Recent works on landslide displacement forecasting using machine learning or deep learning models show relevant performance. However, they are mostly based on the use of historical displacement information and do not provide information on the most predictive features in terms of meteorological and hydrogeological variables for the forecast, and thus the identification of possible precursory factors. In this context, providing approaches based on EXplainable Machine Learning (XML) is essential for landslide forecasting as it concerns making decisions about risk mitigation actions, it supports the identification of possible precursory factors and it increases confidence in the predictions.The proposed XML-based landslide forecasting approach is developed and tested using ensemble learning methods such as Random Forest and XGBoost. It relies on the use of multi-year and multi-parameter data chronicles to analyse the relationships between surface displacements (target data) and hydro-meteorological conditions (predictor data). Displacement and meteorological data are acquired through the landslide monitoring network. Hydrological data, when not available, are simulated discharge calculated with reservoir based-model; the simulations allow to construct water level time series for each water reservoirs identified in the unstable slope. The predictive time series are decomposed into a set of 340 descriptive features (mean, variance, difference, number of rainy days, number of consecutive rainy periods of X days, …). The displacement time series are detrended using the multiplicative decomposition method.This method has been applied to several use cases, such as the Séchilienne landslide located southwest of the Belledonne massif (French Alps). The Random forest and XGBoost models are trained and tested over periods of 12 and 5 years respectively, and applied to three automatic extensometers located in the most active part of the landslide. The results indicate that the main features used include variations in water levels over past 10 to 30 days, as well as the number of consecutive rainy period during the month. These results are associated with accurate predictions for the three extensometers, with coefficients of determination ranging between 0.37 and 0.46.We show that these models have high predictive power while informing about the most important hydro-meteorological features. The application of the models to trendless displacement time series significantly improves prediction accuracy.

Deep-seated landslides are affected by slow and progressive deformation with successive acceleration/deceleration periods controlled by hydro-meteorological factors and slope structures. Simulating groundwater pressures in deep-seated landslides is critical to understanding their mechanisms, forecasting their evolution in time, and estimating landslide hazards. Validating complex deterministic physically based models for deep-seated landslides is challenging in terms of multi-parameter observations and the identification of the physical properties of the media. Using simpler empirical tank models, allowing the simulation of water mass balance and fluxes, is an alternative to simulating their behavior. Tank models must conceptualize the main water reservoirs and use a long history of monitoring observations (rainfall-groundwater levels) to train the model parameters. This study aims at modelling the hydrological dynamics of two deep-seated landslides in fractured rocks (Séchilienne, Mont de La Saxe) with the KarstMod open-source library. Analyzing 6 to 9 years of monitoring data allows for the models’ calibration and validation. Two model structures are identified: the Séchilienne landslide’s model, which consists of two tanks and a direct flux to the outlet representing a bimodal flow, and the Mont de La Saxe landslide’s model, which integrates a snow routine and consists of two and a flux feeding a reservoir, representing unimodal flow. The models are validated over 3 and 2 years, respectively. They allow the prediction of the discharge and groundwater levels over time, reproducing the slope hydrology in the past before the setup of the monitoring system, thus providing insights into identifying hydrological thresholds controlling landslide motion.

This study aims to analyze spatio-temporal piezometric data and integrate them with geological, geotechnical, and geophysical data to enhance their interpretation. The research focuses on a site located in the Meuse and Haute-Marne departments of France, which has been under investigation since 1994 as part of the surface facilities characterization for the Meuse-Haute-Marne underground laboratory and the CIGEO (Centre Industriel de stockage Géologique) Andra project. These investigations span different spatial and temporal scales. We observed the contribution of water masses associated with external forcing and identified two types of aquifer responses: a rapid response to rainfall events when fractures are well-connected, and minor reactivity at the matrix level. Additionally, we demonstrated that the matrix compartment can be finely characterized through a combined interpretation of piezometric response analysis, fracture analysis, and surface nuclear magnetic resonance (SNMR) soundings. The methodology developed in this project offers an improved understanding of karst piezometry and/or unsaturated zone extension, which is essential for comprehend ding flow dynamics and better constraining the functioning of karst aquifers. Furthermore, this site serves as an ideal workshop for studying flow in fractured media, providing valuable insights into hydrodynamic behavior in complex subsurface environments.

