Géo morphologie
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Géomorphologie : Relief, Processus, Environnement vol. 23, n° 3 (2017), p. 265-276 Mise en ligne le 16 octobre 2017 sur Revues.org URL : http://geomorphologie.revues.org/11825 DOI:10.4000/geomorphologie.11825
RELIEF, PROCESSUS, ENVIRONNEMENT
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Tree-ring reconstruction of reactivation phases of the Schimbrig landslide (Swiss Alps) Reconstitution des phases de réactivation du glissement de terrain de Schimbrig (Alpes suisses) au moyen d’une approche dendrogéomorphologique Jérôme Lopez-Saez *a, Pauline Morel a, Christophe Corona b, Bastian Bommer-Denns c, Fritz Schlunegger c, Frédéric Berger a, Markus Stoffel d,e Université Grenoble Alpes, Irstea, UR EMGR – 2 rue de la Papeterie, BP76, 38402 St-Martin-d'Hères, France. Centre National de la Recherche Scientifique (CNRS), UMR 6042-GEOLAB – 63057 Clermont-Ferrand cedex, France. University of Bern, Institute of Geological Sciences – Baltzerstrasse 1+3, 3012 Bern, Switzerland. d Dendrolab.ch, Department of Earth Sciences, University of Geneva – 13 rue des Maraichers, 1205 Geneva, Switzerland. e Climatic Change Impacts and Risks in the Anthropocene (C-CIA), Institute for Environmental Sciences, University of Geneva – 66 Bvd Carl-Vogt, 1205 Geneva, Switzerland. a
b c
ABSTRACT
ARTICLE INFORMATION Received 05 june 2017. Received in revised form 20 september 2017. Accepted 16 october 2017.
*Corresponding author. Tel: +33 4 76 76 28 33; E-mail adresses:
[email protected] (J. Lopez-Saez)
[email protected] (P. Morel)
[email protected] (C. Corona)
[email protected] (B. Bommer-Denns)
[email protected] (F. Schlunegger)
[email protected] (F. Berger)
[email protected] (M. Stoffel)
One of the most important issues of current landslide research is related to the dating of their reactivations, both in spatial and in temporal terms. Landslide chronologies thus play a key role because they provide very essential information on past activity and thereby contribute substantially to hazard assessment, in particular in areas with intense anthropogenic uses. In most cases, however, knowledge of past landslide activity remains incomplete and archive records of past activity typically over represent the largest and miss the smaller events. In this paper, a chronology of past reactivations of the Schimbrig landslide (Swiss Alps) has been derived from the dendrogeomorphic analysis of 184 disturbed P. abies trees growing on the landslide body. In total, 318 growth disturbances identified and dated in the tree-ring series enabled reconstruction of 26 reactivation phases of the landslide body between 1859 and 2010 (mean return period: 0.17 event yr‑¹). Given the spatio-temporal completeness of the reconstruction, probabilities of landslide reactivation were computed and mapped using a Poisson distribution model for an event to occur within 5, 20, 50, and 100 years. Probabilities of landslide reactivation increase from 0.33 for a 5-year period to 0.99 for a 100-year period. High-resolution maps also indicate a strong spatial variability with lower values computed on the margins and in the central portion of the landslide body whereas less frequent reactivations are predicted in its lower part. The field-based reconstruction proposed in this paper provides quantitative probability maps of reactivation derived directly from the frequency of past events that appear complementary to conventional susceptibility maps, used for landslide zoning that provides an estimate of where landslides are expected to occur. This approach is considered a valuable tool for land managers in charge of protecting and forecasting people and their assets from the negative effects of landslides as well as for those responsible for land use planning and management. It demonstrates the reliability of dendrogeomorphic mapping that should be used systematically in forested shallow landslides. Keywords: dendrogeomorphology, landslide, mapping, probability, reactivation, Swiss Alps
RÉSUMÉ L’objectif de cette étude est de proposer une reconstitution de l’activité spatio-temporelle des phases de réactivation d’un glissement de terrain au moyen d’une approche dendrogéomorphologique. L’étude a été réalisée sur le glissement de terrain de Schimbrig, à proximité de la commune de Hasle (canton de Lucerne, Suisse). L’analyse des échantillons a permis de dater 684 perturbations anatomiques depuis 1859, dont 318 ont permis de reconstruire 26 réactivations du glissement de terrain. La période de retour moyenne est de 0,17 glissement par an et les probabilités de réactivation dans les secteurs les plus actifs du glissement varient de 0,33 dans les 5 années à venir, à proche de 1, au cours des cent prochaines années. Enfin, la robustesse de la reconstruction a été validée par l’analyse diachronique des photographies aériennes et les archives historiques. En conclusion, cet article démontre la fiabilité de l’approche dendrogéomorphologique appliquée aux glissements de terrain et malgré certaines limites (notamment l’âge du peuplement), il met en évidence l’intérêt opérationnel de cette approche pour la gestion des risques future. Mots clés : dendrogéomorphologie, glissement de terrain, cartographie, probabilité, réactivation, Alpes suisses.
