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Clay shrink-swell consists in volume changes of clayey, smectite-rich soils as a function of their soil water content. Building foundations can be affected by soil shrinkage during droughts, entailing what is called subsidence damage. This is the second costliest peril covered by the French national natural disaster compensation scheme, the losses amounting to more than 16B€ between 1989 and 2021 (CCR, 2021). As illustrated by the 2022 drought in France, these costs are likely to increase as a result of climate change and of the related amplification of annual soil moisture cycles.In this context, we investigate the relationship between drought and subsidence damage, using the ISBA land surface model developed by the French meteorological service (Météo-France), geotechnical data from the French geological survey (BRGM) and data from a national claim database operated by the French state-owned national reinsurance company (CCR). We compute several yearly drought indices based on multi-layer soil moisture time series simulated by the ISBA model. Different configurations of the indices are considered, varying in particular the ISBA model settings, and the soil drought definition through a threshold value accounting for a given temporal frequency, for each model soil layer. We assess a large range of configurations by using the Kendall rank correlation of the indices with yearly town-scale insurance claim data from 2000 to 2018, processed using the geotechnical data. The analysis is repeated for five sets of four towns with an important damage history distributed throughout France, in contrasting climate conditions.Highest rank correlation coefficients are obtained for soil layers deeper than 60 cm, and with temporal frequency threshold values corresponding to intense droughts. Under these conditions, the indices are able to fairly represent the occurrence of damages. The relationship between drought indices and the number of claims is non-linear. This study benefits from the latest improvements in land surface modeling and is a step forwards in climate risk modeling since the indices investigated can be considered as new predictors for subsidence damage. Climate change impact studies will be conducted in a next phase.[References] CCR: Les Catastrophes naturelles en France, Bilan 1982-2021, 2021.

PHUSICOS platform aims at gathering nature-based solutions (NBS) relevant to reduce hydro-geological risks in mountain landscapes. The platform can be accessed directly through a web portal. It is based on an Open Source CMS website, including a filter to store documents and a map server to bring ergonomic and powerful access.To design the platform, an in-depth review of 11 existing platforms has been performed. Furthermore, a list of metadata has been proposed to structure the information. These metadata have provided the baseline for database. The PHUSICOS platform currently references 176 NBS cases and 83 documents of interest (review articles, assessment papers…). It is continuously enriched through the contribution of NBS community.For that, a questionnaire based on relevant data, necessary for the definition and identification of the NBS (metadata, to be used for searching the NBSs within the platform) has been defined to enter new entries. A preliminary analysis of the cases has been realized. To characterize and analyse the current 152 solutions, we have worked on the following four categories: The nature of impacted ecosystems, The hazard(s) concerned, The other challenges treated by the NBS, The type of exposed assets.The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: disaster risk reduction, technical and economical feasibility, environment, society, and local economy. The criteria level is sufficiently general to be analysed for the entire PHUSICOS platform NBSs whatever the type of work, the realized approaches, the problematic or the spatial or temporal scale.The structure of the platform and a first analysis of the qualitative NBS assessment are presented in this work.

In this work, we use a probabilistic approach for modelling rainfall thresholds (Caine 1980) triggering shallow landslides with a case study for the Alpes-Maritimes region (France).In particular, the CTRL-T algorithm (Melillo and al. 2018) is tested to output critical rainfall thresholds, based on the accumulated rainfall – duration parameters (E-D), for different exceedance probabilities from respectively a landslide and two climate datasets. The first climate dataset stores high resolution gridded rainfall data (1km resolution, hourly) and the second climate dataset contains lower resolution gridded rainfall, snow, temperature and evapotranspiration data (8km resolution, daily); the first dataset provides the rainfall records directly used for defining the rainfall events and then for the threshold construction; the second one enables to assess the region’s climate via parameters imported in CTRL-T. The thresholds are then validated using a method designed by Gariano and al. (2015).Several improvements are made to the method. First, potential evapotranspiration values approximated from temperatures and latitudes in one of the process’ steps are replaced by values from the second climate dataset, the result accounting best for the regional climate. Then, climate-specific duration values, used to split the raw rainfall records in events and sub-events, are computed for each mesh point. This second modification enables considering the heterogeneity of the Alpes-Maritimes climate.Rainfall thresholds are eventually obtained for different exceedance probabilities, first from a set of probable conditions (MRC), then from a set of highly probable conditions (MPRC). The validation process strengthens the analysis as well as enables to identify best performing thresholds. This work represents novel scientific progress towards landslide reliable warning systems by (a) making a case study of probabilistic rainfall thresholds for Alpes-Maritimes, (b) using for the first time high-resolution rainfall data and (c) adapting the method to climatically heterogeneous zones.