Documenting landslide activity over long periods and monitoring standards (sensors, acquisition rates, quality-control) is critical for understanding the landslide forcing factors, develop process-based models, identify the effect of climate change on their behavior, and ultimately define warning thresholds.The French Landslide Observatory (Observatoire Multi-Disciplinaire des Instabilités de Versants) OMIV is the service of the French Research Institute (CNRS) in charge of deploying, acquiring, exploiting and disseminating multi-parametric sensor data over several large landslides in France. OMIV has developed, since more than 15 years, standards in terms of sensor types, using both high-grade and low-cost sensing in order to construct reference and spatially dense monitoring time series. The service provides open access to records of landslide kinematics, landslide micro-seismicity, landslide hydro-meteorology and landslide hydro-geophysics. Combined, these four categories of observations are unique worldwide for long-term landslide observations. OMIV is currently supervisizing the acquisition and dissemination of sensor data on 8 permanent unstable slopes (Avignonet/Harmallière, La Clapière, Séchilienne, Super-Sauze/La Valette, St-Eynard, Pégairolles, Vence, Villerville) and on unstable slopes currently experiencing gravitational crises (La Clape, Viella, Marie-sur-Tinée, Aiguilles). The service is organized around the dissemination of qualified data (in international reference file format) and products for 5 categories of observation (Geodesy, Seismology, Hydrology, Meteorology, Hydrogeophysics). For each categories of observation, specific FAIR data repository and access portals have been developed and automated processing methods have been proposed to meet the needs of the landslide research community. The products being generated are time series of GNSS and total station positions, catalogue of endogeneous landslide micro-seismicity, resistivity tomography datasets, and hydro-meterological parameters).OMIV provides consistent and harmonized landslide monitoring data in order to identify the physical processes that control the landslide dynamics, both for slopes affected by slow-moving slides and cliffs affected by rockfalls, use these datasets to develop and validate landslide deformation/propagation models, extract (from the long-term observations) the patterns that may characterize changes in the landslide dynamics (annual, seasonal, event) and propose possible forerunners. The OMIV observations aim at contributing at identifying the key controlling parameters of different landslide types (e.g. soft/hard rock, cohesion/friction, slip/fracture, localized/diffuse damage) and at monitoring their evolution in time and space (deceleration or acceleration according to the triggering factors, sliding- flowing transition).The objectives are to present the OMIV datasets, sensing standards and automated processing methods that has been developed, both for the science community and for operational partners in charge of landslide risk management (ONF-RTM, BRGM, CEREMA), for some of the monitored landslides. The objectives are also to present the future directions of the service with a focus on the modelling of the landslide processes using both process-based and machine learning approaches.

