance throughout my studies in master course in Nagasaki University. Without his

patient instruction, insightful criticism and expert guidance, the completion of this thesis

would not have been possible. He taught me how to think about a problem independently,

how to become more confident, more passionate, more aware of what I am striving after,

and to think about how well beyond. Acknowledgements are due to Assistant Professor

Bo Li who always kindly teaches me how to write the thesis and how to revise my English

and Japanese. Acknowledgements are also due to Assistant Professor Satoshi Sugimoto

who gives me many supports in my study and daily life.

I would like to thank Prof. Akihide Tada and Prof. Kiyoshi Omine in Nagasaki

University for their generous help and continuous supports for my research. I would like

to express my appreciation to all the professors, associate professors and assistants in

Graduate School of Engineering and all the students studying now and graduated from

Nagasaki University for their supports and for the inspiring atmosphere they have created.

I wish to thank my friends in China and the Chinese friends in Japan for their

supports and encouragement during my study in Japan. My grateful thanks should be

given to Dr. Richeng Liu, Dr. Xiaoshan Wang, Dr. Qu Wang, Dr. Xuezhen Wu, Dr.

Jianhua Wang, Dr. Na Huang, Dr. Chen Wang, Dr. Xuepeng Zhang, Dr. Jian Zheng,

Mr. Hao Huang, Mr. Han Xia, Mr. Kai Liu, Miss Ying Li and Miss Xuening Guo. I am

always encouraged by our great friendships. I also thank Dr. Santos Chicas, Dr. Yukihiro

Higashi and Dr. Junpei Ishida and I will always remember the wonderful time we spent

together.

I should finally like to express my deepest gratitude to my beloved parents who have

always been helping me out of difficulties and supporting without a word of complaint. I

definitely can’t smoothly finish my doctoral study without their love and supports.

Xiao Shi Nagasaki University

III

Abstract

In this study, failure mechanism research of the large-scale slope and its induced

movement research, including (1) insufficient inventory mapping of slope failure, (2)

selecting method in stability analysis of large-scale slope and (3) movement simulating

methods of large-scale slope was reviewed. Slope failure is a complicated system, for the

purpose of slope failure mitigation, the simulation of slope failure should be conducted

in the scale of region area. However, a problem is that the stratum mechanics

characteristics and surface topography in a large-scale slope are some degree difficult to

grasp. Slope failure or movement usually occurs in a short period of time and the

destructive power can cause great damage and loss of life. Few researches took the

prediction of slope failure and movement into account.

Slope failure simulation are studied with finite difference method (FDM), which is

a mesh-based method in stability analysis of large-scale slope. The FLAC3D is an FDM

software and used in this study. For a large-scale slope, how to judge the stability of slope

is difficult. The high accuracy terrain data is hard to be obtained. Airborne laser scanning

is an effective method to measure terrain data in a large-scale region. The airborne laser

data and FDM modeling are applied to analyze the mechanism of Aso-Ohashi landslide

during 2016 Kumamoto earthquake. In this case, Aso-Ohashi landslide was reproduced

by using numerical simulation. The Shear Strength Reduction Method (SSRM) was

adopted and earthquake wave was input to explore the mechanism of Aso-Ohashi

landslide. From the result of simulation, we could estimate that:

1) Earthquake wave reduced strength of rock and made collapsed rock liquefaction.

2) The foreshock simulated by SSRM indicated that, critical values of strength were

c = 16 kPa and φ = 33.87 degree.

3) The passive collapsed region was gently dipping region where failure of slope

was hardly occurred. The primary triggering factor of slide might shear force produced

when mass of active collapsed region flew past.

Another case is to analyze the stability of lava dome in Unzen volcano. The

appearance, growth, and stability of Heisei Lava Dome in Unzen volcano, Japan was

Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope

IV

analyzed. A new division method of lava dome was presented. Lava dome was divided

into 10 PCBs (potential collapsed blocks) by the surface distribution and the deep of PCBs

was calculated by airborne laser data in different period. From stability analysis, if slide

plane was not considered, the reduction rate would be 30% (c was 120 kPa, φ was 23.2

degree), the model was likely to be unstable. That meant it was hard to induce slope

failure and movement. But if slide plane was considered, the model without earthquake

input would be unstable when reduction rate was 70% (c of PCBs was 280 kPa, φ of PCBs

was 46.0 degree, c of interface was 168 kPa, and φ of interface was 17.3 degree). The

critical reduction rate of unstable status was 76%, 81%, 84%, 90%, 95%, 99%, 100%

when intensity scale respectively was 1, 2, 3, 4, 5, 6 and 7. Potential failure in maximum

volume was inferred from lobes 1 to 11 and including PCBs 1 ~ 9.

For the movement of failure of slope, a Bingham model is developed in which the

movement is assumed to be continuous, incompressible, unsteady flow. The model which

is based on the continuity equations and Navier-Stokes equations can simulate the

propagation and deposition of movement across the three dimensional complex terrain.

Raster grid networks of digital elevation model in GIS (Geographic Information System)

provide a uniform grid system to describe complex topography. As the raster grid can be

used as the finite difference mesh, the continuity and momentum equations are solved

numerically using the finite difference method. The accuracy of model was verified

through the comparison of simulation results with the experimental results obtained from

the U.S. Geological Survey debris flow flume between 1994 and 2004. The model

achieved reasonable results in comparison with experiment. The numerical model is

applied to simulate the earthquake-induced movement occurred in Aso-Ohashi landslide.

Through simulation of movement caused by failure of slope, it was verified that the mass

had an initial velocity. Therefore, the active collapsed region caused by earthquake wave.

In another case, the prediction of the potential pyroclastic flow in lava dome, Unzen

volcano shows that the total volume of failure region would be 1.46×107 m3. Pyroclastic

flows caused by that were estimated based on a Bingham model and the average velocity

would be approximately 20 m/s, the flow travels approximately 8.5 km. That means in

approximately 7 minutes, the pyroclastic flow will submerge the downstream city.