This paper presents a hydrologically modulated transient motion of world's largest active landslide occurring along the western shore of the Kara-Bogaz-Gol (KBG) lagoon of the Caspian Sea (CS) using Interferometric Synthetic Aperture Radar (InSAR) data. Here a dataset of Sentinel 1A/B IW SAR imagery acquired on ascending and descending modes between 2014 and 2020 has been processed to analyze the present-day evolution of this giant coastal landslide. The results shows that the eastern bank of the KBG lagoon (25x5 km) is horizontally sliding toward the lake at a rate of 25 mm/yr. The time series analysis reveals week-long accelerating slip events when the KBG reservoir water level reached its seasonal maximum. This study presents new information on the potential roles of the hydrological forces modulated by sea-level rises on the ancient landslides which originated during successive CS transgressions in the Late Glacial.

Sea-level rise of the Caspian Sea (CS) during the early Khvalynian (approximately 40–25 ka BP) generated hundreds of giant landslides along the sea’s ancient coastlines in western Kazakhstan, which extended hundreds of kilometers. Although similar landslides have been observed along the present-day coastlines of the CS in the area of a prominent high escarpment, it remains unclear whether some of these ancient landslides are still active and whether the movement is slow or catastrophic, as previously suggested. The present study is the first to show evidence proving that the geomorphic responses to sea-level changes of the CS that were triggered in the Pleistocene are currently active. Using interferometric synthetic aperture radar (InSAR) data, we show that one of these giant landslides occurring along the western shore of the Kara-Bogaz-Gol (KBG) lagoon of the CS presents active transient motion, which makes it the world’s largest active landslide reported thus far. Extending more than 25 km along the eastern coast of the inundated KBG depression in a N–S direction with maximum landward expansion of 5 km from the shoreline to the flat Ustyurt Plateau, this landslide conveys ~ 10 × 109 m3 rocks toward the lagoon at a rate of ~ 2.5 cm/year. This event releases a nearly episodic aseismic moment of 6.0 × 1010 Nm annually, which is equivalent to the response of an Mw 5.1 earthquake. We analyze the present-day evolution of this giant coastal landslide at high temporal and spatial resolutions using Sentinel-1 radar images acquired on descending and ascending modes every 12 days between 2014 and 2020. Modelling with elastic dislocations suggests that the KBG landslide was accommodated mostly by a shallow basal décollement with a nearly horizontal listric slip plane. Moreover, our analysis reveals week-long accelerating slip events at changing amplitudes that occur seasonally with slow, lateral spreading rather than sudden catastrophic motion. A strong correlation between the episodic slip events and seasonal water-level changes in the KBG lagoon suggests a causative mechanism for the transient accelerating slip events. Although water-level changes are widely acknowledged to trigger transient motion on a land mass, such movement, which is similar to a silent earthquake, has not been observed thus far at this mega scale; on an extremely low-angle detachment planes at

Several studies have shown that global changes have important impacts in mountainous areas, since they affect natural hazards induced by hydrometeorological events such as landslides. The present study evaluates, through an innovative method, the influence of both vegetation cover and climate change on landslide hazards in a Pyrenean valley from the present to 2100. We first focused on assessing future land use and land cover changes through the construction of four prospective socioeconomic scenarios and their projection to 2040 and 2100. Secondly, climate change parameters were used to extract the water saturation of the uppermost layers, according to two greenhouse gas emission scenarios. The impacts of land cover and climate change based on these scenarios were then used to modulate the hydromechanical model to compute the factor of safety (FoS) and the hazard levels over the considered area. The results demonstrate the influence of land cover on slope stability through the presence and type of forest. The resulting changes are statistically significant but small and dependent on future land cover linked to the socioeconomic scenarios. In particular, a reduction in human activity results in an increase in slope stability; in contrast, an increase in anthropic activity leads to an opposite evolution in the region, with some reduction in slope stability. Climate change may also have a significant impact in some areas because of the increase in the soil water content; the results indicate a reduction in the FoS in a large part of the study area, depending on the landslide type considered. Therefore, even if future forest growth leads to slope stabilization, the evolution of the groundwater conditions will lead to destabilization. The increasing rate of areas prone to landslides is higher for the shallow landslide type than for the deep landslide type. Interestingly, the evolution of extreme events is related to the frequency of the highest water filling ratio. The results indicate that the occurrences of landslide hazards in the near future (2021–2050 period, scenario RCP8.5) and far future (2071–2100 period, scenario RCP8.5) are expected to increase by factors of 1.5 and 4, respectively.