The versatility, cost-efficiency and easy deployment of seismic sensor nodes facilitate geophysical monitoring in environments that were previously inaccessible for instrumentation, and among them landslides and unstable slopes, most of the time located in remote mountains. Using nodes allows for the setup of dense arrays with sensor inter-trace distances that become compatible with the geometries and dimensions of the geological structures to image. This becomes particularly true for landslides which have complex 3D architectures (hummocky bedrocks, layering, multi-dimensional fractures, diverse geotechnical material, deep and perched aquifers and water circulations) and are shallow processes with respect to the classical investigation depths and sensitivity of most geophysical survey techniques.Here we develop a specific processing workflow to allow the computation of 3D shear-velocity models with Ambient-Noise-based tomography applied to dense arrays of seismic stations. The workflow is applied to a dataset acquired at the Viella shallow landslide (France) developed in altered schists and moraine deposits. We deployed 70 IGU-16HR-3C-5Hz SmartSolo sensors (EOST/PISE service) with inter station distances of 70 m for a period of 25 days.The processing consists in several steps, all of them being tuned to the specific case of shallow depths of investigation. In areas where only few strong (ML>4) earthquakes are triggered, with a low azimuthal distribution, surface-waves velocity fields are complex to estimate with earthquakes. Ambient noise cross-correlation tomography has the advantage of using the ambient noise to model the surface waves velocities by retrieving the interstation Green’s functions. The main hypothesis for retrieving the Green’s functions is a homogeneous noise-source distribution, which is never achieved in a natural environment. Therefore, data filtering and daily stacking are crucial to reduce the effect of non-uniform noise distributions and lead to consistent velocity models. Due to the noisy environment of Viella (torrential flows, farming activity, anthropogenic noise), several procedures were implemented to optimize the processing (reduction of the coherent noises in the processed data, use of a pseudo-topography to estimate as accurately as possible the inter-station distances and travel times). We then computed the dispersion curve diagrams for the surface waves on which we applied a strict selection to only keep the consistent part of the surface waves dispersion curves. The selection parameters were optimized for the Rayleigh and Love waves. Then, we inverted the inter-station travel times to compute group velocities maps at several frequencies. Finally, we proceed to a Markov-Chain-Monte-Carlo inversion of each of the dispersion curves extracted from the group velocity maps. We finally obtained a 3D shear velocity model, which is further combined with geological and borehole information in order to document the 3D structure.The objectives are to present the processing workflow developed specifically for shallow imaging and the retrieval of 3D heterogeneities; effects of the processing parameters will be discussed on the Viella dataset. The approach developed for Viella is generic and has been further applied to other geological processes (permafrost at the Chauvet rock glacier, Marie-sur-Tinée mudslide), and the models will be discussed.

Over the last decade, many Electrical Resistivity Tomography (ERT) surveys have been acquired on landslides, both from surface and boreholes. The surveys aimed at inferring the geometry of the landslide body, at imaging conductive and resistive structures possibly linked to in-depth water storage, and even at qualifying underground water flows. Several ERT galvanic-type configurations have been deployed according to the sites, all of them using buried metallic electrodes as conductors. Devices were deployed both on hard rocks (mostly crystalline) and soft rock (mostly clayey) landslides, and most were associated with hydrogeological observations (soil temperature, groundwater table, soil humidity). The acquired time-lapse resistivity profiles represent real added-value information for the long-term understanding of landslide processes and their links to meteorological and hydrological triggering factors. In France, most of the ERT surveys on landslides were acquired by the French Landslide Observatory (OMIV) of the Institute of Earth and Universe Science (INSU), in collaboration with many Universities (Strasbourg, Nice, Montpellier) and with the Geological Survey of Austria (Vienna). The electrical resistivity datasets are acquired either individually on particular dates with possible repeated measurements or at high-frequency with fixed and automated measurement devices and permanent arrays. At the surface, multi-electrode ERT surveys are recorded by SYSCAL Pro (Iris Instrument) or GEOMON4D resistivimeters (GSA / Supper et al., 2002). Using the GEOMON4D device, at least 2 measurements of resistance are performed daily (using multiple gradient array). The SYSCAL resistivity surveys are measured every day using a Wenner-Schlumberger array. In boreholes, dipole-dipole electrical soundings are recorded daily using an autonomous acquisition system (ImaGeau®) with inter-electrode spacings of one meter. The objective of this work is to present the OMIV-ERT free online repository of electrical resistivity data. Data are provided at three interpretational levels: (i) raw data (Vn and In, level 0), (ii) filtered and computed apparent resistivity (level 1), and (iii) inverted data (resistivity model, level 2). The information system consists of a PostgreSQL/PostGIS spatial database, R and Python scripts for data pre-processing and integration in the database. The pyGIMLi (Rücker et al., 2017) library is interfaced with R scripts to invert the resistivity data (from level 1 to level 2). An R-shiny-based web interface for data visualization and download is accessible online. The OMIV-ERT database will permit analyses of relationships between measured resistivities and landslide conditions.

