Landslides are one of the most damaging disasters and have killed tens of thousands of people over the 21^st century. Slow-moving landslides (i.e., those with surface velocities on the order of 10^-2-10¹ m a^-1) can be highly disruptive but are often overlooked in hazard inventories due to their subtle surface signatures and slow movement. Here, we discuss an approach to automatically map slow-moving landslides using feature tracking of freely- and globally-available Sentinel-2 optical satellite imagery.

We evaluate this method through case studies from different environments in the USA, Chile, Italy, and Nepal. Our workflow identifies both known landslides and previously unknown slow-moving landslides in these case studies across very different geographical environments. In particular, in a test case on the well-documented Slumgullion earthflow, our workflow successfully delineates the active portion of the earthflow with velocity magnitudes consistent with field measurements. In another test case on the margin of the Southern Patagonian Icefield, Chile, we identified a very large (>6 km²) composite landslide in the eastern lateral moraine of Glacier Occidental, part of which catastrophically collapsed onto the glacier in early 2023. Finally, we tested our tool to the Ponzano landslide in central Italy which failed catastrophically in 2017.

We are able to detect slow-moving landslides in complex environments using 10-m resolution globally available satellite imagery, all without any manual intervention. Taken together, this means that our workflow can be applied to any region on Earth, regardless of the availability of prior information. We leverage this workflow to conduct a preliminary national-scale survey of slow-moving landslides in Nepal, identifying over 10,000 deforming hillslopes across the country, many of which are populated. Improved mapping of the spatial distribution and surface displacement rates of slow-moving landslides will improve our understanding of their role in the multi-hazard chain and can direct detailed investigations into their dynamics.

Figure: Large slow-moving landslide complex in the lateral moraine of Glaciar Oriental, Chilean Patagonia detected using our workflow.

How to cite: Van Wyk de Vries, M., Arrell, K., Basyal, G., Dadson, S., Densmore, A., Di Martire, D., Dunant, A., Francioni, M., Guerriero, L., Harvey, E., Jimee, G., Kincey, M., Li, S., Novellino, A., Pujara, D., Shrestha, R., and Rosser, N.: Regional-scale monitoring of hillslope deformation through optical satellite imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12753, https://doi.org/10.5194/egusphere-egu24-12753, 2024.

PlanetScope imagery, with its high spatial resolution (3 m) and high revisit time (possibly 1 day, according to cloud cover) is a game changer for operational landslide monitoring especially for monitoring surface deformation using Optical Image Correlation (OIC) approaches. The high spatial resolution should allow to enhance both the sensitivity and the accuracy of the measurements with the possibility to obtain a theoretical deformation detection of 0.30 m. The high revisiting time ensures the completion of dense image time series, useful to increase the Signal-to-Noise ratio associated with multiple image pairing and to possibly construct deformation time series on daily temporal scales. These two aspects of PlanetScope imagery fill the gap of current optical constellations that usually offer either lower spatial resolution with regular and rather short revisit time (e.g. Sentinel-2, Landsat-8) or very high spatial resolution with irregular revisit time (e.g. Pléiades, Worldview). However, the specifications of the PlanetScope L3B data products do not meet the expected quality in terms of ortho-rectification and image time series co-registration and a specific workflow needs to be implemented. 

We propose a new workflow for -processing  PlanetScope L3B data products. The developed approach consists firstly in removing  clouds and water, using Fmask algorithm and PlanetScope Unusable Data Mask products delivered with the L3B products.

