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The use of surface monitoring data for the interpretation of landslide movement patterns
Geomorphology 66 (2005) 133 – 147 www.elsevier.com/locate/geomorph
The use of surface monitoring data for the interpretation of landslide movement patterns D.N. Petleya,*, F. Mantovanib, M.H. Bulmerc, A. Zannonid a University of Durham, Department of Geography, Durham DH1 3LE, UK Universita` di Ferrara, Dipartimento di Scienze della Terra, C.so Ercole I 8 d’Este 32, 44100 Ferrara, Italy c Joint Center for Earth Systems Technology, University of Maryland, 1000 Hilltop Circle, Baltimore, MD 21250, USA d CNR-IRPI, National Research Council, Research Institute for Hydrological and Geological Hazard Prevention, C.so Stati Uniti 4, 35127 Padova, Italy b
Received 1 July 2003; received in revised form 9 December 2003; accepted 15 September 2004 Available online 23 November 2004
Abstract The Tessina landslide is a large, seasonally active slope failure located on the southern slopes of Mt. Teverone, in the Alpago valley of NE Italy, consisting of a complex system that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, threatens two villages and is hence subject to detailed monitoring, with high quality data being collected using piezometers, inclinometers, extensometers, and through the use of a highly innovative, automated Electronic Distance Measurement (EDM) system, which surveys the location of a large number of reflector targets once every 6 h. These systems form the basis of a warning system that protects the villages, but they also provide a very valuable insight into the patterns of movement of the landslide. In this paper, analysis is presented of the movement of the landslide, concentrating on the EDM dataset, which provides a remarkable record of surface displacement patterns. It is proposed that four distinct movement patterns can be established, which correspond closely to independently defined morphological assessments of the landslide complex. Any given block of material transitions through the four phases of movement as it progresses down the landslide, with the style of movement being controlled primarily by the groundwater conditions. The analysis is augmented with modelling of the landslide, undertaken using the Itasca FLAC code. The modelling suggests that different landslide patterns are observed for different parts of the landslide, primarily as a result of variations in the groundwater conditions. The model suggests that when a movement event occurs, displacements occur initially at the toe of the landslide, then retrogress upslope. D 2004 Elsevier B.V. All rigths reserved. Keywords: Landslide; Monitoring; Deformation; Modelling; Strain; Movement
* Corresponding author. Tel.: +44 191 374 2099; fax: +44 191 374 2456. E-mail address: [email protected] (D.N. Petley). 0169-555X/$ - see front matter D 2004 Elsevier B.V. All rigths reserved. doi:10.1016/j.geomorph.2004.09.011
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1. Introduction The investigation and interpretation of the patterns of movement associated with landslides have been undertaken using a wide range of techniques, including the use of survey markers; extensometers; inclinometers; analogue and digital photogrammetry, both terrestrial and aerial; and synthetic aperture radar interferometry (InSAR). These techniques have allowed substantial improvements in the understanding of landslide movement patterns in recent years. However, in general, these techniques suffer from serious shortcomings in terms of spatial or temporal resolution. Many techniques, such as extensometers and inclinometers, are able to provide high quality data pertaining to movement patterns for very small areas of the landslide, albeit with a potentially very high level of temporal resolution. Although these techniques provide abundant datasets on movement styles, they are difficult to interpret in terms of the overall evolution of movement across the whole of a landslide, especially where the system is large and/or complex. Photogrammetry and InSAR on the other hand can provide excellent spatial coverage but are generally limited in terms of the temporal resolution, meaning that large movement events are rarely captured in detail using these techniques. As a result, the understanding of the patterns of movement in large landslides, and the mechanisms and processes through which they occur, remains surprisingly poor. At the Tessina landslide in northern Italy, a solution to this problem has been implemented. This utilises a series of electronic distance measurement (EDM) reflectors located across much of the landslide, providing high levels of spatial resolution in terms of both area covered and movements recorded. High spatial resolutions are achieved through the use of an automatic laser EDM system that seeks and records the location of each point at six hourly intervals. Thus, the system is able to provide very detailed information about the evolution of movement patterns across the landslide. This paper examines in detail the nature of the surface movement pattern at the Tessina landslide through an analysis of this very detailed monitoring record collected over a six year period, and attempts to link movement style with the geomorphological setting and landslide process occurring in this area. A range of
movement styles have been observed. These are further investigated through the application of the Itasca FLAC finite difference modelling package to investigate the causes of the movement types. 2. Analysing landslide movement patterns Two main approaches are commonly adopted for the description of the movement patterns of landslides based upon monitoring data. The first concentrates on the analysis of movement velocities and cumulative displacements to try to classify the styles of movement that a landslide displays. For example, Allison and Brunsden (1990) used a comprehensive monitoring programme to examine the mechanisms of movement in coastal mudslides, proposing that four main types of movement can be observed. These are: 1. Small, multiple movements which appear to display stick-slip characteristics. Here the landslide appears to undergo repeated small movements closely spaced in time, interspersed by periods in which no movement occurs. Generally, the displacements observed were extremely small. 2. Gradual or graded slip, in which a single movement event was observed to occur at low strain rates over long periods (typically in the order of tens of centimeters over a 24-h period). 3. Surge movements, characterised by rapid displacements over short periods, typically in the order of metres over 20 min. 4. Occasional small random displacements that reflect slight internal adjustments within the landslide mass, and shrinkage/swelling associated with wetting and drying cycles. Such investigations provide useful information about the styles and patterns of movement, especially where they are supplemented by measurement of pore pressure through the landslide system. However, such studies are limited by the relatively low aerial coverage of the instruments. Indeed, Allison and Brunsden (1990) noted that (p. 309): it has to be recognized that recordings were taken at a limited number of points on one landslide. A
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more comprehensive spatial sampling framework would further elucidate the interrelationships within an individual system. The alternative approach that can be used to analyse landslide monitoring data to investigate movement mechanisms concentrates upon the nature of behaviour during periods of acceleration. It has long been recognized that it might be possible to analyse basal processes through surface displacement records (Terzaghi, 1950 for example). Perhaps the best known manifestation of this is the so-called dSaitoT method for predicting the time of failure of a landslide, originally proposed by Saito (1965, 1969) and developed by Fukozono (1990). In this technique, the displacement data during an accelerating phase are plotted in K–t space, where K=velocity 1 and t=time (Petley et al., 2002). Saito (1965) noted that during a phase of acceleration that leads to catastrophic failure, this graph has a linear form, with the point of failure being extrapolated to be the time when K=l. This linearity appears to be a fundamental character of brittle materials prior to catastrophic failure (Voight, 1988, 1989) that is associated with subcritical crack growth. A simple explanation contends that the exponential acceleration in deformation rate occurs as a result of crack growth that increases the stress on adjacent areas of rock, triggering accelerating failure (Main, 1999). However, Reches and Lockner (1994) provided an alternative explanation based upon more subtle mechanisms. They suggested that once the critical crack density has been reached, adjacent microcracks interact, enhancing dilation within each crack. This creates a process zone that propagates unstably into the adjacent intact rock. During continued growth of the process zone, the central portion yields by shear, forming a shear surface that subsequently propagates into the undeformed rock. At present, it is not possible to determine which of these mechanisms dominates, although it is possible that this is material dependent. Considerable efforts have been made to develop further the Saito method. These are reviewed in detail by Federico et al. (2002). In general, these have been based upon attempts to develop mathematical models to account for accelerating phases of creep (see
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Bhandari, 1988 for example). However, Federico et al. (2002) note that The . . .methods are empirical and phenomenological and do not take into account the soil mechanical behaviour and its influence on the progression of the landslideT (p. 177). Clearly, therefore, most attempts to examine this phenomenon to date have essentially been academic exercises. Fell et al. (2000) made a similar observation, noting that it would be foolhardy at this stage to put too much reliance on predictions of the time of failure while the mechanisms dominating the accelerating phase of movement are uncertain. However, Petley et al. (2002) attempted to investigate in detail this accelerating behaviour and to determine whether there is an identifiable physical mechanism that explains the Saito method. Based on the analysis of a large number of landslide movement records, they noted that linearity in K–t space only occurs where the deforming materials are capable of undergoing brittle failure mechanisms. Where the deformation process is dominated by sliding on existing shear surfaces or as a result of ductile deformation, the physical explanation does not appear to apply. This in agreement of a mathematical analysis of the effects of crack nucleation and growth (Kilburn and Petley, 2003), which demonstrated that deformation without crack growth will not normally be characterised by linearity in K–t space. Petley et al. (2002) analysed landslide movement records for reactivations of existing landslide systems and for movements in ductile materials, all of which showed an asymptotic trend in K–t space, with the rate of movement increasing to a constant velocity value. Detailed inclinometer records were used to show on the other hand that linearity is always associated with crack growth and indeed that the initiation of a linear trend at any point in the landslide mass can be associated with the state of development of the shear plane in that area (Petley et al., 2002). Finally, Petley and Petley (in press) re-examined the Vaiont failure in light of these observations, noting that the analysis of the accelerating phases of movement supports the proposition of Petley (1996) and Petley and Allison (1997) that there is a change in material behaviour from ductile to brittle controlled the final failure event.
