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Italian Journal of Engineering Geology and Environment - Book Series (6) www.ijege.uniroma1.it © 2013 Sapienza Università
Editrice
245
DOI: 10.4408/IJEGE.2013-06.B-22
HAZARD AND RISK CLASSIFICATION FOR
LARGE UNSTABLE ROCK SLOPES IN NORWAY
R
eginald
L. HERMANNS
(*)
, T
hieRRy
OPPIKOFER
(*)
, e
inaR
ANDA
(**)
, l
aRs
H. BLIKRA
(*)
,
M
aRTina
BÖHME
(*)
, h
alvoR
BUNKHOLT
(*)
, g
iovanni
B. CROSTA
(***)
, h
algeiR
DAHLE
(****)
,
g
Raziella
DEVOLI
(****)
, l
uzia
FISCHER
(*)
, M
ichel
JABOYEDOFF
(*******)
,
s
iMon
LOEW
(*******)
, s
Tine
SÆTRE
(********)
& F
Reddy
X
avieR
YUGSI MOLINA
(*)
(*)
Geological Survey of Norway (NGU) - Trondheim, Norway
(**)
Åknes Tafjord Beredskap
(***)
University of Milano-Bicocca - Milan, Italy
(****)
Norwegian Road Authorities
(*****)
Norwegian Water and Energy Directorate
(******)
University of Lausanne - Lausanne, Switzerland
(*******)
ETH Zurich - Zurich, Switzerland
(********)
The county of Møre og Romsdal
INTRODUCTION
Catastrophic failure of large rock slopes in Nor-
way has several times per century led to rock ava-
lanches or large rock falls, which directly affected
settlements, but also caused either a displacement
wave when impacting a water body with often fatal
consequences or damming of narrow valleys with a
high loss of property (B
likRa
et alii, 2006a; F
uRseTh
,
2006). Such events will also occur in the future. For
catastrophic failure we follow here the definition
given by h
eRManns
& l
ongva
(2012) as rock slope
failures that could involve substantial run-out and
fragmentation of the rock mass and could impact with
high velocity an area larger than that of a rockfall with
typical shadow angles of ca. 28-34° (e.g, e
vans
&
h
ungR
, 1993). This limitation is permissible as there
are other mapping products in Norway that character-
ize the source and invasion areas and its likelihood for
small scale rock slope failures (rockfall susceptibility
map, detailed hazard maps) (e.g h
øsT
et alii, 2013).
The Geological Survey of Norway (NGU), fol-
lowing its obligation towards society and the Norwe-
gian Water and Energy Directorate (NVE) carries out
systematic geologic mapping of potentially unstable
rock slopes that might fail catastrophically (h
eRManns
et alii, 2013a). Within the last years mapping in only
three of the 17 relevant counties of Norway has revealed
more than 300 sites of potential future rock slope fail-
ures. This number necessitates a systematic mapping
approach that focuses on the relevant geological data
ABSTRACT
We present a classification system for hazard and
risk that is posed by unstable rock slopes in Norway
that might undergo catastrophic failure in future and
can cause loss of life. The system is scenario-based
as the intensity and rate of displacement, as well as
the geological structures activated by the sliding rock
mass vary significantly on the slopes. In addition, for
each scenario the secondary effects, such as genera-
tion of displacement waves or landslide damming of
valleys with the potential of later outburst floods, are
evaluated. The hazard analysis is based on two types
of criteria: 1) Structural site investigations including
analysis of the development of a back-scarp, lateral
boundaries and basal sliding surface. This includes
a kinematic analysis for sliding and toppling based
on slope orientation, persistence of main structures
and morphologic expressions of the sliding surface.
2) Analysis of slope activity primarily based on slide
velocity, change of deformation rates, observation of
rockfall activity, and historic or prehistoric events.
The analysis of consequences focuses on the potential
fatalities to the rock slide scenarios and secondary ef-
fects. Based on the hazard and consequence analysis
each scenario is classified in a risk matrix into cat-
egory low, medium or high risk.
