Geomorphology 120 (2010) 77–90
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Geomorphology
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / g e o m o r p h
The role of landslides in mountain range evolution
Oliver Korup a,⁎, Alexander L. Densmore b, Fritz Schlunegger c
a
b
c
Swiss Federal Research Institutes WSL/SLF, CH-7260 Davos, Switzerland
Department of Geography, University of Durham, UK
Institute of Geological Sciences, University of Berne, Switzerland
a r t i c l e
i n f o
Available online 22 September 2009
Keywords:
Landslide
Geomorphic hillslope–channel coupling
Threshold hillslope
Tectonic geomorphology
Stream power
Bedrock river
a b s t r a c t
We review the role of landslides in current concepts of the topographic development of mountain ranges.
We find that many studies in this field address basin- or orogen-scale competition between rock uplift and
fluvial bedrock erosion. Hillslopes in general, and bedrock landslides in particular, are often assumed to
respond rapidly to incision and development of the fluvial drainage network. This leads to a one-sided view
of the geomorphic coupling between hillslopes and rivers that emphasizes the fluvial control of hillslopes,
but ignores the alternative view that landslides can affect the fluvial network.
There is growing evidence that landslides are a dominant source of sediment in mountain belts and that they
exert a direct geomorphic control on fluvial processes. Landslides can influence the river network in a variety
of ways, from determining basin area and drainage divide positions, to setting streamwise variations in
sediment load and calibre. The geomorphic legacy of large landslides on hillslope and channel morphologies
may persist for up to 104 yr, adding considerable variability to fluvial erosion and sedimentation patterns
over these timescales.
We identify a number of questions for future research and conclude that a better understanding and
quantification of the geomorphic feedbacks between landslides and river channels builds an important link
between short-term (< 101 yr) process studies and long-term (> 105 yr) landscape evolution models.
© 2009 Elsevier B.V. All rights reserved.
1. Introduction
The topographic development of mountain belts is commonly
portrayed as a competition between tectonic fluxes of material into
the orogen, modulated by geodynamic processes such as crustal
faulting or lithospheric deformation, and erosional fluxes of material
out of the orogen, modulated by Earth surface processes (Koons,
1989; Montgomery et al., 2001; Willett and Brandon, 2002; Bishop
et al., 2003). Perhaps foremost among these surface processes is the
incision of a network of bedrock rivers into the growing range and
fluvial transport of erodible sediment by the river network. Sediment
is supplied to the river network by a range of hillslope processes, of
which landsliding is likely the most dominant in many humid
mountain belts (e.g. Hovius et al., 1997; Shroder and Bishop, 1998;
Oguchi et al., 2001). While landslides are recognised as being
important agents of mass wasting and hillslope evolution on local
scales, their overall role in the growth of mountainous topography is
not well understood.
Here we review the role of landslides in the evolution of mountain
ranges, drawing on key concepts that have arisen from studies in
tectonic geomorphology. Our motivation for this is spurred by the
growing recognition that landsliding exerts a primary control on the
⁎ Corresponding author.
E-mail address: [email protected] (O. Korup).
0169-555X/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.geomorph.2009.09.017
planform development, incision history, and sediment discharge of
watersheds (Hovius et al., 1997, 1998; Hewitt, 1998; Strasser and
Schlunegger, 2005; Korup et al., 2006). This observation is not
accounted for by recent conceptual models of bedrock fluvial incision
in response to tectonic uplift, in which hillslopes achieve threshold
gradients and respond rapidly to fluvial network incision.
We conclude by presenting several research questions and
highlighting future research potential to further integrate processes
of landsliding into current concepts of feedback mechanisms between
uplift and erosion in tectonically active mountain belts.
2. Current concepts of fluvial driven mountain range evolution
2.1. Fluvial bedrock incision
There is a growing notion that fluvial incision into bedrock both
establishes the relief structure of a mountain belt, and sets the lower
boundary condition for hillslope processes (e.g. Whipple and Tucker,
1999; Burbank, 2002; Whipple, 2004). Topographic relief in mountain
ranges can be conceptually divided into two components: relief on
unchanneled or colluvial hillslopes, and relief on the fluvial river
network. Observations from some tectonically active mountain ranges
suggest that the fluvial network spans 80% or more of the total relief
(Whipple and Tucker, 1999; Whipple, 2004). Thus, the fluvial
network can be thought of as the ‘skeleton’ of a mountain belt, with
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O. Korup et al. / Geomorphology 120 (2010) 77–90
the hillslopes extending above the tips of the drainage network.
Because of this, the longitudinal profiles of rivers in mountainous
environments effectively dictate the magnitude and spatial distribution of relief over geological timescales, and a large body of research
over the last decade has focused on understanding the controls on the
form and development of these longitudinal profiles (e.g. Tarboton
et al., 1992; Montgomery and Foufoula-Georgiou, 1993; Whipple and
Tucker, 1999; Tucker and Whipple, 2002; Stock and Dietrich, 2003;
Whipple, 2004; Schlunegger et al., 2006).