Following a rockslide in 2018, a landslide was reactivated affecting the town of Viella in the Hautes-Pyrénées (South France). The slope movement threatens road infrastructure and buildings. The landslide is in the Bayet-Badoueil watershed. This torrential stream has its source on the heights of Viella and has the Bastan river as its outfall. The Bastan flows at the toe of the landslide. The landslide is compartmentalized and covers an area of about 50 ha. he is composed of a morainic floor on which colluvium and scree have been deposited following the dismantling of the mountain above Viella. The whole thing rests on a Devonian substratum. The colluviums are composed of schists and limestones (Devovian). The study aimed at improving the state of knowledge of the Viella landslide to better manage the natural disaster. Water circulation within the massif is the motor of the sliding. Modelling the hydrogeological conditions allow better understanding the phenomena and will help to design mitigation solutions. A three-dimensional geological model was built as a prerequisite of the hydrogeological modelling with the 3D GeoModeller software. The model was built from the geological map, the logs of the fifteen drillings, including eight piezometers and seven inclinometers, as well as 3D geophysical models (3D resistivity model, 3D P-wave velocity model). The heterogeneity of the colluvium was simplified into two layers to locate the rupture surface at the interface of these layers. The depth of the rupture surface in relation to the topographic surface varies from a few meters below the Bayet to 55 meters deep at the I10 inclinometer. The construction of the geological model makes it possible to improve knowledge of the local structures and to propose geometry for the formations and the position of the rupture surface. The realization of a three-dimensional finite element water flow model, built from the geological model and an electrical resistivity model, with the software FEFLOW (©DHI) provides an understanding of the functioning of the landslide aquifer. This integrative approach on hydrogeological modeling makes it possible to propose a robust model which made it possible to establish the piezometric map of the site at equilibrium. In the landslide, the piezometry is between 780m and 970m the general orientation of the groundwater flow is about 340° north. The hydraulic conductivities determined by the model are between 10-4 and 10-5 m.s-1 in the colluvium under the village. From the calibrated model, various simulations were carried out to estimate the impacts of mitigation works on the water storage and circulation. It further helped to simulate the piezometric response of the slope to a flood event at the toe of the landslide. Model simulations showed that the (“sealing” or “waterproofing”) of a 650m section in the lower part of the Bayet-Badoueil stream would lower the piezometric height under the village to a maximum of 30m and reduce the hydraulic load upstream of the landslide. A decrease of 5 to 10 meters seems achievable and would be sufficient to significantly reduce the sliding kinematics.

Deep Seated Gravitational Slope Deformation (DSGSD) are gravitational processes damaging slopes over long periods of time. These processes may be reactived with the occurrence of smaller, shallow gravitational events. Thus, a better understanding of DSGSDs, from their formation to more catastrophic phases of activity, is an important goal for natural hazard prevention in mountainous areas. .A first inventory of DSGSD in the Western Alps has been proposed by Crosta et al. (2013) with 1057 DSGSDs identified. A similar work has been conducted more recently at the scale of the French Alps by Blondeau (2018) who identified nearly 460 DSGSDs. Despite the importance of these works, there are still many Alpine sub-massifs where high concentrations of DSGSDs (Blondeau., 2018) have been recognized but where no detailed studies have been conducted. This is the case of the Queyras Massif (South French Alps). It is in this context that this study is carried out, with both the objectives of locating and characterizing the DSGSDs observed in this area and identifying their recent activity. The proposed approach is based on quantitative geomorphological studies combining photo-interpretation of multi-date aerial imagery, analysis of DSMs and field observations. Quantitative description criteria are proposed to identify DSGSDs and discriminate them from large deep-seated landslides. Thirty DSGSDs are inventoried and their lithological and structural setting is analyzed. Analysis of multi-date aerial photographs and InSAR derived landslide velocities (NSBAS processing of Sentinel-1 observations; e.g. André et al., XX?) allow characterizing their gravitational activity.

