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Example of Cairns, Australia
Regional risk analysis
Quantitative approach
Landslide risk as basis for planning and emergency
management purposes
Input data:
Historical landslide information
Geological information
Geomorphological information
Run out of landslide (empirical model)
Information on buildings, roads and demography
Michael-Leiba, Baynes, Scott, 1999
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Example of Cairns, Australia
Michael-Leiba, Baynes, Scott, 1999
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Example of Cairns,
Australia
Michael-Leiba, Baynes, Scott,
1999
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Example of Cairns, Australia
Risk assessment
from magnitude
recurrence graph
Michael-Leiba, Baynes, Scott, 1999
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Example of
Cairns, Australia
Landslide data map
Michael-Leiba, Baynes, Scott, 1999
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Example of
Cairns, Australia
Landslide risk map
Number of houses and
blocks of flats expected to
be destroyed per square km
per 100 years
Michael-Leiba, Baynes, Scott, 1999
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Example of Cairns, Australia
Major findings of the study
Greatest total risk for buildings on hill slopes
Total of 13 buildings could be destroyed in 100 years,
if no mitigation measure is taken
Highest total risk for people is in proximal parts of
debris flows
Total of 16 people could be killed in 100 years
Main access to Cairns, north and south, pass to steep
slopes and can be blocked by landslides
=> Makes Cairns vulnerable to isolation
Michael-Leiba, Baynes, Scott, 1999
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Example of Cairns, Australia Drawbacks:
Paucity of data from which landslide magnitude-
recurrence were derived
Regional study
Site-specific assessments should be checked by
geotechnical experts
Lack of discrimination between the effects of shorter,higher intensity rainfall events, of antecedent rainfall and
of longer, lower intensity rainfall events
Assumptions:
shadow angles are uniform for all debris flows in the
study area
Vulnerability is independent of landslide magnitude
Landslide intensity is uniform across a landslide
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Summary: Qualitative & quantitative assessments
Qualitative assessment (Rheinhessen) Regional assessment
Coarse data sets (information from flood research)
First approximation of landslide risk
Quantitative assessments (Iceland / Cairns)
Regional assessments
Detailed spatial information
Differentiate: Specific Risk / Total Risk (MultiRISK)
Be aware that independent on your method ......... these analysis are PURELY approximations
... there are high uncertainties
... local assessments are always needed for critical locations
... analysis can only support - and not enforce - decisions
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Determination of runout zones of landslides
- From field surveys to modelling -
PD Dr. Thomas [email protected]
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Risk assessment & management (1/3)
P robability oflandsliding
Triggeringfactors
Landslideinventory
P reparatoryfactors
Hazardassessment
Runoutbehavior
Land use
E lements atrisk
Vulnerabilityassessment
Riskassessment
Riskmanagement
C ost-benefitanalysis Dai et al. (2002)
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Lecture Overview Repetition:
Landslide activity & rate of movement
Temporal & spatial occurrence of landslides
Soil mechanical basics
Preparatory, triggering and controlling factors
General considerations to spatial modeling
Calculation of runout zones
Parameters defining & contributing to runout behavior
Methods for predicting runout distance
Empirical models
Analytical models
Numerical models
Coupling local and regional assessments
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Active
Suspended
Reactivated
Inactive
Dormant
Abandoned
Stabilized
Relict
Ac ti ve Suspended
Reactivated Inactive
Landslide activity State of activity
Adopted from Cruden & Varnes, 1996
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Active
Suspended
Reactivated
Inactive
Dormant
Abandoned
Stabilized
RelictRelict
Dormant Abandoned
Stabilized
Landslide activity State of activity
Adopted from Cruden & Varnes, 1996
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Advancing Retrogressive
Enlarging Diminishing
Confined Moving Widening
Landslide activity - Distribution of activity
Adopted from Cruden & Varnes, 1996
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Complex
Composite
Successive
Single
Multiple
Landslide activity Styles of activity
Cruden & Varnes, 1996
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Rate of movement
Cruden & Varnes, 1996
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Rate of movement
http://walrus.wr.usgs.gov/elnino/landslides-
sfbay/photos.html
USGS
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Temporal and spatial occurrence of natural hazards
Earthquake
Tsuna
mi
Snow
avalancheLandslide
Volcanism
Storm
tide
Storm
Flooding
Drought
Desertification
Space
Space
LocalLocal
PunctualPunctual
Second
Second
Day
Day
Year
Year
Decade
Decade
TimeTime
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Space
Time
Topple/Rockfall
Slide/ Sackung
Debrisflow
short