The rate of river incision into bedrock is commonly assumed to be
a power-law function of mean bed shear stress, leading to the socalled ‘stream power’ family of incision models (for thorough reviews,
see Whipple and Tucker, 1999; Whipple, 2004). An attractive feature
of these models is that they can be rewritten to provide a physical
explanation for the commonly observed power-law relationship
between river bed slope S and contributing drainage area A, usually
expressed as
S = ks A
–θ
ð1Þ
where θ is the concavity index, and ks is a coefficient generally known
as the steepness index. Eq. (1) is typically applicable to a longitudinal
profile only beyond some threshold drainage area, which is often
observed to be of the order of 105 m2 in tectonically active mountain
ranges (e.g. Whipple, 2004). For our purposes, the important features
of the stream power family of models are that they assume that
(1) channel slope is set only by fluvial processes; (2) adjustments in
channel slope are the only means for a river to respond to tectonic or
climatic influences; and (3) river incision into bedrock is the ratelimiting process for topographic change or relief production in a
mountain belt. Despite these limiting assumptions, the stream power
models provide a convenient and attractive tool for inferring regional
patterns of fluvial incision at the mountain-belt scale (Finlayson et al.,
2002; Sobel et al., 2003). They also have been widely used to quantify
streamwise variations in differential rock uplift, erodibility, and the
influence of climate (e.g. Roe et al., 2003; Kirby et al., 2003; Kobor and
Roering, 2004).
2.2. Threshold hillslopes and limits to relief
If fluvial bedrock incision both sets the relief structure of the
landscape and acts as the rate-limiting process in dictating erosion
rates (Whipple and Tucker, 1999; Godard et al., 2004; Safran et al.,
2005), it follows that hillslopes must rapidly and passively adjust to
variations in fluvial incision rates (Fig. 1). According to this concept,
an increase in fluvial incision rates will steepen the adjacent
hillslopes, which will respond by rapid landsliding (Fig. 1A, B).
Alternatively, a decrease in fluvial erosion rates, or accumulation of
sediment in channels, will reduce local relief, which, in turn, then
tends to reduce rates of landsliding on the adjacent hillslopes
(Fig. 1C).
Burbank et al. (1996) suggested that spatially uniform hillslope
angles in the northwestern Himalayas resulted from close geomorphic
hillslope–channel coupling (Harvey, 2002), and proposed that the
hillslopes were at a limiting or threshold slope angle for failure. Slopeangle distributions across other tectonically active mountain belts,
such as the Southern Alps of New Zealand, are also strikingly uniform
despite strong gradients in rates of uplift, precipitation, and erosion,
as well as varying rock types (Fig. 2). The occurrence of such threshold
hillslopes implies that local relief is a function of drainage density, but
independent of rates of fluvial incision and rock uplift (Burbank, 2002;
Fig. 1A). Hence, fluvial incision as the rate-limiting process would, at
least in non-glaciated mountain belts, control hillslope sediment flux,
assuming full geomorphic coupling between channels and hillslopes
(Whipple and Tucker, 1999).
Fig. 1. The concept of threshold hillslopes as a form of dynamic adjustment to fluvial
bedrock incision (Burbank, 2002). A. Local relief is independent of fluvial incision rate
Ec, as hillslopes are at a critical slope φc, where shear stress equals hillslope strength,
and where rate of divide lowering Ed = Ec. Hillslope sediment flux qs is controlled by Ec
only. B. Increase in Ec steepens slope angle φ2 > φc, leading to rapid response by
landsliding to maintain φc. C. Landscapes with hillslope angles <φc may result from
Ed > Ec, with qs controlled by some (non-linear) function of slope φ. Stages B and C have
also been interpreted as the result of drier and wetter climate, respectively (Gabet et al.,
2004).
The concept of threshold hillslopes has since been developed into a
predictive tool, with slope-angle distributions being compared to
precipitation patterns in order to detect possible climatic or process
controls on threshold slope angle (Brozovic et al., 1997; Burbank et al.,
2003; Gabet et al., 2004; Fig. 1C). Orographic effects on precipitation
patterns, however, make it difficult to interpret these relationships,
especially if limited historic climate data are used exclusively, and
without addressing longer-term climatic variability.
Montgomery (2001) found that a normal distribution of hillslope
angles in a landscape did not necessarily support the interpretation of
the presence of threshold hillslopes. Schmidt and Montgomery (1995)
proposed an alternative to this model, and suggested that dip-angle
hillslopes prone to frequent bedrock landsliding were essentially
limited by their large-scale strength properties. Although the
modified Cullman method they used may not fully be applicable to
most mountain hillslopes, it considers rock-slope stability in a
geotechnical sense, explicitly addressing properties of rock-mass
strength. Also, this limit-equilibrium approach implies by definition
that landsliding solely occurs as a function of critical hillslope height,
while not accounting for landsliding on sub-critical hillslope portions.
3. Current concepts of landslides and their role in mountain
range evolution
3.1. Landslide-dominated mountain belts
Most studies of mountain range evolution have concentrated on
basin- to orogen-scale competition of rock uplift and fluvial incision
into bedrock (Pavlis et al., 1997; Lavé and Avouac, 2001; Snyder et al.,
2003; Kirby et al., 2003; Clark et al., 2004), to which hillslopes
passively adjust. Hillslope processes in general, and landslides in
particular, have so far been rarely quantified or modelled in a
physically-based manner over such large spatial and temporal scales
(see 3.5). Little is known about what role landslides play in the
O. Korup et al. / Geomorphology 120 (2010) 77–90
79
Fig. 2. Slope-angle distributions (sampled from a 25-m digital elevation model within circles of 10-km radius, and normalised by area) across the Southern Alps of New Zealand show
remarkable similarity despite order-of-magnitude changes in uplift rate U, precipitation rate P, denudation rate D, as well as varying rock types (schistose greywacke in the
northwest to unaltered greywacke in the southeast). Note how the shape of the histograms appears to change slightly along the strike of the orogen.
shaping of mountainous topography, and how they influence spatial
and temporal scales of mountain belts, and to what extent they
contribute to the overall sediment budgets of mountainous catchments, despite the growing notion of landslide-dominated mountain
belts (Hovius et al., 1997; Shroder and Bishop, 1998; Hovius et al.,
2000; Oguchi et al., 2001).