V

Contents ACKNOWLEDGEMENTS .................................................................................................................. I

Abstract ............................................................................................................................................... III

CHAPTER 1 ......................................................................................................................................... 1

Introduction ........................................................................................................................................... 1

1.1 Background and objectives ..................................................................................................... 1

1.2 Thesis arrangement and outline .............................................................................................. 8

References ................................................................................................................................... 11

CHAPTER 2 ....................................................................................................................................... 15

Review of slope stability analysis research and slope movement research ........................................ 15

2.1 Insufficient slope failure inventory mapping ........................................................................ 15

2.2 Selecting method in slope failure susceptibility .................................................................... 16

2.3 Simulating methods of slope movement ............................................................................... 17

References ................................................................................................................................... 24

CHAPTER 3 ....................................................................................................................................... 31

Finite difference method and its application to the study of stability analysis on large-scale slope ... 31

3.1 Introduction ........................................................................................................................... 31

3.2 Terrain data from airborne laser scanning system ................................................................. 31

3.3 Description of finite difference method (FDM) and FLAC3D ............................................... 33

3.4 FDM simulation of three dimensional model ....................................................................... 34

3.4.1 Shear Strength reduction method ............................................................................... 36

3.4.2 Earthquake loading .................................................................................................... 37

3.5 Conclusions ........................................................................................................................... 42

References ................................................................................................................................... 43

CHAPTER 4 ....................................................................................................................................... 45

GIS-based numerical simulation of slope movement: a Bingham model ........................................... 45

4.1 Introduction ........................................................................................................................... 45

4.2 Governing equations ............................................................................................................. 46

4.3 Geographic Information System (GIS) ................................................................................. 48

4.3.1 Basic concept of GIS.................................................................................................. 48

4.3.2 Introduction of GIS structure ..................................................................................... 50

4.4 Incorporation of numerical simulation with GIS .................................................................. 51

4.4.1 Digital elevation model based on GIS ....................................................................... 51

4.4.2 Numerical scheme ...................................................................................................... 52

4.4.3 Bingham determine statement .................................................................................... 54


VI

4.5 Comparison of simulation results of Bingham model with the experimental results ............ 55

4.6 Conclusions ........................................................................................................................... 58

References ................................................................................................................................... 60

CHAPTER 5 ....................................................................................................................................... 65

Simulation of the initiation and motion of seismically induced Aso-Ohashi landslide during 2016

Kumamoto earthquake ........................................................................................................................ 65

5.1 Introduction ........................................................................................................................... 65

5.1.1 Summary of 2016 Kumamoto earthquake ................................................................. 67

5.1.2 Earthquake-induced landslides and outline of Aso-Ohashi landslide ........................ 68

5.2 Geologic background ............................................................................................................ 69

5.3 Comparison of terrain before and after earthquake ............................................................... 70

5.4 FDM Modeling and reproduction of destruction process ..................................................... 72

5.5 Stability analysis of foreshock by using shear strength reduction method ........................... 75

5.6 Stability analysis of mainshock by seismic inputs ................................................................ 78

5.7 Motion simulation of slide mass in the slope failure ............................................................ 81

5.8 Conclusions ........................................................................................................................... 83

References ................................................................................................................................... 85

CHAPTER 6 ....................................................................................................................................... 89

Growth and potential collapse of the lava dome in Unzen volcano and the estimation on slope

movements .......................................................................................................................................... 89

6.1 Introduction ........................................................................................................................... 89

6.1.1 Formation and Growth of lava dome ......................................................................... 91

6.1.2 Temporal variation of volcanic activity ..................................................................... 92

6.2 Division of lava dome ........................................................................................................... 95

6.2.1 Airborne laser data available ...................................................................................... 95

6.2.2 Block division in the surface ...................................................................................... 99

6.2.3 Evaluation of elevation change ................................................................................ 100

6.2.4 Depth of collapsed blocks ........................................................................................ 102

6.2.5 Reconstruction of the buried terrain of lobe 4.......................................................... 104

6.2.6 Conclusions .............................................................................................................. 107

6.3 Modeling and analysis of failures ....................................................................................... 108

6.3.1 Evaluation method of slope stability ........................................................................ 108

6.3.2 Stability analysis without considered slip plane ...................................................... 109

6.3.3 Stability analysis considered slip plane .................................................................... 116

6.4 Potential pyroclastic flow simulation of Heisei Lava Dome ............................................... 128

6.4.1 Rheological model and input parameters ................................................................. 128


VII

6.4.2 Quantitative evaluating the influence of pyroclastic flow by the collapse of lava dome

.......................................................................................................................................... 129

6.5 Conclusions ......................................................................................................................... 133

References ................................................................................................................................. 135

CHAPTER 7 ..................................................................................................................................... 139

Summaries and conclusions .............................................................................................................. 139


VIII


1

CHAPTER 1

Introduction

1.1 Background and objectives

Failure of slope involving rock, mud, and its induced movement are dominant

geomorphic processes in humid foreland environments worldwide. The environmental

variables governing failure of slope, however, are not well known because most mass

movement studies have been confined to areas influenced by human activities. By

studying patterns of failure of slope in natural ecosystems, government officials, policy

makers, engineers, geologists and others will become better informed about likely success

of prevention or amelioration programs in risk-prone areas. Increased population and economic pressures have focused failure of slope research

on those areas where failure of slope has the potential to affect human lives and

infrastructure (Turner and Shuster, 1996). According to Cruden and Varnes (1996),

various factors control failure of slope. These include geological, morphological, physical

and human causes. Geological causes include: material properties such as: weakness,

sensitivity, degree of weathering, shear strength, jointing, bedding, schistosity, thrusts,

faults, unconformities, contrast in permeability, and contrast in stiffness (Varnes, 1978).

Morphological causes involve: tectonic or volcanic uplift, glacial rebound, fluvial, glacial

or wave erosion of slope toe, erosion of lateral margin and deposition and vegetation

removal. Similarly, physical causes involve: intense rainfall, rapid snow melt, prolonged

exceptional precipitation, rapid drawdown, earthquake, volcanic eruptions, thawing, and

shrink-and-swell weathering. Although the human causes are negligible in this study area

as there are no significant human activities, there are several human-induced failure of


2

slope triggered all over the world. Human causes may be excavation of slope, loading of

slope, drawdown or reservoirs, deforestation, irrigation, mining, artificial vibration, water

leakage from utilities, etc.

According to Keller (2000), failure of slope causes can be grouped as external causes

or internal causes. External causes include: loading of a slope by erosion or excavation,

and earthquake shocks. Internal causes produce failure of slope without any recognized

external changes and include such changes as increase in pore-water pressure or decrease

in cohesion of the slope materials. Some causes of failure of slope are intermediate,

having some attributes of both external and internal causes. For example, rapid

groundwater drawdown involves an increase in the shear stress accompanied by decrease

in shear strength caused by high pore water pressure.

