Réf. Meusburger & Alewell 2008

Référence bibliographique complète

MEUSBURGER, K., ALEWELL, C. 2008. Impacts of anthropogenic and environmental factors on the occurrence of shallow landslides in an alpine catchment (Urseren Valley, Switzerland). Natural Hazards and Earth System Sciences, 8, 509-520.

Abstract: Changes in climate and land use pose a risk to stability of alpine soils, but the direction and magnitude of the impact is still discussed controversially with respect to the various alpine regions. In this study, we explicitly consider the influence of dynamic human-induced changes on the occurrence of landslides in addition to natural factors. [The] hypothesis was that if changes in land use and climate have a significant influence on the occurrence of landslides we would see a trend in the incidence of landslides over time. [The authors] chose the Urseren Valley in the Central Swiss Alps as investigation site because the valley is dramatically affected by landslides and the land use history is well documented. Maps of several environmental factors were used to analyse the spatial landslide pattern. In order to explain the causation of the temporal variation, time-series (45 years) of precipitation characteristics, cattle stocking and pasture maps were compared to a series of seven landslide investigation maps between 1959 and 2004. [The authors] found that the area affected by landslides increased by 92% from 1959 to 2004. Even though catchment characteristics like geology and slope largely explain the spatial variation in landslide susceptibility (68%), this cannot explain the temporal trend in landslide activity. The increase in stocking numbers and the increased intensity of torrential rain events had most likely an influence on landslide incidence. In addition, our data and interviews with farmers pointed to the importance of management practice.

Mots-clés
 

Organismes / Contact

Institute of Environmental Geosciences, University of Basel, Bernoullistrasse 30, 4056 Basel, Switzerland - Correspondence: katrin.meusburger@unibas.ch


(1) - Paramètre(s) atmosphérique(s) modifié(s)
(2) - Elément(s) du milieu impacté(s)
(3) - Type(s) d'aléa impacté(s)
(3) - Sous-type(s) d'aléa
    Landslides  

Pays / Zone
Massif / Secteur
Site(s) d'étude
Exposition
Altitude
Période(s) d'observation
Switzerland Gotthard / Aare massif (Central Swiss Alps) Urseren valley   1400-3200m a.s.l. 1959-2004

(1) - Modifications des paramètres atmosphériques
Reconstitutions
 
Observations

The Spearman correlation coefficients between precipitation characteristics (yearly maximum 1 day-events, – 3 day-events and – 5 day-events; yearly mean precipitation) and landslides were not significant. The Mann-Kendall’s Tau test was not significant for mean precipitation data of the Andermatt station, too. However, for torrential events >150mm 3d−1 a significant (P<0.05) increase of 1.32mm 3d−1 per year is evident. Thus exceedance of the landslide triggering threshold became more likely. Farmers confirmed that prolonged rainfall of 2–3 days triggers landslides. The maximum event in the observed period occurred in November 2002 (270mm in three days), which triggered at least 17 landslides (Berger, August 2005; Swissphoto; personal communication) and mainly contributed to the affected area we observe in 2004. Extreme events from August 1987 (226mm in three days) and November 1991 (242mm in three days) also triggered several landslides. However, no triggering event could be observed between 1993 and 2000.

Modélisations
 
Hypothèses
 

Informations complémentaires (données utilisées, méthode, scénarios, etc.)
 

(2) - Effets du changement climatique sur le milieu naturel
Reconstitutions
 
Observations
 
Modélisations
 
Hypothèses
 

Sensibilité du milieu à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)
 

 


(3) - Effets du changement climatique sur l'aléa
Reconstitutions
 
Observations

Evolution of landslide incidence compared to human induced changes:
The area affected by landslides increased dramatically since 1959. [...] The Neumann-test shows a significant increasing trend (P<0.01) for landslide numbers and landslide area. While the number of landslides continuously increased with time, the increase of eroded area happened in two phases: from 1959 to 1980 by 45% and from 2000 to 2004 by 32%. From 1980 to 2000, new landslides occurred but the total affected area did not increase due to partial regeneration of older landslides. In total, the eroded area nearly doubled between 1959 and 2004 (increase of 92%). [...] In order to explain the increasing trend, the evolution of landslide incidence is compared to other causative factors that changed over time and have a geophysical association to landslide triggering [...].

Climate factors: avalanche frequency and precipitation:
The analysis of time-series data showed that several dynamic factors change simultaneously in the Urseren Valley. This impedes the determination of a definite causation of the landslide trend. Moreover, the temporal resolution of the air photographs to analyse the landslides is too low and too irregular, to deduce significant correlations.