3.2. Changes to catchment morphology
Large landslides may exert first-order controls on catchment
morphology such as catastrophic divide shifting and sculpting (Ellis
et al., 1999; Hasbargen and Paola, 2000; Cruden, 2000); headwater
stream truncation and piracy; escarpment retreat (de Berc et al.,
2005); or drainage reversal, while small catchments may form in
detachment areas of deep-seated bedrock landslides (Hovius et al.,
1998; Schramm et al., 1998; Blair, 1999; Fig. 3).
Large landslides modify hillslope gradient and slope curvature
(Roering et al., 2005; Korup, 2006b), and thus also influence slope–
area relationships. Especially where they have deposited extensive
hummocky debris sheets, they considerably reduce hillslope gradients along the slope profile, thus lowering hillslope steepness, while
retaining most of the hillslope's concavity (Fig. 4). This may in turn
influence colluvial erosion laws proposed on the basis of slope–area
data (Lague and Davy, 2003).
Interestingly, the morphologic expression of tectonics on the scale
of individual slopes seems to have been largely neglected in tectonic
geomorphology and models of mountain belt evolution. Zaruba and
Mencl (1969) illustrated the development of large gravitational
landslides caused by increases in folding and uplift rates. Such deepseated slope deformation (sackung) often involves several tens of
km2, and controls local relief and modulates low-order drainage by
interfluve migration and stream piracy (Persaud and Pfiffner, 2004;
Korup, 2006b; Fig. 5A). Large-scale thrusting at mountain-range
fronts may also be a preparatory cause for giant slope failures along
low-angle basal shear planes, as for example along the Gurvan Bogd
fault zone, Mongolia (Bayasgalan et al., 1999). Another impressive
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O. Korup et al. / Geomorphology 120 (2010) 77–90
Fig. 3. Giant landslides and their effects on catchment morphology. A. Panoramic view of Tsergo Ri rockslide (V ~ 1010 m3), Langtang Himalaya, Nepal, from Naya Kanga (5849 masl);
-.-.- = headscarp, - - - - = deposit, ⇐ = direction of movement, ll = Langtang Lirung (7234 masl), d = Dragpoche (6562 masl), pr = Phrul Rangtshan Ri (6960 masl); s = Shisha
Pangma (8027 masl), p = Pangshungtramo (5321 masl); t = Tsergo Ri (4984 masl), dt = Dranglung fault; I = Ledrub–Lirung glacier, k = Kyimoshung glacier, y = Yala glacier, ka =
Kyangjin Kharka (photo courtesy of J.T. Weidinger). B. Bedrock gully development in detachment area (da) of postglacial Tamins rockslide (V ~ 109 m3), Swiss Alps. Note dip-slopes
(→) in limestone bedrock. C. Green Lake rockslide (V ~ 2.7 × 1010 m3), Fiordland, New Zealand, shows headwater drainage developed upstream of displaced rock blocks (rb); → =
movement direction of slope failure.
example of deep-seated slope deformation and gravitational faulting
that affects low-order drainage is the Lluta Collapse, Chile, which is
one of the largest (V ~ 2.6 × 1010 m3) and oldest giant landslides in a
terrestrial environment (Strasser and Schlunegger, 2005; Zeilinger
et al., 2005; Fig. 5B).
Although it may be argued that such slow and gradual slope
deformation may be subsumed in terms of hillslope diffusivity, the
resulting landforms such as bowl-shaped basins, counterscarps or
double-sided ridge lines, or bulging toe slopes, are difficult to
reproduce from regional-scale diffusivity modelling. The geomorphic
feedback between such “chronic” sackung-type movement and fluvial
incision or undercutting will be an important point to quantify and
model in future research.
Smaller, but more frequent, landslides may alter drainage density
(Oguchi, 1997). Similar influences of landslides on the length scales of
mountain belts were studied in the Swiss Alps, where valley
morphologies reveal a distinct pattern in relation to landsliding, or
the Peruvian Andes, where landsliding is considered to control the
spacing of channels (Schlunegger et al., 2006).
Densmore and Hovius (2000) presented a conceptual means of
differentiating between landslide trigger mechanisms from the
resulting valley morphology. They argued that earthquake-triggered
Fig. 4. A. Slope–area plot of the area affected by the giant Dead Lakes rock avalanche (V ~ 2.5 × 109 m3), western Tien Shan (black), and an arbitrarily placed sample area of 400 km2 of
surrounding mountainous terrain (grey). B. Slope gradient versus relative slope position (0 = thalweg, 1 = divide) with respect to channel network with 1 km2 minimum
contributing catchment area. Data were derived from a smoothed 3″ SRTM digital elevation model at ~ 81-m cell-size resolution using an Albers Equal Area projection.
O. Korup et al. / Geomorphology 120 (2010) 77–90
Fig. 5. A. Large rockslide-sackung (V ~ 109 m3) at Gotschna, Prättigau, Swiss Alps; hs =
bowl-shaped headscarp; rd = rockslide debris. B. Enhanced satellite image of the giant
Lluta Collapse (lc), Chile, which evolved as a response to initial landsliding at >2.5 Ma
that mobilised ~ 2.6 × 1010 m3. Subsequent fluvial incision into the landslide scar
occurred by headward erosion (hs) along a dendritic drainage network and removed a
further ~ 2.4 × 1010 m3 of material.
landslides would preferentially nucleate near ridge crests, as opposed
to pore-water and rainfall-triggered failures that clustered on toe
slopes, forming “inner gorges”. They hypothesised that the presence
of inner gorges in a landscape should reflect the dominance of
climatic, rather than tectonic, landslide triggers. While inner gorges
do seem to occur in areas that are historically dominated by
climatically-triggered landslides, this hypothesis awaits further
testing.