Following a rockslide in 2018, a landslide was reactivated affecting the town of Viella in the Hautes-Pyrénées (South France). The slope movement threatens road infrastructure and buildings. The landslide is in the Bayet-Badoueil watershed. This torrential stream has its source on the heights of Viella and has the Bastan river as its outfall. The Bastan flows at the toe of the landslide. The landslide is compartmentalized and covers an area of about 50 ha. he is composed of a morainic floor on which colluvium and scree have been deposited following the dismantling of the mountain above Viella. The whole thing rests on a Devonian substratum. The colluviums are composed of schists and limestones (Devovian). The study aimed at improving the state of knowledge of the Viella landslide to better manage the natural disaster. Water circulation within the massif is the motor of the sliding. Modelling the hydrogeological conditions allow better understanding the phenomena and will help to design mitigation solutions. A three-dimensional geological model was built as a prerequisite of the hydrogeological modelling with the 3D GeoModeller software. The model was built from the geological map, the logs of the fifteen drillings, including eight piezometers and seven inclinometers, as well as 3D geophysical models (3D resistivity model, 3D P-wave velocity model). The heterogeneity of the colluvium was simplified into two layers to locate the rupture surface at the interface of these layers. The depth of the rupture surface in relation to the topographic surface varies from a few meters below the Bayet to 55 meters deep at the I10 inclinometer. The construction of the geological model makes it possible to improve knowledge of the local structures and to propose geometry for the formations and the position of the rupture surface. The realization of a three-dimensional finite element water flow model, built from the geological model and an electrical resistivity model, with the software FEFLOW (©DHI) provides an understanding of the functioning of the landslide aquifer. This integrative approach on hydrogeological modeling makes it possible to propose a robust model which made it possible to establish the piezometric map of the site at equilibrium. In the landslide, the piezometry is between 780m and 970m the general orientation of the groundwater flow is about 340° north. The hydraulic conductivities determined by the model are between 10-4 and 10-5 m.s-1 in the colluvium under the village. From the calibrated model, various simulations were carried out to estimate the impacts of mitigation works on the water storage and circulation. It further helped to simulate the piezometric response of the slope to a flood event at the toe of the landslide. Model simulations showed that the (“sealing” or “waterproofing”) of a 650m section in the lower part of the Bayet-Badoueil stream would lower the piezometric height under the village to a maximum of 30m and reduce the hydraulic load upstream of the landslide. A decrease of 5 to 10 meters seems achievable and would be sufficient to significantly reduce the sliding kinematics.

Peatlands and associated ecosystem services are sensitive to climate changes and anthropogenic pressures such as drainage. This study illustrates these effects on the Forbonnet bog (7 ha), belonging to the Frasne peatland complex (~300 ha, French Jura Mountain), and shows how they can inform about the ecohydrological functioning of peatlands. The southern part of the Forbonnet bog was restored in 2015–2016 by backfilling of artificial drains dating from the end of the 19th century. Piezometric data from 2014 to 2018 allow to evaluate the restoration effect on the water table depth (WTD) and highlight the reactivation of lateral inflows from the surrounding raised peatland complex. Vertical electrical conductivity (EC) profiles permit to identify three main peat compartments depending on different water supplies arguing for a nested hydrological functioning. This involves (1) one‐off karst groundwater inputs at the substratum/peat interface supplying the deepest peat layer, (2) lateral seepage inputs from the neighbouring raised wooded peatlands sustaining the intermediate peat level and (3) direct rainfall infiltrating the most superficial peat layer. This nested multi‐reservoir model operates at various spatio‐temporal scales and is consistent with the complex seasonal hydrological and physico‐chemical response at the bog outlet, which will be increasingly affected by climate change in the coming decades.

Summary In order to characterize the structure and the distribution of geological materials at the Viella landslide, two dense 3D geophysical tomographies were realized. The spatial distribution of electrical resistivity and of the p-wave travel-time were indeed modeled. The resistivity model revealed clearly a complex organization in the subsurface. The p-wave velocity model, sparsely resolved, allowed to observe some spatial variations, coherent relatively to the resistivity model. To take at best advantage of these two data sets, data fusion techniques are explored, integrating the two 3D tomographies together with geodynamic surface-data (lime-lapse LiDAR observations and tacheometer data at high temporal frequency), borehole core samples analysis, as well as piezometric and inclinometric data.