K
ey
words
: catastrophic rock slope failure, secondary ef-
fects, hazard analysis, consequence analysis, risk matrix
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R.L. HERMANNS, T. OPPIKOFER, E. ANDA, L.H. BLIKRA, M. BÖHME, H. BUNKHOLT, G.B. CROSTA,
H. DAHLE, G. DEVOLI, L. FISCHER, M. JABOYEDOFF, S. LOEW, S. SÆTRE & F.X. YUGSI MOLINA
246
International Conference Vajont 1963-2013. Thoughts and analyses after 50 years since the catastrophic landslide Padua, Italy - 8-10 October 2013
ures. This has to be taken into account when assess-
ing spontaneous (seismically-triggered rockslides) for
that a minimum magnitude of M 6 was established by
k
eeFeR
(1984) based on 40 historical earthquakes. His-
toric observations over the past 200 years indicate that
with the premise of an acceleration phase prior to col-
lapse we could capture the vast amount of rock slope
failures in Norway (F
uRseTh
, 2006). Said that, triggers
(e.g. seismic activity) with a longer recurrence period
are not captured in this observational period, highlight-
ing that this classification system cannot be used as a
risk management tool alone, but has to be used espe-
cially in areas with higher levels of seismic activity in
connection with seismic hazard maps as presented by
s
TandaRd
n
oRge
(2008).
Hence the hazard analysis focuses on capturing
unfavorable geological conditions, morphological
features expressing slope deformations and changes
within the slope that can give a hint of the stability
state of the slope as well as on the area that will be
impacted by the direct impact of the rockslide or a re-
lated secondary effect. The risk classification focuses
on the potential loss of life only.
This classification system is built for the special
geographic and geological conditions in Norway that
is dominated by crystalline rock and does not present
large rock slopes with weak sedimentary rocks such
as the Alps, Apennine or the Rocky Mountains. Other
observations would have to be included in mountain
terrains with thick weakly consolidated sedimentary
or volcanic rocks. The classification system might also
be applied in other areas in the world, but needs to be
adapted to local geologic, geographic and climatic con-
ditions. The classification system is flexible for such
adaptations by giving the possibility to exclude some of
the criteria used in Norway and to add new ones. We es-
pecially underline that today there is insufficient quan-
tity of information on geological occurrences to support
the prediction of large rock slope failures on geological
conditions alone and that instrumental monitoring is the
appropriate tool for monitoring changes in rock slope.
DEFINING FAILURE SCENARIOS
Deformation of unstable rock slopes can be either
uniform over the entire slope or spatially distributed.
In the latter case, deformation varies between different
compartments of an unstable rock slope (also called
parts, blocks or similar). This difference in deforma-
for assessing the likelihood of failure. Furthermore, it
requires prioritization of follow-up activities, such as
periodic or permanent monitoring, early-warning sys-
tems, and other mitigation measures. A first guideline on
the mapping approach and a hazard and risk classifica-
tion is given in a geological report (h
eRManns
et alii,
2012) and is summarized in this publication. Mapping
as well as hazard and risk classification will follow in
Norway in the upcoming years these guidelines until a
large number of sites are classified and related geologi-
cal data and data on potential consequences stored in a
related database (B
unkholT
et alii, 2013). Then the clas-
sification system can be reviewed based on real data. As
the likelihood of failure cannot be given quantitatively
in hundreds or thousands of years with today's scien-
tific knowledge, the risk analysis is built on a qualitative
hazard analysis and a quantitative consequence analysis.
The goal is to assemble enough data on historic and pre-
historic rock slope failures in Norway that will allow for
a calibration of the qualitative hazard analyses.
The working approach for the elaboration of this
classification system was to combine a broad national
and international experience on large rock slope fail-
ures and a group of 18 Norwegian and 5 international
experts had participated in the discussion preceding
this classification system (see summary in h
eRManns
et
alii, 2012). Furthermore, earlier proposed classification
systems that focus on long term slope stability of large
rock slopes have been taken as guide (h
anTz
et alii,
2002; h
ungR
& e
vans
, 2004; g
lasTonBuRy
& F
ell
,
2008; J
aBoyedoFF
et alii, 2012).