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Through these developments, the Saito method appears to have the potential for providing a mechanism that allows slope deformation processes to be constrained with more confidence, and for developing a landslide warning system that might be applicable to both ground based instruments and the outputs from an InSAR analysis. However, it is clear that further research is needed. For example, there is a need to test the methodology on a wider range of landslides to investigate whether it has uniform applicability, especially where movements or the landslide components themselves have a complex form. Additionally, there is a need to determine how the results of monitoring from a range of locations within a landslide mass vary both spatially and temporally, and in terms of the range of movement types that can be observed.
3. The Tessina landslide The Tessina landslide is located on the southern slopes of Mount Teverone, in the Alpago valley in north-east Italy (Fig. 1). It consists of a large, highly active, complex gravitational failure that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, now threatens
two villages and is hence subject to detailed monitoring. As a result, a large volume of movement data has been collected. The occurrence of the landslide is closely related to the geological structure of the flanks of Mount Teverone. The area affected by the landslide is part of the northern flank of the small Alpago syncline, which has a NW–SE orientation. As a result, the Eocene Flysch deposits are characterised by nearly vertical strata that are cut by the Belluno overthrust (Fig. 2). The thrust has emplaced porous, fractured carbonate rocks over the Flysch deposits. These carbonates form the main body of Mount Teverone, with the Flysch forming the lower slopes on the southern side. The Flysch consists of a rhythmic sequence of marlstones, clay shales and calcarenite layers up to 1 m thick. The formation is highly fissured due to the tectonic disturbance, and hence is permeable. Towards the lower slopes, small amounts of Quaternary deposits are found. These consist primarily of colluvium and of moraines from the Piave valley glacier and other local glaciers. The presence of a large, high altitude carbonate mass adjacent to the steeply dipping Flysch deposits creates ideal conditions for the development of slope instability. A large head of water within the carbonate rocks means that there is a flow of water through the
Fig. 1. The location of the Tessina Landslide in northern Italy.
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Fig. 2. Indicative geological cross section showing the setting of the Tessina landslide based upon Mantovani et al. (2000).
slope that induces artesian conditions on the flanks of the mountain. These high water pressures are probably the major cause of instability at this site (Mantovani et al., 2000). The landslide itself extends from an elevation of 1200 m at the crown to 610 m a.s.l. at the toe of the mudflow. Its total track length is approximately 3 km from the crown to the toe of the mudflow, and its maximum width is about 500 m, in the rear scar area, with a maximum depth of about 50 m. The landslide represents a complex failure that consists of a rotational slide in its upper portions that transitions into a mudflow lower down. Mantovani et al. (2000) divided the failure into four main morphodynamic zones (Fig. 3): (i) the ddetaching zoneT (1200–1000 m a.s.l.), which consists of a highly fractured crown beyond the main scarp and the active scarp itself; (ii) the dupper accumulation zoneT (1000 to 975 m a.s.l.), identified in a sub-horizontal embayment, 500 m across and 350 m downslope, within which newly collapsed material can be accumulated before being eventually transported onto a secondary scarp at about 975 m a.s.l.; (iii) the dconnection canal zoneT (975 to 900 m a.s.l.), corresponding to the steep scarp (ca. 308 slope) immediately below the upper accumulation zone which funnels landslide material with the highest acceleration into the main valley below; (iv) the dlower accumulation zoneT (below 900 m a.s.l.) in which the landslide material, remo-
bilised as a mudflow, fills the existing valley. The latter now extends for about 1.5 km from 900 to 610 m a.s.l., and threatens the villages of Funes and Lamosano. The landslide currently involves a source area with a volume of about 500,000 m3 of material, and has a total potential volume of about 7 million m3. Movement rates vary greatly, with periods of almost no movement being interspersed by frequent rapid movements, triggered by high groundwater levels. The maximum measured velocities were recorded uphill of Lamosano in May 1992, with displacements of the main flow reaching 70 to 100 m day 1.
4. Monitoring of the Tessina landslide The Tessina landslide is intensively monitored for both scientific and civil defence purposes. The monitoring system is described in detail by Mantovani et al. (2000). Briefly, the connection canal zone and the lower accumulation zone are both monitored using an automatic alarm system, that consists of poles hanging vertically above the debris, suspended from wires. Fitted within the poles are tilt meters. In the event of a large surge of debris, the poles will be displaced, triggering an automatic alarm. In addition, two echometers are situated on the same wires, measuring the height of the debris in order to trigger an alarm should movement occur.
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Fig. 3. (a) A morphodynamic zonation of the Tessina landslide, based upon Mantovani et al. (2000); (b) Corresponding airphoto of the detaching and upper accumulation zone with the benchmarks identified.
Two multiple wire extensometer units have been located in the upper section of the landslide, with a movement resolution of 1 mm. Over much of the detaching and upper accumulation zones, 20 EDM targets have been emplaced. Every six hours, the EDM unit, which is located on a stable piece of terrain adjacent to the landslide, automatically determines the location of these targets. Inclinometers have been located within the landslide mass and around the crown to determine the depth of movement. Finally, ground water levels are monitored with a network of piezometers.
5. Patterns of movement of the Tessina landslide We have analysed the Tessina movement records during the period 1997–2002, primarily using the
EDM-based benchmark system as a data source. The accuracy of this type of surveying technique is high (mm accuracy), yielding much better basic surface movement data than the extensometers or inclinometers. The major problems are associated with failures and downtime of the EDM equipment, which result in frequent gaps in the data, and the potential for spurious movements associated with rotations of the poles upon which the targets are located, although these are rarely observed in reality. Even with these shortcomings, the datasets are excellent and allow a very high level of understanding of surface movements. Analysis of the movement data suggests that the movement patterns within the landslide fall into four distinct groups (Fig. 4) both in terms of the magnitude of the total displacement and the pattern of movement observed. These patterns are as follows:
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Fig. 4. Graph showing displacement against time for four representative monitoring points. Each shows a distinctly different movement pattern. Benchmarks 301 and 307 are plotted against the right hand axis; benchmarks 401 and 9 are plotted against the left hand axis.
Type I.
Type II.