Peatland hydrology forms, together with vegetation cover and carbon dynamics, a sensitive interconnected three-pillar system, which furnishes essential ecosystem services from the local (specific biodiversity, interaction with the watershed) to the global scale (carbon and fresh water storage). The present study focuses on the hydrological function of the Frasne peatland, and especially investigates how restoration of water supplies can be used to mitigate climate change effects on peatland hydrology and sustainability. In this perspective, the Forbonnet bog, belonging to the Frasne peatland complex (300 ha; French Jura Mountains; 46.826 N, 6.1754 E; 850 m a.s.l) is monitored in the framework of the French observatory of peatland (SNO Tourbières) since 2008. The site, restored in 2015 (European program "Life Tourbières"), is located in a wide karstifed syncline overlain by moraine deposits. Between 2009 and 2019, mean annual precipitation and air temperature were respectively 1618 mm and 7 °C. In order to identify and model water supply and transfers at the ecosystem scale, this study combines a range of hydrological, geochemical and reservoir modeling approaches. This enabled us to propose a conceptual scheme of the hydrological functioning that implies a nested organization of 3 water origins: (1) The superficial reservoir (acrotelm) featuring a low mineralization, has a fast (daily) reactivity to precipitation, suggesting a strong dependence to direct atmospheric inputs. In addition, the outlet discharge shows a complex relation with the water level of this layer, highlighting a threshold effect where the saturation degree of the acrotelm seems to be involved. (2) Five years of outlet discharge and electrical conductivity (EC) monitoring highlight a seasonal pattern. During low flow periods (June-Oct.) EC is positively correlated with rainfall recharge of the previous winter (Nov.-May). Furthermore, the bog water budget is loss-making when only considering the topographical watershed. Considering the geological context, these elements argue for groundwater inflows from the surrounding karst aquifer likely occurring at the base of the bog, throughout the permeable or discontinuous moraine layers. Vertical EC profiles show that these inflows supply the mineralized water deep reservoir of the bog. (3) The monitoring of the restoration effects (by backfilling of drainage channels) through panpipe piezometers suggests that lateral seepage from the neighboring wooded, more elevated and mature peatlands supplies a transitional peat reservoir. Moreover, spatial (horizontal and vertical) and temporal EC variability argue for advective water transfers through the bog. This work supports the interest in monitoring over the long-term (several and contrasted hydrological years) for constraining hydrological processes. The three water supplies delineated could have contrasted responses to climate change and then impact both biological and carbon cycles. This work also highlights the importance to integrate hydrological processes beyond the ecosystem scale, to consider climate change and anthropogenic pressure effects on the regional hydrology that probably interact with peatlands in mountainous environments. In this perspective, the current hydrological monitoring is nowadays combined with isotopic (δ18O and δ2H) evaluation to refine this conceptual scheme and quantify the contribution of the 3 identified water flow paths.