Examples of 32 historic catastrophic rock slope fail-
ures from Norway and around the world show that un-
stable rock slopes do not fail under aseismic conditions
without any pre-failure slope deformation (h
eRManns
et alii, 2012). This classification system only focuses
on aseismic failures because the timing of earthquakes
cannot be predicted up to now, making early-warning
of earthquake-triggered rockslides impossible. We have
to highlight here that in Norway seismicity rates over
the 20th century suggest that the region typically re-
veals one magnitude (M) 5 earthquake every 10 years
and one M 7 earthquake every 1100 years (B
unguM
et alii, 1998, 2000, 2005). However, there are clear
regional differences with most of the seismic activity
concentrated in small areas located in the near-shore or
off shore area (s
TandaRd
n
oRge
, 2008) that should be
considered in the risk management of rock slope fail-
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HAZARD AND RISK CLASSIFICATION FOR LARGE UNSTABLE ROCK SLOPES IN NORWAY
Italian Journal of Engineering Geology and Environment - Book Series (6) www.ijege.uniroma1.it © 2013 Sapienza Università
Editrice
247
Based on the combination of those observations
the hazard and risk classification for each potential
scenario has to be carried out independently.
In order to reduce costs, the development of sce-
narios has to be an iterative process in which detail of
analysis increases stepwise following the principles
outlined in Fig. 1. The term assessment is here used to
describe a semi-quantitative evaluation carried out by
the mapping geologist, while the term "analysis" is used
here for more thorough, quantitative investigations.
HAZARD CLASSIFICATION
ORGANIZATION OF THE HAZARD CLASSI-
FICATION SYSTEM
The classification system uses nine criteria de-
scribing the present state of an unstable rock slope
(Fig. 2). They can be arranged into two main groups:
1. the structural development of the unstable rock
slope; 2. displacement rates and other signs of activ-
ity. For each criterion (κ
i
) several conditions (χ
ij
) are
possible to choose from and a score (ν
ij
) is assigned
to each condition. The sum of scores for the chosen
conditions gives the total score, which is called hazard
tion style also becomes evident when looking back into
geological records indicating that some unstable slopes
collapsed repeatedly while others slopes failed in a
single event (e.g. h
eRManns
et alii, 2001; W
illenBeRg
,
2004; h
eRManns
et alii, 2006 and references there in,
AA et alii, 2007). These multiple failure sites suggest
that at some rock slopes parts of the rock mass can get
to a critical state at different moments in time. These
compartments may have different failure probabilities,
different consequences and pose therefore also different
levels of risk. One can define a scenario by a compart-
ment of the unstable rock slope, which might fail in a
single event and individually from other compartments.
An additional hint to define failure scenarios is the
analyses of historic and prehistoric failures along slope
sections built by the same lithologies and controlled by
the same structures.
Different scenarios are therefore justified and need
to be analyzed at slopes that show a combination of:
• Different deformation rates
• Varying structural conditions
• Internal scarps, cracks and depression which dissect
the unstable rock slope
Fig. 1 - Development of the scenario based hazard and risk assessment by gradually increasing detail (from left to right) of
hazard and consequence analyses in an iterative approach. The term assessment is here used for a semi-quantitative
evaluation during project development, while analysis is a quantitative evaluation
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R.L. HERMANNS, T. OPPIKOFER, E. ANDA, L.H. BLIKRA, M. BÖHME, H. BUNKHOLT, G.B. CROSTA,
H. DAHLE, G. DEVOLI, L. FISCHER, M. JABOYEDOFF, S. LOEW, S. SÆTRE & F.X. YUGSI MOLINA
248
International Conference Vajont 1963-2013. Thoughts and analyses after 50 years since the catastrophic landslide Padua, Italy - 8-10 October 2013
However, this average hazard score does not ex-
press the uncertainties on the individual criteria and
therefore on the hazard score. In order to compute the
entire range of possible outcomes, the criteria are or-
ganized in a decision tree. Each criterion, κ
i
, represents
a node of the decision tree and each condition, χ
ij
, forms
a branch of the tree. For each path of the tree, its hazard
score, ρpath, and its probability, φpath, can be calcu-
lated using Equations (1) and (3), respectively:
(3)
with j corresponding to the chosen condition χ
ij
for
criterion κ
i
.