Several studies have shown that global changes have important impacts in mountainous areas, since they affect natural hazards induced by hydro-meteorological events such as landslides. To estimate the capacity of mountainous valleys to cope with landslide hazard under global change (climate change as well as climate- and human-induced land use change), it is necessary to evaluate the evolution of the different components that define this type of hazard: topography, geology and geotechnics, hydrogeology and land cover. The present study evaluates, through an innovative methodology, the influence of both vegetation cover and climate change on landslide hazard in a Pyrenean valley from the present to 2100. Once the invariant features of the studied area, such as geology and topography, were set, we first focused on assessing future land use changes through the construction of four prospective socioeconomic scenarios and their projection to 2040 and 2100. These inputs were then used to spatially model land use and land cover (LUCC) information to produce multi-temporal LUCC maps. Then, climate change inputs were used to extract the water saturation of the uppermost layers, according to two greenhouse gas emissions scenarios. The impacts of land use and climate change based on these scenarios were then used to modulate the hydro-mechanical model to compute the factor of safety (FoS) and the hazard levels over the considered area. The results demonstrate the influence of land use on slope stability through the presence and type of forest. The resulting changes are significant despite being small and dependent on future land use linked to the socioeconomic scenarios. In particular, a reduction in human activity results in an increase in slope stability; in contrast, an increase in anthropic activity leads to an opposite evolution in the region, with some reduction in slope stability. Climate change may also have a significant impact in some areas because of the increase in the soil water content; the results indicate a reduction in the FoS in a large part of the study area, depending on the landslide typology considered. Therefore, even if future forest growth leads to slope stabilization, the evolution of the groundwater conditions will lead to destabilization. These changes are not uniform over the area and are particularly significant under the most extreme climate scenario, RCP 8.5. Compared to the current period, the size of the area that is prone to deep landslides is higher in the future than the area prone to small landslides (both rotational and translational). On the other hand, the increase rate of areas prone to landslides is higher for the small landslide typology than for the deep landslide typology. Interestingly, the evolution of extreme events is related to the frequency of the highest water filling ratio. The results indicate that the occurrences of landslide hazards in the near future (2021–2050 period, scenario RCP 8.5) and far future (2071–2100 period, scenario RCP 8.5) are expected to increase by factors of 1.5 and 4, respectively.

International audience; -Riskcoast est un projet financé par le fond européen Interreg SudOE à hauteur de 1,07 M€ qui se concentre sur l'étude des risques géologiques en zone côtière, liés au changement climatique. Riskcoast intervient sur la chaîne complète du risque, de la compréhension de l'aléa à l'amélioration de la gestion du risque, de la prévention à la crise possible ainsi que la réhabilitation de zones sinistrées. Il a démarré en novembre 2019 et s'achèvera en octobre 2022. ABSTRACT-Riskcoast project is funded by the European fund Interreg Sudoe for 1.07 M€. It focuses on the study of geological risks in coastal areas related to climate change. Riskcoast intervenes on the whole risks, from a better understanding of the hazard to the improvement of the risk management, from the prevention to the possible crisis as well as the rehabilitation of disaster areas. It starts on November 2019 and lasts 3 years.