Very slow movements, typically with rates in the order of less than 1 mm day 1 (e.g. Benchmark 307 in Fig. 4). This benchmark is located 20 m back from the edge of the scarp on a rocky surface composed of Flysch. These movements tend to occur in areas above the crown and close to, but not situated on, the landslide flanks. Movement patterns tend to consist of slow creep, but with increases in velocity associated with the wetter winter months. Low velocity movements at rates in the order of 2–3 mm day 1, but with the rate of movement being highly variable. A typical movement pattern is shown by benchmark 301 (Fig. 4), but similar movement patterns are seen for benchmarks across the detaching zone. Benchmark 301 is located on a slope with a gradient of 30–358, characterised by ground cracks. Faster movements generally occur during the months
when groundwater levels are high. This pattern of movement is typical of blocks that have undergone detachment from the crown of the landslide. Type III. Movements at rates of in the order of 10 mm day 1, such as seen for benchmark 9 (Fig. 4). This benchmark is located on the lower part of the principal scarp of the landslide which is 30 m high. The flysch that outcrops in the scarp is weathered in the upper part compared with the lower where it is intact. Creep occurs more-orless continuously, rates undergoing only relatively small seasonal fluctuations. This type of movement is typically seen at other benchmarks in the main scarp area within 50 m of benchmark 9. Type IV. Episodic, very rapid movements, with peak rates in the order of 1–2 m day 1 or greater (benchmark 401 in Fig. 4, for example). This benchmark is located inside the
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accumulation zone between two drainage channels. In between movement events, the system is essentially static. Movement is initiated rapidly, and also terminates abruptly. This type of movement occurs in the connection canal and lower accumulation zones. There is a clear linkage between the movement patterns and the morphodynamic setting of the benchmarks, as described by Mantovani et al. (2000). Type I movement occurs within the ddetaching zoneT located above the main landslide crown in the area of tension, or is located on areas of tension on the flanks of the landslide. In both cases, the movement occurs in materials that are undergoing disruption as retrogression of the landslide crown occurs. Type II movement also occurs within the detaching zone, but here it is associated with material that has become fully detached and incorporated into the landslide. Type III movement is associated with blocks moving into the upper accumulation zone, where the blocks are rapidly disaggregating into loose material. Finally, Type IV movement occurs within the connection canal zone and the lower accumulation zone in which the landslide material moves as a remobilised mudflow. All of the movement patterns show seasonality. Mantovani et al. (2000) demonstrated that in general, movements of the Tessina landslide were related to the groundwater level and not to short-term precipitation inputs. However, simple reliable threshold groundwater levels have not yet been identified, probably reflecting the complex and changing hydrogeology of this large landslide complex. Logically, as a given block moves downslope, the displacement should transition through the four movement patterns (Fig. 5). The model suggests that as retrogression of the landslide occurs, a benchmark should, over a period of a number of years, move through the different types of movement. Initially the benchmark will be stable. As the crown of the landslide retrogresses, it will define a series of blocks above the scarp that will begin to fail into the overall complex. Thus, the benchmark should show Type I movement, progressively transitioning to Type II, in which most deformation occurs during periods of high groundwater level when the effective normal stresses are minimised. Movement rates are slow because
Fig. 5. Conceptual graph illustrating movement patterns as a point transitions from Type I to Type IV movement.
deformation requires the formation of a distinct shear plane, either through the generation of a discontinuity or through the mobilisation of existing fractures. In time, the fracture will be fully developed and the materials will be at residual strength. Now the resistance of the block to movement is lower, leading to the development of Type III movement. The block is fully incorporated into the landslide complex, and is undergoes considerable deformation and disturbance. At this point, one of two processes can occur. The block can either slowly disaggregate and deform, continuing with Type III movement. Alternatively, complete disaggregation can occur and the material from the block can be incorporated into an earthflow or mudflow, at which point it will transition into Type IV movement patterns. Either way, the benchmark will eventually enter the canal zone and will thus show Type IV movement patterns. There are some indications that these transitions can be seen in the data in Fig. 4. Notably, the movement pattern of benchmark 307 has become more rapid and seasonal towards the end of the sequence as the block detaches from the crown area. More striking is the increase in movement rate of benchmark 301 from relatively small movements in 1998–1999 to large, highly seasonal movements in 2001–2002. Thus, through time, the movement pattern is increasingly tending towards those of Type IV.
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Fig. 6. Type IV movement patterns expressed in K–t space: (a) Benchmark 605, 2000 movement event; (b) Benchmark 402, 1998 movement event.
Fig. 7. The geometry of the simple FLAC simulation of the upper zone of the landslide. The vertical slope simulates the effects of the limestone. The contours indicate the initial groundwater level before precipitation was initiated.
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The type of movement pattern is defined by the morphology of the block in motion, its geomorphological setting and the properties of the basal (deforming) materials (Petley et al., 2002). The Type IV movement pattern could be explained either by the effects of rapid loss of shear strength, perhaps through rapid increases in water content at the basal zone, causing the sediments to transition to a water content above the plastic limit, or through the effects of undrained loading. The K–t technique described by Petley et al. (2002) is instructive in this regard. Mantovani et al. (2000) noted that the September 1998 movement event showed a progressive increase in the rate of deformation for a few days prior to the
failure. Plotting these data and those for other benchmarks that show Type IV movements yields a generally nonlinear asymptotic trend (Fig. 6). This is as would be expected for the acceleration of movement in a previously deformed material (Petley et al., 2002).
6. Modelling movement of the Tessina landslide One potential explanation for the change in movement style downslope is the variation in geotechnical properties. Surprisingly, however, a systematic analysis of the variation of angle of internal friction and cohesion, undertaken by Wilson et al.
Fig. 8. (a) Groundwater contours for the FLAC simulation at the time of failure. (b) Horizontal displacements for the failure in FLAC. It is clear that in this case, the failure consists of a shallow, translational movement.
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(2000) using both in situ (shear vane) and laboratory (shear box) tests, failed to show any consistent pattern of change of material properties that could account for this behaviour. It is therefore more likely that this change in behaviour is associated with changing groundwater and stress conditions in the landslide itself. To examine this, we have analysed the movement patterns observed for the Tessina landslide using a simplified model within the Itasca FLAC 4.0 software package. Fast Lagrangian Analysis of Continua (FLAC) is a sophisticated twodimensional continuum code for modelling soil, rock and structural behaviour. The code can model large displacements and strains, and both linear and nonlinear material behaviour, even if yield or failure occurs over a large area or if total collapse occurs.
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Modelling of coupled groundwater-deformation problems can be accommodated. In addition, it is able to assess factors of safety for slope problems. A simplified model of the detaching and upper accumulation zone of the landslide has been established within FLAC to determine the nature of movements that occur on different parts of the slope as a result of groundwater changes. This model was designed to examine the patterns of movement within material that is detached from the in situ rock mass— i.e. within the upper accumulation zone. This part of the landslide is simulated with a linear slope in a strong sandstone, representing the flysch (Fig. 7). At the head of the slope, the large limestone massif is represented by a large vertical cliff. The slope itself is mantled in landslide material, with geotechnical
Fig. 9. Strain rate (velocity)–time plots for four locations on the surface of the simulated slope. Note the different y-axis scales. (a) Point 1, located above the crown of the main landslide; (b) Point 2, just below the crown of the mobile mass; (c) Point 3 in the midst of the mobile mass; and (d) Point 4 at the toe. Note that movement started at the toe of the slide and retrogressed up slope. The highest velocities were seen in the middle of the mobile mass.