Using scores and conditions for the nine criteria
shown in Fig. 2 leads to 48'600 possible paths and
probabilities for individual paths may be very low.
However, several paths may lead to the same path
hazard score, ρpath. Therefore, the total probability of
having a given hazard score corresponds to the sum of
score, ρ (Equation 1):
1)
with j corresponding to the chosen condition χ
ij
for
criterion κ
i.
Using the nine criteria, the hazard score, ρ, can
range from 0 to 12. It is assumed that the likelihood of
an unstable rock slope to fail increases with ρ.
CONDITION UNCERTAINTIES
Unstable rock slopes are complex landslide phe-
nomena and it may often be difficult to choose only one
of the conditions (χ
ij
) for a given criterion (κ
i
). In order
to include these uncertainties, probabilities (p
ij
) for each
condition can be given. The average (expected) hazard
score, ρ, is obtained by summing all the scores (νij)
multiplied by the conditions probabilities (Equation 2):
(2)
Fig. 2 - Nine criteria describing the present state of the slope: For each criterion several conditions are possible to choose
from and a score is assigned to each condition
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HAZARD AND RISK CLASSIFICATION FOR LARGE UNSTABLE ROCK SLOPES IN NORWAY
Italian Journal of Engineering Geology and Environment - Book Series (6) www.ijege.uniroma1.it © 2013 Sapienza Università
Editrice
249
dating the deformation could solve the problem. How-
ever this information from the geological past does
not necessarily indicate anything on the performance
of the slope in future and continuous fatigue of rock
in the past 10,000 years could have led to a critical
stability today. Similarly, rock slopes that failed cata-
strophically could define the very high hazard class, if
the slope conditions in the period of months/years pri-
or to the catastrophic failure are used. Unfortunately,
there is generally not enough information available on
past catastrophic rock slope failures, in order to assess
their hazard score with satisfying reliability.
The advantage of this decision tree analysis is
obvious: instead of giving a single hazard score for
an unstable rock slope, the proposed technique with
the decision tree analysis gives a range of probable
hazard classes.
Note that due to the use of probabilities in the
classification system, it can also be used to determine
whether more detailed analyses are necessary. For
example, often during early site investigations, no in-
formation is available on the displacement rate of the
slide. Hence, this high level of uncertainty should be
expressed in the analyses. If the result of the analyses
indicates that there is a probability that the sites might
be defined to be of moderate or high risk, then more
investigations become necessary focusing on defining
the velocity. If also under the worst case assessment the
site remains a low risk object, no further investigations
are required.
CONSEQUENCE AND RISK ANALYSIS
AND SUGGESTED SURVEILANCE OF
UNSTABLE ROCK SLOPES
F
ell
et alii (2008) define risk as "a measure of the
probability and severity of an adverse effect to health,
property or the environment
". We focus in our conse-
quence/risk analyses on loss of life only. "Risk is often
estimated by the product of probability of a phenom-
enon of a given magnitude times the consequences"
(p. 86). The risk, R, can be calculated using the widely
used risk equation (modified from l
eRoi
, 1996; F
ell
et alii, 2005) (Equation 4):
(4)
with P
F
= probability of failure; P
P
= probability of
propagation (probability of the landslide and its sec-
ondary effects reaching the element at risk); PE =
all φpath with the same ρpath.