The increasing evolution of urban areas in landslide-prone regions and the modification of precipitation due to global climate change have led to a growing need for landslide hazard assessment (LHA) for local land management and security services. LHA is based on the definition of the spatial and temporal probability of landslide occurrences and is split into three steps: (i) a phenomenon inventory, (ii) a landslide susceptibility analysis, and (iii) a landslide hazard analysis. Nevertheless, in practice, essential information is often missing, and LHA corresponds most of the time to landslide susceptibility assessment acquired by expert knowledge. This article presents a physical-based model (ALICE – Assessment of Landslides Induced by Climatic Events) that can integrate different types of landslides (shallow and deep) with different sizes. This tool can be used at the meso or broader scale (1:25,000 to 1:10,000) of work according to expert knowledge. However, a calibration must be carried out to fit observations and to take uncertainties into account. Thus, a specific strategy is applied to the model on a study site located in the French South Alps where numerous different landslide types were observed and analyzed. After calibration on a small representative area, the best-fitted parameters are applied to a larger area for different types of landslides. Three landslide susceptibility maps (shallow translational landslides, rotational landslides and complex landslides) are produced, and the different susceptibility classes are compared with a landslide susceptibility map produced by a geomorphological approach. The different susceptibility envelopes computed by the model are well integrated into the high-susceptibility envelopes defined by the so-called expert geomorphological approach. Thus, the tool makes it possible to improve the mapping of potentially unstable areas by taking into account parameters, such as the groundwater level in different surficial formations or the geotechnical values of landslide-prone formations, that experts are not always able to integrate. ALICE is therefore proven to be a useful tool for mapping potential landslide-prone areas if the tool is well calibrated, taking into account the expert vision of the field, different landslide types, and different triggering factors, including rainfall and seismic acceleration.

International audience; Better understanding the pathways through which future socioeconomic changes might influence land use and land cover changes (LULCCs) is a crucial step in accurately assessing the resilience of societies to mountain hazards. Participatory foresight involving local stakeholders may help building fine-scale LULCC scenarios that are consistent with the likely evolution of mountain communities. This paper develops a methodology that combines participatory approaches in downscaling socioeconomic scenarios with LULCC modelling to assess future changes in mountain hazards, applied to a case study located in the French Pyrenees. Four spatially explicit local scenarios are built each including a narrative, two future land cover maps up to 2040 and 2100, and a set of quantified LULCC. Scenarios are then used to identify areas likely to encounter land cover changes (deforestation, reforestation, and encroachment) prone to affect gravitational hazards. In order to demonstrate their interest for decision-making, future land cover maps are used as input to a landslide hazard assessment model. Results highlight that reforestation will continue to be a major trend in all scenarios and confirm that the approach improves the accuracy of landslide hazard computations. This validates the interest of developing fine-scale LULCC models that account for the local knowledge of stakeholders.

Continuous geodetic measurements in landslide prone regions are necessary to avoid disasters and better understand the spatiotemporal and kinematic evolution of landslides. The detection and characterization of landslides in high alpine environments remains a challenge associated with difficult accessibility, extensive coverage, limitations of available techniques, and the complex nature of landslide process. Recent studies using space-based observations and especially Persistent Scatterer Interferometry (PSI) techniques with the integration of in-situ monitoring instrumentation are providing vital information for an actual landslide monitoring. In the present study, the Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process the series of Sentinel 1-A and 1-B Synthetic Aperture Radar (SAR) images acquired between 2015 and 2019 along ascending and descending orbits for the selected area in the French Alps. We applied the proposed approach, based on extraction of Active Deformation Areas (ADA), to automatically detect and assess the state of activity and the intensity of the suspected slow-moving landslides in the study area. We illustrated the potential of Sentinel-1 data with the aim of detecting regions of relatively low motion rates that be can attributed to activate landslide and updated pre-existing national landslide inventory maps on a regional scale in terms of slow moving landslides. Our results are compared to pre-existing landslide inventories. More than 100 unknown slow-moving landslides, their spatial pattern, deformation rate, state of activity, as well as orientation are successfully identified over an area of 4000 km2 located in the French Alps. We also address the current limitations due the nature of PSI and geometric characteristic of InSAR data for measuring slope movements in mountainous environments like Alps.

International audience; The ANR-SAMCO project aims to develop a proactive resilience framework enhancing the overall resilience of societies on the impacts of mountain risks. The project aims to elaborate methodological tools to characterize and measure ecosystem and societal resilience from an operative perspective on three mountain representative case studies. To achieve this objective, the methodology is split in several points: (1) the definition of the potential impacts of global environmental changes (climate system, ecosystem e.g. land use, socioeconomic system) on landslide hazards, (2) the analysis of these consequences in terms of vulnerability (e.g. changes in the location and characteristics of the impacted areas and level of their perturbation) and (3) the implementation of a methodology for quantitatively investigating and mapping indicators of mountain slope vulnerability exposed to several hazard types, and the development of a GIS-based demonstration platform available on the web. The strength and originality of the SAMCO project lies in the combination of different techniques, methodologies and models (multi-hazard assessment, risk evolution in time, vulnerability functional analysis, and governance strategies) that are implemented in a user-oriented web-platform, currently in development. We present the first results of this development task, architecture and functions of the web-tools, the case studies database showing the multi-hazard maps and the stakes at risks. Risk assessment over several area of interest in Alpine or Pyrenean valleys are still in progress, but the first analyses are presented for current and future periods for which climate change and land-use (economical, geographical and social aspects) scenarios are taken into account. This tool, dedicated to stakeholders, should be finally used to evaluate resilience of mountainous regions since multiple scenarios can be tested and compared.