3.3. Changes to valley-floor morphology and river long profiles
An important aspect of large landslides is their effect on valley
floors, and hence, river long profiles (Korup, 2006a). Together with
structural and glacial pre-design, and transient variations in local
sediment supply, e.g. by debris flows (Benda et al., 2003), landslides
add noise to ideally concave river longitudinal profiles (Eq. (1)), thus
affecting their use for isolating specific external forcing on profile
development (Sklar and Dietrich, 1998; Schlunegger, 2002; Cui et al.,
2003; Korup et al., 2004). Catastrophic long-runout rock or debris
avalanches may completely obliterate valley floors by scouring and
subsequently covering them with tens of metres of debris for lengths
>10 km, thus interrupting and slowing down fluvial bedrock incision
(e.g. Shang et al., 2003; Fig. 6A, B).
Knickpoint formation associated with large landslides is a wellknown, though rarely quantified, phenomenon (Fig. 6C). Using Eq. (1)
with an arbitrarily fixed concavity index θ = 0.45, a value common to
many rivers in active mountain belts (Whipple, 2004), is a way to
81
highlight significant changes in the steepness index ks (Hodges et al.,
2004). Korup et al. (2006) found that, regardless of local geological,
climatic, and tectonic conditions, the highest values of ks and inferred
specific stream power Ω in mountain rivers spatially very often
coincided with the occurrence of large rock-slope failures. Although in
some cases this could be interpreted as rapid hillslope response to
locally higher rates of fluvial incision (Fig. 1A), most of the reaches in
question are breach channels cut through large rockslide and rockavalanche debris of 102–104 yr in age, and hence post-date landslide
occurrence (Fig. 7).
Large landslide dams add scatter to slope–area relationships,
which in some cases leads to significant changes to ks, whereas θ
appears to be less sensitive (Fig. 8). Since these variables are often
used to quantify rates of climatic and tectonic forcing (Lague et al.,
2003; Kirby et al., 2003) or to explain variations in erosion rates
(Safran et al., 2005), the use of data points affected by landslides in
slope–area plots may bias such estimates. Naturally, there are many
other possibilities of knickpoint formation, e.g. base-level changes,
contrasts in lithology, differential uplift, or variations in sediment
supply.
The presence of one or several landslide dams for 102 to 104 yr also
significantly increases the response time of a basin to external
perturbations. There are numerous examples of Late Pleistocene and
Holocene rockslide dams in the Himalayas, the Tien Shan, and the
Southern Alps of New Zealand, which formed persistent (≤104 yr)
knickpoints and sediment reservoirs in the river long profile (Korup,
2006a; Korup et al., 2006; Fig. 7). Fluvial transport limitation and
massive aggradation upstream of these landslide dams have effectively inhibited fluvial incision into bedrock and reduced local relief
on these timescales (Figs. 9 and 10). Therefore, changes in base level
at the basin outlet, e.g. may not be communicated to all parts of the
basin until the landslide dam is removed and any accumulated
sediment is dispersed downstream (Cui et al., 2003).
In cases where landslide-impacted river channels were forced to
cut into bedrock, epigenetic gorges and fluvial hanging valleys have
evolved (Hewitt, 1998; Korup et al., 2006; Fig. 10A). These landforms
attest to the landslide-driven delay or local repetition of fluvial
bedrock incision. Absolute age constraints on the inception of such
epigenetic gorges are another way to constrain local bedrock incision
rates.
3.4. Sediment delivery and retention
The geomorphic efficiency, and thus importance, of landslides can
generally be characterised by the rate at which they produce
sediment, the efficiency of sediment delivery to the channel network,
and the total contribution of landslides to the sediment budget.
The amount of total sediment produced by landslides within a
given catchment is a function of their magnitude and frequency
(Crozier and Glade, 1999; Reid and Page, 2002). Sediment production
from landslides is often estimated from inventories of small and
shallow failures, and averaged rates vary greatly with study area and
observation period (Table 1; Fig. 11). However, the contribution of
less frequent and larger landslides has so far been less quantified
(Lavé and Burbank, 2004). Whitehouse (1983) calculated that, e.g.
large (>106 m3) rock avalanches in the central Southern Alps of New
Zealand produced debris at an average rate of ~50 m3 km− 2 yr− 1
throughout the Late Holocene, while more recent estimates raise this
figure by an order of magnitude (McSaveney, 2002).
The frequency of landslides in both space and/or time is
increasingly found to be a more or less robust function of landslide
magnitude, on 101-yr timescales at least (e.g. Hovius et al., 1997;
Brardinoni and Church, 2004). Given such empirical relationships,
landslide sediment production may be extrapolated for crude
predictions. However, earthquake- or rainstorm-induced landslide
episodes often create significant peaks in sediment production with
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O. Korup et al. / Geomorphology 120 (2010) 77–90
Fig. 6. A. The Karivhoh rock avalanche (V ~ 2 × 109 m3) obliterated >8 km of the Ardon River valley, Caucasus; da = detachment area; ra = rock-avalanche deposit. B. Breached
rockslide-rock avalanche dam (V ~ 109 m3), Kokomeren River, Tien Shan, Kyrgyzstan; sd = secondary breached debris dam (photos A and B courtesy of Alexander Strom).
C. Rockslide-derived (rd) boulder lag forcing step-pool morphology and local stream-power expenditure, Kyngyrga River, East Sayan Mountains, Russia.