Secondly, we observe that the misalignment between scenes  can go up to 8 pixels of difference (24 m on ground), varying highly within the images and from one image to another. To correct such errors, a co-registration process in two steps is applied. At first, using the AROSICS library (Scheffler et al., 2017), the misalignment errors at a local scale are computed by image correlation in the frequency domain on overlapping subwindows pinned on a grid covering the whole image. These offsets are used to correct the local scale co-registration errors. After this step, a global shift is still observed between scenes, leading to the second step of co-registration at global scale. The global shift is corresponding to the mean offsets between image tie points, and is corrected by applying these offsets directly on the product. These developments have been integrated within the  GDM-OPT-Slide service and have been tested on two sites: La Valette (South East France) and Aiguilles (South East France) landslides to retrieve the mean velocity and the ground displacement time series for each pixel. We validate the proposed workflow by comparing the results of the processing chain and in-situ dataset (GNSS, Lidar and photogrammetry). We show that the proposed methodology allows envisaging the operational use of Planetscope imagery to document and monitor the displacement of large landslides with velocity larger than 0.3 m/year.

How to cite: Wirtz, B., Provost, F., Malet, J.-P., and Méric, O.: PlanetScope time series for the operational monitoring of large landslide terrain motion., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19353, https://doi.org/10.5194/egusphere-egu24-19353, 2024.

Around 1300 lakes make up Tajikistan, which is situated where the Euro-Asian and Indian tectonic plates intersect, and the majority of these were formed by rockfalls and collapsing moraine deposits. Moreover, the area is susceptible to powerful earthquakes due to its localisation. In 1911 a big earthquake in the area generated the Usoi dam, which consequently led to the creation of Lake Sarez, in the Easter side of the country. The region is dominated by high snow-covered mountains, and this complicated topography makes difficult to reach and work in it. So, due to this inaccessibility remote sensing plays an important role in risk assessment and monitoring of the region. The purpose of this work is to provide a detailed overview of ground deformation of the area of Lake Sarez using both the Interferometric Synthetic Aperture Radar (InSAR) technique and optical analysis, with a specific focus on both the right bank and left bank side landslides that affect and threaten the lake.

To study and analyse the two landslides, an integrated satellite analysis has been applied with the aim to collect as much information as possible about the slope instability phenomena of the area of interest. In particular, remote sensing practices such as InSAR using the Sentinel-1, processed through the SqueeSAR approach, and an optical image correlation using COSI-Corr technique applied to SPOT-6 and SPOT-7 acquisitions have been used. In this way, a synoptic and complete analysis of the ongoing displacements was retrieved, allowing to reconstruct the temporal evolution and to solve the spatial variability of the deformation affecting the Lake Sarez banks.

The InSAR data cover the period between 2016 and 2020, and the optical images have been chosen between 2015 and 2021. The two methods emphasize movement and displacement in both right-bank and left-bank landslide, and they concur on the definition of the broader kinematic picture of landslides that doesn't seem to have significant acceleration during the monitored period. The optical method shows the movement especially in the left-side bank landslide. In addition, since the volume of the right-bank landslide is still widely debated (estimated volume around 1.4·10⁹ m³ and area 5.34km²), InSAR data have been also used to develop a model of the geometry and the depth of the sliding surface of a potential landslide that could occur and cause a huge wave that could top over the dam and create a destructive flood downstream. Data shows that most of the movement is located in the central part of the body.

The multi-perspective analysis performed has provided interesting results on the displacement and movement of the two landslides and it may represent a solid base and a starting point for modelling the mechanism of the landslides and also for the evaluation, reduction and mitigation of geohazard risks, especially in impervious areas.

How to cite: Nardini, O., Confuorto, P., Intrieri, E., Montalti, R., Montanaro, T., Robles, J. G., and Raspini, F.: Integration of satellite SAR and optical acquisitions for the characterization of the Lake Sarez landslides in Tajikistan , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15408, https://doi.org/10.5194/egusphere-egu24-15408, 2024.

In recent years, the monitoring of natural phenomena has become increasingly essential, with scientific innovations continuously enhancing its quality through more effective tools and efficient techniques. This study focuses on the synergistic utilization of two complementary monitoring techniques employed at the Poggio Baldi natural laboratory to monitor the active rock scarp: photomonitoring and laser surveys.