The Andean Amazon foreland basin is prone to failure of slope activities. Indeed,

the South American Andean Mountains have been subjected to a number of major failure

of slope catastrophes. In 1962, Ancasa in Peru had a major failure of slope called

Huscarac debris avalanche with a net volume of 13 × 106 m3. It killed 4,000 - 5,000 people

and much of Ranrahirca village was destroyed (Guadango and Zampelli, 2000). Although

the triggering factor was unknown at the time, it is believed that the failure of slope was

triggered by heavy rain. Similarly, in 1966 in Rio de Janeiro, Brazil a major failure of

slope of avalanches debris and mud flows occurred. That was triggered by heavy rainfall

and killed approximately 1000 people. The Nevados Huascara rock/debris avalanche in

Peru, in 1970, was triggered by an earthquake of magnitude 7.7, killing 1,800 people and

destroyed the town of Yungay (Guadango and Zampelli, 2000). These examples show

that the tectonically active regions with high rainfall are prone to failure of slope activities.

Several past and present failure of slope of San Francisco were also triggered either by

heavy rain or by earthquakes resulting from tectonic activity (Griffiths, 2005).

Failure of slope range from simple rock/mud fall to complex slides and flows.

According to Dikau et al. (1996) landslides are classified as fall, topple, slide, spread and

flow. Fall and topple include detachment due to pre-existing discontinuities or tension

failure surfaces. These landslides may be free fall, break up, bounce, slide or flow down

slopes and may involve fluidization, liquefaction, cohesion less grain flow, heat

generation or other secondary effects. Slide movement includes rotational or non-


3

rotational and translational. In slides, the toe area may deform in a complex way. The

ground can bulge, the slide may creep or even flow. Flow, bulge or slide can override

existing failures. Failure might be retrogressive or progressive, and a graben often

develops at the head of the landslide or it may include a toe failure. Spreads are lateral

spreading of deformed ductile or soft material. Lateral spreading can develop sudden

spreading failures in quick clays when the slope opens up in blocks and fissures followed

by liquefaction. Sometimes, there might be a slow movement associated with

denudational unloading. Flows are defined as debris movement by flow from unconfined

and/or channeled failure surfaces. Flows involve a complex runout mechanism and these

may be catastrophic in effect and may move in sheets or lobes. The form of movement is

a function of the rheological properties of the material (Dikau et al., 1996).

The occurrence of different kinds of failure of slope depends on the causes behind

them and the triggering factors. Brunsden (1993) explains how different factors trigger

failure of slope. Physical, chemical and biological weathering cause changes in the

physical and chemical properties in soil and rock. Triggering factors create changes in

grading, cation exchange, and cementation. These changes cause formation of weak

discontinuities and increased depth of low strength materials. Eventually, there are

changes in density, strength, permeability and pore water pressure in the soil and rock.

Another type of weathering, which also changes the slope geometry, is associated with

fluvial, glacial or coastal erosion. The changes in slope relief, slope height, length, angle

and aspect results the changes in stress, strength and permeability along the slope and

eventually triggers failure of slope.

Erosion and weathering can also undermine soils and rocks resulting in mechanical

disintegration, solution, loss of cementing materials, leaching, and seepage. Undermining

creates loss of support, consolidation of materials, changes in pore water pressure and

loss of strength. Similarly, deposition of material by fluvial, glacial or mass movement

processes creates long-term loading in drained areas and short-term loading in undrained

areas, causing changes in relief, slope height, length, angle, and aspect of the terrain

(Brunsden, 1993). Deposition of material eventually creates changes in permeability,

strength and pore water pressure. Changes in water storage in groundwater can also

trigger failure of slope. This change may cause rising or falling groundwater, development


4

of perched water tables, surface saturation and flooding. The typical changes in this case

could be floods, lake bursts, intense precipitation, snow and ice melts and rapid drawdown.

These changes in water storage also eventually create excess pore water pressure, changes

in bulk densities and reduction in effective shear strength (Brunsden, 1993). Human

interference causes similar changes in terrain. The observation of air photos of the study

area from different years shows that the majority of failure of slope in my study area are

earth flows, and a few are rotational slides. This observation is also supported by literature

and historical failure of slope records. According to Chorley et al., (1984) humid tropical

rainforest areas undergo maximum chemical weathering, episodic mass wasting,

moderate slope wash and erosion/sedimentation related fluvial processes and these areas

have high dissolved and suspended loads in rivers. Morphologically, these areas contain

low gradient rivers, wide, flat floodplains, and steep slopes arising abruptly from valleys,

stabilized by vegetation and knife edge ridges. To identify the causes for failure of slope

occurrences, different casual factors and triggering factors must be studied. According to

Sower and Royster (1978), data for six parameters are necessary for any detailed failure

of slope investigation: topography, geology, hydrology (groundwater and surface water),

history of slope changes, weather, and vibration. Topographic data includes contour maps,

surface drainage, slope profiles and data on topographic changes. Geological data

includes lithology at the site, geological structure, and nature and depth of weathering.

Hydrologic data include piezometric levels, variations in piezometric level, groundwater

chemistry, nature and extent of surface water, seepage and data on water withdrawal. Data

on history of slope changes means any information on slope changes due to natural

processes (long term geological changes, erosion, and past movements), rate of

movement, correlation of movement with other factors such as surface and groundwater,

weather, and human activity. Weather data include precipitation, temperature and

barometric changes. Similarly vibration data are seismic data, and any human induced

vibration data such as blasting and heavy machinery. Site-specific failure of slope model

which incorporates geology, geomorphology, anthropology and the range of external

process is also useful (Sower and Royster, 1978). Collecting, storing, analyzing, and

manipulating the above-mentioned data are important tasks in any failure of slope study.

Development of GIS and spatial statistical techniques are recent technological


5

developments in earth sciences. These tools are constantly being used to improve

investigation techniques and mitigative measures for the failure of slope in populated

regions. There is improvement of quantitative methods to assess the probability of future

failure of slope occurrences (Clerici, 2002). Most GIS-based failure of slope studies are,

so far, most effectively used in failure of slope susceptibility studies and failure of slope

hazard/risk mapping. However, some research also focus on the future prediction of

failure of slope and failure of slope distribution in natural terrain. Brenning (2005) used

spatial statistics to develop a spatial prediction model for failure of slope hazards. Guthrie

and Evans (2004), after analyzing failure of slope frequencies and characteristics in

British Columbia, Canada, concluded that GIS failure of slope studies must focus on

failure of slope in natural ecosystems.

Dai (2001) used GIS techniques to study and map failure of slope susceptibility on

the natural terrain. Burton et al., (1998) used spatial statistics to generate a failure of slope

model, and later they field checked the model. Lan et. al., (2005) analyzed the dynamic

characteristics of failure of slope in response to rainfall and concluded that the water

pressure distribution and slope stability can be used as failure of slope predictor in GIS.

Some studies even compare the different methods. Suzen and Doyuran (2004) compare

the GIS based failure of slope susceptibility assessment methods by using multivariate

and bivariate approaches.