International audience; This work focuses on the development of FLAME (Forecasting Landslides induced by Acceleration Meteorological Events) that analyze of the relationship between displacements and precipitations using a statistical approach in order to predict the surface displacement at active landslide. FLAME is an Impulse Response model (IR) that simulates the changes in landslide velocity by computing a transfer function between the input signal (e.g. rainfall or recharge) and the output signal (e.g. displacement). This model has been applied to forecast the displacement rates at Séchilienne (French Alps). The FLAME model is enhanced by achieving the calibration using joint inversion of multiple time series data. We consider that the displacements at two different sensors are explained by the same long-term response of the system to ground water level variations. The parameters describing the long-term response of the system are therefore identical for all sensors. The joint inversion process allows decreasing the ratio between the number of parameters to be inverted and the volume of data and is thus more statically steady. The results indicate that the models are able to reproduce the displacement pattern in general to moderate kinetic regime but not extreme kinetic regime. Our results do not give clear evidence of an improvement of the models performance with joint inversion of multiple time series of data. The reasons which could explain these inconclusive results are discussed in the paper.

Open image in new window Global changes would have impacts worldwide, but their effects should be even more exacerbated in areas particularly vulnerable. Mountainous areas are among these vulnerable territories. In order to estimate the capacity of such mountainous valleys to face global changes (climate, but also climate- and human- induced land-use changes), it is necessary to be able to evaluate the evolution of the different threats. The present work shows a methodology to evaluate the influences of both vegetation cover and climate on landslides activities over a whole valley until 2100, to propose adequate solutions for current and future forestry management. Firstly, the assessment of future land use is addressed through the construction of four prospective socio-economic scenarios up to 2040 and 2100, which are then spatially validated and modeled with LUCC models. Secondly, the climate change inputs of the project correspond to 2 scenarios of emission of greenhouse gases. The used simulations were performed with the GHG emissions scenarios RCP 4.5 and RCP 8.5. The impact of land use and climate change is then addressed through the use of these scenarios into hazards computations. For that we use a large-scale slope stability assessment tool ALICE which combines a mechanical stability model, a vegetation module which interfere with the first model, to take into account the effects of vegetation on the mechanical soil properties, and a hydrogeological model. The results demonstrate the influence of the forest on slope stability; the absence of the forest implies an increase of the probability of landslide occurrence, and at the contrary, the presence of forest has a local stability effect on the slope. The results also indicate some future evolution of the land use, leading to significant modifications of the stability of the slopes. Finally the climate change may have noteworthy impact on the occurrence of landslide with the increase of the water content of the soil when regarding future long periods; the results point out a reduction of the SF in a large part of the studied area. These changes are not uniform over the area, and are particularly significant for the worse scenario RCP 8.5.

Physically based model may be used to assess landslide susceptibility over large areas. However, majority of case studies are applied for complex phenomena for a one event, a little site or over large areas when landslides have simple geometry and environmental conditions are homogeneous. Thus, assessing landslide prone areas for different type of landslides with several geometries and for large areas needs some specific strategies. This work presents an application of a specific procedure based on a physically based model for one complex area with several landslide types. By different steps, it is demonstrated this is possible to improve susceptibility map and take into account of different slope failure with different depths. This first attempt encourages us to continue on this path in order to improve the existing susceptibility maps in this area.