1. Introduction Each year, mass movements cause considerable financial damage to alpine societies (Hilker et al., 2009) and are a major driver of landscape changes and evolution by transferring sediment from
sources to sinks (Guzzetti et al., 2005). They pose a serious threat to the populations by repeatedly destructing settlements, disrupting transportation corridors, or even leading to the loss of life. The occurrence of mass movements has recently become a topic of major interest for both research and administration, especially in relation
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with the assessment of landslide hazards and risks (Magliulo et al., 2008). The increasing interest in landslides certainly reflects the increasing awareness of the socio-economic significance of landslides (Aleotti and Chowdhury, 1999) but also indicates quite clearly that human pressure on the environment has become more important for land development and urbanization (Petrascheck and Kienholz, 2003). Global statistics show that damage from landslides has risen for the last 30 years in mountain areas (Alexander, 2008). This trend is linked both to an increase in the occurrence of hazardous events, attributed to climate change (Gariano and Guzzetti, 2016) and to larger populations living in constantly growing Alpine settlements (Petrascheck and Kienholz, 2003). An appropriate assessment of existing and potential future landslide hazards requires, among others, detailed determination of the spatial and temporal occurrences of landslides at the site level (Claessens et al., 2006; Thiery et al., 2007; Corominas and Moya, 2008). The spatial extent and failure type of individual landslides can be further clarified via field investigations and surveys of tension cracks, secondary scarps, and scars around the landslide (Cruden and Varnes, 1996). Landslide activity can be inferred from multi-temporal remote sensing measurements or repeat field surveys (Cruden and Varnes, 1996; Montgomery et al., 2000). However, such data are not normally available with satisfying spatial resolution over long enough timescales and as a continuous record, landslide chronologies thus play a key role because they provide very essential information on past activity and thereby contribute substantially to hazard assessment (Šilhán and Stoffel, 2015). In previous studies, historical records were reconstructed for single landslides or landslide-prone regions and estimates were usually derived from existing archives such as narrations, historical documents, terrestrial or aerial photographs, remote sensing series, incidental statements or, more rarely, from public historical databases (Brunsden et al., 1976; Coe et al., 2000; Crovelli, 2000; Martin et al., 2002). Yet, the temporal window of such records only rarely spans more than a few decades and almost never covers centuries (LopezSaez et al., 2013a). In addition, and even more importantly, archival data on landslides have not normally been recorded for geomorphic purposes. As a result, they lack spatial completeness, resolution, and precision and invariably emphasize events that caused damage to human structures (Mayer et al., 2010). At the same time, they tend to typically overrepresent the largest and will, at the same time, miss the smaller events (Carrara et al., 2003). Finally, considerable problems exist in interpretation because of the changing standards and criteria of reporting in archival records over time (Ibsen, 1996). As a consequence, past research thus focused more on landslide susceptibility, see Guzzetti (2000), and references therein for a review, rather than on the documentation of landslide hazards. To compute accurate probability maps of landslide reactivation at the local scale, available for disaster prevention and the generation of risk maps, an approach is thus required that offers both an adequate temporal and spatial resolution. In forested shallow landslides, the analysis of growth disturbances contained in tree-ring records (Alestalo, 1971; Astrade et al., 2012; Stoffel and Corona, 2014) can greatly help the documentation of past events and may allow reconstruction of accurate chronologies of landslide reactivations over considerable periods in the past (Lopez-Saez et al., 2013a; Corona et al., 2014). As tree-ring series provide a continuous record over the lifespan of the tree and, collectively, over the lifespan of the sampled population (Procter et al., 2011), they offer a unique spatio-temporal resolution of past process activity. According to Carrara and O'Neill (2003), the first investigators using tree rings to date landslides were McGee (1893) in Tennessee and Fuller (1912) in Mississippi. However, modern dendrogeomorphology
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dates back to the early 1970s (Alestalo, 1971) and the information contained in tree-ring records has been used extensively in the United States (Jensen, 1983; Carrara, 2007) ever since. In Europe, tree rings have been used to document landslide reactivations in the French (Astrade et al., 1998; Lopez Saez et al., 2011, 2012, 2013a) and Italian Alps (Fantucci, 1999; Stefanini, 2004), the Spanish Pyrenees (Corominas and Moya, 1999), the Flemish Ardennes (Van Den Eeckhaut et al., 2009) or more recently in Czech Republic (Silhan et al., 2016; Silhan, 2017). Whereas these studies focused on the overall activity or possible triggers of landslides, they did neither define the temporal frequency of reactivation for specific areas nor address the probability of future events to occur in certain compartments on the landslide body. However, the location of past and potential future landslide reactivation along with a detailed assessment (i.e. annual resolution) of actual landslide triggers appears key for a better understanding of the process and for the management of sites at risk. The purpose of this study therefore is to provide a high-resolution, spatio-temporal chronology of reactivations on a forested, shallow landslide body located in the Schimbrig area (Entlebuch, Canton of Lucerne, Switzerland). The specific goals of this study are (i) to derive periods of landslide reactivation with annual resolution using the dendrogeomorphic record of 197 spruce trees (Picea abies (L.) Karst.). In addition, (ii) single-point data on past landslides was then compiled to derive a high-resolution landslide return period map for 24 geomorphic compartments identified on the landslide body and, in a final step, (iii) to quantify and map the probability of landslide reactivation for the coming 5, 20, 50, and 100-yrs, using a Poisson distribution.
2. Regional setting The study area is the Schimbrig landslide (8°5'58"E; 46°56'39"N; 1100-1440 m) located in the northern foothills of the central Swiss Alps (Clapuyt et al., 2015), in the UNESCO world heritage site of Entlebuch (Canton of Lucerne). The landslide is part of the Entlen catchment whose outlet is located near the town of Entlebuch. It consists in a complex 5‑10 m thick earth slide (Schwab et al., 2008), almost entirely lying in the Flysch domain, which promotes hillslope instability due to the low mechanical strength of the geological material (fig. 1E). With a maximum length of 1,280 m and a maximum width of 530 m, the landslide body occupies a surface of approximately 300,000 m² with an average slope of 16°. The landslide body is made up of cm- to dm-large clasts that are embedded in a matrix of silt and mud. The head of the landslide is translational, whereas the central part and the toe show sinusoidal downslope profiles. The flysch landslide mass currently moving is located between the Schimbrig ridge, formed by Early Cretaceous and Early Tertiary suite of marls, limestones, siliceous limestones, and quartzites of the Helvetic thrust nappes, and two longitudinal NE‑SW striking compartments made up of Molasse conglomerates (Mollet, 1921). According to Schwab et al. (2008) and Savi et al. (2013), a detailed field survey of the local morphology reveals that the landscape of the Schimbrig area is currently modulated by complex slab slides with shallow surface ruptures, multiple cracks and creeping surfaces. Climatic conditions at Schimbrig are characterized by a subarctic climate without dry season « Dfc » according to the Köppen-Geiger classification (Rubel and Kottek, 2010). Presentday climatic conditions are humid with average precipitation rates of approximately 1,500 mm.yr‑¹ (MeteoSwiss rain gauge at Entlebuch). Mean annual temperature is 4.6°C and, on average, the maximum temperature is below the freezing point 60 days per year (Schwab et al., 2008).
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Tree-ring and landslide in the Swiss Alps
Fig. 1 – Location and geological setting of the study site.
Fig. 1 – Localisation et contexte géologique du site d'étude.
A: the Schimbrig landslide is located in the Swiss Alps, near the village of Hasle, in the Unesco World Heritage Entlebuch area. B-C: view of the main scarp and of the landslide body. D: age structure of the forest stand growing on the Schimbrig landslide. 1. River; 2. Forest road; 3. House; 4. Eroded area; 5. Study site; 6. Subsections; 7. Recent scarp. E: simplified geological map (adapted from Schwab et al., 2008). 1. Helvetic nappe; 2. Subalpine Flysch; 3. Lower freshwater molasse; 4. Moraine; 5. Landslide; 6. Talus slope deposit; 7. Postglacial alluvial terrace; 8. Alluvial terrace; 9. Swamp; 10. Scree slope; 11. Fault; 12. Study site.
A : le glissement de terrain de Schimbrig est situé dans les Alpes suisses, à proximité du village de Hasle, dans la région d'Entlebuch, classée au patrimoine mondial de l’Unesco. B-C : vue de l’escarpement principal et du corps du glissement de terrain. D : cartographie de l'âge des arbres échantillonnés. 1. Rivière ; 2 : Route forestière ; 3. Habitations ; 4. Secteur fortement érodé ; 5. Site d’étude ; 6. Sous-secteur ; 7. Escarpement récent. E : Carte géologique simplifiée (adaptée de Schwab et al., 2008). 1. Nappe helvétique ; 2. Flysch subalpin ; 3. Molasse ; 4. Moraine ; 5. Glissement de terrain ; 6. Talus d’éboulis ; 7. Terrasse alluviale postglaciaire ; 8. Terrasse alluviale ; 9. Marais ; 10. Pierrier ; 11. Faille ; 12. Site d’étude.