Large scale slope instabilities are complex objects controlled by multiple parameters. The underground and superficial structure of the slope plays a major role as it often controls water circulations, potentially causing weathering and damaging processes, and permits the local storage of water masses, causing temporary overload. In addition, the structure of the subsurface often delineates rock-volumes with variable mechanical properties, whose spatial distribution greatly influences the behavior of the slope. This work illustrates how Dense 3D Electrical Resistivity Tomography can provide relevant constraints on these parameters. The village of Viella, in France (Hautes-Pyrénées), is affected by strong slope movement since 2018, when a massive rockslide above the village modified the stress conditions of the entire slope and, potentially, the hydrogeological context. As a consequence, some houses and infrastructures are progressively damaged, leading to heavy measures (houses evacuation). This complex, deep-seated (> 80 m), slope instability covers an area of ca. 650 000 m², is primarily composed of altered shists, colluviums, and non-consolidated alluvial deposits, forming several kinematic units with surface velocities in the range [0.5 – 5] mm.month-1. A 3D dense electrical resistivity tomography was realized using the FullWaver system, to characterize the structure and the forcing factors of this unstable slope. 55 V-FullWavers receivers (3 -electrodes, 2 channels sensors) were quasi-evenly distributed over a surface area of 400 x 500 m² with an interval of 90 m, apart from the village area, where no electrode could be grounded. Each V-FullWaver recorded signals through two orthogonal dipoles of 25 m length. Current injections were realized with a high-power transmitter (6 kW, 16 A, 3000 V). 235 injection dipoles were used. The system injected current between a fixed remote electrode (more than 1 km away from the site to increase the investigation depth) and a local mobile electrode, moved all over the investigated area in between the V-Fullwaver receivers, with an interval of approximately 40 m, except in the village area. The resulting 3D resistivity model presents a high spatial variability until 100 to 150 m depth approximately, that highly relates to the complex strain dynamics of the slope and the hydrogeological observations. It highlights the relation between the most active kinematic compartments and the large-scale structure of the slope. It provides a first understanding of the role of local compacted rocks in the buildup of surface deformation but also on the localization of heterogeneities (fissures, scarps) which may relate to water circulation paths. . This 3D image of the slope is the first structural reference model for future hydrogeological and geomechanical studies aiming at deducing the possible evolution of the slope.

This study makes use of a highly instrumented active landslide observatory (9 years of data) in the French Alps, the Séchilienne slope. Here, we use a combination of major element chemistry and isotopes ratios (87Sr / 86Sr, δ34S) measured in different water types of the stable and unstable part of the Séchilienne instability to assess the contribution of the different lithologies of the slope and the chemical weathering mechanisms. Chemical and isotopic ratios are used to characterize weathering processes and the origin of waters and their flow paths through the massif. A mixing model allows us to allocate the different major elements to different sources, to identify secondary carbonate formation as a major process affecting solutes in the subsurface waters of the instability, and to quantify the involvement of sulfuric and carbonic acids as a source of protons. We show that the instability creates favorable and sustained conditions for the production of sulfuric acid by pyrite oxidation, by opening new fractures and supplying fresh reactive surfaces. We clearly identify the contribution of the dissolution of each mineral phase to the chemistry of the waters, with a clear role of remote gypsum dissolution to the sulfate budget in the sampled waters. We are also able to refine the preexisting hydrogeological views on the local water circulation and water flow paths in the instability by showing the hydrological connectivity of the different zones. Overall, our results show that the Séchilienne landslide, despite its role in accelerating rock chemical and physical weathering, acts as a geological source of CO2 to the atmosphere. If generalizable to other large instabilities in mountain ranges, this study illustrates the complex coupling between physical and chemical erosion and their impact on the carbon cycle and global climate. The study also highlights the importance of distinguishing between sulfite oxidation and gypsum dissolution as a source of sulfate ions to rivers, particularly in mountain ranges.

Peatlands are habitats for a range of fragile flora and fauna species. Their eco-physicochemical characteristics make them as outstanding global carbon and water storage systems. These ecosystems occupy 3% of the worldwide emerged land surface but represent 30% of the global organic soil carbon and 10% of the global fresh water volumes. In such systems, carbon speciation depends to a large extent on specific redox conditions which are mainly governed by the depth of the water table. Hence, understanding their hydrological variability, that conditions both their ecological and biogeochemical functions, is crucial for their management, especially when anticipating their future evolution under climate change. This study illustrates how long-term monitoring of basic hydro-meteorological parameters combined with statistical modeling can be used as a tool to evaluate i) the horizontal (type of peat), ii) vertical (acrotelm/catotelm continuum) and iii) future hydrological variability. Using cross-correlations between meteorological data (precipitation, potential evapotranspiration) and water table depth (WTD), we primarily highlight the spatial heterogeneity of hydrological reactivity across the Sphagnum-dominated Frasne peatland (French Jura Mountain). Then, a multiple linear regression model allows performing hydrological projections until 2100, according to regionalized IPCC RCP4.5 and 8.5 scenarios. Although WTD remains stable during the first half of 21th century, seasonal trends beyond 2050 show lower WTD in winter and markedly greater WTD in summer. In particular, after 2050, more frequent droughts in summer and autumn should occur, increasing WTD. These projections are completed with risk evaluations for peatland droughts until 2100 that appear to be increasing especially for transition seasons, i.e. May-June and September-October. Comparing these trends with previous evaluations of phenol concentrations in water throughout the vegetative period, considered as a proxy of plant functioning intensity, highlights that these hydrological modifications during transitional seasons could be a great ecological perturbation, especially by affecting Sphagnum metabolism.