The Poggio Baldi landslide is one of the largest rock and debris landslide phenomena in the Emilia-Romagna Apennines, with an estimated volume of approximately 4 million cubic meters. Two documented episodes of activation occurred on March 25, 1914, and March 18, 2010, with ongoing rockfall phenomena on the scarp. To monitor the current rockfall phenomena on the landslide slope in 2021, the University La Sapienza inaugurated the Poggio Baldi natural laboratory. Over the past three years, a combination of monitoring techniques for rockfall has been employed at this site.

Utilizing affordable sensors such as optical cameras enable the daily monitoring of slopes. Through the implementation of automated acquisitions, images can be captured at an hourly frequency or even more frequently. This approach provides detailed information on rockfall occurrences, including their specific locations, affected surface areas, and the frequency magnitude relationships. To further validate rockfall occurrences, additional instruments like microphones and seismic devices can be integrated. The acquired images possess a lightweight quality, making photomonitoring a practical and cost-effective option for continuous surveillance. These images facilitate change detection analyses, allowing for the assessment of any alterations between successive images. The analytical process has been seamlessly automated to enhance efficiency.

The combined use of laser scanners and photomonitoring creates a comprehensive monitoring strategy. While laser scanners provide detailed volumetric data, photomonitoring enhances the understanding of individual events' frequency, size, and location. This combined approach leverages the strengths of each technique, mitigating the limitations of the individual methods. Relying only on periodic LiDAR acquisitions wouldn't enable us to assess whether portions of the landslide slope collapsed in a single event or multiple events, and if smaller rockfalls could be precursors to larger magnitude events. Moreover, employing this combination of permanently installing an optical instrument and conducting periodic LiDAR surveys proves advantageous both economically and in managing the volume of data.

The advantage of this combined method lies in its ability to provide both detailed, high-resolution data from laser surveys and near real-time information from photomonitoring. This approach allows for a better understanding of the ongoing dynamics of the landslide at Poggio Baldi, contributing valuable insights for hazard assessment and facilitating the development of more effective risk mitigation strategies.

How to cite: Santicchia, G., Cosentino, A., Mastrantoni, G., Molinari, A., and Mazzanti, P.: Automatic Photomonitoring Analyses for Rockfall Detection and Mapping at the Poggio Baldi Landslide, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21116, https://doi.org/10.5194/egusphere-egu24-21116, 2024.

Irrigation-triggered landslides have received much attention in recent years as they directly threaten the agricultural production and the lives of local communities. Although the triggering of such landslides has been well documented, their long-term post-triggering dynamics and complete activity history (important for landslide risk assessment) remain poorly understood. In this study, we focus on one of the largest irrigation-triggered landslides in Peru, i.e., the Punillo Sur landslide. Previous studies failed to observe and characterize the full cycle of landslide activity due to their inadequate monitoring capabilities, prompting us to combine satellite interferometric synthetic aperture radar (InSAR) and optical offset measurements to track its full 8.5-year kinematics from 2014 to 2023.

Our key findings include: (1) The landslide experienced three times of very large accelerations (i.e., three activity cycles) respectively in 2016, 2019 and 2022, with accumulated displacements of over 150 m; (2) These large accelerations, accompanied by headscarp retrogression, were all found to initiate from precursory/sudden movements of > 10 cm/yr (observed by InSAR) and were driven by long-term infiltration of irrigation water; (3) The southern portion of the landslide exhibited a greater magnitude of acceleration due to its thinner sliding layer that favors seepage-driven motion; (4) After the three large accelerations, the landslide invariably shifted to deceleration without catastrophic failures, which was found to be controlled by water evacuation and rate-strengthening friction.

These findings will serve as import materials for understanding the cycle of landslide activity and highlighting the prolonged effect of irrigation water on landslide dynamics. This will greatly increase our understanding of the long-term risk of irrigation-triggered landslides. Based on our findings, we also proposed critical disaster prevention/mitigation measures to support local communities in their disaster management efforts.

How to cite: Song, C., Yu, C., Li, Z., and Peng, J.: Satellite observations reveal the activity cycle of a giant irrigation-triggered landslide in southern Peru, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11428, https://doi.org/10.5194/egusphere-egu24-11428, 2024.