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properties that represent those measured for the site (Wilson et al., 2000). The slope geometry closely represents that of the actual site in terms of slope angle, height and length. A low groundwater regime was applied initially (Fig. 7) by setting up hydrostatic conditions based on a groundwater table 100 m below the surface at the rear of the limestone massif. The system was allowed to equilibrate and the minimum factor of safety of 1.45 was calculated, with the least stable part of the slope being the lower part of the superficial deposits mantling the slope. Thereafter, the pore pressures in the slope were increased by raising the water level in the limestone to the surface. This was undertaken by applying a precipitation input to the surface of the model, representing 20 mm h 1. As this was undertaken, the displacement history of four points on the slope was monitored, allowing graphs of displacement and velocity against time to be produced. Pore pressures 5 m below ground level were monitored for three of these points. The model was configured to
allow interaction between the pore pressure regime and the material deformation so that, for example, dilation in the materials can cause a reduction in pore pressure that might increase resistance to shear. The equilibrated groundwater regime at the end of the model run, when failure of the slope had occurred, is shown in Fig. 8a. Failure was initiated as a superficial translational movement with a shear surface at about 5-m depth (Fig. 8b). This simulates well the reactivation of movement in the landslide deposits. Ground water elevation through precipitation was initiated at model step 50,000. Displacements in the landslide materials were first noted at about model step 53,000, with movement being initiated near to the toe of the slope (Fig. 9d). It is clear from Fig. 9 that the failure retrogressed upslope, movement in the upper toe area started at about step 57,000 (Fig. 9c); in the midslope area at about step 60,000 (Fig. 9b); and limited movements started in the crown area at around step 64,000 (Fig. 9a).
Fig. 10. The data from this figure plotted in K–t space. These plots highlight the asymptotic form of the acceleration for each point and the different times of the initiation of movement at each point, starting at the toe, and retrogressing upslope. (a) Point 1; (b) Point 2; (c) Point 3; and (d) Point 4.
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These points of initiation are more clearly seen in the K–t plots (Fig. 10). Note that in all cases, a very small increase in movement can be observed when the precipitation was initiated, presumably as a result of creep within the wetted soil materials. In all cases, this creep occurs at a constant velocity until failure is initiated. Note also that the creep occurs at the greatest rate for the upper toe (Fig. 10d), and at the slowest rate for the area above the crown of the landslide (Fig. 10a). The point of acceleration is clearly noted in all cases, but interestingly for the area above the crown, the acceleration was preceded by a short period of slight deceleration. The plots all show that, as proposed by Petley et al. (2002), and in agreement with the monitoring data, this non-brittle failure is characterised by an asymptotic trend in K–t space. Thus, the simulation appears to agree with the observed behavior for the Tessina landslide. In addition, the acceleration and K–t plots seem to suggest that different movement patterns are observed for different parts of the landslide. Based upon these results, it would appear that changing movement patterns might well be associated with varying pore pressure conditions within the different parts of the landslide complex. In Fig. 11, the pore pressure conditions 5 m below the surface for three of the points (1, 2 and 4) are plotted alongside the respective surface velocity–time curve for that point. The results are interesting. First it is notable that movement does not initiate at the same pore pressure for all three points, even though the model uses a simple linear slope. Second, the pore pressure response is very different for the three points. For point 1, located above the crown of the landslide, increases in pore pressure do not occur until about step 62,000 (Fig. 11a), thereupon pore pressure rises in a linear fashion. The movement of this point does not occur until considerably later, and indeed the rate of movement remains low in comparison with other points. It is likely that this simple pore pressure and movement response is associated with the location of the point, which is above the landslide crown. Thus, the behaviour of the system is somewhat different. Point 2 on the other hand is rather more complex (Fig. 11b). Here pore pressure response is seen considerably earlier, but the pore pressure and movement of the point are initiated almost simultaneously. Interestingly, as the movement rate increases
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the pore pressure reaches a peak, which is maintained for approx. 3000 steps, after which the pore pressures decline before stabilising at ca. 60% of the peak value. Clearly here we are seeing the effects of the interaction between the material deformation processes and the pore pressure, with dilation postfailure allowing reductions in pore pressure to occur.
Fig. 11. Pore pressure variations for three of the points, plotted with the respective velocity-time curve. (a) Point 1; (b) Point 2; (c) Point 4.
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It is notable, however, that even though pore pressure is reducing the movement rate, it appears to be unaffected. At the toe, the displacements and the pore pressure response occur much earlier (Fig. 11c). Even though the pore pressure increases rapidly before eventually settling to an approximately constant value, the movement is initiated considerably later (although much earlier than upslope). Once movement has been initiated, the rate of increase is considerably slower than that of further upslope. Thus, the modelling suggests that the different patterns of movement observed in the Tessina landslide maybe primarily controlled by variations in the pore pressure conditions within the slope and by the interaction between these pore pressures and the deformation of the materials. Even though the model used just a simple, linear slope, considerable differences in strain rate were seen. Superimposed on top of this is the likely impact of changes in the cohesion and effective angle of internal friction associated with the disintegration of the landslide materials, which were not simulated here.
7. Conclusions The EDM monitoring of the Tessina landslide presents a unique opportunity for the assessment of the surface movement patterns of a large complex system. The results of the analysis suggest that four types of movement can be recognized, with any particular block of unfailed material transitioning through them as movement downslope occurs. Detailed modelling of the slope system suggests that the transition from one movement type to the next is associated primarily not with changes in material properties but instead with pore pressure conditions and the inter-relationships between pore pressures and the deformation of the materials in question. As Petley et al. (2002) proposed, analyses of movement patterns can be powerfully undertaken using the K–t technique. Both the monitoring and the modelling data for the landslide confirm the thesis of Petley et al. (2002) that failures that do not require brittle failure mechanisms will show an asymptotic trend in K–t space.
This analysis of the surface monitoring data for the Tessina landslide has demonstrated that the movement patterns of complex landslides are themselves complex, but that systematic analysis using, for example, the K–t tool can yield important and insightful outputs.
References Allison, R.J., Brunsden, D., 1990. Some mudslide movement patterns. Earth Surface Processes and Landforms 15 (4), 297 – 311. Bhandari, R.K., 1988. Some practical lessons in the investigation and field monitoring of landslides. Proceedings of the 5th International Symposium on Landslides, Lausanne vol. 3, pp. 1435 – 1457. Federico, A., Fidelibus, C., Interno, G., 2002. The prediction of landslide time to failure — a state of the art.Proceedings of the 3rd International Conference on Landslides, slope Stabbility and the Saftey of Infrastructures, Singapore, pp. 167 – 180. Fell, R., Hungr, O., Leroueil, S., Riemer, W., 2000. Geotechnical engineering of the stability of natural slopes, and cuts and fills in soil. Proceedings of the Geoengineering Conference, Melborne, pp. 21 – 120. Fukozono, T., 1990. Recent studies on time prediction of slope failure. Landslide News 4, 9 – 12. Kilburn, C.J., Petley, D.N., 2003. Forecasting giant, catastrophic slope collapse: lessons from Vajont, Northern Italy. Geomorphology 54 (1–2), 21 – 32. Main, I.G., 1999. Applicability to time-to-failure analysis to accelerated strain before earthquakes and volcanic eruptions. Geophysical Journal International 139 (3), 1 – 6. Mantovani, F., Pasuto, A., Silvano, S., Zannoni, A., 2000. Collecting data to define future hazard scenarios of the Tessina landslide. ITC Journal 1, 33 – 40. Petley, D.N., 1996. The mechanics and landforms of deep-seated landslides. In: Brooks, S., Anderson, M. (Eds.), Advances in Hillslope Processes, vol. 2. Wiley, Chichester, pp. 823 – 835. Petley, D.N., Allison, R.J., 1997. The mechanics of deepseated landslides. Earth Surface Processes and Landforms 22, 747 – 758. Petley, D.N., Petley, D.J., 2005. On the initiation of large rockslides: perspectives from a new analysis of the Vaiont movement record. In: Evans, S. (Ed.), Large Rock Slope Failures. Balkema, Rotterdam. in press, Paper accepted, NATO Science Series. Petley, D.N., Bulmer, M.H.K., Murphy, W., 2002. Patterns of movement in rotational and translational landslides. Geology 30 (8), 719 – 722. Reches, Z., Lockner, D.A., 1994. Nucleation and growth of faults in brittle rocks. Journal of Geophysical Research, B, Solid Earth and Planets 99 (9), 18,159 – 18,174. Saito, M., 1965. Forecasting the time of occurrence of a slope failure. Proceedings of the 6th International Conference on Soil Mechanics and Foundation Engineering, vol. 2, pp. 537 – 539.