Slope movement is a common and important factor in erosion and sediment transfer

in mountainous areas, and constitutes an important risk to the population. Slope

movement happened between July 19th to 20th in 2003 in Kumamoto prefecture due to

heavy rainfall, which killed 19 people and damaged numerous properties. Slope

movements can originate either at a single source, typically from the fluidization of a

failed mass, or by the re-entrainment of sediment accumulated in a torrential catchment

(Beguería et al., 2009). When slope movements are confined on a torrent, they can

propagate over very large distances before final spreading over an alluvial fan. The threats

to human life and property from mud and slope movements is great, due to their higher

velocity and capacity to propagate even on very gentle slopes (Iverson and Denlinger,

1987; Takahashi, 1991; Iverson, 1997).

Previous studies have elucidated that rainfall or earthquake is the triggering factor


6

of slope movement. The slope movement is a gravity-driven flow with free upper surface

that move across three dimensional terrain, which is rapid, transient, and includes a steep

front mainly constituted of boulders (Laigle and Coussot, 1997). Slope movements have

very strong destructive power and bring about extensive property damage and loss of life

to the communities in their path (Takahashi, 1991; Hunt, 1994; Huang and Garcia, 1997;

Lien and Tsai, 2003). Up-to-date studies have strongly improved the ability to estimate

and predict the implications of slope movement. These studies can be primarily divided

into two groups: 1) physically based theoretical studies, and 2) field and laboratory studies.

Researchers have proposed different theoretical models to study the slope movement,

typical ones of which include Newtonian models, Bingham model, Herschel-Bulkley

model, generalized viscoplastic model, dilatant fluid models, biviscous modified

Bingham model, and frictional models (Wang et al., 2008). For in-situ monitoring work

and experiment study, Hungr et al. (1984, 2005) introduced a concept of yield rate which

denotes the volume eroded per meter of the path and discussed its range based on data

collection from 14 debris-flow events in the literature. Rickenmann et al. (2003) adopted

this concept, analyzing six sets of data from in-situ experiments and pointing out that

slope movements with a high sediment concentration tend to be less erosive than that with

more fluid mixtures. Wise (1997) collected forensic data of erosion depth from 449

debris-flow events. Iverson et al. (1987, 1992, 1997 and 2010) conducted a mass of large-

scale experiments of debris flow at U.S. Geological Survey (USGS) debris flow flume,

and found that the aggregated data were well-suited for testing both the conceptual

underpinnings and quantitative predictions of debris flow models.

In the past formation and motion of large-scale slope researches, some problems are

remained. First problem is how to do the research systematically. Failure of slope is a

complicated system, for the purpose of failure of slope mitigation, the simulation of

failure of slope should be conducted in the scale of region area. However, a problem is

that the stratum mechanics characteristics and surface topography in a large scale region

are some degree difficult to grasp. The second problem is that, failure of slope or slope

movement usually occurs in a short period of time and the destructive power can cause

great damage and loss of life. Few researches take the prediction of failure of slope and

slope movement into account.


7

Slope movement is concerned with rock, soil and water or only rock and soil. This

thesis cannot contain all types of slope movement (Figure 1.1). Due to the slope

movement induced by failure of slope, the movement is one of the types: (1) the type of

movement is flow, (2) the material is complex with rock, soil and water, (3) the

predominant material is coarse. In this research, we defined the initial of movement when

collapses happened as “failure of slope” (formation of a slope movement) and the

movement of rock and soil or the mixtures as “debris flow” (chapter 4) or “pyroclastic

flow” (which is to describe the slope movement of volcano in chapter 6). This thesis will

systematically analyze failure of slope and debris flow through database (data acquisition),

modeling to application. Thus, the objectives of this research are:

Figure 1.1 Types of slope movement depending on type of motion and type of

material (Varnes, 1978) as described by Roy and Hirotoka (2006)

Type of motion Type of material

Bedrock Engineering soil

Predominantly coarse

Predominantly fine

Falls Rock fall Debris fall Earth fall

Topples Rock topple Debris topple Earth topple

Slides Rotational

Rock slide Debris slide Earth slide Translational

Lateral spread Rock spread Debris spread Earth spread

Flows Rock flow

(deep creep) Debris flow (Soil creep)

Earth flow

Complex Combination of two or more principal types of movement

(1) to understand the mechanism and cause of failure of slope. Finite difference

method was applied in static mechanical analysis. The terrain data in a large-

scale slope is from airborne laser data. SSRM and earthquake loading in FLAC

(Fast Lagrangian Analysis of Continua) was adopted to analysis slope stability.

(2) to present a useful numerical method to simulate the propagation and deposition

of slope movement across the three dimensional complex terrain. To analysis the

velocity and range of influence of slope movement, and to integrate GIS with the


9

Chapter 1 introduces background of failure of slope and its induced slope movement,

and gives an introduction about the definition, causes, triggering factors and damage.

Objectives and organization of this thesis was also introduced.

Chapter 2 reviews the failure of slope research and slope movement research

including (1) insufficient failure of slope inventory mapping, (2) Selecting method in

failure of slope susceptibility and (3) slope movement simulating methods.

Chapter 3 introduces finite difference method and its application to the study of

stability analysis on large-scale slope. Airborne laser scanning is an effective method to

measure terrain data in a large-scale region. By using airborne laser scanning data, the

model can be built by finite-difference program FLAC3D. SSRM and earthquake loading

in FLAC is adopted to analysis slope stability.

Chapter 4 presents a depth-averaged numerical model to simulation the propagation

and the inundated area of debris flow, and numerical simulation methods in combination

with GIS-technology were applied. A GIS environment provides a good platform for

coupling a numerical model of a slope movement. As raster grid networks of digital

elevation model in GIS can be used as the finite difference mesh, the continuity and

momentum equations are solved numerically using finite difference method. All the input

and output data are processed in GIS. The accuracy of model is verified through the

comparison of simulation results with the experimental results obtained from the U.S.

Geological Survey slope movement flume between 1994 and 2004.

Chapter 5 is a case study of Aso-Ohashi landslide during 2016 Kumamoto

earthquake. Terrain data is measured by airborne laser scanning. Aso-Ohashi landslide is

reproduced by using numerical simulation. The SSRM is adopted and earthquake wave

was input to explore the mechanism of Aso-Ohashi landslide.

Chapter 6 analyzes the appearance, growth, and stability of Heisei Lava Dome in

Unzen volcano, Japan. A new division method of lava dome is presented. Lava dome is

divided into 10 PCBs by the surface distribution and the deep of PCB was calculated by

airborne laser data in different period. From stability analysis, if slide plane is not

considered and slide plane is considered, the model the critical status of model is

estimated. The potential collapses in maximum volume and the total volume of collapsed

region are verified. Slope movements caused by that were estimated based on a depth-


10

averaged numerical model and the average velocity are predicted.