Since the first impoundment in 2003 of the Three Gorges Reservoir (TGR), one of the largest reservoirs in the world, the issues of slope instability in the Three Gorges Area (TGA) have attracted significant worldwide attention. The operation of TGR, coupled with anthropogenic activities, has influenced slope instability and reactivation of plenty of landslides in the region. This study introduces a methodology to assess the slope instabilities over TGA using advanced integration of hydrological triggering factors with multi-temporal InSAR (MT-InSAR) techniques.

Our approach involves characterizing the transient deformation of reservoir bank slopes under the coupling effect of rainfall and reservoir water level (RWL) changes. To achieve this, we propose a methodology that uses MT-InSAR analysis and regression analysis to identify triggering factors, taking into account the periods when slope instability is influenced by the drainage/storage period of the reservoir and seasonal rainfall. Determining the optimal window size for the triggering factors involves iterative searching through wavelet analysis, considering the time-lag between rainfall and RWL data. To extract step-like kinematic features for slowing-moving landslides, we apply a constrained least-squares optimization to InSAR-derived displacement time series. We then use independent component analysis (ICA) to isolate and recover the dominant source features, facilitating unsupervised spatiotemporal clustering to elucidate slope kinematics.

This study utilized nearly 100 high-resolution Spotlight TerraSAR-X (TSX) and 50 medium-resolution Sentinel-1 (S1) SAR images captured between 2019 and 2021 to assess the slope instability. Here, we first test our proposed approaches for the single Huangtupo landslide in the TGA, which is one of China's largest reservoir-wading landslides along the Yangtze River; then, the approaches have been expanded to the whole study region near the Badong County. Overall, our proposed framework is transferable and can be applied to other local landslide or regional studies for monitoring slope instability and analyzing complicated cascading hazard chains.

How to cite: Xia, Z., Motagh, M., Wang, W., Li, T., Peng, M., and Zhou, C.: Assessing instability of slow-moving landslides over Three Gorges area using InSAR techniques considering hydrogeological triggering factors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14201, https://doi.org/10.5194/egusphere-egu24-14201, 2024.

Persistent Scatterer Interferometry (PSI) is a valuable technique for investigating shallow ground displacement phenomena, such as slow landslides and subsidence. Its flexibility in time intervals and spatial scales allows to use PSI as an ideal tool for mapping and continuous monitoring over vast areas, ranging from regional to continental scales. In a four years collaboration (since 2019) between the University of Florence and the Veneto Region (Northeastern Italy), this study aims to enhance understanding of natural, gravity-induced phenomena while providing scientific support for geohazard management. The Veneto Region serves as an exemplary study site due to its complexity in terms of extent, geological setting, and geomorphological processes, challenging the PSI technique to prove its efficacy. For this work, ESA (European Space Agency) Sentinel-1 satellite constellation, with a revisiting time of 6 and 12 days (after the end of the operative life of Sentinel 1B in January 2022), were used. Radar data undergoes a set of different analysis: firstly, from Persistent Scatterer (PS)-derived deformation maps, clusters of high mean velocity were detected and classified using machine learning algorithms in order to mapping hotspot areas. Then, relevant displacement anomalies associated with periods of acceleration and deceleration of the deformation in the time series of each PS (Persistent Scatterer)  were identified and classified to recognize the cause of deformation (e.g. landslide or subsidence). Furthermore, a Principal Component Analysis (PCA) and a machine learning clustering were done on up-down and east-west InSAR components to identify specific time series patterns on regional scale. The implementation of this methodology revealed significant outcomes, particularly in the Belluno province where, in Cortina d’Ampezzo municipality, hotspot areas associated with known landslides were accurately identified and in the Lozzo di Cadore municipality, where the analysis detected high anomalous displacement rates within a narrow time frame. Notably, four anomalous PS points exhibited peak displacement rates ranging from 56 mm/yr to 78 mm/yr from February 2023 to October 2023, where no landslides were previously inventoried. The PCA and clustering procedure was successfully applied over the whole Region and, in particular, Lamosano village (Belluno province) where a known landslide movement was recognized.  This study underscores the efficacy of Sentinel-1 data for mapping and continuous, real-time ground displacement monitoring over wide areas. The cluster mapping and anomaly detection procedures proved to be crucial in identifying anomalies with high displacement rates, particularly in areas lacking prior landslide inventory. The Cortina d’Ampezzo, Lozzo di Cadore and Lamosano case studies exemplify how the PSI technique can contribute to risk mitigation strategies by suggesting updates to landslides inventories based on hotspot mapping and anomalies detection and classification. In conclusion, this work demonstrates the potential of PSI in advancing the understanding of ground displacement and contributing to proactive geohazard management.