Fig. 7. Influence of large rock-slope failures (grey boxes) on steepness index ks and its running mean (black line) of selected mountain river long profiles (grey lines) for an arbitrarily
fixed θ = 0.45 (see Eq. (1)). A. Swiss Alps; B. New Zealand Southern Alps; C. Nepal Himalaya; D. Tien Shan. Highest values of ks spatially coincide with former breach channels
through rockslide and rock-avalanche deposits. Modified after Korup (2006a), and Korup et al. (2006).
O. Korup et al. / Geomorphology 120 (2010) 77–90
83
Fig. 8. Changes to steepness index ks and concavity index θ of 37 river long profiles
affected by large bedrock failures in the European Alps, the Himalayas, the Tien Shan,
and the New Zealand Southern Alps. Removal of slope–area data points associated with
landslides on average decreases ks greater than one standard deviation (error bars),
while θ appears to be more robust. Modified after Korup (2006a).
respect to the long-term background rate. Such events have
historically produced landslide debris of up to 1010 m3 in volume
(Keefer, 1999). Also, there remains substantial uncertainty about
adequately modelling the extreme ends of the landslide magnitude–
frequency spectrum (Brardinoni and Church, 2004).
Thus, sediment delivery of landslide material to the drainage
network may be considered as a stochastic process in the short-term
(Benda and Dunne, 1997; Tucker, 2004). Integrating over longer
timescales is a way to overcome this problem. Using a simplistic
sediment continuity equation under steady-state conditions of longterm balanced rock uplift rate U and denudation rate D, average
sediment discharge qs from a mountain basin may be estimated as
qs = ðρr = ρs ÞA D SD
ð2Þ
where ρr and ρs are mean densities of bedrock and sediment,
respectively; and SD is the sediment delivery ratio.
Hovius et al. (1997) estimated qs from the western Southern Alps
of New Zealand, assuming that SD = 1, and that D was fully accounted
for by shallow aseismic landsliding in the montane zone recorded
between 1948 and 1986. They managed to upscale the sediment
production from individual landslides by using a power-law relationship between landslide frequency and magnitude (Czirók et al., 1997),
and estimated D by landsliding to be 9 ± 5 mm yr− 1 (Table 1).
Values of SD however vary in different geomorphic settings and
through time, such as for regional landslide episodes triggered by
earthquakes or rainstorms (Pain and Bowler, 1973; Pearce and
Watson, 1986; Owen et al., 1996; Peart et al., 2005). These episodes
produce significant spikes in long-term sediment production,
although the rate of diffusion of the resulting debris fluctuates
significantly, depending, among others, on climate, lithology, and
transport conditions. Thus care should be taken when assuming either
a general value for SD or a balance between landslide production and
sediment export rates. With increasing landslide size, deposit
residence time also becomes an issue for sediment delivery.
Specifically, many extremely large deposits have remained in
mountain landscapes for 104–106 yr. Not surprisingly, some of the
oldest dated landslide deposits are reported from arid mountain areas,
where erosion rates are low (Strasser and Schlunegger, 2005;
Phartiyal et al., 2005; García and Hérail, 2005). Nevertheless, the
control of landslide-affected area or mobilised volume on the deposit
residence time is largely unresolved.
Fig. 9. A. Upstream view of large landslide that blocked the Min Jiang River, Sichuan
Province, China, after the 1933 M = 7.5 Diexi earthquake (Chen et al., 1994). The
landslide formed a lake that persisted for four months and reached a maximum water
depth of 94 m before draining. The Min Jiang has re-incised through the dam. B. Smaller
rockfall dam (ld) that formed ~ 5 km upstream of the landslide in (A) during the same
earthquake. The Min Jiang has partially re-incised ~ 25 m through the rockfall deposit
(bch), but water (bw) and sediment are still impounded behind the dam. C. Upstream
view of sediment accumulation in the Min Jiang upstream of the rockfall dam in (B).
Note that the valley floor is completely covered by sediment (ag). Backwater
aggradation associated with the 1933 landslide dams extends > 15 km upstream
from the rockfall dam.
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O. Korup et al. / Geomorphology 120 (2010) 77–90
Fig. 10. Cartoons summarizing the ways in which landslide dams can influence fluvial processes and landforms on timescales of 100–104 yr. A. Downstream view (height
exaggerated); B. Along-profile view.
Large river-damming landslides cause temporary sediment storage either upstream (i.e. backwater aggradation), downstream (steep
debris fans from catastrophic outburst flooding), or within the
landslide-dam deposit (Fig. 10). In the Karakoram Himalayas,
individual infilled lake basins dammed by large rock avalanches
store up to 1010 m3 of sediment (Hewitt, 1998). Conversely,
catastrophic drainage of landslide-dammed lakes disperses up to
108 m3 of sediment during single events downstream (Table 2).
Erosional bedrock scour from such hyper-concentrated or debris
flows may lead to overestimates in fluvial incision rates.
Landslide-derived sediment pulses have considerable, yet rarely
quantified, implications for sediment-flux dependent models of river
incision (Sklar and Dietrich, 1998; Whipple and Tucker, 2002; Cui
et al., 2003), and consequences include changes to transport capacity
(Miller and Benda, 2000; Benda et al., 2003; Fig. 10), or landslideinduced channel avulsions (Korup, 2004).
Altogether, the contribution to the total catchment or regional
sediment flux determines the importance of landslides (Eaton et al.,
2003; Lavé and Burbank, 2004; Arsenault and Meigs, 2005). Kirchner
et al. (2001) demonstrated that the choice of timescale, which is often
a function of the chosen absolute dating method(s), for measuring
erosion rates in mountain basins may be crucial. Even when averaged
over longer timescales, the contributions of shallow landslides and
landslide-related extreme events remain at considerable levels when
compared to reported values for sediment yields from mountainous
terrain on 100–104 yr timescales (Tables 1 and 2).