We have developed a macro in Microsoft Visual
Basic 6.5 (implemented in Microsoft Excel® 2007)
that is downloadable at the same website as the report
(see h
eRManns
et alii, 2012 in the references). It com-
putes all possible paths of the decision tree including
ρpath and φpath and creates the sum of all φpath lead-
ing to the same ρpath. Using the scores presented in
Figure 2, the path hazard score, ρpath, ranges from 0
to 12 with steps of 0.25. The final outcome is a prob-
ability for each of these 49 different hazard scores,
φscore. The probability distribution of φscore allows
obtaining the minimum and maximum hazard scores,
ρ, using the chosen probabilities, p
ij
. The modal value
indicates the most probable ρ located at the peak of
the probability distribution, while the mean value is
computed using Equation 2.
HAZARD CLASSES
Simplified to allow for effective communication,
the hazard score is divided into five hazard classes
using equal intervals (Fig. 3). Equal intervals are
preferred over expert-knowledge-based class limits,
because the latter are more controversial and need to
be supported by calibrations of past rock slope fail-
ures. For example, one could define the very low haz-
ard class by slopes that move since more than 10,000
years and that did not yet fail catastrophically; hence
Fig. 3 - Risk classification matrix for follow-up with moni-
toring and further investigations of unstable rock
slopes in Norway: green = low risk; yellow = mo-
derate risk; red = high risk. The risk of an unsta-
ble rock slope is represented by its mean value, the
minimum and maximum consequences (horizontal
arrows), the 5% and 95% percentiles of the hazard
score (vertical arrows) and the minimum and ma-
ximum scores of the hazard analysis (dotted line)
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R.L. HERMANNS, T. OPPIKOFER, E. ANDA, L.H. BLIKRA, M. BÖHME, H. BUNKHOLT, G.B. CROSTA,
H. DAHLE, G. DEVOLI, L. FISCHER, M. JABOYEDOFF, S. LOEW, S. SÆTRE & F.X. YUGSI MOLINA
250
International Conference Vajont 1963-2013. Thoughts and analyses after 50 years since the catastrophic landslide Padua, Italy - 8-10 October 2013
probability of presence of the element at risk; V = vul-
nerability of the element at risk to the landslide event
(degree of loss from 0% to 100%); E = element at risk
(i.e. exposed population).
Several of the factors of Equation 4 are difficult to
quantify within the framework of this hazard and risk
classification for unstable rock slopes in Norway, es-
pecially the probability of failure, P
F
, which cannot be
assessed with today's technical understanding of large
unstable rock slopes within the timeframe of hundreds
to thousands years. For this hazard and risk classifica-
tion system the hazard score is used as a qualitative
measure of P
F
.
PRELIMINARY CONSEQUENCE AND RISK
ANALYSIS
The preliminary risk analysis is a first, rough anal-
ysis aiming to distinguish between low risk objects
and medium to high risk objects that require more de-
tailed risk analyses. Therefore, a worst case scenario
is assumed for the preliminary risk assessment and P
P
,
P
E
and V are set to 1 and E is the maximum number
of persons living and being present or transit in the
affected area.
This means that the entire area computed in the
run-out assessment will be reached by the rock ava-
lanche or displacement wave (P
P
= 1), all the popula-
tion and persons that transit are present in the affected
area (P
E
= 1) and their loss of life is certain (V = 1).
The number of potential life losses is thus equal to E.
DETAILED CONSEQUENCE AND RISK
ANALYSIS
For potential medium to high risk objects based
on the preliminary risk assessment a detailed con-
sequence analysis becomes necessary (Fig. 1). This
includes a more detailed quantification of the param-
eters in Equation 4. Detailed run-out modeling (and
displacement wave assessment if relevant) allows
the determination of P
P.
The parameter PE is mainly
depending on the building type (house, office, shop,
school etc.) and can be determined roughly at a na-
tional level. Different vulnerabilities can be defined,
depending if a building is hit directly by a rock ava-
lanche and loss of life is nearly certain (V=1) or if it
is hit by a displacement wave that have an assumed
survival rate of 30% (V=0.7) (B
likRa
et alii, 2006b).