D.N. Petley et al. / Geomorphology 66 (2005) 133–147 Saito, M., 1969. Forecasting time of slope failure by Tertiary creep. Proceedings of the 7th International Conference on Soil Mechanics and Foundation Engineering, vol. 2, pp. 677 – 683. Terzaghi, K., 1950. Mechanism of landslides. In: Paige, S. (Ed.), Application of Geology to Engineering Practice, Geological Society of America, Berkey Volume, pp. 83 – 123. Voight, B., 1988. A relation to describe rate-dependent material failure. Science 243, 200 – 203.
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Voight, B., 1989. A method for prediction of volcanic eruptions. Nature 332, 125 – 130. Wilson, A., Murphy, W., Petley, D.N., 2000. Some observations on the geotechnics and movement of large volume earth flows in Alpine Regions. In: Bromhead, E., Dixon, N., Ibsen, M.-L. (Eds.), Landslides in Research, Theory and Practice. Thomas Telford, London, pp. 1581 – 1586.
The use of surface monitoring data for the interpretation of landslide movement patterns D.N. Petleya,*, F. Mantovanib, M.H. Bulmerc, A. Zannonid a University of Durham, Department of Geography, Durham DH1 3LE, UK Universita` di Ferrara, Dipartimento di Scienze della Terra, C.so Ercole I 8 d’Este 32, 44100 Ferrara, Italy c Joint Center for Earth Systems Technology, University of Maryland, 1000 Hilltop Circle, Baltimore, MD 21250, USA d CNR-IRPI, National Research Council, Research Institute for Hydrological and Geological Hazard Prevention, C.so Stati Uniti 4, 35127 Padova, Italy b
Received 1 July 2003; received in revised form 9 December 2003; accepted 15 September 2004 Available online 23 November 2004
Abstract The Tessina landslide is a large, seasonally active slope failure located on the southern slopes of Mt. Teverone, in the Alpago valley of NE Italy, consisting of a complex system that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, threatens two villages and is hence subject to detailed monitoring, with high quality data being collected using piezometers, inclinometers, extensometers, and through the use of a highly innovative, automated Electronic Distance Measurement (EDM) system, which surveys the location of a large number of reflector targets once every 6 h. These systems form the basis of a warning system that protects the villages, but they also provide a very valuable insight into the patterns of movement of the landslide. In this paper, analysis is presented of the movement of the landslide, concentrating on the EDM dataset, which provides a remarkable record of surface displacement patterns. It is proposed that four distinct movement patterns can be established, which correspond closely to independently defined morphological assessments of the landslide complex. Any given block of material transitions through the four phases of movement as it progresses down the landslide, with the style of movement being controlled primarily by the groundwater conditions. The analysis is augmented with modelling of the landslide, undertaken using the Itasca FLAC code. The modelling suggests that different landslide patterns are observed for different parts of the landslide, primarily as a result of variations in the groundwater conditions. The model suggests that when a movement event occurs, displacements occur initially at the toe of the landslide, then retrogress upslope. D 2004 Elsevier B.V. All rigths reserved. Keywords: Landslide; Monitoring; Deformation; Modelling; Strain; Movement
* Corresponding author. Tel.: +44 191 374 2099; fax: +44 191 374 2456. E-mail address: [email protected] (D.N. Petley). 0169-555X/$ - see front matter D 2004 Elsevier B.V. All rigths reserved. doi:10.1016/j.geomorph.2004.09.011
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1. Introduction The investigation and interpretation of the patterns of movement associated with landslides have been undertaken using a wide range of techniques, including the use of survey markers; extensometers; inclinometers; analogue and digital photogrammetry, both terrestrial and aerial; and synthetic aperture radar interferometry (InSAR). These techniques have allowed substantial improvements in the understanding of landslide movement patterns in recent years. However, in general, these techniques suffer from serious shortcomings in terms of spatial or temporal resolution. Many techniques, such as extensometers and inclinometers, are able to provide high quality data pertaining to movement patterns for very small areas of the landslide, albeit with a potentially very high level of temporal resolution. Although these techniques provide abundant datasets on movement styles, they are difficult to interpret in terms of the overall evolution of movement across the whole of a landslide, especially where the system is large and/or complex. Photogrammetry and InSAR on the other hand can provide excellent spatial coverage but are generally limited in terms of the temporal resolution, meaning that large movement events are rarely captured in detail using these techniques. As a result, the understanding of the patterns of movement in large landslides, and the mechanisms and processes through which they occur, remains surprisingly poor. At the Tessina landslide in northern Italy, a solution to this problem has been implemented. This utilises a series of electronic distance measurement (EDM) reflectors located across much of the landslide, providing high levels of spatial resolution in terms of both area covered and movements recorded. High spatial resolutions are achieved through the use of an automatic laser EDM system that seeks and records the location of each point at six hourly intervals. Thus, the system is able to provide very detailed information about the evolution of movement patterns across the landslide. This paper examines in detail the nature of the surface movement pattern at the Tessina landslide through an analysis of this very detailed monitoring record collected over a six year period, and attempts to link movement style with the geomorphological setting and landslide process occurring in this area. A range of
movement styles have been observed. These are further investigated through the application of the Itasca FLAC finite difference modelling package to investigate the causes of the movement types. 2. Analysing landslide movement patterns Two main approaches are commonly adopted for the description of the movement patterns of landslides based upon monitoring data. The first concentrates on the analysis of movement velocities and cumulative displacements to try to classify the styles of movement that a landslide displays. For example, Allison and Brunsden (1990) used a comprehensive monitoring programme to examine the mechanisms of movement in coastal mudslides, proposing that four main types of movement can be observed. These are: 1. Small, multiple movements which appear to display stick-slip characteristics. Here the landslide appears to undergo repeated small movements closely spaced in time, interspersed by periods in which no movement occurs. Generally, the displacements observed were extremely small. 2. Gradual or graded slip, in which a single movement event was observed to occur at low strain rates over long periods (typically in the order of tens of centimeters over a 24-h period). 3. Surge movements, characterised by rapid displacements over short periods, typically in the order of metres over 20 min. 4. Occasional small random displacements that reflect slight internal adjustments within the landslide mass, and shrinkage/swelling associated with wetting and drying cycles. Such investigations provide useful information about the styles and patterns of movement, especially where they are supplemented by measurement of pore pressure through the landslide system. However, such studies are limited by the relatively low aerial coverage of the instruments. Indeed, Allison and Brunsden (1990) noted that (p. 309): it has to be recognized that recordings were taken at a limited number of points on one landslide. A