The upper area of the landslide is characterized by steep slopes (unsuitable for agriculture) and partially covered by forest. The tree stand is mainly composed of spruce (Picea abies (L.) Karst.) intermixed with younger deciduous trees. Spruce forms nearly homogeneous stands outside the surfaces affected by the scarps and recent earth slides. The tilted and deformed trees also clearly indicate that the Schimbrig landslide has been affected by multiple reactivations in the past (fig. 1B-C). Contrariwise, the lower part is characterized by gentle slopes, allowing cattle and sheep to graze. During the past centuries this area has been mainly covered by meadows (Savi et al., 2013). From a historical perspective, landslide activity at Schimbrig has been documented since the beginning of the 1920s (Mollet, 1921). The earth slide has experienced a period of intense activity between spring 1994 and May 1995 when slip rates reached maximum values of several meters per day (Savi et al., 2013)
features were mapped at a scale of 1:1,000 (fig. 1D). At each unit, P. abies trees damaged by past landslide activity were sampled based on an outer visual inspection of the stem. Four cores per tree were extracted: two in the supposed direction of landslide movement (i.e. upslope and downslope cores), and two perpendicular to the slope. To gather the greatest amount of data on past events, trees were sampled within the tilted segment of the stems (Stoffel and Bollschweiler, 2008). To avoid misinterpretation, trees growing in sectors influenced by processes other than landslide or anthropogenic activity (sylviculture) were not considered for analysis. A total of 197 disturbed P. abies trees were sampled resulting in a total of 788 increment cores. For each tree, additional data were collected, such as (i) tree height; (ii) diameter at breast height; (iii) visible defects in tree morphology, and particularly the number of knees; (iv) position of the extracted sample on the stem; (v) photographs of the entire tree; and (vi) data on neighboring trees (following Stoffel et al., 2005). Tree coordinates were obtained with an accuracy 150 years) scattered within the stand. A total of 318 GD related to a past landslide reactivation was identified in the 184 disturbed trees. The most common reaction to landslide events was in the form of abrupt growth reductions (GS) with 47% of all GD (323 GD). The onset of compression wood (169 GD, e.i. 25%) and TRD (150, e.i. 22%) represents another common response of P. abies to landsliding. In contrast, growth release (GR: 42 GD, e.i. 6%) was by far less abundant. The earliest GD observed in the tree-ring series dates back to 1852; however, this year was not considered a landslide event as only one tree showed GD (fig. 3). In 1882, the number of GD surpassed five which was defined the threshold for GD to be considered as a landslide event.
Fig. 3 – Reconstructed time series obtained with dendrogeomorphic methods at Schimbrig. A total of 26 landslide reactivations was reconstructed from the tree-ring series since AD 1859. A: in black (grey), the major (minor) events reconstructed. B: decadal resolution (given as variations from the mean, 1.6 events per 10 yr).
Fig. 3 – Reconstitution des phases de réactivation du glissement de terrain de Schimbrig au moyen d’une approche dendrogéomorphologique.
4.2. Landslide reactivations and decadal landslide frequency
Depuis 1859, 26 phases de réactivation ont été reconstruites. A : en noir (gris), les événements majeurs (mineurs) datés. B : résolution décennale de l’activité (période de retour moyenne de 1,6 glissements par décennie).
In total, 27 years did exceed the 2% threshold for It with ≥5 trees exhibiting a GD between 1859 and 2010 (fig. 2). Major reactivations with GD>10 and It>5% were reconstructed in 17 different years, namely in 1897, 1917, 1928, 1930, 1940, 1945, 1947, 1955, 1956, 1973, 1983, 1993, 1994, 2001, 2002, 2003, and 2006 (fig. 2-3A). For the years 1859, 1860, 1882, 1890, 1903, 1906, 1922, 1936, 1962 and 1975, the number of GD was >5 and 5%> It >2%; these years
could not be considered reactivation events with equal confidence and were therefore tested further with yearly Moran’s I statistics. Results point to a spatial clustering with sufficient aggregation in 1859 (0.55), 1860 (0.55), 1882 (0.37), 1890 (0.29), 1903 (0.36), 1906 (0.4), 1922 (0.42), 1936 (0.24), and 1962 (0.1); as a result, these years were considered events with minor landslide reactivation (fig. 3A).
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In 1975, Moran’s I statistics point to a dispersed distribution of affected trees (0.06) with no significant pattern; this year was not therefore kept for further analysis. Considering the 26 reactivations within the sampled area, the mean return period for the Schimbrig landslide is 0.17 event.yr-¹ for the period 1859-2010. At the decadal scale (fig. 3B), 1.6 reactivations are recorded on average over the period covered by the tree-ring record. Above-average activity occurred in 1890-1899, 1900-1909, 1920-1929, 1930-1939, 1950-1959 and 1990-1999 (with 2 events for each of the periods), 1940-1949 (3 events) and 2000-2009 (4 events), whereas very limited landslide activity is observed for 1850-1869, 1880-1889, 1910-1919, and 19601989 with only one reactivation each. No event was recorded in 1870-1879. At the multi-decadal scale, landslide frequency does not show any clear trend. Whereas 12 landslides occurred between 1850 and 1939 (1.33 events per 10 yr), 14 events have been recorded since 1940 (2 events per 10 yr).
into landslide occurrence probability using a Poisson distribution. Highly resolved maps of return period derived from the 184 crossdated P. abies trees were thereby used to represent the probability for a landslide reactivation to occur within 5, 20, 50, and 100 yrs (fig. 4BE). As expected, the probability for a landslide to be reactivated increases from 0.33 for a 5-year period to 0.77 for a 20-years and 0.99 for a 100-year period. On a spatial plan, the probabilities for an event to recur are highest in the northeastern part of the landslide. In other units, event probabilities are lower, yet they exceed 0.8 in 21 out of the 24 geomorphic units for the 100-year period.
5. Discussion 5.1. Reliability of the tree-ring reconstruction
When analyzed spatially, the return period of reactivations is lower in the northeastern part of the landslide body and reaches a clear minimum (13-20 years) in the geomorphic units 10, 22, 23 and 24. Conversely, they exceed 30 years in the geomorphic units 14-17 located on the southwestern margins of the earth slide to reach maximum values (>75 years) in units 3, 6, 15 and 17 (fig. 4A). Return periods of landslide reactivations were then transformed
Dendrogeomorphic analysis of 788 increment cores taken from 184 P. abies allowed reconstruction of 26 events for the Schimbrig landslide since 1859 yielding a return period of 0.17 event yr-¹. The reconstructed time series represents a minimum frequency of reactivation events for the Schimbrig landslide in the recent past as the reconstruction was limited by tree age and sample depth. In addition, several limitations are apparent as to the potential of tree-ring analysis to detecting past periods of landslide activity. Reactivation of the landslide body must be, on one hand, powerful enough to damage a sufficiently large number of trees through stem topping, tilting or root damage. At the same time, more violent
Fig. 4 – Interpolated return periods and probability maps for the sampled area of the Schimbrig landslide.