small
large
long
Ahrtal, Germany (PhotoT. Glade)
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Canada(Photo: M. Crozier)
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Mattertal, Switzerland (Photo: H. Grtner)
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Hawke Bay, New Zealand (Photo: N. Trustrum)
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Isle of Wight, UK (Photo: T. Glade)
Otago, New Zealand(Photo: M. Crozier)
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Temporal and spatial occurrence
of landslides
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fall, slide
flow, slide,
slump, creep
creep
deposition,
creep
Summerf
ield1991
Spatial occurrence of landslides - local
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Gisborne 2002 ( Michael Crozier))
Earth flow / Debris flow
HawkeBay 1998 ( Noel Trustrum)
Wairarapa1972 ( Noel Trustrum)
HawkeBay 1988 ( Noel Trustrum)
Spatial occurrence of landslides - regional
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Soil mechanical basics of landslides
The shear strength of soils is mainly determined by
Cohesion (c)
Internal friction angle ()
and is expressed in the Coulomb equation
f= c + n . tan
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Selby 1993
Cohesion (c)
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Cohesion (c)
Selby 1993
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Press & Siever, 1997
Cohesion (c) and internal friction angle ()
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Internal friction angle ()
Block of rock lies upon a horizontal surface Weight of the block (N) generates an equal and opposite
reaction (R) -> compressive stress, block is immobile
Addition of horizontal stress
Reaction (R) adjusts from normal to the horizontal plane to
the resultant N and H. The relationship between N, H, R and
the angle is shown by the triangle of forces.
Horizontal stress at failure conditions
Increase in H causes increases in R and. When slidingbegins the frictional contact will be broken and will haveattained its maximum possible value. That maximum value is
the internal friction angle ().
tan = N/H = / = shear stress, = normal stress
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shear stress
normal stress
shear plane
Stress acting at a slope
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f= c + n . tan
f = shear stress at failurec = cohesion
n = normal stress = angle of internal friction
f= c + (n - u) . tan
for saturated soils
taking into account the effect ofpore water pressure (u)
negative pore water pressure -> stabilizing effect
positive pore water pressure -> destabilizing effect
Coulomb equation
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Selby 1993
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Methods of slope stability analysis
Field investigations
Define Purpose: Regional - / Spatial assessment
Slope stability modelling
translational slides (infinite slope model)
Rotational slides
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Crozier1986
Factors indicating slope stability (1/2)
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Factors indicating slope stability (2/2)
Crozier 1986
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cossin
tan)(cos 2
+==
z
mzcsFS w
FS = Factor of Safety (
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sin
]tan)cos([
+==
A
B
A
B
W
uLWcLs
FS
The slide is divided into a number of slices of length L and the forces acting on each
of these slices are aggregated.
FS = Factor of Safety (
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Preparatory factors - Disposition
Weathering
Change in slope geometry
Change in soil hydrology
Melting permafrost
Change in vegetation
Land use change
...
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Triggering factors
Heavy or long lasting rainfall
Snow melting
Earthquake, volcanic eruption
Undercutting of slope
...
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Controlling factors
Slope
Curvature (convex, concave,...)
Vegetation
Channel roughness
...
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Spatial modeling - Advantages
Abstraction to key-issues
Subjectivity by model development and choice
Objectivity: Repetition of similar analysis gives
identical results
Unambiguous rules - Concepts and structures
Uniformity based on objective criteria
Transparency is inherent
Transferability is possible
Potential for scenarios
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Spatial modeling - Disadvantages
Reduction to single parameter indispensable
Commonly statistical relation (if - when)
Danger: Essential, important process-determining
parameter will not be considered
Quality has to be ensured
Assumptions have to be reflected for interpretations
Transferability has to be critically questioned
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Scientific challenges in spatial modeling
Development of process-specific methods
Scale dependent choice of methods is important
Spatial models have to be improved, or further
developed
Validation of results is essential for the judgement of
the quality
Scenarios of events
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Modeling of runout zones
Delimiting extent of endangered areas is fundamental
to landslide risk assessment
=> Prediction of runout behavior of landslides
How far and how fast?