The number of potential life losses is then obtained by
multiplying P
P
, P
E
, V and E for each building and sum-
ming over the entire area affected by a rock avalanche
and its secondary effects. Areas frequently visited by
tourists and all infrastructure with persons in transit
are assessed in the same manner as buildings (e.g.,
B
likRa
et alii, 2013).
An exception from the approach outlined above, is
up- and downstream flooding related to rockslide dams.
In contrast to the direct impact of a rockslide on a build-
ing or the impact of a rockslide-triggered displacement
wave on a building, people affected by upstream and
downstream flooding related to landslide damming and
subsequent dam breaching can be evacuated from the
building. Hence this secondary effect is treated as a
flood hazard and in these cases the evaluation of haz-
ard and risk related to dam formation and dam failure
should be included as outlined in d
ahle
et alii (2011a)
and h
eRManns
et alii (2013b). However, the final risk
classification will mainly be based on the number of
people which might lose their life in a potential event.
RISK MATRIX AND RISK CLASSES
This classification system combines the hazard
score and the potential life losses in a risk matrix
(Fig. 3). Isorisk lines are often used in a risk matrix
to distinguish between acceptable, tolerable and unac-
ceptable risks as proposed for example for landslides
and rock falls from natural slopes in Hong Kong (g
eo
-
Technical
e
ngineeRing
o
FFice
, 1998). However, these
isorisk lines are not applicable for the present risk
classification system, since the hazard score is only
a qualitative measure of the probability of failure and
the classification focuses on rock slope failures pre-
ceded by an acceleration phase only, thus excluding
earthquake-triggered rock slope failures. The risk can
therefore not be expressed in terms of number of casu-
alties per year, and this is not a risk management tool
in its own but a support for risk management
The purpose of the risk matrix is helping to decide
on follow-up actions for unstable rock slopes includ-
ing monitoring, further field investigations, and/or
possible mitigation measures. For that reason the risk
matrix is divided into three risk classes: low (green),
medium (yellow) and high (red). The limit between
the low and medium risk classes is set along the di-
agonal going from the high hazard class with very low
consequences (0.1 to 1 casualties) down to very low
hazard class with high consequences (100 to 1000 cas-
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HAZARD AND RISK CLASSIFICATION FOR LARGE UNSTABLE ROCK SLOPES IN NORWAY
Italian Journal of Engineering Geology and Environment - Book Series (6) www.ijege.uniroma1.it © 2013 Sapienza Università
Editrice
251
IMPLICATION OF THE RISK CLASSIFICA-
TION
The risk classification of unstable rock slopes in
Norway will be used by the NGU and the NVE in
order to decide on follow-up investigations and miti-
gation measures. It will also help municipalities and
other stakeholders as a basis for land use planning and
contingency planning.
A document describing the implications of the risk
classification related to the low, medium and high risk
classes will be presented in due time by NVE. This
will include implications related to land use planning,
monitoring and early-warning, contingency planning
and structural measures. All decisions on mitigation
measures will be based on cost-benefit reasoning that
will be explained in more detail in the NVE document.
In general, low risk objects will not be followed
up except a routine scanning in the field or based on
remote sensing data (air photos, satellite data) every
10 to 20 years. For medium risk objects, periodic
monitoring is recommended and the techniques used
and the measurement intervals applied will depend
on geological conditions on the site, applicability of
the various methods under cost-benefit reasoning.
For high-risk objects mitigation measures are recom-
mended that will often be coupled monitoring and
early warning techniques. This has to be discussed
among risk owners and geoscientists.
SUMMARY AND DISCUSSION
Due to the geomorphologic conditions of Norway
with high mountains deeply penetrated by fjords, large
rock slope failures occurred repeatedly in the past, of-
ten accompanied by secondary effects such as displace-
ment waves. Therefore, in contrast to other mountain
belts in the world, these rock slope failures resulted in
disasters with a high death toll far from the source area
of the rock slope failure. As such events will also oc-
cur in the future, systematic mapping of rock slopes has
been started in the first decade of the 21
st
century and
today more than 300 unstable rock slopes are known.