Fig. 4 – Cartes des périodes de retour et de la probabilité de réactivation du glissement de terrain de Schimbrig.
A: the calculation of return period maps was based on the entire tree-ring sample and for the period 1859-2010. 1. River; 2. Forest road; 3. House; 4. Eroded area; 5. Study site; 6. Subsections; 7. Recent scarp. Probability maps of reactivation for the Schimbrig landslide within the next (B) 5, (C) 20, (D) 50, and (E) 100 yr obtained with a Poisson distribution model.
A : le calcul de la période de retour repose sur l’ensemble des données dendrogéomorphologiques et sur la période 1859-2010. 1. Rivière ; 2. Route forestière ; 3. Habitations ; 4. Secteur fortement érodé ; 5. Site d’étude ; 6. Sous-secteur ; 7. Escarpement récent. Cartographie de la probabilité de réactivation dans les 5 (B), 20 (C), 50 (D) et (E) 100 ans à venir (loi de Poisson).
4.3. Return period and landslide probability maps
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and destructive events are likely to kill trees and evidence of this category of events is not likely to be available to the investigator, as dead trees will disappear rather soon after an event. Despite these limitations, the It and GD thresholds as well as the spatial analysis of event-response maps minimized the risk of GD resulting from nonlandslide events to be included in the chronology. The thresholds also allowed rejection of GD related to creep or fall processes which have been shown to affect a rather limited number of trees per event (Stoffel and Perret, 2006; Trappmann and Stoffel, 2015). Moreover, historical archives and ancient maps confirm the reliability of our reconstruction. The topographic map (fig. 5A), dated to 1892, does not show a continuous forest in the Schimbrig area and therefore supports our data suggesting tree germination and the establishment of a forest at the end of the nineteenth century. Similarly, tree demography, represented indirectly through sample depth, is confirmed by the topographic map of 1941 (fig. 5B), on which a rapid afforestation of the catchment can be observed. The resolution of topographic information reported on the 1892 map does not, at the same time, permit to attest to the presence of a clear scarp or crown at Schimbrig at the end of the 19th century. According to Mollet (1921), however, farmers in the region were aware of the difficulty to use the lands in this sector, and reported several incidents of slide events, which is clearly in agreement with the reactivations reconstructed in 1897 and 1917. Our results also reveal that landslide activity at Schimbrig predates the 20th century, and that the movements described by contemporary landowners refer to local reactivations rather than to the initial triggering of the landslide. For the period 1962-2007, the diachronic analysis of aerial photographs provides additional evidence for the spatio-temporal accuracy of the dendrogeomorphic reconstruction presented in this paper. The reactivation of 1973, deciphered from tree-ring records, is thus confirmed by the slight extension of bare areas observed in the central part of the landslide body between 1962 and 1980 (fig. 5C-D). Similarly, our reconstruction reveals that the prominent earth slide of spring 1994, which occurred after periods of enhanced precipitation rates and wet autumns (Liniger and Kaufmann, 1994) and removed a total of approximately 322,000 t of sediments supplied to the channel network through by soil creeping, slumps and earth flows (Schwab et al., 2008), had damaged a large number of trees in 13 out of the 24 geomorphic units identified in the landslide body. According to aerial photographs, this event also created bare areas, secondary scarps and cracks (fig. 5D-E). Interestingly, growth disturbances – mainly in the form of compression wood – were already observed in trees scattered throughout the landslide body in the growing season 1993. These disturbances suggest that ground displacements, sufficient to modify stem verticality, were in place in the year before peak instability and can thus be seen as precursor signals of the high-magnitude event of 1994. These findings also confirm a technical report realized for the site in which localized ground deformation was observed as early as in spring 1992 (Liniger and Kaufmann, 1994). Finally, between 1998 and 2007 (fig. 5E-F), bare areas that appear preferentially in the central part of the landslide body, corroborate the most recent events reconstructed to 2001, 2002, 2003 and 2006.
5.2. Temporal correlations and clustering of landslide reactivations The reconstruction of spatio-temporal patterns of landslide activity with dendrogeomorphic techniques is recent but has been helpful for the understanding of landslide kinematics and its spatial evolution (Corominas and Moya, 2010). In our study, the exhaustive
sampling of P. abies trees enabled computation of a very detailed spatio-temporal chronology of landslide reactivation at Schimbrig. Given the completeness of the reconstruction (since AD 1859), we were able to map return periods of reactivation at each of the 24 geomorphic units identified on the landslide body. Adopting a Poisson probability model (Guzzetti et al., 2005), we were also able to determine the probability of having a reactivation in each unit for time intervals varying from 5 to 100 years. Smallest return periods associated with major probabilities of reactivation are mapped on the right bank of the Rosslochbach main stream, with probabilities of reactivation that exceed 0.4 within the next 5 years and 0.8 within the next two decades. On the contrary, the southwestern units of the landslide body appear more stable with return periods >30 years since 1859 and probabilities ranging for 0.4 and 0.6 for the next 20 years. Our approach purposely does not include physically based modeling, as this conventional method has been shown to predict the spatio-temporal occurrence of landslides with difficulties (Jaiswal et al., 2011). Most previous work focusing on landslide mapping has been based on susceptibility maps and therefore provides an estimate of where landslides are expected to occur (Brabb, 1984; Guzzetti et al., 2005). Much less work has been done on the establishment of the temporal probability of reactivation (Coe et al., 2000; Guzzetti et al., 2005). The approach presented in this paper enables determination of quantitative probabilities of reactivation estimated directly from the frequency of past landslide events and does not require a landslide susceptibility analysis as a complete inventory of past landslide events was reconstructed with dendrogeomorphic techniques (Corominas and Moya, 2008). However, the temporal occurrence of reactivations is assumed to conform to a Poisson probability model which among others assumptions are: (i) the probability of an event occurring in a very short time is proportional to the time interval; (ii) the probability of more than one event in a short time interval is negligible (iii) the number of events which occur in one-time interval or region of space are assumed to be independent incidents of the number that occurs in any other disjoint time interval or region; (iv) the a posteriori probability distribution in the future are considered to be the same as those of the past (Crovelli, 2000). Most hazardous events, including landslides, do not probably correspond to uncorrelated time series and do not therefore occur at random (Coe et al., 2000). Witt et al (2010), who examined historical landslide time series reporting 2,255 events between 1951-2002 for an area in the Emilia-Romagna Region (Italy), demonstrated that landslide time series show significant correlations in time, and a temporal clustering of extremes over a given threshold. Clustering is attributed to a reactivation that may make the landslide more or less susceptible to future landslides, thus creating stability or instability in the future. In addition, changing land use (Lopez-Saez et al., 2016), locally changing climatic conditions (Lopez-Saez et al., 2013b; Gariano and Guzzetti, 2016) or the implementation of landslide mitigation measures, may consequently render landslide occurrence more or less likely in the future, a fact which is further jeopardizing the possibility of using an uncorrelated process to model the temporal occurrence of landslide reactivation (Chleborad et al., 2006; Witt et al., 2010). Based on these limitations, care should be taken when estimating the recurrence times of landslide events (Guzzetti et al., 2003, 2005, 2006). Nevertheless, the Poisson model is often used when no information other than the mean rate of event occurrence is known. Under such circumstances, the Poisson model provides a good first-cut estimate for the probability of event occurrence in the future (Coe et al., 2000).