Deep Seated Gravitational Slope Deformation (DSGSD) is defined as a set of rock mass characterized by a very slow movement (mm.yr-1) affecting large portions of slopes of a mountain range. These typical slope instabilities must not be neglected and need to be better identified and characterized to anticipate related hazard (e.g. landslides). Characterize them requires first of all to locate them as for example recently the inventories carried out for the European Alps or in France. These specific processes, which can lead to hazard and disasters (e.g. La Clapière landslides), should not be neglected and need to be better identified and characterized to anticipate related hazard). Documenting the DSGSDs requires first of all to locate them as for example the recently published inventories initiated for the European Alps and France. These studies initiated approaches aiming at defining the factors controlling their evolution in time and space. The research developed in this study targets a better understanding the short- (<100 yrs) and long-term (> 100 yrs) evolution of DSGSDs developed in the sedimentary rocks of the Queyras Massif (South-East French Alps). The main objective is to propose models of DSGSDs evolution with key interpretations of future developments to locate possible new landslide prone areas. The Queyras Massif was chosen because it represents an under-studied area of DSGSDs. The massif is characterized by Cenozoic marine sedimentary rocks accreted and metamorphized by the Alpine orogen. The massif is characterized by a regional schistosity plunging to the West and complex and active fault networks mark the landscape (Tricart et al., 2004). The highest summits reach an altitude of 2500m a.s.l. and are separated by deep valleys incised by the Riss and Würm glaciers and currently by torrential streams. The method is based on a geomorphological analysis of the landscape and landforms, field observations and image interpretation of remote sensing data. Results allow locating the DSGSD, estimating their degree of activity, and characterizing their structure. Several dating methods (14C, 10Be or 36Cl) complete the interpretations in order to reconstruct the history of the slopes and understand the factors that control their evolution. At the scale of the massif, the DSGSDs were first identified using the approach proposed by Blondeau (2018). Visual remote sensing revealed the occurrence of thirty DSGSDs. These slopes were detected as they associate six common features commonly observed in DSGSDs. Eight DSGSDs were selected in order to investigate at the local scale their geomorphology, geology and hydrogeology and reconstruct their historical (millennial) and recent (last 50 years) evolution from dating methods and field observations. Through this multidisciplinary approach, present the observed bedrock and gravitational structural features and determine the predisposing factors of the formation of DSGSD. The research is part of the Program “Référentiel Géologique de la France / RGF – Chantier Alpes” which targets to update the geological knowledge of the Alpine basement, surficial formations and associated hazards in three dimensions and in digital format.

Sinkholes are among the most typical landforms of karst terrains. They may originate from a simple downward process, through dissolution of carbonate rocks, or through rapid, sometimes catastrophic, collapse, due to the presence of underground voids or cavities, from where the instability may eventually reach the ground surface. These two extremes imply a great variety in vulnerability of man-made structures, and damage to the population, which makes the analysis of sinkholes extremely important to society. In this contribution, we present an integrated workflow to detect, classify and analyze sinkholes. The ultimate aim is to evaluate the sinkhole susceptibility and hazard. The methodology used will be illustrated by means of an example from the karst of Apulia, south-eastern Italy.