3.5. Landslides in landscape evolution models
Several numerical models of landscape evolution have attempted to
include the process of either shallow or bedrock landslides, mainly
through the use of deterministic or rule-based algorithms. The net
effects of long-term hillslope sediment transport are often modelled by a
diffusive-type equation, in which sediment transport rate qs is a function
of diffusivity K, and slope gradient ∇z. To include the effect of shallow
landsliding Martin and Church (1997) proposed a surface lowering rate
∂z
2
= ½α + ω∇ z
∂t
ð3Þ
where α and ω are diffusivities for soil creep processes, and shallow
landslides, respectively; and ∇2z is a Laplacian expressing slope
O. Korup et al. / Geomorphology 120 (2010) 77–90
Table 1
Rates of estimated mean sediment production from landslides in selected mountain belts.
Region
Study area Observation Mean sediment Reference
(km2)
period (yr) production
(m3 km− 2 yr− 1)
Western
Southern Alps,
New Zealand
Coast Mountains,
B.C., Canada
Olympic
Peninsula, USA
Northwest
Nelson, New
Zealand
Cascade Mountains,
B.C., Canada
Saru River,
Hokkaido, Japan
Vancouver Island,
Canada
2670
39
1900–18,800
San Gabriel
Mountains, USA
Chugach-St Elias
Range, Alaska,
USA
West Vancouver,
B.C., Canada
Hawaii, Papua New
Guinea–Irian Jaya
Queen Charlotte
Islands, Canada
Central Southern
Alps, New
Zealand
60–1265
~ 60
20–550
19
30
480b
6.1–6.7
30
41–404
0.3–277
12–90
4–14,700
24
6–84
70–11,770
6.6–1182
200a
300–2100
38–48
30–53
92–2030
2
30
1000
517–560
30–60
7–555
n.a.
n.a.
>200
166.7.
40
100
10,000
2000
50d
c
Hovius et al.
(1997)
Brardinoni
et al. (2003a)
Brardinoni
et al. (2003a)
Pearce and
Watson (1986)
Brardinoni
et al. (2003a)
Shimizu (1998)
(Martin et al.,
2002; Brardinoni
et al., 2003a)
Lavé and
Burbank (2004)
Arsenault and
Meigs (2005)
Brardinoni
et al. (2003b)
Keefer (1999)
Martin et al.
(2002)
Whitehouse
(1983)
curvature. Roering et al. (1999) suggested a non-linear relationship
between transport rate and slope gradient on steep soil-mantled
hillslopes, based on the ratio of resisting and driving forces in hillslope
stability
K∇z
1−ðj∇z j =Sc Þ2
Table 2
Estimated mean sediment discharge from eroding individual landslides and landslide
dams, scaled by upstream catchment area.
Location
Observation
period (yr)
Mean sediment Reference
discharge
(m3 km− 2 yr− 1)
Rio Barrancas, Argentina
<0.01a
>120,000
Tsaoling rockslide, Ching-Shui
Creek, Taiwan
Mt Adams rock avalanche, New
Zealand
Pokhara rock avalanche-debris
flow, Seti Khola, Nepal
Falling Mountain rock
avalanche, New Zealand
27 rock avalanches, central
Southern Alps, New Zealand
Polnoon Burn rockslide,
New Zealand
Latamrang rockslide,
Marsyandi River, Nepal
Flims rockslide, Vorderrhein
River, Switzerland
2.5
111,100
3
<42,380b
~ 500
22,860
71
16,860
c
2000
2–3870
2050–4050
620–1240
5400
110
8450
28
Hermanns
et al. (2004)
Chen et al.
(2005)
Korup et al.
(2004)
Fort (1987)
Korup et al.
(2004)
Whitehouse
(1983)
Korup et al.
(2006)
Pratt-Sitaula
(pers. comm.)
This study
Averaging over longer timescales likely underestimate peak sediment pulses
subsequent to dam failure.
a
Sediment discharge estimated from single dam-break event.
b
Possibly includes upstream fluvial sediment.
c
Based on re-calculated 14C dates.
order relief, these continuum approaches do not capture the
mechanics of bedrock landslides, nor do they allow for discrete or
stochastic landslide events.
Densmore et al. (1998) used a modified Cullman limit-equilibrium
slope-stability model to allow for the probabilistic occurrence of
bedrock landslides, in which the probability of failure at any particular
node is given by
n.a. = not available.
a
Estimated for 200-yr earthquake recurrence interval.
b
Three rockslides only.
c
Modelled long-term production from earthquake-triggered landslides.
d
Late Holocene rock avalanches >106 m3 only.
qs =
85
ð4Þ
where Sc is the effective coefficient of friction, and assumed to fully
contain all properties of soil shear strength. Although sufficient for
modelling the long-term role of hillslope processes in reducing first-
pfail =
H
Hc
ð5Þ
where H is hillslope height; and Hc (≥H) is the maximum stable
hillslope height
Hc =
4C sin β cosϕ
ρg½1− cosðβ−ϕÞ
ð6Þ
where C is effective cohesion on the failure plane; β is surface slope; ϕ
is effective angle of friction on the failure plane; ρ is rock density; and
g is gravitational acceleration.
Fig. 11. Averaged rates of landslide sediment production in selected humid mountainous catchments from around the world show considerable scatter with regard to study area and
observation period.
86
O. Korup et al. / Geomorphology 120 (2010) 77–90
Other models (e.g. Champel et al., 2002; Dadson and Church, 2005)
use similar rules in which hillslope stability is mainly dependent on
topography, such as a combination of critical relief or slope values,
above which landsliding will always occur, hence inherently assuming relief-limitation by threshold hillslopes. We further note that the
Cullman criterion was initially developed for steep soil cliffs prone to
failure along tension cracks. Many large landslides however involve
deep-seated failure of rock slopes along a rotational failure plane.