How to cite: Barbadori, F., Becattini, F., Bianchini, S., Caleca, F., Confuorto, P., Del Soldato, M., and Poggi, F.: Mapping and monitoring ground deformations: Insights from a Sentinel-1 Persistent Scatterer Interferometry study in Northeastern Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6755, https://doi.org/10.5194/egusphere-egu24-6755, 2024.

Detection of spatial and temporal deformations of landslides, along with the acquisition of precursor information, is crucial for hazard prediction and landslide risk management. Contemporary landslide monitoring systems based on remote sensing techniques (RST) play an important role in risk management and provide important support for Early Warning Systems. Research into the feasibility of using RST for monitoring different types of landslides also includes an analysis of the impact of radar wavelength on the obtained displacement results. The paper compares the time series results of landslide displacements obtained from satellite interferometric imaging in the C-band and L-band. The focus has been particularly on analyzing how the radar wavelength can impact the accuracy of the obtained displacement values and the ability to penetrate dense vegetation, especially under conditions of varying vegetation density. This poses a significant challenge for correct displacement detection. The obtained results are particularly relevant for geographical areas, such as Poland, where a large number of landslides occur in regions covered by dense vegetation. These are the conditions under which scientists encounter the greatest challenges in accurately monitoring these areas using radar systems. The final findings of the research are an important contribution to the development of landslide risk management strategies, crucial for the safety of people and infrastructure.

How to cite: Strząbała, K., Ćwiąkała, P., and Puniach, E.: Monitoring landslides covered by vegetation using interferograms of different wavelengths, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16395, https://doi.org/10.5194/egusphere-egu24-16395, 2024.

Slope instabilities, further destabilized by global warming and extreme weather conditions, pose increasing risks to life and property. Hence, understanding these potentially destructive phenomena is crucial to mitigate associated losses. Established approaches like remote sensing and radar-based observations yield important information on surface displacement. However, seismic imaging and monitoring techniques offer complementary insights into subsurface structures, physical properties and internal time-dependent processes that drive the slope instability evolution.

The ‘Cuolm da Vi’ slope near Sedrun in Central Switzerland is one of the largest mass movements in the Alps (100-200 million m³) and is moving by up to 20cm/year. Even though it currently does not pose an immediate threat, the surface displacement of the slope instability is closely monitored. Yet, knowledge about its internal structure is limited such as, for example, the vertical extent of the unstable section which is suspected to reach several hundred meters in depth. The main objective of our project is to gain new insights into the slope instability structure and evolution. Furthermore, we aim to extend this towards innovative seismic strategies for the characterization and monitoring of large-scale mass movements in general.

In summer 2022, we deployed an extensive seismic sensor network at Cuolm da Vi covering an area of approximately 0.6 km². This network consisted of over 1'000 autonomous nodes arranged in a hexagonal grid pattern. In addition, we installed a 6-kilometer-long fiber-optic cable, targeted for long-term Distributed Acoustic Sensing (DAS) and Distributed Strain Sensing (DSS) measurements. This unique multi-sensor geophysical network enables us to investigate the unstable slope with an unprecedented level of spatial and temporal resolution, allowing us to monitor time-dependent changes over a broad spectrum of scales in space and time. During 2022 and 2023, we collected an extensive data set, including extended periods of continuous acquisition using the nodal, DAS, and DSS systems.