[The authors] evaluated the frequency of avalanches over time as one important proxy for changes in snow dynamics. [...] The time-series of avalanches show a slightly increasing trend of the linear regression. However, the latter is only due to the high number of avalanches in the winter of 1999. Apart from that extreme event no trend over time is distinguishable. A direct comparison between the time series of the number of avalanches and number of landslides for single years in the valley did not result in a clear relationship (rsp=−0.43, P=0.38). Although there is a connection between spatial pattern of avalanches and landslides, no temporal correlation was found, e.g. the winter of 1999 with 30 avalanches did not cause a noticeable rise of the eroded area in 2000. [...] The absence of tension fissures in the field and the time-series data lead to the conclusion that avalanches do not directly triggered landslides at [this] site but rather occur in the same places, because the stability of snow cover and stability of soils are controlled by similar environmental conditions. To conclude, [the authors] could not identify avalanches as a causative factor for the landslide trend.

[...] The Spearman correlation coefficients between precipitation characteristics (yearly maximum 1 day-events, – 3 day-events and – 5 day-events; yearly mean precipitation) and landslides were not significant. The Mann-Kendall’s Tau test was not significant for mean precipitation data of the Andermatt station, too. However, for torrential events >150mm 3d−1 a significant (P<0.05) increase of 1.32mm 3d−1 per year is evident. Thus exceedance of the landslide triggering threshold became more likely. Farmers confirmed that prolonged rainfall of 2–3 days triggers landslides. The maximum event in the observed period occurred in November 2002 (270mm in three days), which triggered at least 17 landslides (Berger, August 2005; Swissphoto; personal communication) and mainly contributed to the affected area we observe in 2004. Extreme events from August 1987 (226mm in three days) and November 1991 (242mm in three days) also triggered several landslides. However, no triggering event could be observed between 1993 and 2000.

Land use factors: Intensity, management practices and land-cover:
[...] Land use was mainly intensified in the valley during the last decades, which is shown by the decreasing pasture area per animal [...] Except between 2000 and 2004, a good correspondence between increase of stocking number and landslides could be observed. However, correlations between the increase of stocking numbers (sheep rsp=0.10, P=0.87, cattle rsp=0.35, P=0.56) and new landslides of corresponding years was not significant. One reason is that the interaction with the triggering rainfall event and even the timing of the event needs to be considered. A multiple regression with stocking increase and yearly maximum 3 day-events could improve the explained variance (R=0.4) of the landslide development but was still not significant. Both predictors showed similar significance in the multiple regression (stocking number of sheep and cattle P=0.52, yearly maximum 3 day-events P=0.58). A reason for the low significance of the predictors is the usually non-linear relationship between landslides and its triggering factors. Rainfall events, for example, need to exceed a certain threshold to initialise landslides. Moreover, significant correlations might be obscured by the low temporal resolution of the air photographs (and thus low resolutions of landslide increase).

[...] The change of management practice is apparent from the pasture maps of 1955 and 2006. [...] Most of the changes took place in the beginning of the 1970s as local agriculture became mechanised and traditional farming practices were abandoned. [...] The remote and extensively used pastures were already slightly affected by landslides in 1959, but no increase in landslides could be observed over time. Today these areas are almost exclusively used as sheep pastures. The latter might indicate that sheep are not the main cause of the increase of landslide frequency.[...]

Parallel and partly due to the above described changes in grassland management [the authors] determined an alteration of landcover, which manifests in an encroachment of shrubs. Landcover was not an independent parameter. Nor did it significantly improve the explained variance of the spatial landslide distribution in the multiple logistic regression model. [...]

To summarise, we can see a clear impact of the changed management practice in the Urseren Valley: The accessible, more intensely used areas destabilised whereas areas of extensification to the point of abandonment did not destabilise. [...] [The authors] found that the consequence of abandonment of the remote pastures which is the accompanying intensification through concentration of animals on smaller areas in combination with increasing stocking numbers is a greater threat to soil stability than the abandonment itself. Although less pronounced than in the Urseren Valley, this is a general agricultural development in the Swiss Alps (Baur et al., 2007; Troxler et al., 2004).

Modélisations
 
Hypothèses

The observed increased frequency and intensity of torrential rainfall events is in correspondence with the generally described climate change effects (IPCC, 2007). Moreover, precipitation is expected to increase more in the winter (Beniston, 2006) when vegetation is sparse. The most severe events were observed in November in the Urseren Valley. On lower altitudes, precipitation will less often fall as snow while for higher altitudes a thicker snow pack in spring is predicted that results in more intense snowmelt events (Beniston, 2006). Thus, landslide hazard can be expected to increase through the described effects (Frei et al., 2007). [The present] analysis of extreme 3-day precipitation events seem to confirm this statement.

[...]