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Fig. 5 – Diachronic evolution of the Schimbrig landslide between 1892 and 2007.
Fig. 5 – Étude diachronique du glissement de terrain de Schimbrig entre 1892 et 2007.
Historical maps of the landslide in 1892 (A) and 1941 (B). Aerial photographs of the landslide in 1962 (C), 1980 (D), 1998 (E) and 2007 (F); Extracted from the Atlas topographique de la Suisse). The white line delineates the Schimbrig landslide body, white arrows indicate areas with interpreted landslide movements. (G): differences between removed and accumulated volume obtained from photogrammetric techniques between 1993 and 1998 in the Schimbrig landslide, adapted from Schwab et al. (2008). Event-response maps showing the 1993 and 1994 reconstructed reactivation event. Yellow (orange) squares indicate trees affected by the 1993 (1994) reactivation, small squares represent trees which were alive but did not show any signs of disturbance in that particular year.
Cartes historiques de 1892 (A) et 1941 (B). Photographies aériennes du glissement de terrain en 1962 (C), 1980 (D) et 2007 (E); Atlas topographique de la Suisse). La ligne blanche délimite le glissement de terrain de Schimbrig, les flèches blanches indiquent les mouvements de terrain interprétés. (G) : Cartographie des secteurs d’accumulation et d’ablation du glissement de terrain entre 1993 et 1994 obtenue au moyen d’une approche photogrammétrique (d’après Schwab et al., 2008). Les cercles jaunes (orange), les arbres perturbés en 1993 (1994), les petits cercles représentent les arbres vivants mais qui n'ont montré aucun signe de perturbation au cours de cette année.
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6. Conclusions As human activities increase in mountain areas, landslides have become a more serious social and economic issue. As a consequence, improved and more detailed landslide forecasting becomes a prerequisite, even at the local scale. In this paper, we investigated the potential of extensive tree-ring analyses for landslide forecasting and show how dendrogeomorphology can add substantially to the spatio-temporal record of landslides at a study site. Many reactivations, which remained unnoticed in archival data, could be identified and thus help extend the history of landslides back to the mid-19th century. Comparison of treering data with aerial photographs clearly demonstrates the spatiotemporal accuracy of the reconstruction. In terms of land-use planning, the identification of endangered areas is of paramount importance and dendrogeomorphic reconstruction should therefore be used systematically for hazard zoning in forested areas affected by shallow landslides. Finally, if coupled with a Poisson model, dendrogeomorphic mapping can improve our knowledge about the probability of reactivation. These probability maps should be used for disaster prevention and the generation of risk maps, as well as for the detailed design phase of engineering works and for the construction of slope stabilization works, keeping in mind that the premises for a random Poisson-type process are not necessarily met.
Acknowledgements This research has been supported by the “Topo-Europe project” and the “European Science Foundation (ESF)” called SedyMONT project (Timescales of Sediment Dynamics, Climate and Topographic Change in Mountain Landscapes). The authors acknowledge the valuable input from anonymous referees and GIE’s editorial team.
References Alexander D. (2008) – A brief survey of GIS in mass-movement studies, with reflections on theory and methods. Geomorphology, 94, 261-267. DOI : 10.1016/j.geomorph.2006.09.022 Aleotti P., Chowdhury R. (1999) – Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the Environment, 58, 21-44. DOI : 10.1007/s100640050066 Alestalo J. (1971) – Dendrochronological interpretation of geomorphic processes. Fennia, 105, 1-140. Astrade L., Bravard J.P., Landon N. (1998) – Mouvements de masse et dynamique d'un géosystème alpestre : étude dendrogéomorphologique de deux sites de la vallée de Boulc (Diois, France). Géographie Physique et Quaternaire, 52, 153-166. DOI : 10.7202/004765ar Astrade L ., Stoffel M., Corona C ., Lopez-Saez J. (2012) – L'utilisation des cernes de croissance des arbres pour l'étude des événements et des changements morphologiques : intérêts, méthodes et apports des recherches alpines à la dendrogéomorphologie. Géomorphologie : Relief, Processus, Environnement, 18 (3), 295‑316. DOI : 10.4000/geomorphologie.9925 Butler D.R., Malanson G.P. (1985) – A history of high-magnitude snow avalanches, southern Glacier National Park, Montana, U.S.A. Mountain Research and Development, 5, 175-182.
Brabb E. (1984) – Innovative approaches to landslide hazard mapping. Proceedings of 4th International Symposium on Landslides. Canadian Geotechnical Society, Toronto, Canada, 307-323. Brunsden D., Jones D.K.C., Arber M.A. (1976) – The evolution of landslide slopes in Dorset. Philosophical Transactions of the Royal Society of London. Series A: Mathematical and Physical Sciences, 283, 605-631. Carrara P. O'Neill J. (2003) – Tree-ring dated landslide movements and their relationship to seismic events in southwestern Montana, USA. Quaternary Research, 59, 25-35. DOI : 10.1016/S0033-5894(02)00010-8 Carrara A., Crosta G., Frattini P. (2003) – Geomorphological and historical data in assessing landslide hazard. Earth Surface Processes and Landforms, 28, 1125-1142. DOI : 10.1002/esp.545 Carrara P. (2007) – Movement of a large landslide block dated by tree-ring analysis, Tower Falls Area, Yellowstone National Park, Wyoming. Integrated geoscience studies in the greater Yellowstone area–volcanic, tectonic, and hydrothermal processes in the Yellowstone geoecosystem: Morgan, L.A., U.S. Geological Survey Professional Paper, 43-49. http://digitalcommons.unl.edu/usgspubs/67 Chleborad A.F., Baum R.L., Godt J.W. (2006) – Rainfall Thresholds for Forecasting Landslides in the Seattle, Washington, Area-Exceedance and Probability. USGS Open-File Report, 1064. https://pubs.usgs.gov/of/2006/1064/pdf/of2006-1064.pdf Claessens L., Verburg P.H., Schoorl J.M., Veldkamp A. (2006) – Contribution of topographically based landslide hazard modelling to the analysis of the spatial distribution and ecology of Kauri (Agathis australis). Landscape Ecology, 21, 63-76. DOI : https://doi.org/10.1007/s10980-005-5769-z Clapuyt F., Vanacker V., Van Oost K. (2015) – Reproducibility of UAV-based earth topography reconstructions based on Structurefrom-Motion algorithms. Geomorphology, 260, 4-15. DOI : 10.1016/j.geomorph.2015.05.011 Coe J., Michael J., Crovelli R., Savage W. (2000) – Preliminary map showing landslide densities, mean recurrence intervals, and exceedance probabilities as determined from historic records, Seattle, Washington. USGS Open-file Report 00-0303. Available at http://pubs.usgs.gov/of/2000/ofr-00-0303/ Cook E. (1985) – A time series analysis approach to tree-ring standardization. Ph.D. thesis. University of Arizona, Tucson. Cook E. (1990) – Methods of Dendrochronology: Applications in The Environmental Science. Kluwer Academic Publishers; International Institute for Applied Systems Analysis, Dordrecht, Netherlands, 394 p. DOI : 10.1007/978-94-015-7879-0 Corominas J., Moya J. (1999) – Reconstructing recent landslide activity in relation to rainfall in the Llobregat River basin, Eastern Pyrenees, Spain. Geomorphology, 30, 79-93. DOI : 10.1016/S0169-555X(99)00046-X Corominas J., Moya J. (2008) – A review of assessing landslide frequency for hazard zoning purposes. Engineering Geology, 102, 193-213. DOI : 10.1016/j.enggeo.2008.03.018 Corominas J., Moya J. (2010) – Contribution of dendrochronology to the determination of magnitude–frequency relationships for landslides. Geomorphology, 124, 137-149. DOI : 10.1016/j.geomorph.2010.09.001
Géomorphologie : relief, processus, environnement, 2017, vol. 23, n° 3, p. 265-276
273
Jérôme Lopez-Saez et al.