During the summer 2022 acquisition period, we conducted a controlled-source seismic experiment to characterize the 3D subsurface structure using seismic imaging techniques. Recordings of 163 dynamite shots by the 1’000 node array resulted in more than 30’000 P-wave first-arrival travel-time picks. Using 3D travel-time tomography, we established a first 3D subsurface P-wave velocity model of the Cuolm da Vi body. The resultant tomograms exhibit strong lateral and vertical velocity contrasts, which correlate at the surface with mapped tectonic features and identified instable sections. Furthermore, velocity anomalies within the slope instability volume indicate significant structural and/or geological variations in space. In combination with the other seismic and geotechnical information, the 3D seismic velocity model allows us to, for example, revise hazard scenarios.

How to cite: Kiers, T., Schmelzbach, C., Maurer, H., Amann, F., Edme, P., and Robertsson, J.: High-resolution 3D seismic characterization of an Alpine slope instability using a 1'000 node array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14904, https://doi.org/10.5194/egusphere-egu24-14904, 2024.

An efficient stability analysis is closely linked to a good assignment of geotechnical parameters to the strata identified in the construction of the geological model. However, it is not always possible to determine the geotechnical parameters from direct tests, but there are indirect methods in the literature for determining the main geotechnical parameters of the ground using seismic parameters such as seismic velocities.

Numerous correlations exist in the literature between shear wave velocity (VS), and the N-SPT value derived from penetrometric tests.

This study presents the geotechnical model of the Theilly landslide (Western Alps, Italy) obtained by integrating the results of a multi-parameter geophysical survey (H/V seismic noise and ground-penetrating radar) with stratigraphic and geomorphologic observations, digital terrain model and field survey data. It is shown how VS values can be related to values obtained from direct tests such as N-SPT and, using the direct or estimated N-SPT value, it is possible to directly derive the friction angle value (φ'). Although, the indirect estimation of N-SPT is subject to a higher level of error, it could be very useful in the early stages of an emergency, when direct data are not available, and a preliminary forward and backward stability analysis could be performed to assess landslide evolution and civil protection actions.

Geophysical surveys were conducted on the landslide body and on nearby locations. The H/V survey identified the presence of 2 discontinuity surfaces and thus the presence of 3 seismo-layers. The GPR survey allowed the surface portion of the slope to be studied, identifying an extremely heterogeneous debris layer.

The H/V data allowed the interface depth to be related to the frequency of the identified peaks and the VS of the identified seismic layers. It was then possible to apply empirical equations to derive the value of N-SPT, and consequently φ', from the VS obtained through the H/V measurements.

The geotechnical parameters obtained from geophysical and direct tests were used to create a geotechnical model of the landslide to perform a reliable stability analysis. The analysis of the triggering conditions of the landslide was conducted through hydrologic-geotechnical modelling, evaluating the behaviour of the slope under different rainfall scenarios, and considering the stabilization interventions present on the slope.

The results of the filtration analyses showed a top-down saturation mechanism, which resulted in the generation of positive pore water pressure in the first few meters of soil and the formation of a saturated front with a maximum thickness of 5 m. Stability analyses conducted for the same events showed the development of a shallow landslide affecting the first few meters of saturated soil.

The geotechnical parameters estimated from the geophysical tests are in agreement with the data from the direct tests and have made it possible to create a geotechnical model that is faithful to reality.

The modelling results are compatible with the actual evolution of the phenomenon and have provided insight into the triggering mechanism, providing models to support future interventions.

How to cite: Pazzi, V., Innocenti, A., Gargini, E., Segoni, S., Rosi, A., Masi, E. B., Tofani, V., and Casagli, N.: Geophysical survey for the estimation of geotechnical parameters and for the stability assessment of the Tehilly landslide (VdA, Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10833, https://doi.org/10.5194/egusphere-egu24-10833, 2024.

