naosite: nagasaki university's academic output...
TRANSCRIPT
-
This document is downloaded at: 2020-08-05T21:07:18Z
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.
-
II
-
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.
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
VIII
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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-
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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.
-
Xiao Shi Nagasaki University
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
-
Xiao Shi Nagasaki University
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-
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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.
-
Xiao Shi Nagasaki University
11
References
Beguería, S., Van Asch, T.W.J., Malet, J.P., et al., 2009. A GIS-based numerical model for
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
parameters, Environmental Geology Vol. 35, 100-114.
Chorley, R.J., Schumm, S.A., and Sugden, D.E., 1984. Geomorphology. London,
Muthuen & Co, UK, 605.
Clerici, A., 2002. A GRASS GIS based shell script for landslide susceptibility zonation
by the conditional analysis method. Proceedings of the open source GIS-GRASS
user’s conference 2002, Trento, Italy, 11-13.
Cruden, D.M., and. Varnes, D.J., 1996. “Landslide types and processes,” In: Landslides
Investigation and Mitigation, edited by A. K. Turner, and R. L. Schuster, Natl. Acad.
Press, Vol. 247, Washington, D. C., 36–75.
Dai, F.C., Lee, C.F., Li, J., Xu, Z.W., 2001. Assesment of landslide susceptibility on the
natural terrain of Lantau Island, Hong Kong, Environmental Geology, Vol. 40, issue
3, 381-391.
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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.
Roy, C.S., Hirotoka O., 2006. Landslides Processes, Prediction and Land Use. American
Geophysical Union, AGU Books Board Publication, 312.
-
Xiao Shi Nagasaki University
13
Sower, G. F., Royster, D. L., 1978. “ Field Investigation Landslides: Analysis and Control,”
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.
Varnes, D.J., 1978. “Slope movement types and processes”, In: Landslide Analysis and
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.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
14
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
23
turbulent stresses, and a Herschel-Bulkley rheology representing a viscoplastic fluid.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
24
References
Agliardi, F. and Crosta, G. 2003. High resolution three-dimensional numerical modelling
of rockfalls. Int. J. Rock Mech. Min., Sci., 40, 455-471.
Anderson, S. A. 1995. Analysis of Rainfall-induced debris flows, J. Hydraul. Eng., ASCE,
121(7), 544–552.
Arai, M. and Takahashi, T. 1986. The Karman constant of the flow laden with high
sediment, Proc. 3rd Int. Symp. on River Sedimentation, Univ. of Mississippi, 824–
833.
Arattano, M. and Franzi, L. 2003. On the evaluation of debris flows dynamics by means
of mathematical models, Nat. Hazards Earth Syst. Sci., 3, 539–544.
Ayalew, L. and Yamagishi, H. 2005. The application of GIS-based logistic regression for
landslide susceptibility zoning in the Kakuda-Yahiko Mountains, Central Japan.
Geomorphology, 65, 15-31.
Bagnold, R.A. 1954. Experiments on a gravity free dispersion of large solid spheres in a
Newtonian fluid under shear. Proc. R. Soc. London, A 225:49-63.
Bouchut, F. and Westdickenberg, M. 2004. Gravity driven shallow water models for
arbitrary topography, Comm. Math. Sci., 2(3), 359–389.
Campbell, C.S. 1990. Rapid granular fows. Ann. Rev. Fluid Mech. 22:57-92.
Chen, C. 1988. Generalized viscoplastic modeling of debris flow, J. Hydraul. Eng., ASCE,
114(3), 237–258.
Chen, C.L. 1987. Comprehensive review of debris flow modeling concepts in Japan, Geol.
Soc. Am. Rev. Eng Geol. Vol. VII, pp. 13-29.
Chen, G. 2003. Numerical modeling of rock fall using extended DDA. Chinese Journal
of Rock Mechanics and Engineering, 22(6), 926-931.
Chen, H. and Lee, C.F. 1999. Numerical simulation of debris flows, Can. Geotech. J., 37,
146–160.