Chapter 7 summarizes and concludes the results and achievements of the study.

Problems are also highlighted for future studies.


11

References

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simulating the kinematics of mud and debris flows over complex terrain.

Brenning, A., 2005. Spatial prediction models for landslide hazards: review, comparison

and evaluation, European Geosciences Union, Natural Hazards and Earth System

Sciences 5, 853–862.

Brunsden, D., 1993. The persistence of landforms. Zeitschrift für Geomorphologie, 13–

28.

Burton, A., Arkell, T.J., Bathurst, J.C., 1998. Field variability of landslide model

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Chorley, R.J., Schumm, S.A., and Sugden, D.E., 1984. Geomorphology. London,

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Dikau, R., Brunsden, D., Ibsen, M.L., and Schrott, L., 1996. Landslide Recognition:

Identification, Movement and Causes, John Wiley & Sons, Chichester, UK, 251.

Griffiths, J. S., 2005. “Landslides”, In: Geomorphology for engineers, edited by Fookes

P.G., M. Lee and G. Milligan, Whittles Publishing, Scotland, UK, Pp.173-206.

Guadagno, F.M., Zampelli, S. P., 2000. “Triggering Mechanisms of the landslides that

inundated Sarno, Quindici, siano and Bracigliano (S. Italy) on May 5-6, 1998,” In:

Landslides in Research, Theory and Practice, edited by E. Bromhead, N. Dixon, and

M.L. Ibsen, Thomas Telford Ltd., Cardiff, UK, 671-676.

Guthrie, R.H., Evans, S.G., 2004. Analysis of Landslide Frequencies and Characteristics

in a Natural System, Coastal British Columbia, Earth Surface Processes and


12

Landforms, 29, 1321-1339.

Huang, X. and Garc´ıa, M.H., 1997. A perturbation solution for Binghamplastic mudflows,

J. Hydraul. Eng., ASCE, 123(11), 986–994.

Hungr, O, Morgan, G.C., Kellerhals, R., 1984. Quantitative analysis of debris torrent

hazards for design of remedial measures. Canadian Geotechnical Journal, 21(4):

663-677.

Hungr, O., McDougall, S., Bovis. M., 2005. Entrainment of material by debris flows.

Debris-flow hazards and related phenomena. Springer Berlin Heidelberg, 135-158.

Hunt, B., 1994. Newtonian fluid Mechanics treatment of debris flows and avalanches, J.

Hydraul. Eng., ASCE, 120, 1350–1363.

Iverson, R.M., Costa, J.E., LaHusen, R.G., 1992. Debris-flow flume at HJ Andrews

experimental forest, Oregon. US Geological Survey, Dept. of the Interior.

Iverson, R.M., Denlinger, R.P., 1987. The physics of debris flows―a conceptual

assessment. IAHS-AISH publication, 165, 155-165.

Iverson, R.M., Logan, M., LaHusen, R.G., et al., 1997. The perfect debris flow?

Aggregated results from 28 large-scale experiments. Journal of Geophysical

Research: Earth Surface (2003–2012), 115(F3).

Iverson, R.M., 1997. The physics of debris flows. Reviews of geophysics, 35(3), 245-296.

Keller, A. E., 2000. Environmental Geology, Prentice-Hall, Inc., NJ, 132-160.

Laigle, D., Coussot, P., 1997. Numerical modeling of mudflows. Journal of Hydraulic

Engineering, 123(7): 617-623.

Lan, H.X., Lee, C.F., Zhou, C.H., Martin, C.D., 2005. Dynamic characteristics analysis

of shallow landslides in response to rainfall event using GIS, Environmental

Geology, 47, 254-267.

Lien, H.P., Tsai, F.W., 2003. Sediment concentration distribution of debris flow. Journal

of Hydraulic Engineering, 129(12): 995-1000.

Rickenmann, D., Weber, D., Stepanov, B., 2003. Erosion by debris flows in field and

laboratory experiments. Debris-flow hazards mitigation: mechanics, prediction, and

assessment, 883-894.

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Geophysical Union, AGU Books Board Publication, 312.


13

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In:, Transportation Research Board Special Report, edited by R. L. Schuster and R.J.

Krizek ,Vol.176, 81-111.

Suzen, M.L., Doyuran, V., 2004. A comparison of the GIS based landslide susceptibility

assessment methods: multivariate versus bivariate, Environmental Geolgoy, Vol. 45,

665-679. Takahashi T., 1991.Debris flow. Balkema. Turner, A.K., Schuster, R.L., 1996. “Landslides: Investigation and Mitigation,” In: United

States National Research Council, Transportation Research Board, Special Report,

Vol. 247, Washington DC. 247.

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Control, edited by M. Clark, Transportation Research Board, National Academy of

Science, National Res. Council, Special Rep., Vol. 176, Washington, DC, 11-33.

Wang, C, Li, S., Esaki, T., 2008. GIS-based two-dimensional numerical simulation of

rainfall-induced debris flow. Natural Hazards and Earth System Science, 8(1): 47-

58.

Wise, M.P., 1997. Probabilistic modelling of debris flow travel distance using empirical

volumetric relationships. University of British Columbia.


14


15

CHAPTER 2

Review of slope stability analysis research and slope movement

research

Several issues in quantitative slope risk analysis includes developing technique in

inventory mapping, particularly in a data scarce environment, selecting methods for slope

susceptibility assessment, and developing approaches for slope risk analysis. It varies

depending on the availability of secondary data, geomorphological characteristic, and

failure of slope typology. The availability of data input is very important prior to failure

of slope risk analysis. It can affect the overall methodology or approaches applied in the

failure of slope risk analysis. Despite the availability of failure of slope inventory,

geomorphological characteristic of the study area should also be considered prior to

selecting suitable failure of slope susceptibility and risk analysis. Some approaches in

failure of slope susceptibility and risk analysis can also not be applied in slope movement

susceptibility and risk analysis. For example, failure of slope susceptibility assessment

based on GIS and statistics uses failure of slope area represented by polygon to estimate

susceptibility. Whereas, it is not suitable for slope movement susceptibility analysis

because the dangerous zone in slope movement is represented by trajectory line.