This high number necessitated a quantitative classifica-
tion system based on hazard and risk related to the po-
tential failures that should help deciding on follow-up
activities. This system was elaborated in a large effort
combining national and international experts from vari-
ous disciplines in earth sciences. During the elabora-
tion of this system it became obvious that today there
ualties). It is expected that most of the sites in Norway
fall into the low risk class. Those sites are either con-
sidered to have low consequences and further follow
up is not economically sustainable, or the site would
require dramatic changes in the geological conditions
prior to failure. Such changes could be captured with
a scanning of geological conditions by means of field
visit or remote sensing data interpretation every 10 to
20 years. Medium risk sites are expected to be less
common in Norway. However, potential consequenc-
es are higher or the probability of failure is higher so
that a low-level follow up is recommended to reduce
the risk level. The limit between the medium and high
risk classes is not precisely defined and is shown as a
yellow to red gradient. In this transition zone between
medium and high risk, in general further site-specific
geological criteria are needed to be studied in order
to have a good enough understanding for a final clas-
sification. These sites will generally require additional
expert judgement that will be used to classify the risk .
REPRESENTING UNSTABLE ROCK SLOPES
IN THE RISK MATRIX
An unstable rock slope can be placed in the risk
matrix based on the hazard analysis and the conse-
quence analysis. As both factors have uncertainties,
the minimum and maximum values for hazard and
consequences can also be plotted in addition to the
mean value (Fig 3).
The uncertainties on the hazard score and the con-
sequences can have an influence on the risk classifica-
tion and on the decision on follow-up activities. An
unstable rock slope might for example be classified
as low risk based on the most likely hazard class, but
there might be a certain probability that it ends up as
a medium risk. If this probability exceeds 5%, more
site investigations should be considered in order to
reduce the uncertainties on the assessment of condi-
tions for the different criteria. If this is not feasible, the
unstable rock slope might be classified with the higher
risk class. The 5% and 95% percentiles of the hazard
score are therefore also shown in the risk matrix (Fig.
3). Similarly, there is uncertainty related to the con-
sequences and more detailed consequence analyses
could be considered in order to reduce the uncertainty.
The decision on follow-up activities will be made af-
ter a thorough discussion of the uncertainties related
to both hazard and consequences.
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R.L. HERMANNS, T. OPPIKOFER, E. ANDA, L.H. BLIKRA, M. BÖHME, H. BUNKHOLT, G.B. CROSTA,
H. DAHLE, G. DEVOLI, L. FISCHER, M. JABOYEDOFF, S. LOEW, S. SÆTRE & F.X. YUGSI MOLINA
252
International Conference Vajont 1963-2013. Thoughts and analyses after 50 years since the catastrophic landslide Padua, Italy - 8-10 October 2013
2012). The analysis of pre-failure conditions indicat-
ed a high hazard for that slope (in h
eRManns
et alii,
2012). We take this as a first positive test of our clas-
sification system. Furthermore, the probability of the
Åknes rock slope in Norway was assessed earlier, and
independently of this system, and the results are com-
parable (B
likRa
et alii, 2005; h
eRManns
et alii, 2012).
Nevertheless we want to highlight that this classifi-
cation system should be updated once more scientific
knowledge becomes available, and that more research
is necessary to better understand failure processes of
large rock slope failures through time. These efforts
will then hopefully allow replace the qualitative haz-
ard analysis with a quantitative hazard analysis.