Calculation/Modeling is often simply ignored
Modeling is complex and data demanding
Runout behavior is a set of quantitative and
qualitative spatially distributedparameters thatdefine destructive potential of a landslideDai et al., 2002
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Parameters defining runout behavior
Runout distance
Damage corridor width
Velocity
Depth of the moving mass
Depth of deposits
Wong et al, 1997 &
Hungr et al., 1999 in Dai et al., 2002
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Factors contributing to runout behavior
Factors that control travel:
Slope characteristics
Mechanisms of failure & modes of debris movement
Downhill path
Residual strength behavior sheared zones
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Slope characteristics
Slope geometry
Redistribution of potential energy at failure into:
Friction energy
Disaggregating energy
Kinetic energy
Slope-forming material
Convergence of hydrologic pathways
Upslope influence zone
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Mechanisms of failure & modes of debris movement
Velocity and travel distance is influenced by:
Modes of debris movement
Disintegration of the failure debris
Convergence of surface runoff
Contractive soils often evolve into debris flows that
may travel great distances
Dilatant soils tend to be slow-moving landslides
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Downhill path
Gradient of downslope path
Possibility of channelization
Characteristics of ground surface
Susceptibility to depletion
Response to rapid loading
Type of vegetation
Extent of catchment
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Residual strength behavior of sheared zones
Presence or absence of pre-existing shears
Degree of brittleness
Three types of residual strength
Neutral rate effect
Constant residual strength
Positive rate effect
Soils showing an increase in residual strength
above the slowly drained residual value at
increasing rates of displacement
Negative rate effect
Soils showing a significant drop in strength when
sheared at rates higher than a critical value
Increasingrateofdisplacement
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Rate effect and landslide velocity/runout distance
After initial failure => landslide ceases equilibrium =>
movement to new position
Positive rate effect:
Strength increases with velocity => Landslide deceleration
Negative strength effect:
Landslide acceleration => development of fast movement
=> possibility of long runout distance
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Methods for predicting runout distance
Empirical models
practical tools for predicting runout and distribution
Analytical models
Physical behavior of movement
Numerical simulations
Dynamic motion of debris and/or
Rheological model to describe material behavior
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Empirical models
1. Mass change model
Volume of mobilized material/length of trail
2. Angle of reach
Angle of the line connecting the crest of the landslide
source to the distal margin of the displaced mass
Corominas (1996): linear correlation between
volume and angle of reach for all types of failures
Decrease of angle of reach with increase in volume
Scatter of data is large => preliminary predictions of
travel distance => incorporation of judgement
But: required information can be generated easily
with historic landslide database
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Empirical models: Corominas 1996
Types of topographic constraints considered
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Empirical models: Corominas 1996
Landslide volume vs. tangent of
the reach angle for 204 landslide
events
Regression equations for
considered individual groups
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Analytical models
Based on lump mass approaches in which the debris
mass is assumed as a single point
Cannot account for lateral confinement and spreading
=> suitable only for comparing similar paths
(geometry, material)
Required parameters:
Pore pressure parameters
Debris thickness
Relation of residual strength with shear rate
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Numerical Models
1. Fluid mechanics models
Conservation equations of mass, momentum and
energy => dynamic motion
Rheological model => material behavior
Rheological properties are difficult to determine
2. Distinct element method
Model of large strain particle movement
Important for understanding failure mechanics of
landslides through back analysis
Sophisticated & Time-consuming
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References
Bundesamt fr Umwelt, Wald und Landschaft 1999:Risikoanalyse beigravitativen Naturgefahren - Fallbeispiele und Daten. In: Umwelt-Materialien
Nr. 107/II Naturgefahren. Bern, 129 pp.
Corominas, J. 1996: The angle of reach as a mobility index for small and large
landslides. Canadian Geotechnical Journal. Vol. 33, pp 260-271.
Crozier, M.J. 1986:Landslides: causes, consequences and environment. London.
Cruden, D.M. and Varnes, D.J. 1996: Landslide types and processes. In Turner,
A.K. and Schuster, R.L., editors,Landslides: investigation and mitigation,
Washington, D.C.: National Academey Press, 36-75.
Dai, F.C., Lee, C.F. and Ngai, Y.Y. 2002:Landslide risk assessment and
management: an overview. Engineering Geology 64, 65-87.
Press, F. & Siever, R. 1997: Understanding Earth. New York.
Summerfield, M.A. 1991: Global geomorphologyan introduction to the study
of landforms.New York. pp 537.
Turner, A.K. and Schuster, R.L. (editors) 1996:Landslides: investigation and
mitigation, Washington. pp. 673.
Landslide movie: http://walrus.wr.usgs.gov/elnino/landslides-sfbay/photos.html