International audience; An integrated analysis on the relationship between rainfall and displacement in the most active area of the Séchilienne unstable slope was performed. This study combines several techniques and models to adequately reproduce the landslide movement induced by the rainfall. The analysis of available time series shows a long term trend and seasonal variations in the displacement, respectively independent and synchronous to precipitations. In particular wavelet analysis highlights that the movement is rather linked to groundwater recharge than to precipitation (rainfall + snowfall), involving then the importance of groundwater process in the area. A first and simple relationship between the water input and the fluctuations of displacements apart from the general trend is shown using a tank model. Moreover, a seasonal analysis of this relationship was performed, showing that displacement rate follows the behavior of the hydrological cycle. Two different models were applied to the long temporal series of extensometric and precipitation data: the FLAME model, from BRGM and the FORESEES model, from Univ. Lausanne. These tools are based on a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in precipitation amounts. The forecasting tool FLAME associates 1) a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the rainfall and the displacements, and 2) a 1D mechanical (ME) model (e.g. visco-plastic rheology), in order to take into account changes in pore water pressures. The performance of different combinations of models was evaluated against observed displacement rates at the selected pilot study area. Our results indicate that both models are able to reproduce, with a high degree of accuracy, the observed displacement pattern in the general kinematic regime. Finally the variability of the results, depending in particular on the input data, is discussed.

article i nfo Non-invasive geophysical techniques offer an interesting alternative to traditional soil sampling methods, es- pecially for estimating spatial variations of soil parameters in the landscape. The spectral analysis of seismic surface-waves (MASW) can be used to determine the vertical shear-wave velocity (Vs) model (i.e., vertical variations in Vs with depth). In our study, MASW soundings were determined at each point in a grid spread over a wind-eroded field plot of 15,600 m 2 . Vs was then mapped in terms of the thickness and stiffness of the superficial loamy material horizon, which are called ThickLM and StiffLM, respectively. To relate the Vs values to the soil stiffness, cone resistance (Qd) soundings were also performed using a Dynamic PANDA penetrom- eter. Concurrently, boreholes were used to sample the same horizon for bulk soil density (ρb) measurements. Based on these measurements, large variations in ThickLM were observed. The distribution of Vs values along a 130 m transect allowed for the distinction between two layers corresponding to different mechanical prop- erties. The Vs value of 240 m/s was then used as a limit between the loamy material and the underlying clays. This limit was validated using drilling observations performed on the same transect. Therefore, it was possi- ble to map the ThickLM, which varied between 0.2 and 6.5 m over the entire field. The comparison between the averaged values of Vs and Qd in the loamy material layer showed a significant correlation (R 2 =0.4) such that the mapping of StiffLM was realised from the Vs map and the Vs-Qd relationship. Density comparison be- tween the ρb measured on drill samples and the ρb calculated from Vs was also performed using previously published relationships; however, significant correlations were not observed. The obtained maps of ThickLM and StiffLM were consistent with the expected effects of erosion at the catchment scale and provide indica- tions of historical erosion events. This methodology, which provides a structural and mechanical characteri- sation of subsurface materials, should help to focus conservation measures to the most threatened areas (i.e., the identification of areas that show a reduced ThickLM and increased StiffLM, which are associated with high soil erosion vulnerability and/or high compaction state).

One of the main features of "post mining" research relates to available methods for monitoring mine-degradation processes that could directly threaten surface infrastructures. In this respect, GISOS, a French scientific interest group, is investigating techniques for monitoring the eventual collapse of underground cavities. One of the methods under investigation was monitoring the stability of a salt cavity through recording microseismic-precursor signals that may indicate the onset of rock failure. The data were recorded in a salt mine in Lorraine (France) when monitoring the controlled collapse of 2 000 000 m3 of rocks surrounding a cavity at 130 m depth. The monitoring in the 30 Hz to 3 kHz frequency range highlights the occurrence of events with high energy during periods of macroscopic movement, once the layers had ruptured; they appear to be the consequence of the post-rupture rock movements related to the intense deformation of the cavity roof. Moreover the analysis shows the presence of some interesting precursory signals before the cavity collapsed. They occurred a few hours before the failure phases, when the rocks were being weakened and damaged. They originated from the damaging and breaking process, when micro-cracks appear and then coalesce. From these results we expect that deeper signal analysis and statistical analysis on the complete event time distribution (several millions of files) will allow us to finalize a complete typology of each signal families and their relations with the evolution steps of the cavity over the five years monitoring.

The monitoring of the stability of old mines constitutes an important research objective for our institution, BRGM. The study reported here shows the contribution of high-frequency (>30 kHz) acoustic emissions to the detection of the damage within a rock mass, during an experiment within a pilot site of an old flooded iron mine. The experiment consisted of recording all the hydroacoustic events in a broad frequency band (between 30 Hz and 180 kHz), during 18 months. The monitoring network has been calibrated by a triggered block fall that made it possible to highlight a relationship between the occurrence of high-frequency/low-frequency hydroacoustic emissions and rock falls. The events recorded have been associated with the micro-failure of the rock mass near the roof, prior to the detachment of the blocks. This monitoring showed important high-frequency hydroacoustic activity, which may be associated with mechanical instabilities generated by the evolution of water pressure during the experiment. In conclusion, the high-frequency hydroacoustic activity appears to be a good indicator of instability and, therefore, this new technique constitutes a promising tool for monitoring abandoned underground cavities.