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more comprehensive spatial sampling framework would further elucidate the interrelationships within an individual system. The alternative approach that can be used to analyse landslide monitoring data to investigate movement mechanisms concentrates upon the nature of behaviour during periods of acceleration. It has long been recognized that it might be possible to analyse basal processes through surface displacement records (Terzaghi, 1950 for example). Perhaps the best known manifestation of this is the so-called dSaitoT method for predicting the time of failure of a landslide, originally proposed by Saito (1965, 1969) and developed by Fukozono (1990). In this technique, the displacement data during an accelerating phase are plotted in K–t space, where K=velocity 1 and t=time (Petley et al., 2002). Saito (1965) noted that during a phase of acceleration that leads to catastrophic failure, this graph has a linear form, with the point of failure being extrapolated to be the time when K=l. This linearity appears to be a fundamental character of brittle materials prior to catastrophic failure (Voight, 1988, 1989) that is associated with subcritical crack growth. A simple explanation contends that the exponential acceleration in deformation rate occurs as a result of crack growth that increases the stress on adjacent areas of rock, triggering accelerating failure (Main, 1999). However, Reches and Lockner (1994) provided an alternative explanation based upon more subtle mechanisms. They suggested that once the critical crack density has been reached, adjacent microcracks interact, enhancing dilation within each crack. This creates a process zone that propagates unstably into the adjacent intact rock. During continued growth of the process zone, the central portion yields by shear, forming a shear surface that subsequently propagates into the undeformed rock. At present, it is not possible to determine which of these mechanisms dominates, although it is possible that this is material dependent. Considerable efforts have been made to develop further the Saito method. These are reviewed in detail by Federico et al. (2002). In general, these have been based upon attempts to develop mathematical models to account for accelerating phases of creep (see
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Bhandari, 1988 for example). However, Federico et al. (2002) note that The . . .methods are empirical and phenomenological and do not take into account the soil mechanical behaviour and its influence on the progression of the landslideT (p. 177). Clearly, therefore, most attempts to examine this phenomenon to date have essentially been academic exercises. Fell et al. (2000) made a similar observation, noting that it would be foolhardy at this stage to put too much reliance on predictions of the time of failure while the mechanisms dominating the accelerating phase of movement are uncertain. However, Petley et al. (2002) attempted to investigate in detail this accelerating behaviour and to determine whether there is an identifiable physical mechanism that explains the Saito method. Based on the analysis of a large number of landslide movement records, they noted that linearity in K–t space only occurs where the deforming materials are capable of undergoing brittle failure mechanisms. Where the deformation process is dominated by sliding on existing shear surfaces or as a result of ductile deformation, the physical explanation does not appear to apply. This in agreement of a mathematical analysis of the effects of crack nucleation and growth (Kilburn and Petley, 2003), which demonstrated that deformation without crack growth will not normally be characterised by linearity in K–t space. Petley et al. (2002) analysed landslide movement records for reactivations of existing landslide systems and for movements in ductile materials, all of which showed an asymptotic trend in K–t space, with the rate of movement increasing to a constant velocity value. Detailed inclinometer records were used to show on the other hand that linearity is always associated with crack growth and indeed that the initiation of a linear trend at any point in the landslide mass can be associated with the state of development of the shear plane in that area (Petley et al., 2002). Finally, Petley and Petley (in press) re-examined the Vaiont failure in light of these observations, noting that the analysis of the accelerating phases of movement supports the proposition of Petley (1996) and Petley and Allison (1997) that there is a change in material behaviour from ductile to brittle controlled the final failure event.
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Through these developments, the Saito method appears to have the potential for providing a mechanism that allows slope deformation processes to be constrained with more confidence, and for developing a landslide warning system that might be applicable to both ground based instruments and the outputs from an InSAR analysis. However, it is clear that further research is needed. For example, there is a need to test the methodology on a wider range of landslides to investigate whether it has uniform applicability, especially where movements or the landslide components themselves have a complex form. Additionally, there is a need to determine how the results of monitoring from a range of locations within a landslide mass vary both spatially and temporally, and in terms of the range of movement types that can be observed.
3. The Tessina landslide The Tessina landslide is located on the southern slopes of Mount Teverone, in the Alpago valley in north-east Italy (Fig. 1). It consists of a large, highly active, complex gravitational failure that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, now threatens
two villages and is hence subject to detailed monitoring. As a result, a large volume of movement data has been collected. The occurrence of the landslide is closely related to the geological structure of the flanks of Mount Teverone. The area affected by the landslide is part of the northern flank of the small Alpago syncline, which has a NW–SE orientation. As a result, the Eocene Flysch deposits are characterised by nearly vertical strata that are cut by the Belluno overthrust (Fig. 2). The thrust has emplaced porous, fractured carbonate rocks over the Flysch deposits. These carbonates form the main body of Mount Teverone, with the Flysch forming the lower slopes on the southern side. The Flysch consists of a rhythmic sequence of marlstones, clay shales and calcarenite layers up to 1 m thick. The formation is highly fissured due to the tectonic disturbance, and hence is permeable. Towards the lower slopes, small amounts of Quaternary deposits are found. These consist primarily of colluvium and of moraines from the Piave valley glacier and other local glaciers. The presence of a large, high altitude carbonate mass adjacent to the steeply dipping Flysch deposits creates ideal conditions for the development of slope instability. A large head of water within the carbonate rocks means that there is a flow of water through the
Fig. 1. The location of the Tessina Landslide in northern Italy.
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Fig. 2. Indicative geological cross section showing the setting of the Tessina landslide based upon Mantovani et al. (2000).
slope that induces artesian conditions on the flanks of the mountain. These high water pressures are probably the major cause of instability at this site (Mantovani et al., 2000). The landslide itself extends from an elevation of 1200 m at the crown to 610 m a.s.l. at the toe of the mudflow. Its total track length is approximately 3 km from the crown to the toe of the mudflow, and its maximum width is about 500 m, in the rear scar area, with a maximum depth of about 50 m. The landslide represents a complex failure that consists of a rotational slide in its upper portions that transitions into a mudflow lower down. Mantovani et al. (2000) divided the failure into four main morphodynamic zones (Fig. 3): (i) the ddetaching zoneT (1200–1000 m a.s.l.), which consists of a highly fractured crown beyond the main scarp and the active scarp itself; (ii) the dupper accumulation zoneT (1000 to 975 m a.s.l.), identified in a sub-horizontal embayment, 500 m across and 350 m downslope, within which newly collapsed material can be accumulated before being eventually transported onto a secondary scarp at about 975 m a.s.l.; (iii) the dconnection canal zoneT (975 to 900 m a.s.l.), corresponding to the steep scarp (ca. 308 slope) immediately below the upper accumulation zone which funnels landslide material with the highest acceleration into the main valley below; (iv) the dlower accumulation zoneT (below 900 m a.s.l.) in which the landslide material, remo-
bilised as a mudflow, fills the existing valley. The latter now extends for about 1.5 km from 900 to 610 m a.s.l., and threatens the villages of Funes and Lamosano. The landslide currently involves a source area with a volume of about 500,000 m3 of material, and has a total potential volume of about 7 million m3. Movement rates vary greatly, with periods of almost no movement being interspersed by frequent rapid movements, triggered by high groundwater levels. The maximum measured velocities were recorded uphill of Lamosano in May 1992, with displacements of the main flow reaching 70 to 100 m day 1.
4. Monitoring of the Tessina landslide The Tessina landslide is intensively monitored for both scientific and civil defence purposes. The monitoring system is described in detail by Mantovani et al. (2000). Briefly, the connection canal zone and the lower accumulation zone are both monitored using an automatic alarm system, that consists of poles hanging vertically above the debris, suspended from wires. Fitted within the poles are tilt meters. In the event of a large surge of debris, the poles will be displaced, triggering an automatic alarm. In addition, two echometers are situated on the same wires, measuring the height of the debris in order to trigger an alarm should movement occur.