Corona C., Rovéra G., Lopez-Saez J., Stoffel M., Perfettini P. (2010) – Spatio-temporal reconstruction of snow avalanche activity using tree rings: Pierres Jean Jeanne avalanche talus, Massif de l'Oisans, France. Catena, 83, 107-118. DOI : 10.1016/j.catena.2010.08.004 Corona C., Lopez-Saez J., Stoffel M., Bonnefoy M., Richard D., Astrade L., Berger F. (2012) – How much of the real avalanche activity can be captured with tree rings? An evaluation of classic dendrogeomorphic approaches and comparison with historical archives. Cold Regions Science and Technology. DOI : 10.1016/j.coldregions.2012.01.003 Corona C., Lopez-Saez J., Stoffel M. (2014) – Defining optimal sample size, sampling design and thresholds for dendrogeomorphic landslide reconstructions. Quaternary Geochronology, 22, 72-84. DOI : 10.1016/J.quageo. 2014.02.006 Crovelli R.A. (2000) – Probability models for estimation of number and costs of landslides. USGS Open-File Report 00-249. USGS, Denver, CO. https://pubs.usgs.gov/of/2000/ofr-00-0249/ProbModels.html Cruden D.M., Varnes D.J. (1996) – Landslide types and processes. In Turner A.K., Schuster R.L. (Eds.). Landslides, Investigation and Mitigation, Special Report 247. Transportation Research Board, Washington D.C., 36-75. ESRI (2005) – ArcGIS 9.2. Redlands, California. Fantucci R. (1999) – Dendrogeomorphological analysis of a slope near Lago, Calabria (Italy). Geomorphology, 30, 165-174. DOI : 10.1016/S0169-555X(99)00052-5 Fuller M. (1912) – The New Madrid Earthquake. U.S. Geological Survey Bulletin, 494, 119 p. Gariano S.F., Guzzetti F. (2016) – Landslides in a changing climate. Earth-Science Reviews, 162, 227-252. DOI : 10.1016/j.earscirev.2016.08.011 Guzzetti F., Cardinali M., Reichenbach P. (1994) – The AVI project: A bibliographical and archive inventory of landslides and floods in Italy. Environmental Management, 18, 623-633. DOI : 10.1007/BF02400865 Guzzetti F. (2000) – Landslide fatalities and the evaluation of landslide risk in Italy. Engineering Geology, 58, 89-107. DOI : 10.1016/S0013-7952(00)00047-8 Guzzetti F., Reichenbach P., Cardinali M., Ardizzone F., Galli M. (2003) – Impact of landslides in the Umbria Region, central Italy. Natural Hazards and Earth System Sciences, 3, 469-486. DOI : 10.5194/nhess-3-469-2003 Guzzetti F., Reichenbach P., Cardinali M., Galli M., Ardizzone F. (2005) – Probabilistic landslide hazard assessment at the basin scale. Geomorphology, 72, 272-299. DOI : 10.1016/j.geomorph.2005.06.002 Guzzetti F., Galli M., Reichenbach P., Ardizzone F., Cardinali M. (2006) – Landslide hazard assessment in the Collazzone area, Umbria, central Italy. Natural Hazards and Earth System Sciences, 6, 115-131. DOI : 10.5194/nhess-6-237-2006 Hilker N., Badoux A., Hegg C. (2009) – The Swiss flood and landslide damage database 1972–2007. Natural Hazards and Earth System Science, 9, 913-925. DOI : 10.5194/nhess-9-913-2009 Holmes R. (1983) – Computer-assisted quality control in tree-ring dating and measurement. Tree-Ring Bulletin, 44, 69-75. http:// hdl.handle.net/10150/261223 Holmes R. (1994) – Dendrochronology Program Library – Users Manual. Laboratory of Tree-Ring Research, Tucson, Arizona,U.S.A.