2.1 Insufficient inventory mapping of slope failure

Generating slope failure analysis is difficult in some areas because the unavailable

of the failure of slope inventory map. However, the recent technology developments such

as the availability of the modern field instrument, high resolution DTMs, high resolution

satellite imagery, recent development on GIS and remote sensing technology have made

generating failure of slope map easier. But, the selection of this technique should be

carefully reviewed based on the purpose, the extent of the study area, the scale of base


16

maps and analysis, resolution and characteristics of the available imagery, and the skill

and experience of the interpreter (Guzetti et al., 2000; van Westen et al., 2006). Slope

failure mapping through field survey is the oldest technique for failure of slope inventory

mapping and considered as the most accurate technique for mapping fresh failure of slope

events. But it is difficult, by using field survey, to recognize old failure of slope in the

field where the natural process (e.g. erosion, vegetation) and the anthropogenic activities

(e.g. urbanization, road construction, ploughing) are exist.

2.2 Selecting method in slope failure susceptibility

Quantitative statistical analysis has been widely applied as a standard method for

failure of slope susceptibility zoning in large-scale areas (regional scale). It includes

bivariate statistic, multivariate statistic and soft computing. Bivariate analysis assumes

that the presumed controlling factors of failure of slope are not interrelated each other

(Suzen and Doyuran, 2004). It is a robust and flexible method, but has several limitations,

including over simplification of input thematic data related to failure of slope and loss of

data sensitivity of controlling factors (Thiery et al., 2007). Bivariate statistical methods

can also be used to determine which factors or combination of factors or combination of

factors play a role in the initiation of failure of slope.

In the other hand, multivariate analysis assumes that the presumed controlling

factors of failure of slope are interrelated each other. It determines the relative

contribution of each failure of slope causal factor in the presence or absence of past failure

of slope events (Dai et al., 2001; Suzen and Douran, 2004; Ayalew and Yamagishi, 2005;

Nandi and Shakoor, 2009). Multivariate statistical analysis can be used to predict a result

measured by a binary variable such as the absence or presence of failure of slope based

on a set of one or more failure of slope causal factors as independent variables. The

independent variables can be nonlinear, continuous, categorical or a combination of both

continuous and categorical; and does not to be normally distributed.

Soft computing techniques were used in assessment of the failure of slope

susceptibility because of a limitation such as insufficient knowledge about the area of

interest. Its computing procedure has the ability to handle imprecise and fuzzy data with

continuous, categorical and binary data without violating assumptions and also


17

independent of the statistical distribution of the data. The purpose of soft computing

technique, i.e. ANN, is to build a model of the data-generating process so that the network

can generalize and predict outputs from inputs that it has not previously seen (Lee et al.,

2001).

One of the main advantages of data driven failure of slope susceptibility is the easy

updating of the failure of slope susceptibility assessment procedure and also relatively

easy to apply for land-use planning. However, it can be affected by shortcomings such as

the assumption that failure of slope occur due to the same combination of factors

throughout a study area, spatial factors can vary widely in areas with complex

geomorphological settings, and the lack of suitable expert opinion on failure of slope

processes and causal factors (Corominas et al., 2013). Selecting method, i.e. either

bivariate, multivariate or soft computing is essential to apply for land use planning based

on complete failure of slope inventory.

2.3 Simulating methods of slope movement

Several attempts of slope movement susceptibility zoning have been carried out

through several ways, relatively similar to failure of slope susceptibility zoning, i.e.

heuristic, statistic and trajectory-energy/velocity approaches. Heuristic methods involve

geomorphological analysis and rating based approaches. Field work and photo

interpretation are the main sources of the geomorphological analysis for determining the

trajectories of slope movement. Geomorphologic elements connected to slope movement

are taken into account to delineate landscape that is susceptible to slope movement. It is

subjective and need well experienced geomorphologist. Weight of each element is also

added to determine the debris susceptibility based on rating approach (Romana, 1993;

Pierson et al., 1990; Hoek, 2007). The mapping unit used in geomorphological approach

is usually geomorphological unit or landform. For example, Sasaki et al. (2000) generated

land condition map showing geomorphologic element which is susceptible to slope

movement. Statistic approaches such as logistic regression using pixel/mesh unit was also

applied in slope movement susceptibility zone (Shizadi et al., 2012). But, it is not widely

applied, as in failure of slope susceptibility zoning, due to difficulties in delineating debris

affected area. Single slope movement may only affect a narrow area as a trajectory of


18

slope movement.

The most common method in slope movement susceptibility zoning is a trajectory-

energy/velocity modeling (Guzzetti et al., 2002; Lan et al., 2007; Chen, 2003; Agliardi

and Crosta, 2003). It is a quantitative approach employing computer simulation to

calculate probability of reach, velocity and the kinetic energy distribution at each point of

the slope. Broadly speaking, a slope movement represents the gravity-driven flow of a

mixture of various sizes of sediment (from clay to boulders), water and air, down a steep

slope, often initiated by heavy rainfall and/or landslides.

Here a brief review of the variety of the current work on the mechanics of granular

materials, and in particular that on slope movements is given. Since dry granular flows,

avalanches, and slope movements are in principle related phenomena, the following

survey is not exclusively restricted to the slope movement literature. Perhaps the most

up-to-date literature source available at the current time on the mechanics and modeling

of slope movements is Takahashi’s (1991) IAHR monograph, which gives a fairly critical

account on the mechanisms of slope movements from their onset to deposition. It

summarizes Takahashi’s own extensive research work, and presents a detailed

understanding of the mechanics of the flow of a layer of a particle-fluid mixture under

simple gravity driven shear for Bagnold’s (1954) grain inertia and macro viscous regimes.

The model equations of the two-constituent model are eventually simplified to essentially

a one-constituent model, and this view is maintained throughout. Time dependent

processes, i.e., development of a slope movement hydrograph and its deformation as well

as snout behavior are also discussed as are inverse grading and the transportation of large

boulders on the free surface of a slope movement and the processes of deposition of

sediments in the run-out zone. Considerations are all based on two-dimensional plane

flow. In a similar spirit is the work of Cheng-Lung Chen (1987). For simple plane shear

flows under gravity (in which a shear stress and a normal stress are the only materially

dependent stress variables that are introduced), Chen presents a detailed analysis of

theological models and deduces with these velocity profiles for steady gravity driven flow

of a strictly parallel sided slab. We shall discuss these equations later on. In the slope

movement literature, there appears to be no other work that goes beyond Takahashi (1991,

and previous work referred to there) and Chen (1987), except perhaps the in-depth, though


19

descriptive, account of Iverson & Denlinger (1987). These authors delineate the range of

applicability of the formulations and, in particular, point out the severe limitation "that

steady uniform flows can exist only when the debris travels down a slope with a specific

inclination. Chen (1987) discusses this phenomenon in detail, but does not seem to be

bothered by this. The reason stated by Iverson & Denlinger seems to be that the variation

of the grain concentration across the debris flow depth is ignored. The problem is that

four equations for three unknowns exist in this case; they mandate a consistency condition

which seems to be the reason for the mentioned peculiarity. Somewhat hidden in existing

formulations of the rheological behavior of slope movements is the fact that these

relations cannot uniquely be extended to a three-dimensional form of the constitutive

relations. In other words, two sets of general constitutive relations can in plane simple

shear be indistinguishable. When attempting to describe a dispersion of a channelized

slope movement into the fanned deposition area this might be of some importance.