International audience; An integrated analysis on the relationship between rainfall and displacement in the most active area of the Séchilienne unstable slope was performed. This study combines several techniques and models to adequately reproduce the landslide movement induced by the rainfall. The analysis of available time series shows a long term trend and seasonal variations in the displacement, respectively independent and synchronous to precipitations. In particular wavelet analysis highlights that the movement is rather linked to groundwater recharge than to precipitation (rainfall + snowfall), involving then the importance of groundwater process in the area. A first and simple relationship between the water input and the fluctuations of displacements apart from the general trend is shown using a tank model. Moreover, a seasonal analysis of this relationship was performed, showing that displacement rate follows the behavior of the hydrological cycle. Two different models were applied to the long temporal series of extensometric and precipitation data: the FLAME model, from BRGM and the FORESEES model, from Univ. Lausanne. These tools are based on a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in precipitation amounts. The forecasting tool FLAME associates 1) a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the rainfall and the displacements, and 2) a 1D mechanical (ME) model (e.g. visco-plastic rheology), in order to take into account changes in pore water pressures. The performance of different combinations of models was evaluated against observed displacement rates at the selected pilot study area. Our results indicate that both models are able to reproduce, with a high degree of accuracy, the observed displacement pattern in the general kinematic regime. Finally the variability of the results, depending in particular on the input data, is discussed.

International audience; The destructive 1999 Chi-Chi earthquake (Mw 7.5) was the largest inland earthquake in Taiwan in the 20th century. Several observations witness the non-linear seismic soil response in sediments during the earthquake. In fact, large settlements as well as evidence of liquefaction attested by sand boils and unusual wet ground surface were observed at some sites. In this paper, we present a seismic response simulation performed with CyberQuake software on a site located within the Chang-Hwa Coastal Industrial Park during the 1999 Chi-Chi earthquake in Taiwan. A non-linear multi-kinematic dynamic constitutive model is implemented in the software. Computed NS, EW and UP ground accelerations obtained with this model under undrained and two-phase assumptions, are in good agreement with the corresponding accelerations recorded at seismic station TCU117, either for peak location, amplitudes or frequency content. In these simulations, liquefaction occurs between depths 1.3 and 11.3m, which correspond to the observed range attested by in place penetration tests and other liquefaction analyses. Moreover, the computed shear wave velocity profile is very close to post-earthquake shear wave velocity profile derived from correlations with CPT and SPT data. Finally, it is shown that in non-linear computations, even though a 1D geometry is considered, it is necessary to take into account the three components of the input motion.

National audience; This work focuses on the use of a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in rainfall amounts. The forecasting tool associates a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the input signal (e.g. rainfall) and the output signal (e.g. displacements) and a simple 1D mechanical (MA) model (e.g. visco-plastic rheology) to take into account changes in pore water pressures. The models have been applied to forecast the displacement rates at the Super-Sauze landslide (South East France), one of the most active and instrumented clayey landslide in the European Alps. Results indicate that the three models are able to reproduce the displacement pattern in the general kinematic regime with very good accuracy (succession of acceleration and deceleration phases); at the contrary, extreme kinematic regimes such as fluidization of part of the landslide mass are not being reproduced: this statement, quantitatively characterised by the Root Mean Square Error between the model and the observations, constitutes however a robust approach to predict changes in displacement rates from rainfall or groundwater time series, several days before it happens. The variability of the results, depending in particular on the fluidization events and on the location of displacement data is discussed.

International audience; This work aims at assessing the impact of local heterogeneities consideration in slope mechanical modelling. We choose to use different geophysical techniques to characterize these heterogeneities, and a fuzzy logic data fusion concept to create a geometrical model from these data. The first mechanical simulation, realized with basic elastic constitutive law, gives a surface displacement pattern in agree-ment with the one measured. This highlights the importance of the model's layer geometry on the results and also the suitability of geophysical imagery tools to constructs high resolution geometrical models.