Corominas, j., van Westen, C., Frattini, et al. 2014. Recommendations for the quantitative
analysis of landslide risk. Bulletin Engineering Geology and the Environment, 73(2),
209-263.
Coussot, P., 1994. Steady, laminar, flow of concentrated mud suspensions in open channel.
J. Hydr. Res. 32, vol. 4:535-559.
-
Xiao Shi Nagasaki University
25
Dai, F.C., Lee, C.F., Li, J. and Xu, Z.W. 2001. Assessment of landslide susceptibility on
the natural terrain of Lantau Island, Hong Kong. Environmental Geology. 40,381-
391.
Dent, J. D. and Lang, T. E. 1983. A biviscous modified bingham model of snow avalanche
motion, Annals Glaciology, 4, 42–46.
Egashira, S., Itoh, T., and Miyamoto, K. 2003. Debris flow simulations for San Julian
torrents in Venezuela, Proc. 3rd IAHR Symposium on River, Coastal and Estuarine
Morphodynamics. Barcelona, Spain, 1–5 September 2003, 976–986.
Fraccarollo, L. And Papa, M. 2000. Numerical simulation of real debris flow events, Phys.
Chem. Earth (B), 25(9), 757–763.
Goodman, M.A., Cowin, S.C. 1972. A continuum theory for granular materials. Arch. Rat.
Mech. Anal. 44:249-266.
Guzzetti, F., Cardinali, M., Reichenbach, P. and Carrara, A. 2000. Comparing landslide
maps: a case study in the upper Tiber River Basin, Central Italy. Environmental
Management, 25(3), 247-363.
Guzzetti, F., Malamud, B., Turcotte, D.L., Reichenbach, P. 2002. Power-law correlations
of landslide areas in central Italy. Earth and Planetary Science Letters, 195,169-183.
Hoek, E. 2007. Practical Rock Engineering. Available online at
http://www.rocscience.com/hoek/pdf/Practical_Rock_Engineering.pdf
Huang, X. and Garcıa, M.H. 1997. A perturbation solution for Bingham plastic mudflows,
J. Hydraul. Eng., ASCE, 123(11), 986–994.
Huang, X. and Garc´ıa, M. H. 1998. A Herschel-Bulkley model for mud flow down a
slope, J. Fluid Mech., 374, 305–333.
Hungr, O. 1995. A model for the runout analysis of rapid flow slides, debris flows and
avalanches, Can. Geotech. J., 32(4), 610–623.
Hunt, B. 1994. Newtonian fluid Mechanics treatment of debris flows and avalanches, J.
Hydraul. Eng., ASCE, 120, 1350–1363.
Hutter, K. 1983. Theoretical Glaciology. Reidel, Dordrecht.
Hutter, K. 1996. Avalanche dynamics, a review. In: Hydrology of Disasters (VP Singh,
ed.) Kluwer Academic Publishers, Amsterdam.
Hutter, K., Rajagopal, K.R. 1994. On flows of granular materials. Cont. Mech.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
26
Thermodyn. 6, 81-139.
Imran, J., Harff, P., and Parker G. 2001. A number model of submarine debris-flow with
a graphical user interface, Computer Geosciences, 27, 717–729. Iverson, R. M. 1997. The physics of debris flows, Rev. Geophys., 35,245–296. Iverson, R.M. and Denlinger, R.P. 1987. The physics of debris flows - A conceptual
assessment. In: Erosion and Sedimentation in the Pacific Rim (Proceedings of the
Corvallis Symposium), IAHS Publ. No. 165:155-165.
Iverson, R. M., and Denlinger R. P. 2001. Flow of variably fluidized granular masses
across three-dimensional terrain, 1. Coulomb mixture theory, J. Geophys. Res., 106,
537–552.
Jan, C. D. 1997. A study on the numerical modelling of debris flow, Debris Flow Hazards
Mitigation, Mech., Pred. and Assessment, ASCE.