Moisture induced landslides in clay slopes are generally driven by heterogeneity in both saturation levels and material properties and their arising complex and dynamic interactions in the subsurface. The use of time-lapse geophysical imaging can illuminate four-dimensional subsurface moisture dynamics and geotechnical property changes at the slope-scale, thereby complementing conventional geotechnical point sampling and sensing, and geodetic observations of the ground surface. Here we consider: (1) the development of novel time-lapse geoelectrical, seismic and fibre-optic geophysical imaging technologies for landslide monitoring; (2) in-situ and laboratory derived petrophysical relationships to enable geotechnical information to be estimated from geophysical models; (3) surface topography determination and ground deformation tracking using geodetic observations; (4) coupled geophysical-hydrological modelling of slopes; (5) perspectives and recommendations for the incorporation of integrated geophysical-geodetic-geotechnical technologies into landslide early warning systems – illustrated using results from a number of long-term field observatories.

How to cite: Chambers, J., Boyd, J., Wilkinson, P., Meldrum, P., Kuras, O., Harrison, H., White, A., Swift, R., Dashwood, B., Novellino, A., Kirkham, M., Bruce, E., Donohue, S., Watlet, A., Whiteley, J., Uhlemann, S., and Binley, A.: Integrated geophysical-geodetic-geotechnical systems for slope-scale landslide monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13082, https://doi.org/10.5194/egusphere-egu24-13082, 2024.

In the last years extreme rainfall events and seasonal cumulated rainfall distribution variations occurred, increasing also the arise of slope instabilities, mostly in the more susceptible areas.

Heavy rainfall events are one of the main triggering factors in shallow landslides occurrence: therefore, a better understanding of the trigger processes is necessary, also for early warning systems development and improvement. The soil water content of the first 3-5 meters of soil becomes thus an important shallow landslide predisposing factor to monitor. At this purpose, the mainly employed technique for soil moisture monitoring is the in-situ measurement, through different types of soil probes directly installed in the first soil layers. However, despite being a very precise technique, this monitoring technique provides only for a punctual dataset.

An integrated method to extend the hydrological characterization from site-specific to a slope scale is presented, combining geotechnical analyses, field data monitoring and geophysical investigations, in particular the electrical resistivity tomography (ERT).

Geophysical models of the first subsoil were carried out through different geoelectrical investigations (2D-3D-4D) and were calibrated and interpreted based on soil monitoring data, stratigraphic logs and trenches carried out in the study areas.

Estimation of the test sites average bulk permeability was performed through time-lapse 3D-S surveys, carried out by simulating very intense precipitations through manual irrigation, that allowed to determine the resistivity variation from undisturbed to disturbed conditions.

Finally, resistivity variations were correlated to soil horizons geotechnical parameters to perform hydrogeological conceptual models of the first soil horizons.

This conference abstract is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).

How to cite: Vivaldi, V., Bordoni, M., Torrese, P., and Meisina, C.: Combined approach for hillslope hydrogeological assessment in rainfall-induced shallow landslides prone area., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11372, https://doi.org/10.5194/egusphere-egu24-11372, 2024.

Retrogressive thaw slumps (RTS) are a common permafrost related landslide type in the Arctic and provide a large amount of material to coastal nearshore zone, lakes and rivers. RTS are characterized by highly dynamic changes and rapid internal processes. Along the Canadian coastline there is an increasing number of RTS documented over the last century, acting sensitive to a warming climate.

The occurrence and behaviour of these landslides is strongly dependent on the presence of ground ice, including their likelihood for polycyclicity and reactivation. To detect and evaluate the ground ice content in different activity- and stabilization stages we used electrical resistivity tomography (ERT) on several RTS on Herschel Island in the Canadian Beaufort Sea. We combined ERT profiles remeasured 10 years apart, with orthophotos since 1952 to gain a detailed insight in their long-term behaviour, the availability of ground ice and the factors controlling polycyclicity.

This study demonstrates the capacity of ERT for detecting massive ice bodies and internal changes. Combining this with a time component and orthophoto analysis, provides a unique insight into the behaviour of retrogressive thaw slumps, but also shows the need to use complimentary techniques to correctly interpret geophysical measurements.