274
Ibsen M. (1996) – The nature, use and problems of historical archives for the temporal occurrence of landslides, with specific reference to the south coast of Britain, Ventnor, Isle of Wight. Geomorphology, 15 (3-4), 241-258. DOI : 10.1016/0169-555X(95)00073-E Jaiswal P., van Westen C.J., Jetten V. (2011) – Quantitative assessment of landslide hazard along transportation lines using historical records. Landslides, 8, 279-291. DOI : 10.1007/%20s10346-011-0252-1 Jensen J. (1983) – The Upper Gros Ventre landslide of Wyoming: a dendrochronology of landslide events and possible mechanics of failure. Geological Society of America, Abstract program, 15, 387. Lee M., Jones D.K.C. (2014) – Landslide Risk Assessment, 2nd edition. Mark Lee and David. Jones. ICE Publishing, London, 524p Liniger M, Kaufmann B. (1994) – Rutschung Schimbrig, Ursachen, Entwicklung, Schadenszenario und Massnahmen. Geotest, Ergänzungsbericht Nr. L9434-B, 13 p. Lopez-Saez J., Corona C., Stoffel M., Astrade L., Berger F., Malet J.P. (2011) – Dendrogeomorphic reconstruction of past landslide reactivation with seasonal precision: Bois Noir landslide, southern French Alps, Landslides, 1-15. DOI : 10.1007s10346-011-0284-6 Lopez-Saez J., Corona C., Stoffel M., Schoeneich F., Berger F. (2012) – Probability maps of landslide reactivation derived from tree-ring records: Pra Bellon landslide, southern French Alps, Geomorphology, 138, 189-202. DOI : 10.1016/j.geomorph.2011.08.034 Lopez-Saez J., Corona C., Stoffel M., Berger F. (2013a) – Highresolution fingerprints of past landsliding and spatially explicit, probabilistic assessment of future activations: Aiguettes landslide, Southeastern French Alps. Tectonophysics, 602, 355-369. DOI : 10.1016/j.tecto.2012.04.020 Lopez Saez J., Corona C., Stoffel M., Berger F. (2013b) – Climate change increases the frequency of snowmelt-induced landslides in the French Alps. Geology, 41 (5), 619-622. DOI : 10.1130/G34098.1 Lopez-Saez J., Corona C., Eckert N., Stoffel M., Bourrier F., Berger F. (2016) – Impacts of land-use and land-cover changes on rockfall propagation: Insights from the Grenoble conurbation. Science of the Total Environment, 547, 345-355. DOI : 10.1016/j.scitotenv.2015.12.148 Magliulo P., Di Lisio A., Russo F., Zelano A. (2008) – Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy. Natural Hazards, 47 (3), 411-435. DOI : 10.1007/s11069-008-9230-x Martin Y., Rood K., Schwab J.W., Church M. (2002) – Sediment transfer by shallow landsliding in the Queen Charlotte Islands, British Columbia. Canadian Journal of Earth Sciences, 39, 189‑205. DOI : 10.1139/e01-068 Mattheck C. (1993) – Design in der Natur. Rombach Wissenschaft. Reihe Okologie, 1, 242 p. Mayer B., Stoffel M., Bollschweiler M., Hübl J., Rudolf-Miklau F. (2010) – Frequency and spread of debris floods on fans: a dendrogeomorphic case-study from a dolomite catchment in the Austrian Alps. Geomorphology, 118, 199-206. DOI : 10.1016/j.geomorph.2009.12.019 McGee W.J. (1893) – A fossil earthquake. Geological Society of America Bulletin, 4, 411-414.
Géomorphologie : relief, processus, environnement, 2017, vol. 23, n° 3, p. 265-276
Tree-ring and landslide in the Swiss Alps
Mollet H. (1921) – Geologie der Schafmatt-Schimberg-Kette, Beitrag zur Geologischen Karte der Schweiz, N.F.37. Secretariat National Geological: Wabern. Montgomery D.R., Schmidt K.M., Dietrich W.E., Greenberg H.M. (2000) – Forest clearing and regional landsliding in the Pacific Northwest. Geology, 28, 311-314. DOI : 10.1130/0091-7613(2000)28%3c311:FCARL%3e2.0.CO;2 Moran P.A.P. (1950) – Notes on continuous stochastic phenomena. Biometrika, 37, 17-23. Panshin A., De Zeeuw C. (1970) – 3rd edition. Textbook of Wood Technology, vol. 1. McGraw-Hill, New York, USA. Petrascheck A., Kienholz H. (2003) – Hazard assessment and mapping of mountain risks in Switzerland. In Rickenmann, D., Chen C.L. (Eds.), Debris-flow Hazards Mitigation: Mechanics, Prediction and Assessment, Rickenmann. Millpress, Rotterdam, Netherlands, Davos, Switzerland, 25-38. Procter E., Bollschweiler M., Stoffel M., Neumann M. (2011) – A regional reconstruction of debris-flow activity in the northern calcareous Alps, Austria. Geomorphology, 132, 41-50. DOI : 10.1016/j.geomorph.2011.04.035 Rinntech (2009) – http://www.rinntech.com/content/ blogcategory/2/28/lang,english2009 Rubel F., Kottek M. (2010) – Observed and projected climate shifts 1901–2100 depicted by world maps of the Köppen–Geiger climate classification. Meteorologische Zeitschrift, 19, 135-141. DOI : 10.1127/0941-2948/2010/0430 Savi S., Schneuwly-Bollschweiler M., Bommer-Denns B., Stoffel M., Schlunegger F. (2013) – Geomorphic coupling between hillslopes and channels in the Swiss Alps. Earth Surface Processes and Landforms 38, 959-969. DOI : https://doi.org/10.1002/esp.3342 Šilhán S., Stoffel M. (2015) – Impacts of age-dependent tree sensitivity and dating approaches on dendrogeomorphic time series of landslides. Geomorphology, 236, 34-43. DOI : 10.1016/j.geomorph.2015.02.003 Šilhán K., Prokešová R., Medveďová A., Tichavský R. (2016) – The effectiveness of dendrogeomorphic methods for reconstruction of past spatio-temporal landslide behaviour. Catena, 147, 325-333. DOI : 10.1016/j.catena.2016.07.035 Šilhán K. (2017) – Evaluation of growth disturbances of Picea abies (L.) Karst. to disturbances caused by landslide movements. Geomorphology, 276, 51-58. DOI : 10.1016/j.geomorph.2016.10.005 Schwab M., Rieke-Zapp D., Schneider H., Liniger M., Schlunegger F. (2008) – Landsliding and sediment flux in the Central Swiss Alps: A photogrammetric study of the Schimbrig landslide, Entlebuch. Geomorphology, 97 (3-4), 392-406. DOI : 10.1016/j.geomorph.2007.08.019 Schneuwly D.M., Stoffel M., Dorren L.K.A., Berger F. (2009a) – Three-dimensional analysis of the anatomical growth response of European conifers to mechanical disturbance. Tree Physiology, 29, 1247-1257. DOI : 10.1093/treephys/tpp056 Schneuwly D.M., Stoffel M., Bollschweiler M., (2009b) – Formation and spread of callus tissue and tangential rows of resin ducts in Larix decidua and Picea abies following rockfall impacts. Tree Physiology, 29, 281-289. DOI : 10.1093/treephys/tpn026