Although arguably more applicable at the local scale, approaches such
as the (simplified) Bishop method or finite-element codes impose
substantial problems of upscaling for basin- or orogen-scale models.
Similarly, infinite-slope models for probabilistic or spatially
distributed modelling of the occurrence of shallow planar landslides
have so far seen exclusive use in GIS-based landslide susceptibility
and hazard studies (e.g. Wu and Sidle, 1995; Refice and Capolongo,
2002). Few attempts have been made to integrate such probabilistic
models of landslide occurrence into models of mountain range
evolution due to their inherent limitation to soil-mantled landscapes
(e.g. Benda and Dunne, 1997; Casadei et al., 2003).
In sum, by treating the bedrock river network as the basis for the
spatial distribution of relief in mountain belts, and by adopting a
stream power-type approach to network incision, many conceptual
models of orogenic topography assume—either explicitly or implicitly—
the occurrence of threshold hillslopes. The common alternatives to
adapting this concept to numerical landscape evolution models are to
• subsume landslides into an effective diffusivity;
• apply simple nonlinear diffusive or Culmann-type stability relations
to hillslopes; or
• take a probabilistic approach, which we feel has not been adequately
explored.
4. Open questions and future research needs
It should be clear that there is considerable scope for further work
in understanding the role of landslides in mountain range evolution.
We identify a number of open questions, which may serve as stepping
stones for future research directions:
Fig. 12. A. Orthophoto of scree-covered slopes (sc) in the eastern Southern Alps, New
Zealand. Fluvial incision and undercutting may promote rapid slope adjustment of noncohesive debris slopes, as proposed in the concept of threshold hillslopes (Fig. 1). Image
courtesy of Land Information New Zealand (I37 Lake Tekapo 2001/02). B. Headward
eroding gully systems (gl) dominated by frequent rill incision and shallow landsliding,
Landwasser valley, Swiss Alps, may be another mechanism of maintaining threshold
hillslope angles other than bedrock landsliding.
4.1. How widespread are threshold hillslopes and how can they be
objectively identified from topographic data?
We identify several important points in this regard. First, we see a
need for a standard methodology for objectively detecting and
quantifying threshold hillslopes in a given mountain belt. So far,
data have been compiled only for selected regions, such as the
northwestern Himalaya (Burbank, 2002) or the northwestern USA
(Montgomery, 2001). If mean slope or slope-angle histograms are
indeed used as measures for threshold hillslopes, they will mask
effects of variations in hillslope strength, materials, and processes
(Fig. 12), and the role of failure-prone or failure-resistant slope
segments such as steep inner gorges or slot canyons. In many
mountain belts, the preservation of fluvial strath terraces with ages of
up to 104 yr as indicators of rapid fluvial bedrock incision (Burbank
et al., 1996; Schaller et al., 2005) is somehow at odds with the
requirement of rapid slope adjustment by bedrock landsliding, which
would likely eliminate such evidence (Fig. 10A).
Second, the concept of threshold hillslopes makes no explicit
mention of the causes and triggers of landsliding, while simplistically
assuming hillslope angle to be the primary control on a static limit
equilibrium without any further dynamic loads. Although this may be
plausible for many slopes, it has not been sufficiently demonstrated,
whereas high-intensity rainstorms, snowmelt, groundwater conditions, or earthquakes may be equally or more important. Lin et al.
(2003), for instance, noted that landslides triggered by the 1999 ChiChi earthquake, Taiwan, occurred on slope angles of 40–50°, as
opposed to those triggered by preceding rainstorms, which had
occurred on slope angles of 20–30°.
Third, there may be the need to more rigorously formulate the
concept of threshold hillslopes to better explain, for instance, frequent
reactivations or precursory creep movement of large landslides
(Chigira et al., 2003); toe-thrust failures, where the failure plane of
the landslide extends beneath the channel bed; and long-term fluvial
transport limitation resulting from landslide damming.
Fourth, and most importantly, numerous landslides are known to
occur well below the few values cited for threshold hillslope angles.
Many large rock-slope failures have initiated on low-angle failure
planes away from major river channels (e.g. Philip and Ritz, 1999).
The fjords of western Norway, for instance, although not considered
tectonically active, form part of a mountain range subjected to
substantial rock uplift from postglacial isostatic rebound. Numerous
large postglacial rock-slope failures are known to have originated
from the steep fjord walls with detachment surfaces that are clearly
decoupled from fluvial and marine processes (Blikra et al., 2005).
Stress decrease through processes of unloading (and potentially slope
debuttressing) is the main cause for large bedrock landslides in this
area. In many cases, the failure surfaces of these landslides are planar,
thus maintaining slope angles without being influenced by base-level
changes. This implies that there is no ultimate need to uniquely
couple landsliding and its control on relief to fluvial bedrock incision
exclusively.
O. Korup et al. / Geomorphology 120 (2010) 77–90
4.2. Geomorphic hillslope–channel coupling and response times
Is the response of hillslopes to fluvial undercutting really
instantaneous as assumed by the threshold hillslope model? How
fast can signals of base-level change at the foot of hillslopes propagate
upslope to eventually reach the ridgeline, and hence maintain local
relief? What is the potential for upward-migrating hillslope knickpoints to be eliminated by subsequent larger slope failures?