The change in management practice is driven by the decrease of farm numbers and farmers, which resulted in less maintenance and the abandoning of time-consuming traditional farming practices and non-profitable farmland since the early 1960s. In general, this leads on the one hand to abandonment and on the other hand to an intensification of the most profitable and accessible areas in the Swiss Alps and other mountainous regions (Tasser and Tappeiner, 2002; Mottet et al., 2006 ). These two extreme states of land use intensity are believed to be most vulnerable to landslides (Tasser and Tappeiner, 2002) and will most likely increase in the future.


Paramètre de l'aléa
Sensibilité des paramètres de l'aléa à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)

Landslide density histograms (landslide occurrences within each factor map and within each factor map’s classes)

 

The effect of environmental catchment characteristics on the probability of landslides is well understood and commonly used to predict landslide risk. Most of the investigated triggering factors are quasi-static in time i.e. do not change their characteristics in the considered time-span (such as geology, topography, etc.). Several studies showed the decisive impact of geology and slope as proxies for the physical parameters that describe soil strength properties and gravitational forces. However, the effect of triggering factors which are variable with time due to anthropogenic influence such as land use and climate (here defined as “dynamic factors”) are only rarely considered. Even tough there is no doubt that land use has a significant effect on the probability of landslides, its influence is still discussed controversially in literature with respect to the various mountainous regions. Overall it is not clear yet, whether we can expect a reduced erosion risk due to reforestation of mountain slopes or an increase due to abandonment and intensification of remote sites in alpine regions. [see references in the study].

Climate change affects soil stability directly via modification of precipitation characteristics and via temperature effects on soils (e.g. melting of permafrost). Indirect effects include the alteration of vegetation cover and snow processes. [...]

Avalanches are regarded as potential landslide risk factors because of the additional friction forces that may trigger tension fissures. [...]

Generally, landslides and precipitation are related by a threshold function (Guzzetti et al., 1999; Zhou et al., 2002) as soil strength properties are a function of soil water content. [...]

Besides the climatic factors the triggering of landslides is dependent on intensity and type of land use (Schauer, 1975; Bunza, 1984; Tasser et al., 2003). Land use management practice is a further dynamic factor.

Analysis of landslide database in relation to human-induced trends in landscape and climate change to evaluate if the land use and climate changes cause a trend in landslide occurrence and to determine possible causes for the temporal variation:

A time-series of landslide inventory maps was generated based on air photographs of seven different years starting in 1959. The occurence of landslides over time was then tested for a significant trend with the Neumann trend test. The landslide inventory maps were then superimposed with environmental factor maps and analysed with multiple logistic regression. In order to illustrate the relation between landslides and causative factors, bivariate statistic is applied for the factors geology, slope, avalanche density, and land-cover. Finally, the evolution of landslide occurrence over time was compared to time-series of dynamic factors, such as climate (precipitation and avalanches) and land use characteristics (stocking numbers and management practice). The database construction and spatial overlay of the data layers was accomplished with the geographic information system (GIS) software ArcGIS. [...]

Landslides in the investigation area (30 km²) were mapped by visually vectorising the affected area from air photographs (Swisstopo, 2006). The photographs had a scale of at least 1:12000 and were available for seven different years: 1959, 1975, 1980, 1986, 1993, 2000, and 2004. [...]

The present and past land use was determined by a series of pasture maps of the years 1955, 1975, 1990, and 2006 that were digitised and georeferenced. [...] Quantitative information on stocking on the pastures was obtained from the archive of the Korporation Urseren. [...] Information on the land-cover was available from the Vector25 dataset (Swisstopo, 2006). [...] The land-cover was additionally mapped for the year 1959 (based on air photograph interpretation) to assess potential changes of land-cover with a spatial overlay.

Climate data with daily rainfall was supplied by MeteoSwiss for the Andermatt station from 1971 to 2006. The avalanches that occurred in the valley were summarized for each year to generate a time-series of avalanche frequency.

In order to identify the most relevant environmental factors a multi-collinearity analysis followed by multiple-logistic regression with forward selection method was used. To illustrate the causative relationship of selected quasistatic factors and landslide occurrence, bivariate analysis was used to produce landslide density histograms (landslide occurrences within each factor map and within each factor map’s classes).

The mean precipitation data and torrential rainfall events were tested for a trend with the Mann-Kendall’s Tau test (Helsel et al., 2006). To assess the influence of dynamic factors, the development of the number of landslides was compared and correlated (Spearman’s rank correlation) to the maximum precipitation event (yearly maximum 1 dayevents, –3 day-events and –5 day-events; yearly mean precipitation), that occurred in the corresponding period, stocking properties (cumulative stocking and increase of stocking within the years, absolute stocking numbers), and avalanche frequency. In order to avoid pseudo-replication only the number of new landslides (not the increased area of existing slides) between each mapped year was used for the correlation. Thus, increase in landslides means that newly affected areas are spatially separated from older ones.