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Fig. 3. (a) A morphodynamic zonation of the Tessina landslide, based upon Mantovani et al. (2000); (b) Corresponding airphoto of the detaching and upper accumulation zone with the benchmarks identified.
Two multiple wire extensometer units have been located in the upper section of the landslide, with a movement resolution of 1 mm. Over much of the detaching and upper accumulation zones, 20 EDM targets have been emplaced. Every six hours, the EDM unit, which is located on a stable piece of terrain adjacent to the landslide, automatically determines the location of these targets. Inclinometers have been located within the landslide mass and around the crown to determine the depth of movement. Finally, ground water levels are monitored with a network of piezometers.
5. Patterns of movement of the Tessina landslide We have analysed the Tessina movement records during the period 1997–2002, primarily using the
EDM-based benchmark system as a data source. The accuracy of this type of surveying technique is high (mm accuracy), yielding much better basic surface movement data than the extensometers or inclinometers. The major problems are associated with failures and downtime of the EDM equipment, which result in frequent gaps in the data, and the potential for spurious movements associated with rotations of the poles upon which the targets are located, although these are rarely observed in reality. Even with these shortcomings, the datasets are excellent and allow a very high level of understanding of surface movements. Analysis of the movement data suggests that the movement patterns within the landslide fall into four distinct groups (Fig. 4) both in terms of the magnitude of the total displacement and the pattern of movement observed. These patterns are as follows:
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Fig. 4. Graph showing displacement against time for four representative monitoring points. Each shows a distinctly different movement pattern. Benchmarks 301 and 307 are plotted against the right hand axis; benchmarks 401 and 9 are plotted against the left hand axis.
Type I.
Type II.
Very slow movements, typically with rates in the order of less than 1 mm day 1 (e.g. Benchmark 307 in Fig. 4). This benchmark is located 20 m back from the edge of the scarp on a rocky surface composed of Flysch. These movements tend to occur in areas above the crown and close to, but not situated on, the landslide flanks. Movement patterns tend to consist of slow creep, but with increases in velocity associated with the wetter winter months. Low velocity movements at rates in the order of 2–3 mm day 1, but with the rate of movement being highly variable. A typical movement pattern is shown by benchmark 301 (Fig. 4), but similar movement patterns are seen for benchmarks across the detaching zone. Benchmark 301 is located on a slope with a gradient of 30–358, characterised by ground cracks. Faster movements generally occur during the months
when groundwater levels are high. This pattern of movement is typical of blocks that have undergone detachment from the crown of the landslide. Type III. Movements at rates of in the order of 10 mm day 1, such as seen for benchmark 9 (Fig. 4). This benchmark is located on the lower part of the principal scarp of the landslide which is 30 m high. The flysch that outcrops in the scarp is weathered in the upper part compared with the lower where it is intact. Creep occurs more-orless continuously, rates undergoing only relatively small seasonal fluctuations. This type of movement is typically seen at other benchmarks in the main scarp area within 50 m of benchmark 9. Type IV. Episodic, very rapid movements, with peak rates in the order of 1–2 m day 1 or greater (benchmark 401 in Fig. 4, for example). This benchmark is located inside the
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accumulation zone between two drainage channels. In between movement events, the system is essentially static. Movement is initiated rapidly, and also terminates abruptly. This type of movement occurs in the connection canal and lower accumulation zones. There is a clear linkage between the movement patterns and the morphodynamic setting of the benchmarks, as described by Mantovani et al. (2000). Type I movement occurs within the ddetaching zoneT located above the main landslide crown in the area of tension, or is located on areas of tension on the flanks of the landslide. In both cases, the movement occurs in materials that are undergoing disruption as retrogression of the landslide crown occurs. Type II movement also occurs within the detaching zone, but here it is associated with material that has become fully detached and incorporated into the landslide. Type III movement is associated with blocks moving into the upper accumulation zone, where the blocks are rapidly disaggregating into loose material. Finally, Type IV movement occurs within the connection canal zone and the lower accumulation zone in which the landslide material moves as a remobilised mudflow. All of the movement patterns show seasonality. Mantovani et al. (2000) demonstrated that in general, movements of the Tessina landslide were related to the groundwater level and not to short-term precipitation inputs. However, simple reliable threshold groundwater levels have not yet been identified, probably reflecting the complex and changing hydrogeology of this large landslide complex. Logically, as a given block moves downslope, the displacement should transition through the four movement patterns (Fig. 5). The model suggests that as retrogression of the landslide occurs, a benchmark should, over a period of a number of years, move through the different types of movement. Initially the benchmark will be stable. As the crown of the landslide retrogresses, it will define a series of blocks above the scarp that will begin to fail into the overall complex. Thus, the benchmark should show Type I movement, progressively transitioning to Type II, in which most deformation occurs during periods of high groundwater level when the effective normal stresses are minimised. Movement rates are slow because
Fig. 5. Conceptual graph illustrating movement patterns as a point transitions from Type I to Type IV movement.
deformation requires the formation of a distinct shear plane, either through the generation of a discontinuity or through the mobilisation of existing fractures. In time, the fracture will be fully developed and the materials will be at residual strength. Now the resistance of the block to movement is lower, leading to the development of Type III movement. The block is fully incorporated into the landslide complex, and is undergoes considerable deformation and disturbance. At this point, one of two processes can occur. The block can either slowly disaggregate and deform, continuing with Type III movement. Alternatively, complete disaggregation can occur and the material from the block can be incorporated into an earthflow or mudflow, at which point it will transition into Type IV movement patterns. Either way, the benchmark will eventually enter the canal zone and will thus show Type IV movement patterns. There are some indications that these transitions can be seen in the data in Fig. 4. Notably, the movement pattern of benchmark 307 has become more rapid and seasonal towards the end of the sequence as the block detaches from the crown area. More striking is the increase in movement rate of benchmark 301 from relatively small movements in 1998–1999 to large, highly seasonal movements in 2001–2002. Thus, through time, the movement pattern is increasingly tending towards those of Type IV.
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Fig. 6. Type IV movement patterns expressed in K–t space: (a) Benchmark 605, 2000 movement event; (b) Benchmark 402, 1998 movement event.
Fig. 7. The geometry of the simple FLAC simulation of the upper zone of the landslide. The vertical slope simulates the effects of the limestone. The contours indicate the initial groundwater level before precipitation was initiated.
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The type of movement pattern is defined by the morphology of the block in motion, its geomorphological setting and the properties of the basal (deforming) materials (Petley et al., 2002). The Type IV movement pattern could be explained either by the effects of rapid loss of shear strength, perhaps through rapid increases in water content at the basal zone, causing the sediments to transition to a water content above the plastic limit, or through the effects of undrained loading. The K–t technique described by Petley et al. (2002) is instructive in this regard. Mantovani et al. (2000) noted that the September 1998 movement event showed a progressive increase in the rate of deformation for a few days prior to the
failure. Plotting these data and those for other benchmarks that show Type IV movements yields a generally nonlinear asymptotic trend (Fig. 6). This is as would be expected for the acceleration of movement in a previously deformed material (Petley et al., 2002).
6. Modelling movement of the Tessina landslide One potential explanation for the change in movement style downslope is the variation in geotechnical properties. Surprisingly, however, a systematic analysis of the variation of angle of internal friction and cohesion, undertaken by Wilson et al.
Fig. 8. (a) Groundwater contours for the FLAC simulation at the time of failure. (b) Horizontal displacements for the failure in FLAC. It is clear that in this case, the failure consists of a shallow, translational movement.