Global changes would have direct impacts on landslide activities through the modifications of triggering events with the evolutions of climate forcing. Howev-er, some predisposing factors would also evolve. Indeed, forests are likely to be modified, either by anthropogenic interventions, natural ageing or adaptation to climate change. This evolution is likely to result in changes of slopes susceptibili-ties to landslides. In order to propose adequate solutions for current and future for-estry management, it is therefore necessary to properly estimate the influences of the vegetation on slope stabilities. In the present study, we develop a complementary module to our large-scale slope stability assessment tool to take into account the effects of vegetation on the mechanical soil properties (cohesion and over-load), but also on the slope hydrol-ogy (change in interceptions, run-off, and infiltration). Hence the proposed meth-od combines a mechanical stability model (using finite slope analysis), a hydro-logical model, and a vegetation module which interfere with both aspects. All these elements are interfaced within a GIS-based solution. Uncertainties on input data are propagated in the models through distributions laws. The method has first been applied to a Pyrenean Valley, a site which is part of the Observatoire Pyré-néen du Changement Climatique (OPCC). A second application is being under-taken on another Pyrenean Valley, for the ANR Project SAMCO.

International audience; The prediction of landslide movement acceleration is a complex problem, among others identified for deep-seated landslides, and represents a crucial step for risk assessment. Within the scope of this problem, the objective of this paper is to explore a modelling method that enables the study of landslide function and facilitates displacement predictions based on a limited data set. An inverse modelling approach is proposed for predicting the temporal evolution of landslide movement based on rainfall and displacement velocities. Initially, the hydrogeology of the studied landslides was conceptualised based on correlative analyses. Subsequently, we applied an inverse model with a Gaussian-exponential transfer function to reproduce the displacements. This method was tested on the Grand Ilet (GI) and Mare-à-Poule-d'Eau (HB) landslides on Reunion Island in the Indian Ocean. We show that the behaviour of landslides can be modelled by inverse models with a bimodal transfer function using a Gaussian-exponential impulse response. The cumulative displacements over 7 years of modelling (2 years of calibration period for GI, and 4 years for HB) were reproduced with an RMSE above 0.9. The characteristics of the bimodal transfer function are directly related to the hydrogeological functioning demonstrated by the correlative analyses: the rapid reaction of a landslide can be associated with the effect of a preferential flow path on groundwater level variations. Thus, this study shows that the inverse model using a Gaussian-exponential transfer function is a powerful tool for predicting deep-seated landslide movements and for studying how they function. Beyond modelling displacements, our approach effectively demonstrates its ability to contribute relevant data for conceptualising the sliding mechanisms and hydrogeology of landslides.

Landslide failures may seriously damage the human and environmental resources of a region. However, it is still uneasy to forecast the evolution of a landslide because it depends both on its dynamics and on external triggering events, such as earthquakes and rainfall (Guzzetti et al. 2007). To better understand these processes, passive seismic monitoring techniques have been developed since the 1960s, in order to detect possible seismic signals triggered by the slope dynamics (Cadman & Goodman 1967; Novosad et al. 1977). It consists generally in identifying seismic sources induced by the slope movement using seismic sensors. This work focuses on the characterisation of seismic sources observed in at La Valette landslide (South French Alps) which is representative of landslides developped in clays. Hydro-acoustic devices installed permanently in boreholes since October 2012 are used to detect seismic events and relate their occurence to environmental factors (rain, groundwater level variations) and to the surface displacement of the landslide.

International audience; Observations from many recent strong motion events have shown the importance of local soil conditions and non-linear soil behaviour on the seismic ground response (site effects). As demonstrated by previous seismic microzoning studies (Lebrun et al.) [1]), as well as by at least three historical major earthquakes, Pointe-à-Pitre is prone to strong site effects, due to the particular geology of the area. In this paper, we present a comparison between the strong-motion data available from the stations operating on the swampy site of Pointe-à-Pitre airport and the ground motions derived from 1D non-linear finite element simulations. Results show that, for moderate to strong ground motions, 1D simulations reproduce the main characteristics of site response in terms of duration, energy distribution, amplitude and frequency content. It also shows the importance of very superficial soft layers as peat or saturated mud in low frequency site effects simulations. This point is important for further engineering studies since such very soft formations overlain by stiffer landfills are commonly expected in the Antilles context. Our work also shows that Anderson's criteria, used to quantify the goodness-of-fit of simulated ground motions to the observed ones, appear to be an interesting diagnostic tool for testing the quality of numerical simulations from an engineering point of view.