(4) - Remarques générales
 

(5) - Syntèses et préconisations

Conclusions:
[The authors] found a natural susceptibility of the catchment to landslides that has been proved by multivariate analysis. Geology and slope were identified as plausible factors to explain the spatial variation of landslides. However, quasi-static environmental factors like geology, and morphology cannot explain the temporal trend in landslide activity. The increase of the landslide area of 92% within 45 years confirms [the] hypothesis that dynamic factors like climate and land use decisively influence the landslide pattern that we observe today. The analysis of the time-series of avalanches revealed that avalanches seem to be of minor importance in triggering landslides. The increase of extreme rainfall events and the increased stocking of the pastures are likely to have enhanced the landslide hazard. In order to quantify the proportion of climate change and to separate its impact form land use the application of a deterministic landslide model seems a promising future task (Collison et al., 2000; Schmidt and Dikau, 2004). In addition to stocking numbers, the change in management practices is decisive. Extensively used or abandoned areas with recently emerging shrub vegetation show low landslide densities in the Urseren Valley and were not responsible for the landslide trend.

Land use affected the spatial distribution of landslides and created new landslide risk areas. In this context, it was shown that not abandonment itself but the accompanying intensification of accessible regions poses a major threat to soil stability in the valley. Although we cannot infer quantitative relationships between landslide hazard and anthropogenic impacts, [these] data indicate an increase of landslide hazard that duplicated the affected area by landslides. The case study in the Urseren Valley clearly highlights the relevance of dynamic anthropogenic driven impacts on landslide hazard. Many of the described developments are representative for other alpine regions, however, it remains to be shown if the impact on landslides is as significant.

Even though estimated soil loss due to landslides might be low compared to arable areas (0.6 t ha−1 yr−1 compared to 2– t ha−1 yr−1 as a limit value in the Swiss soil protection guideline BAFU, 2001), the areal damage is critical. Thus, there is a strong need, that soil loss through landslides is considered in erosion risk models and for guidelines and limit values adapted to mountain ecosystems.

Références citées :

BAFU: Article 18 of the Ordinance of 7 December 1998. Relating to Agricultural Terminology (SR 910.91), Swiss Federal Office for the Environment (German: BAFU), 2001.

Baur, P., Müller, P., and Herzog, F.: Alpweiden imWandel, AGRAR Forschung, 14, 254–259, 2007.

Beniston, M.: Mountain weather and climate: A general overview and a focus on climatic change in the Alps, Hydrobiologica, 562, 3–16, 2006.

Bunza, G.: Oberflächenabfluss und Bodenabtrag in alpinen Grassökosystemen, Ver. Ges. Ökol., 12, 101–109, 1984.

Collison, A., Wade, S., Griffiths, J., and Dehn, M.: Modelling the impact of predicted climate change on landslide frequency and magnitude in SE England, Eng. Geol., 55, 205–218, 2000.

Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy, Geomorphology, 31, 181, 1999.

Helsel, D. R., Mueller, D. K., and Slack, J. R.: Computer Program for the Kendall Family of Trend Tests, Scientific Investigations Report 2005–5275, 4, 2006.

IPCC: Climate Change 2007: The physical science basis. Summary for policymakers., 661, 10th session of working group I of the IPCC, Paris, 2007. [Fiche Biblio]

Mottet, A., Ladet, S., Coque, N., and Gibon, A.: Agricultural landuse change and its drivers in mountain landscapes: A case study in the Pyrenees, Agriculture, Ecosystems and Environment, 114, 296–310, 2006.

Schmidt, J., and Dikau, R.: Modeling historical climate variability and slope stability, Geomorphology, 60, 433–447, 2004.

Swisstopo: Reproduziert mit Bewilligung von swisstopo, BA071108, Zurich, 2006.

Tasser, E. and Tappeiner, U.: Impact of land use changes on mountain vegetation, Appl. Veg. Sci., 5, 173–184, 2002.

Tasser, E., Mader, M., and Tappeiner, U.: Effects of land use in alpine grasslands on the probability of landslides, Basic Appl. Ecol., 4, 271–280, 2003.

Troxler, J., Chatelain, C., and Schwery, M.: Technical and economical evaluation of grazing systems for high altitude sheep pastures in Switzerland, Grassland Science in Europe, 9, 590–592, 2004.

Zhou, C. H., Lee, C. F., Li, J., and Xu, Z.W.: On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong, Geomorphology, 43, 197, 2002.