Furthermore, slope movement specialists also generally abstain from introducing a

variable and associated field equation for the internal structure, say the fluctuations of the

velocity and particle concentration fields due to grain collisions and/or possible

turbulence in the interstitial fluid flow. In the granular flow literature this field is generally

of scalar nature: the collisional fluctuation energy or so-called granular temperature. From

this point of view, the granular literature should also be consulted, e.g., Scheiwiller &

Hutter (1982), or Hutter & Rajagopal (1994). Both works address the formulation of the

constitutive relations for granular materials under rapid shearing. Both contain extensive

literature reviews on constitutive modelling, but they do not present formulations of flow

models deduced from a set of constitutive relations. Hutter & Rajagopal (1994) also do

not address the models suggested by molecular dynamics, in which a large number

(several thousands) of rigid particles are followed in time under free motion and colliding

with each other. Interaction rules for collisions are formulated, the equations of motion of

all the particles integrated, and followed through time, taking into account the free flow

and collisions. Campbell (1990) reviews these methods, and Straub (1995) demonstrates

in a voluminous dissertation its use in pyroclastic flows. Its application to fluid-grain-

grain interaction has not been attempted so far. Consider next the problem of the

derivation of evolution equations. In particular, hydraulic or Boussinesqtype theories


20

have been obtained by, for instance, MacArthur & Schamber (1986), Coussot (1994),

Laigh & Coussot (1993), O’Brien et al. (1993), and Montefusio (1994), and exclusively

consist in establishing vertically, or cross sectionally, integrated, balance laws of mass

and momentum in a Cartesian reference frame, in one occasion restricted to the kinematic

wave approximation. In this approximation, one restricts considerations to a global mass

balance relation for the mixture as a whole,

0,, xt Qh (2.1)

in which h is flow depth, and Q the volume flux, thh t /, , xQQ x /, and writes a

constitutive equation for Q, usually by considering steady state momentum balance to

connect Q with basal and turbulent friction, etc., see, e.g., Hutter (1983). Only in a single

case were these balance laws complemented by a balance of mass for the solids, thus

allowing particle segregation mechanisms and deposition or erosion along the slope

movement path to be accounted for (Takahashi et al. 1992). In a single paper by Jenkins

& Askasi (1994), a hydraulic theory for a slope movement is presented in which the

particle fluctuation energy affects the evolution of the flow.

The drawbacks of these formulations have been pointed out before -- use of a

Cartesian formulation requires that the topography is flat, expressions for the basal drag

cannot clearly be related to constitutive postulates, and nonlinear advective terms in the

momentum equation cannot be properly estimated. Very similar concepts, however, have

been developed in the theory of snow and granular avalanches. A fairly up-to date

summary on this subject is contained in Hutter (1996). Through comparison of theory and

laboratory experiments it is shown that the curvature of the topography affects the

solution non-negligibly and thus should not be ignored. Hutter’s (1996) review also

contains an extensive treatment of powder snow avalanches, which are two-phase

mixtures with balance laws of mass and momentum for both constituents. The works

discussed there indicate, how (i) density variations and thus particle segregation including

deposition and erosion can be dealt with, (ii) how microstructural effects could be

incorporated (e.g., turbulence) and (iii) how hydraulic models can be constructed that

amend the above mentioned drawbacks. From another viewpoint, the existing literature

may be characterized according to whether a model for debris or granular flows is

formulated, or applied in the context of a physically-relevant initial-boundary value


21

problem. In the former category, one finds such works as Chen (1987), Takahashi (1991),

Hutter & Rajagopal (1994), and Hutter (1995); in these, the constitutive behaviour of a

granular material that may exhibit slope movement characteristics is discussed. Such

constitutive models can be formulated on a sound continuum thermos dynamical basis,

as shown by, e.g., Goodman & Cowin (1972), Passman et al. (1984), or more recently in

an extended context by Svendsen & Hutter (1995). In the latter category belongs the work

of, e.g., O’Brien et al. (1993), who present a depth-averaged hydraulic model for the fan-

flow regime of a slope movement. Focusing on the computer implementation of their

slope movement model, they do not, unfortunately, invest time in discussing or

appreciating its theoretical limitations. Such limitations are discussed, e.g., in the works

of Hutter and his associates (see, e.g., Hutter, 1996). Finally, it is also perhaps worth

mentioning that no model appears sufficiently general to deal with processes such as

erosion and/or deposition of sediment. Such processes are governed predominantly by

turbulence in the fluid and agitation of the solid particles at the base of the flow.

Consequently, these processes cannot be left out of any model hoping to address

erosion/deposition. Ideas on how these processes can be modeled are to be found in the

literature on turbidity currents and powder-snow avalanches, and are briefly reviewed in

Hutter (1996).

All the debris flows have at least four characters: rainfall or earthquake is the

triggering factor; a debris flow is a gravity driven flow with free upper surface that move

across three dimensional terrain; the nature of the flow itself, which is rapid, transient,

and includes a steep front mainly constituted of boulders (Laigle and Coussot, 1997); and

debris flows have very strong destructive power and bring about extensive property

damage and loss of life to the communities in their path (Takahashi, 1991; Hunt, 1994;

Huang and Garcia, 1997; Lien and Tsai, 2003). As debris-flows are mixtures of flowing

sediment and water showing complicated flow behavior intermediate between clear-water

flows and mass movements of solid material, a number of mathematical rheological

models were developed to simulate the flow behavior. Many researchers have developed

rheological models for mudflows and debris flows. These models can be classified as:

Newtonian models (Johnson, 1970; Trunk et al., 1986; Hunt, 1994; Hungr, 1995;

Rickenmann, 1999), Bingham model (Johnson, 1970; O’Brien and Julien, 1988; Liu and


22

Mei, 1989; Jan, 1997; Whipple, 1997; Fraccarollo and Papa, 2000; Pastor et al., 2004),

Herschel-Bulkley model (Huang and Garc´ıa, 1997, 1998; Imran et al., 2001; Remaˆıtre

et al., 2005; Rickenmann et al., 2006), generalized viscoplastic model (Chen, 1988),

dilatant fluid models (Bagnold, 1954; Takahashi, 1978, 1991; Mainali and Rajaratnam,