Jenkins, J.T. 1994. Hydraulic theory for a debris flow supported on a collisional shear
layer. Proc. Int. Workshop on 'Floods and Innnndations Related to Large Earth
Movements, Trento, Italy, IAHR, A6.1-A.610.
Johnson, A. M. 1970. Physical processes in geology, Freeman, San Francisco.
Laigle, D. and Coussot, P. 1993. Numerical modeling of debris flow dynamics. Proc. Int.
Workshop on 'Floods and Innundations Related to Large Earth Movements', Trento,
Italy, IAHR, A11.1-A.11.11.
Laigle, D. and Coussot, P. 1997. Numerical modeling of Mudflows, J. Hydraul. Eng.,
ASCE, 123, 617–623.
Lan, H., Martin, C.D. and Lim, C.H. 2007. Rockfall analyst: a GIS extension for three-
dimensional and spatially distributed rockfall hazard modeling. Computer and
Geoscience. 33,262-279.
Lee, S., Ryu, J., Min, K. and Won, J. 2001. Development of two artificial neural network
methods for landslide susceptibility analysis. Proceeding of Geoscience and Remote
Sensing Symposium, IGARSS 01. IEEE 2001 International 5, 2364-2366.
Lien, H. P. and Tsai, F. W. 2003. Sediment concentration distribution of debris flow, J.
Hydraul. Eng., ASCE, 129(12), 995–1000.
Liu, K. F. and Mei, C. C. 1989. Slow spreading of a sheet of Bingham fluid on an inclined
plane, J. Fluid Mech., 207, 505–529.
MacArthur, R.C., Schamber, D.R. 1986. Numerical methods for simulating mudflows.
-
Xiao Shi Nagasaki University
27
Proc. Third Int. Symp. on River Sedimentation, Mississippi, USA, 1615-1623.
Mainali, A. and Rajaratnam, N. 1994. Experimental study of debris flows, J. Hydraul.
Eng., ASCE, 120(1), 104–123.
McDougall, S. and Hungr, O. 2003. Dynamic modelling of entrainment in rapid
landslides, Can. Geotech. J., 42(5), 1437–1448.
Montefusco, L. 1994. A possible 2-D vertical model for debris flow. Proc. Int. Workshop
on 'Floods and lnnundations Related to Large Earth Movements'. Trento, Italy, IAHR,
A9.1-A.9.9.
Naef, D., Rickenmann, D., Rutschmann, P., and McArdell, B. W. 2006. Comparision of
flow resistance relations for debris flows using a one-dimensional finite element
simulation model, Nat. Hazards Earth Syst. Sci., 6, 155–165.
Nandi, A. and Shakoor, A. 2009. A GIS-based landslide susceptibility evaluation using
bivariate and multivariate statistical analyses. Engineering Geology, 110, 11-20.
O’Brien, J. S. and Julien, P. Y. 1988. Laboratory analysis of mudflow properties, J. Hydr.
Engrg., ASCE, 114(8), 877–887.
O'Brien, J.S., Julien, P.Y., Fullerton, W.T. 1993. Two-dimensional water flood and
mudflows simulation. J. Hydr. Eng., ASCE, Vol. 119, No. 2:244-261.
Passman, S.L., Nunziato, J.W., Walsh, E.K. 1984. A theory of multiphase mixtures. In:
Rational Thermodynamics, C. Truesdell (ed.) Springer-Verlag 1984.
Pastor, M., Quecedo, M., Gonz´alez, E., Herreros, M. I., Fern´andez Merodo, J. A., and
Mira, P. 2004. Simple approximation to bottom friction for bingham fluid depth
integrated models, J. Hydraul. Eng., ASCE, 130(2), 149–155.
Pierson, L.A., Davis, S.A. and Van Vickle, R. 1990. Rockfall Hazard Rating System
Implementation Manual, Federal Highway Administration (FHWA) Report FHWA-
OREG-90-01, FHWA, United States Department of Transportation.