Densmore et al. (1997) observed in laboratory experiments that
steep toe slopes, which are often interpreted as evidence for increase
in tectonic or fluvial process rates in high-relief landscapes, may
indeed be one stage of many in the normal hillslope evolution by
frequent landsliding. Mudd and Furbish (2005) investigated these
questions for soil-mantled hillslopes, but comparable analyses for
bedrock hillslopes have not been attempted.
One underlying assumption in most studies of mountain range
evolution is that the present morphology of the landscape, including
that of hillslopes and river channels is a faithful record of long-term
conditions of rock uplift, climate, and surface processes. In other
words, it is often believed that the response time of hillslopes and
river channels is short enough to convincingly preserve evidence of
tectonic or climatic forcing and fluvial bedrock incision as the ratelimiting process.
There is some debate as to whether, and at what scale, short-term
climatic perturbations over e.g. 104-yr timescales are recorded in
channel and hillslope geomorphology (Hsieh and Knuepfer, 2001).
Distinctive periods of Holocene alluviation, possibly associated with a
strengthened Himalayan monsoon, are likely causes for disequilibrium conditions over 104-yr timescales (Pratt-Sitaula et al., 2004; Pratt
et al., 2004). However, the problem remains of whether all of these
perturbations will be recorded in the landscape, and whether possible
recorders are interpreted correctly. Without a clear separation of
climatic from tectonic triggers of synchronous regional-scale slope
instability (Crozier et al., 1995), it remains speculative to infer
changes in palaeoclimatic or seismic regimes from landslide evidence
alone (Pratt-Sitaula et al., 2004; Bookhagen et al., 2005).
One possible explanation of these uncertainties is the occurrence
of time lags in the geomorphic response of channel and hillslope
morphology. For example, Miller et al. (2001) demonstrated that the
87
present morphologies of upland rivers in central Nevada are still
largely influenced by debris fans that accumulated during Late
Holocene periods of enhanced hillslope activity.
4.3. Landslide sediment production and delivery
What are the spatial and temporal variabilities in landslide
sediment input? At issue here is not just the stochastic nature of
sediment supply (Benda and Dunne, 1997), or the volume of sediment
input, but also the sediment calibre or grain size distribution. Both
volume and calibre are important in determining the likelihood of
protecting or armouring the bed, and the availability of tools for river
incision (Sklar and Dietrich, 2001, 2004).
What are the quantitative mismatches between landslide sediment supply and channel sediment transport, and the implications for
temporal changes in sediment storage? In other words, how
coincident are sediment supply to the channel network through
landsliding, and sediment removal from the network by fluvial
processes? This issue, which has been only briefly explored in orogens
like Taiwan (Hovius et al., 2000) and New Zealand (Pearce and
Watson, 1986), has large implications for the residence time of
sediment in a channel network and for temporal changes in sediment
storage within a mountain belt.
4.4. Effects of landslide location
What is the effect of landslide location on landscape form? Do
landslides cluster in parts of the landscape that allow their triggering
mechanisms to be elucidated, as hypothesised by Densmore and
Hovius (2000)? Can magnitude–frequency distributions of landslides
be ‘read’ as a record of landslide behaviour, or the relative importance
of large or small events, in a given mountain topography (Stark and
Hovius, 2001)? For instance, Iwahashi et al. (2003) observed a
Weibull distribution and a power-law distribution of slope angles, and
size frequency of active landslides in central Japan, respectively. They
suggested a slider-block-spring model as a possible mechanistic cause
to link landslide process and form.
Fig. 13. Approximation of relevant timescales of geomorphic feedback between landslides and river channels in tectonically active mountain belts (*assuming repeated valley
glaciations).
88
O. Korup et al. / Geomorphology 120 (2010) 77–90
5. Conclusions
The notion that fluvial bedrock incision in response to tectonic
uplift controls hillslope development has dominated recent models of
mountain range evolution. It is an appealing concept that aims to
integrate geomorphic hillslope–channel coupling, climate, and tectonic fluxes over a range of timescales. Yet the concept is partly at
odds with the recognition that landsliding as a frequent erosional
process in many active mountain belts occurs not exclusively in
response to fluvial slope undercutting. Earthquakes, rainstorms, and
exceeded internal stress thresholds cause and trigger large relieflowering bedrock landslides not influenced by river processes.
Moreover, these rock-slope failures mobilise sufficient material to
block drainage networks, cause significant valley-floor aggradation,
decrease in local relief, and stepped river profiles.
Such landslide-driven disturbances are mostly effective on 100–
104 yr timescales and do not necessarily conflict with those of
mountain range evolution (i.e. 106 yr; Fig. 13). However, they clearly
demonstrate the potential for a more dynamic equilibrium in fluvial
process rates and landforms. Hence, care should be taken when
analysing the present topography, landforms, and process regimes in
order to infer long-term rates of uplift and erosion. Quite conversely,
such medium-term disequilibrium effects fill in nicely between shortterm process studies and long-term models of mountain belt
evolution on <101 and >105 yr timescales, respectively.
Therefore, one way to reconcile the observations of landslides as
both active and passive geomorphic agents in mountain belt evolution
is to investigate and quantify in more detail the role of landscape
disequilibrium and the possibility of nonlinear relationships for upand downscaling of process rates between varying timescales
(Kirchner et al., 2001; Fig. 13). Recognising these and other shortcomings, we present a number of unsolved questions as possible
stepping stones for future research to better elucidate and quantify
the role of landslides in mountain range evolution.
Acknowledgements
We thank Guest Editors Mike Crozier and Thomas Glade for
inviting us to contribute to this Special Issue, Alexander Strom and
Johannes Weidinger for kindly providing photos to some of the
figures. The comments of Profs. Denys Brunsden, Jiun-Chuan Lin, and
Mauro Soldati helped to clarify aspects of an earlier manuscript.
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