1994), dispersive or turbulent stress models (Arai and Takahashi, 1986; O’Brien and

Julien, 1988; Hunt, 1994), biviscous modified Bingham model (Dent and Lang, 1983),

and frictional models (Iverson, 1997; Chen and Lee, 1999; Arattano and Franzi, 2003;

Pastor et al., 2004; Rickenmann et al., 2006; Naef et al., 2006). Takahashi and Tsujimoto

(1984) presented a two dimensional finite difference model for debris flows based on a

dilatant-fluid model coupled with coulomb flow resistance, and modified the model to

include turbulence (Takahashi et al., 1991, 1992). O’Brien et al. (1993) developed a two-

dimensional flooding routing model that is a valuable tool for delineating flood hazards

and simulating flood wave attenuation, mudflows, debris flows (FLO-2D). Iverson and

Denlinger (2001) developed a generalization of the depth-averaged, two-dimensional

grain-fluid mixture model that describes finite masses of variably fluidized grain-fluid

mixtures that move unsteady across three-dimensional terrain. Egashira et al. (2003)

presented a method of numerical simulation for 2-D debris flow on an erodible bed using

the constitutive equations for sediment-water mixture when the equation of erosion rate

is incorporated in the continuity equation. McDougall and Hungr (2003) developed a

depth-averaged model for the simulation of rapid landslide motion across complex 3-D

terrain. Pudasaini and Hutter (2003) presented a two-dimensional depth-integrated theory

for the gravity-driven free-surface flow of a granular avalanche over an arbitrarily but

gently curved and twisted topography which is an important extension of the original

Savage and Hutter (1989) theory. Bouchut and Westdickenberg (2004) developed a

multidimensional shallow water model for arbitrary topography. Pastor et al. (2004)

presented a depth-integrated Bingham model which is discretized using a Taylor-Galerkin

finite element algorithm. Pudasaini and Hutter (2006) provided a survey and discussion

about the motion of avalanche-like flows from initiation to run out. Rickenmann et al.

(2006) compared three two-dimensional debris-flow simulation models with field events,

and these models are based on a Voellmy fluid rheology reflecting turbulent-like and basal

frictional stresses, a quadratic rheologic formulation including Bingham, collisional and


23

turbulent stresses, and a Herschel-Bulkley rheology representing a viscoplastic fluid.


24

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31

CHAPTER 3

Finite difference method and its application to the study of

stability analysis on large-scale slope

3.1 Introduction

Numerical models are mathematical models that use some sort of numerical time-

stepping procedure to obtain the models behavior over time. These are computer

programs that represent the mechanical response of a rock mass subjected to a set of initial

conditions such as in situ stresses and water levels, boundary conditions and induced

changes such as slope excavation. Slope collapse and landslide simulation are studied

with some numerical methods, FDM is a mesh-based method in stability analysis of

landslide. The FLAC3D is an FDM software and used in this study. For a large-scale slope,

how to judge the stability of slope is difficult. The high accuracy terrain data is hard to be

obtained. Airborne laser scanning is an effective method to measure terrain data in a large

scale region.

3.2 Terrain data from airborne laser scanning system

The airborne laser scanning system is ALS60 which is a compact laser-based system

that designed for acquisition of topographic and return signal intensity data from a variety

of airborne platforms. The data is computed using range and return signal intensity

measurements recorded in flight along with position and attitude data derived from

airborne Global Navigation Satellite System (GNSS) and inertial measurement unit

(IMU). Laser distance measuring device, IMU and GPS receiver antenna are installed in

aircraft. GPS antenna measures the position of the aircraft and IMU measures the attitude.


32

Laser is emitted ten thousand or hundred thousand short bursts of light every second,

which will measure range to and reflectance of objects on the earth surface. Schematic

diagram of this system is shown in Figure 3.1.

Airborne laser scanners for recording topographic data have been used in various

applications (Kraus and Pfeifer, 1998). In contrast to microwave radar techniques, lasers

are advantageous for wider range measurements because high energy pulses can be

realized in short intervals and their comparatively short wavelengths can be highly

collimated using small apertures (Wehr and Lohr 1999). Laser scanning is not capable of

any direct pointing to particular objects or object features. The resulting co-ordinates refer

to the footprints of the laser scan as they happen. Laser scanning is high accuracy, high

sampling densities, and a high degree of automation.

Figure 3.1 Airborne laser scanners. Laser distance measuring device, IMU and GPS

receiver antenna are installed in aircraft. GPS antenna measures the position of the

aircraft and IMU measures the attitude. It can offer high standard geo-information

acquisition and processing services for various applications.

φ ω κ Laser distance measuring

φ ω κ

GNSS

X Y Z

GPS antenna

Electronic reference point

GNSS

IMU


33

3.3 Description of finite difference method (FDM) and FLAC3D

Numerical modelling techniques have been widely used to solve complex slope

problems, which otherwise, could not have been possible using conventional techniques.

These models are used to simulate rock slope as well soil slope with complex conditions.

All rock slopes involve many discontinuities such as joint, fault, bedding plane, etc.

Precise representation of discontinuities in numerical models depends on the type of

model. Numerical methods of analysis used for rock slope stability investigations may be

divided into three approaches:

• Continuum modeling

• Discontinuum modeling

• Hybrid modeling

Continuum modeling is best suited for the analysis of slopes that are comprised of

massive, intact rock, weak rocks, and soil-like or heavily fractured rock masses.

Continuum codes assume that material is continuous throughout the body. Discontinuities

are treated as special cases by introducing interfaces between continuum bodies. Discrete

fractures such as faults and bedding planes can be incorporated in most continuum models.

However, these models cannot be used to simulate highly fracture rock mass. Finite

difference method (FDM) is based on this modeling theory. Finite difference methods are

numerical methods for solving differential equations by approximating them with

difference equations, in which finite differences approximate the derivatives. In this

method, the problem domain is discretized into a set of sub-domains or elements. The

solution procedure may be based on numerical approximations of the governing equations.

Two-dimensional continuum codes assume plane strain conditions, which are frequently

not valid in inhomogeneous rock slopes with varying structure, lithology and topography.

Complex behavior of slope can be modeled using continuum codes. Groundwater, pore

pressures and dynamic interaction can also be simulated. It requires input properties such

as constitutive model (e.g. elastic, elasto-plastic, creep etc.), groundwater characteristics,

shear strength of surfaces and in situ stress state. During modeling, effects of boundary,

mesh aspect ratios, symmetry, and hardware memory restrictions are important factors.

Some softwares based on continuum modeling like Phase2 (rocscience), FLAC2D,

FLAC3D (Itasca) and VISAGE (VIPS), PLAXIS are well suited for slope stability

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