Stefanini M. (2004) – Spatio-temporal analysis of a complex landslide in the Northern Apennines (Italy) by means of dendrochronology. Geomorphology, 63, 191-202. DOI : 10.1016/j.geomorph.2004.04.003 Stoffel M., (2008) – Dating past geomorphic processes with tangential rows of traumatic resin ducts. Dendrochronologia, 26 (1), 53-60. DOI : 10.1016/j.dendro.2007.06.002 Stoffel M., Schneuwly D., Bollschweiler M., Lievre I., Delaloye R., Myint M., Monbaron M. (2005) – Analyzing rockfall activity (1600–2002) in a protection forest–a case study using dendrogeomorphology. Geomorphology, 68, 224-241. DOI : 10.1016/j.geomorph.2004.11.017 Stoffel M., Perret S. (2006) – Reconstructing past rockfall activity with tree rings: some methodological considerations. Dendrochronologia, 24, 1-15. DOI : 10.1016/j.dendro.2006.04.001 Stoffel M., Bollschweiler M. (2008) – Tree-ring analysis in natural hazards research - an overview. Natural Hazards and Earth System Science, 8, 187-202. DOI : 10.5194/nhess-8-187-2008 Stoffel M., Hitz O.M. (2008) – Snow ava- lanche and rockfall impacts leave different anatomical signatures in tree rings of Larix decidua. Tree Physiology, 28, 1713-1720. DOI : 10.1093/treephys/28.8.1713 Stoffel M., Bollschweiler M., Butler D.R., Luckman B.H. (2010) – Tree Rings and Natural Hazards: A State-of The-Art. Springer, Heidelberg, Berlin, New York. 505 p. Stoffel M., Corona C. (2014) – Dendroecological dating of geomorphic disturbance in trees. Tree-Ring Research, 70 (1), 3-20. DOI : 10.3959/1536-1098-70.1.3 Thiery Y., Malet J., Sterlacchini S., Puissant A., Maquaire O. (2007) – Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology, 92, 38-59. DOI : 10.1016/j.geomorph.2007.02.020 Timell T. (1986) – Compression Wood in Gymnosperms. SpringerVerlag, Berlin, New York, 625 p. Trappmann D., Stoffel M. (2015) – Visual dating of rockfall scars in Larix decidua (Mill.) trees. Geomorphology 245, 62-72. DOI : 10.1016/j.geomorph.2015.04.030 Van Den Eeckhaut M., Muys B., Van Loy K., Poesen J., Beeckman H. (2009) – Evidence for repeated re-activation of old landslides under forest. Earth Surface Processes and Landforms, 34, 352-365. DOI : 10.1002/esp.1727 Witt A., Malamud D., Rossi M., Guzzetti F., Peruccacci S. (2010) – Temporal correlations and clustering of landslides. Earth Surface Processes and Landforms, 35, 1138-1156. DOI : 10.1002/esp.1998
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Version française abrégée Dans les Alpes, les glissements de terrain font partie des processus géomorphologiques les plus répandus (Hilker et al., 2009). Ce sont des processus souvent complexes, pouvant être ponctuels ou continus, limités dans le temps et l’espace, d’une profondeur variable et affectant de petites ou grandes surfaces. Chaque année, l’aléa est la cause de nombreux dommages socio-économiques qui fragilisent considérablement les sociétés humaines (Hilker et al., 2009). Il est à l’origine de la destruction de nombreuses infrastructures routières, de bâtiments et dans certains cas, cause même la perte de vies humaines. D’après les statistiques, en montagne, la fréquence des glissements de terrain a augmenté au cours des trente dernières années (Alexander, 2008). Cependant, l’évolution de la fréquence de l’aléa est largement biaisée par des connaissances lacunaires de l’activité passée des glissements de terrain tant sur le plan spatial que temporel (Guzzetti 2000 ; Lopez Saez et al., 2011). Pour pallier ces lacunes et améliorer la connaissance de l’aléa, il est nécessaire de fournir des informations spatio-temporelles précises des évènements passés. En ce qui concerne l’évaluation des probabilités de réactivation, de nombreuses méthodes sont disponibles (Aleotti et Chowdhury, 1999). Dans le passé, deux approches indépendantes ont été traditionnellement utilisées, (i) l’analyse du potentiel de rupture de la pente et (ii) le traitement statistique des phases de réactivation passées. La première approche tient compte de plusieurs paramètres tels que la géométrie actuelle du glissement, la géologie et la couverture végétale. Elle évalue ensuite, par croisement de ces informations, le potentiel d’instabilité ou la susceptibilité de déclenchement (Corominas et Moya, 2008). Malheureusement, les archives historiques sont rarement satisfaisantes pour permettre ce type d’approche. Celles-ci restent souvent très fragmentaires et ne fournissent que peu d’informations sur le comportement spatiotemporel passé du glissement (Claessens et al., 2006 ; Thiery et al., 2007 ; Corominas et Moya, 2008). En effet, la distribution temporelle de l’activité des glissements de terrain est souvent estimée à partir de diverses sources historiques, telles que les récits anciens, les peintures, gravures ou objets d’art, les photographies terrestres et aériennes, les images satellites ou les instruments de mesure (Brunsden et al., 1976 ; Coe et al., 2000 ; Crovelli, 2000 ; Martin et al., 2002). De nombreuses lacunes subsistent dans l’accessibilité, l’extraction, l’organisation et l’analyse de ce type d’information. Dans les régions peu habitées, les archives historiques, souvent lacunaires, ont ainsi tendance à se limiter aux évènements majeurs (Guzzetti et al., 1994 ; Ibsen et
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Brunsden, 1996 ; Mayer et al., 2010). Par conséquent, il est essentiel de compléter les archives historiques par des approches à haute résolution spatio-temporelle (Ibsen et Brunsden, 1996). Sur les glissements de terrain superficiels forestiers (quelques mètres d’épaisseur), la dendrogéomorphologie permet de reconstruire, avec une résolution temporelle saisonnière et une emprise spatiale décamétrique, l’acitivité du processus, à partir de l’analyse des perturbations anatomiques contenues dans les cernes de croissance (Alestalo, 1971 ; Lopez-Saez et al., 2013a ; Corona et al., 2014). Cette étude a pour objectif (i) de reconstruire l’activité passée d’un glissement de terrain localisé dans les Alpes Suisses, (ii) de quantifier et cartographier la fréquence de réactivation et (iii) de convertir la période de retour en probabilité d’occurrence au moyen d’une loi Poisson (Crovelli, 2000 ; Corominas and Moya, 2008). Cette loi de probabilité discrète décrit la probabilité qu’un évènement se produise dans un intervalle de temps fixé, dans cette étude, à 5, 10, 20 et 100 ans. L’analyse dendrogéomorphologique a été réalisée sur un glissement de terrain situé sur le versant nord du Schimbrig, à proximité de la commune de Hasle (canton de Lucerne, Suisse). Afin d’atteindre ces objectifs, une cartographie géomorphologique des formes associées à l’activité du glissement de terrain a été réalisée. À partir de cette cartographie, 184 épicéas présentant des signes traumatiques caractéristiques d’une instabilité ont été échantillonnés. En laboratoire, les échantillons prélevés ont été analysés et les données traitées suivant les procédures standards en dendrochronologie (Stoffel and Corona, 2014). L’analyse des échantillons a permis de dater 684 perturbations anatomiques depuis 1859, dont 318 ont permis de reconstruire 26 réactivations du glissement de terrain de Schimbrig entre 1859 et 2006 (1859, 1860, 1882, 1890, 1897, 1903, 1906, 1917, 1922, 1928, 1930, 1936, 1940, 1945, 1947, 1955, 1956, 1962, 1973, 1983, 1993, 1994, 2001, 2002, 2003 et 2006). La période de retour moyenne est de 0,17 glissement par an et les probabilités de réactivation dans les secteurs les plus actifs du glissement varient de 0,33 dans les 5 années à venir, à proche de 1, au cours des cent prochaines années. Enfin, la robustesse de la reconstruction a été validée par l’analyse diachronique des photographies aériennes et les archives historiques. En conclusion, cet article démontre la fiabilité de l’approche dendrogéomorphologique appliquée aux glissements de terrain et malgré certaines limites (notamment l’âge du peuplement), il met en évidence l’intérêt opérationnel de cette approche pour la gestion des risques future.
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