How to cite: Eppinger, S., Heidler, K., Lantuit, H., and Krautblatter, M.: Combining ERT and an orthophoto time series to investigate thaw-related landslides in the Canadian Arctic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17951, https://doi.org/10.5194/egusphere-egu24-17951, 2024.

This study detects the regular alternation of two different reactivation regimes of the Pont-Bourquin Earthflow, occurring from 2010 to 2023, by combining the continuous monitoring of three indicators:
(1) seismic velocity, using ambient noise interferometry ^1,2
(2) displacement rate, using extensometers and RFID tags ^3–5
(3) sensitivity to rainfall and snowmelt, using dynamic impulse response deconvolution ^6,7

The study confirms the hypothesis of a dual mechanism previously suggested on this landslide from the lag of hydrological and displacement response to precipitations ^8,9, and goes further by detecting when these regime changes occur. In an early-warning system, this method might serve to discriminate different regimes during accelerations that are seemingly equivalent.

References related to this study:

¹ Mainsant, G. et al. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. Earth Surf. 117, F01030 (2012).
² Le Breton, M., Bontemps, N., Guillemot, A., Baillet, L. & Larose, É. Landslide monitoring using seismic ambient noise correlation: challenges and applications. Earth-Sci. Rev. 103518 (2021) doi:10.1016/j.earscirev.2021.103518.
³ Le Breton, M. et al. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Eng. Geol. 250, 1–10 (2019).
⁴ Le Breton, M. et al. Dense and long-term monitoring of earth surface processes with passive RFID — a review. Earth-Sci. Rev. 234, 104225 (2022).
⁵ Charléty, A., Le Breton, M., Baillet, L. & Larose, E. RFID Landslide Monitoring: Long-Term Outdoor Signal Processing and Phase Unwrapping. IEEE J. Radio Freq. Identif. 7, 319–329 (2023).
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How to cite: Le Breton, M., Larose, E., Chatelain, F., Baillet, L., Royer, A., and Guillemot, A.: Alternance of two reactivation regimes on Pont-Bourquin earthflow, highlighted by changes in seismic velocity and sensitivity to rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19801, https://doi.org/10.5194/egusphere-egu24-19801, 2024.

The Chamba Distirct is situated in the North Western part of the Himachal Pradesh State where presence of ancient monuments in the form of temples and holy lakes make this district a pilgrimage destination. Extensive damage to some of these monuments has been done due to occurrence of natural disasters. Himalayas represents a highly sensitive ecosystem vulnerable for natural disasters. Landslides are common phenomena in this geodynamically active terrain triggered by a wide variety of factors. The increased magnitude and frequency of Landslides is a cause of concern, since these interfere with human interest, causing immense loss to human life, infrastructure and natural resources. Extensive human activity in the region has further intensified erosion and triggered slope failures. The consequences are occurrence of large landslides, particularly in the zones of active faults and thrusts. The Chamba- Bharmaur highway has number of such active slide zones which causes obstruction for normal activities of the inhabitants. The area lies in seismically active region due to which occurrence of micro-earthquake at repeated intervals disturbs the already weathered rock mass. The initiation of Landslide near Mehla village on NH-153 can be attributed to the developmental activities ranging from farming on hill slopes to development of highways. Based upon geotechnical properties, numerical modeling of the landslide site using Geo5 software was conducted in order to calculate the factor of safety. The results of the numerical study can be used to ascertain the dependability of these slopes for future activities and suggesting mitigation measures to lower the frequency and severity of landslides in areas with similar geological conditions. This will further help in preserving the rich ancient heritage from occurrence of natural disasters in this region.

Keywords: natural disaster, ancient monuments, earthquake, hill slopes.

How to cite: Banshtu, R. S., Versain, L. D., and Singh, A. P.: Slope Stability Analysis and Mitigation of Mehla Landslide, District Chamba, Himachal Pradesh, India., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5431, https://doi.org/10.5194/egusphere-egu24-5431, 2024.