Pudasaini, S. P. and Hutter, K. 2003. Rapid shear flows of dry granular masses down
curved and twisted channels, J. Fluid Mech., 495, 193–208.
Pudasaini, S. P. and Hutter, K. 2006. Avalanche Dynamics:Dynamics of rapid flows of
denses granular avalanches, New York, Springer.
Remaıtre, A., Malet, J., Maquaire, O. Ancey, C., and Locat, J. 2005. Flow behaviour and
runout modelling of Complex debris flow in a clay-shale basin, Earth Surf. Process.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
28
Landforms, 30, 479–488.
Rickenmann, D. 1999. Empirical relationships for debris flows, Nat. Hazards, 19(1), 47–
77.
Rickenmann, D., Laigle, D., McArdell, B. W., and H¨ubl, J. 2006. Comparison of 2D
debris-flow simulation models with field events, Computational Geosciences, 10,
241–264.
Romana, M. 1993. A geomechanical classification for slopes: slope mass rating,
Comprehensive Rock Engineering, Oxford, Pergamon.
Savage, S. B. and Hutter, K. 1989. The motion of a finite mass of granular material down
a rough incline, J. Fluid Mech., 199, 177–215.
Scheiwiller, T., Hutter, K. 1982. Lawinendynamik: Obersicht tiber Experimente und
theoretische Modelle yon Flieβ- und Staublawinen. Laboratory of Hydraulics,
Hydrology and Glaciology, Report No. 58, ETH Ztirich, Switzerland.
Shizadi, A., Saro, L., Joo, O.H. and Chapi, K. 2012. A GIS-based logistic regression
model in rockfall susceptibility mapping along a mountainous road: ASalavat Abad
case study, Kurdistan, Iran, Nat. Hazards, 64, 1639-1656.
Stranb, S. 1995. Schneltes granulares Fliegen in subaerischen pyroklastischen Str6men.
Dissertation an der Bayerischen Julius- Maximilians-Universit~it Wiirzburg.
Suzen, M.L. and Doyuran, V. 2004. Data Driven Bivariate Landslide Susceptibility
Assessment Using GIS: a Method and Application to Asarsuyu Catchment, Turkey.
Engineering Geology, 71, 303-321.
Takahashi, T. 1978. Mechanical characteristics of debris flow, J. Hydr. Div., ASCE,
104(8), 1153–1169.
Takahashi, T. 1991. Debris flow. 1AHR-AIRH Monograph series. A. A. Balkema.
Takahashi, T., Nakagawa, H., Harada, T., Yamashiki, Y. 1992. Routing debris flows with
particle segregation. J. Hydr. Eng., ASCE, Vol. 118, No. 11:1490-1507.
Takahashi, T. and Tsujimoto, H. 1984. Numerical simulation of flooding and deposition
of a debris flow, Disas. Prev. Res. Inst., Kyoto Univ., 27(B-2), 467–485.
Thierry, Y., Malet, J.P.Sterlacchini, S. Puisant, A., and Maquaire, O. 2007. Landslide
susceptibility assessment by bivariate methods at large scale: application to a
complex mountainous environment. Geomorphology, 92, 38-59.
-
Xiao Shi Nagasaki University
29
Trunk, F. J., Dent, J. D., and Lang, T. E. 1986. Computer modeling of large rock slides, J.
Geotech. Engrg., ASCE, 112(3), 348–360.
Van Westen C.J., Asch T.W.J. and Soeters R. 2006. Landslide hazard and risk zonation-
why is it still so difficult? Bull. Eng. Geol. Env., 65, 67-184.
Whipple, K. X. 1997. Open-channel flow of Bingham fluids: applications in debris-flow
research, J. Geol., 105, 243–262.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
30
-
Xiao Shi Nagasaki University
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.
-
Failure Mechanism and Its Induced Movement Simulation of Large-scale Slope
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
-
Xiao Shi Nagasaki University
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