The consequence analysis is focused on number of
loss of lives only and we start with a conservative ap-
proach by assuming that all people that might be hit by
a rock avalanche or a rockslide-triggered displacement
wave are likely to lose their lives. For potential high-
risk objects a more detailed analysis is carried out that
includes the probability of surviving the rockslide trig-
gered displacement wave. Both the qualitative hazard
analysis and the quantitative consequence analyses are
combined in a risk matrix for a risk analysis. Three dif-
ferent risk classes are defined. Low risk where no fur-
ther follow up is needed, medium risk where periodic
monitoring of the rock slope is suggested and high risk
that suggest for further follow up. Follow up for high
risk objects has to be discussed with the risk owners
and could be resettlement, periodic monitoring, con-
tinuous monitoring coupled with early warning or any
other mitigation measure that has to be decided after
cost-benefit reasoning. Often additional geological in-
formation to those summarized in this classification has
to be assembled for optimal monitoring practices and
a thorough slope stability analysis. This might include
subsurface information obtained from core logging,
geophysics and hydrological investigations.
Finally we want to stress again that the hazard
and risk classification system is not a risk manage-
ment tool in itself as it does not include seismically
triggered rock slope failures. It is thus a support tool
for risk management that will help to decide on follow
up (e.g. no follow up necessary, periodic monitoring
is recommended to reduce the risk, more studies are
required and/or risk mitigation measures should be
taken). This is also not a guideline for early warn-
ing practices as these are regulated in Norway by the
is not enough scientific knowledge to predict the tim-
ing of large rock slope failures, and that more research
is needed and much can be learned from rock slope
failures that have been monitored in the years prior
to failure. Therefore, we qualitatively classified the
probability of failure in very high, high, moderate,
low and very low.
Our hazard classification is based on two sets
of criteria: 1) Structural site investigations including
analysis of the development of a back-scarp, lateral
boundaries and basal sliding surface. This includes a
kinematic analysis that tests if rock sliding or toppling
is kinematically feasible with respect to the slope ori-
entation, the persistence of main structures and the
morphologic expression of the sliding surface. 2) The
analysis of the activity of the slope is primarily based
on the slide velocity, but also includes the change of
deformation rates (acceleration), observation of rock-
fall activity and historic or prehistoric events. For each
criterion several observations are possible to choose
from. Each observation is associated to a score and the
sum of all scores gives the total score for a scenario.
The weighting of these scores has changed from the
first proposal of the classification system (h
eRManns
et alii, 2010) over a preliminary usage of it (d
ahle
et
alii, 2011b) to this final version. For example, in this
final version the historic and prehistoric events are
weighted much lower than in the first proposal. This
seemed necessary as the occurrence of a prehistoric
event alone should not raise a site by one hazard class
without any signs of present day activity. Further-
more, the displacement rates and morphological ex-
pressions/kinematic feasibility of failure are weighted
equally. This weighting should be revised once statis-
tically adequate information becomes available.
As all these observations are connected to un-
certainties, the classification system is organized in a
decision tree where probabilities to each observation
can be given. All possibilities in the decision tree are
computed and the individual probabilities giving the
same total score are summed. Basic statistics show the
minimum and maximum total scores of a scenario, as
well as the mean and modal value. The final output is
a cumulative frequency distribution divided into sev-
eral classes, which are interpreted as hazard classes.
Within the completion time of this document a
rock slope failure occurred in Switzerland that has
been monitored for more than a decade (l
oeW
et alii,
background image
HAZARD AND RISK CLASSIFICATION FOR LARGE UNSTABLE ROCK SLOPES IN NORWAY
Italian Journal of Engineering Geology and Environment - Book Series (6) www.ijege.uniroma1.it © 2013 Sapienza Università
Editrice
253
Eikenæs, Corey Froese, Jarle Hole, Aline Saintot) are
thanked that initially have been in the discussion of
elaborating the classification system that later vol-
untarily dropped out as the discussion was very time
consuming. Also Carl Harbitz (Norwegian Geotechni-
cal Institute) and Hallvard Berg (NVE) contributed to
the classification system over a long period.
building code TEK 10 § 7.4 (Byggeteknisk forskrivt,
2010) and we thus do not include a discussion on trig-
gering mechanism here.
ACKNOWLEDGEMENTS
The authors gratefully thank Norwegian Water
and Energy Directorate that made a workshop pos-
sible in 2010 that stared the discussion on the docu-
ment. Numerous scientist (Jordi Corominas, Olianne
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