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(2000) using both in situ (shear vane) and laboratory (shear box) tests, failed to show any consistent pattern of change of material properties that could account for this behaviour. It is therefore more likely that this change in behaviour is associated with changing groundwater and stress conditions in the landslide itself. To examine this, we have analysed the movement patterns observed for the Tessina landslide using a simplified model within the Itasca FLAC 4.0 software package. Fast Lagrangian Analysis of Continua (FLAC) is a sophisticated twodimensional continuum code for modelling soil, rock and structural behaviour. The code can model large displacements and strains, and both linear and nonlinear material behaviour, even if yield or failure occurs over a large area or if total collapse occurs.
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Modelling of coupled groundwater-deformation problems can be accommodated. In addition, it is able to assess factors of safety for slope problems. A simplified model of the detaching and upper accumulation zone of the landslide has been established within FLAC to determine the nature of movements that occur on different parts of the slope as a result of groundwater changes. This model was designed to examine the patterns of movement within material that is detached from the in situ rock mass— i.e. within the upper accumulation zone. This part of the landslide is simulated with a linear slope in a strong sandstone, representing the flysch (Fig. 7). At the head of the slope, the large limestone massif is represented by a large vertical cliff. The slope itself is mantled in landslide material, with geotechnical
Fig. 9. Strain rate (velocity)–time plots for four locations on the surface of the simulated slope. Note the different y-axis scales. (a) Point 1, located above the crown of the main landslide; (b) Point 2, just below the crown of the mobile mass; (c) Point 3 in the midst of the mobile mass; and (d) Point 4 at the toe. Note that movement started at the toe of the slide and retrogressed up slope. The highest velocities were seen in the middle of the mobile mass.
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properties that represent those measured for the site (Wilson et al., 2000). The slope geometry closely represents that of the actual site in terms of slope angle, height and length. A low groundwater regime was applied initially (Fig. 7) by setting up hydrostatic conditions based on a groundwater table 100 m below the surface at the rear of the limestone massif. The system was allowed to equilibrate and the minimum factor of safety of 1.45 was calculated, with the least stable part of the slope being the lower part of the superficial deposits mantling the slope. Thereafter, the pore pressures in the slope were increased by raising the water level in the limestone to the surface. This was undertaken by applying a precipitation input to the surface of the model, representing 20 mm h 1. As this was undertaken, the displacement history of four points on the slope was monitored, allowing graphs of displacement and velocity against time to be produced. Pore pressures 5 m below ground level were monitored for three of these points. The model was configured to
allow interaction between the pore pressure regime and the material deformation so that, for example, dilation in the materials can cause a reduction in pore pressure that might increase resistance to shear. The equilibrated groundwater regime at the end of the model run, when failure of the slope had occurred, is shown in Fig. 8a. Failure was initiated as a superficial translational movement with a shear surface at about 5-m depth (Fig. 8b). This simulates well the reactivation of movement in the landslide deposits. Ground water elevation through precipitation was initiated at model step 50,000. Displacements in the landslide materials were first noted at about model step 53,000, with movement being initiated near to the toe of the slope (Fig. 9d). It is clear from Fig. 9 that the failure retrogressed upslope, movement in the upper toe area started at about step 57,000 (Fig. 9c); in the midslope area at about step 60,000 (Fig. 9b); and limited movements started in the crown area at around step 64,000 (Fig. 9a).
Fig. 10. The data from this figure plotted in K–t space. These plots highlight the asymptotic form of the acceleration for each point and the different times of the initiation of movement at each point, starting at the toe, and retrogressing upslope. (a) Point 1; (b) Point 2; (c) Point 3; and (d) Point 4.
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These points of initiation are more clearly seen in the K–t plots (Fig. 10). Note that in all cases, a very small increase in movement can be observed when the precipitation was initiated, presumably as a result of creep within the wetted soil materials. In all cases, this creep occurs at a constant velocity until failure is initiated. Note also that the creep occurs at the greatest rate for the upper toe (Fig. 10d), and at the slowest rate for the area above the crown of the landslide (Fig. 10a). The point of acceleration is clearly noted in all cases, but interestingly for the area above the crown, the acceleration was preceded by a short period of slight deceleration. The plots all show that, as proposed by Petley et al. (2002), and in agreement with the monitoring data, this non-brittle failure is characterised by an asymptotic trend in K–t space. Thus, the simulation appears to agree with the observed behavior for the Tessina landslide. In addition, the acceleration and K–t plots seem to suggest that different movement patterns are observed for different parts of the landslide. Based upon these results, it would appear that changing movement patterns might well be associated with varying pore pressure conditions within the different parts of the landslide complex. In Fig. 11, the pore pressure conditions 5 m below the surface for three of the points (1, 2 and 4) are plotted alongside the respective surface velocity–time curve for that point. The results are interesting. First it is notable that movement does not initiate at the same pore pressure for all three points, even though the model uses a simple linear slope. Second, the pore pressure response is very different for the three points. For point 1, located above the crown of the landslide, increases in pore pressure do not occur until about step 62,000 (Fig. 11a), thereupon pore pressure rises in a linear fashion. The movement of this point does not occur until considerably later, and indeed the rate of movement remains low in comparison with other points. It is likely that this simple pore pressure and movement response is associated with the location of the point, which is above the landslide crown. Thus, the behaviour of the system is somewhat different. Point 2 on the other hand is rather more complex (Fig. 11b). Here pore pressure response is seen considerably earlier, but the pore pressure and movement of the point are initiated almost simultaneously. Interestingly, as the movement rate increases
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the pore pressure reaches a peak, which is maintained for approx. 3000 steps, after which the pore pressures decline before stabilising at ca. 60% of the peak value. Clearly here we are seeing the effects of the interaction between the material deformation processes and the pore pressure, with dilation postfailure allowing reductions in pore pressure to occur.
Fig. 11. Pore pressure variations for three of the points, plotted with the respective velocity-time curve. (a) Point 1; (b) Point 2; (c) Point 4.
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It is notable, however, that even though pore pressure is reducing the movement rate, it appears to be unaffected. At the toe, the displacements and the pore pressure response occur much earlier (Fig. 11c). Even though the pore pressure increases rapidly before eventually settling to an approximately constant value, the movement is initiated considerably later (although much earlier than upslope). Once movement has been initiated, the rate of increase is considerably slower than that of further upslope. Thus, the modelling suggests that the different patterns of movement observed in the Tessina landslide maybe primarily controlled by variations in the pore pressure conditions within the slope and by the interaction between these pore pressures and the deformation of the materials. Even though the model used just a simple, linear slope, considerable differences in strain rate were seen. Superimposed on top of this is the likely impact of changes in the cohesion and effective angle of internal friction associated with the disintegration of the landslide materials, which were not simulated here.
7. Conclusions The EDM monitoring of the Tessina landslide presents a unique opportunity for the assessment of the surface movement patterns of a large complex system. The results of the analysis suggest that four types of movement can be recognized, with any particular block of unfailed material transitioning through them as movement downslope occurs. Detailed modelling of the slope system suggests that the transition from one movement type to the next is associated primarily not with changes in material properties but instead with pore pressure conditions and the inter-relationships between pore pressures and the deformation of the materials in question. As Petley et al. (2002) proposed, analyses of movement patterns can be powerfully undertaken using the K–t technique. Both the monitoring and the modelling data for the landslide confirm the thesis of Petley et al. (2002) that failures that do not require brittle failure mechanisms will show an asymptotic trend in K–t space.
This analysis of the surface monitoring data for the Tessina landslide has demonstrated that the movement patterns of complex landslides are themselves complex, but that systematic analysis using, for example, the K–t tool can yield important and insightful outputs.
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