NH3.8

Landslides annually cause thousands of casualties and billions of dollars in property loss. Mitigation of their hazards demands answers to three fundamental questions: where are the landslides, how are they evolving, and what damages would they cause upon a runout failure? Radar remote sensing, capable of capturing landslide deformation in near real-time, proves itself an effective and efficient tool to help address these challenges. Here, we highlight a workflow that incorporate SAR (Synthetic Aperture Radar)’s unique values to aid landslide detection, monitoring, and runout damage forecasting. By integrating field instrumentation and hydromechanical modeling, our recent studies over the U.S. West Coast substantiated SAR’s powerful capabilities: (1) Discovering approximately 600 destabilized, slow-moving landslides that were missing from the currently existing, non-systematically mapped landslide database of the United States; (2) Monitoring and characterizing spatiotemporal dynamics of landslides that destroy highways (e.g., the Hooskanaden landslide in southwestern Oregon), damage aquatic habitats (e.g., tens of irrigation-induced landslides in eastern Washington ), and endanger communities (e.g., the Cascade Locks landslide in southern Washington); (3) Constraining source volume to help predict runout hazard of landslides that threaten popular campgrounds (e.g., the Gold Basin landslide in central Washington) and urban communities (e.g., the Cape Meares landslide in northwestern Oregon). Adaptation of our methodology to assimilate SAR observations could prove useful for mitigating similar landslide hazards beyond the regional scale.

How to cite: Lu, Z., Xu, Y., Burgmann, R., and George, D.: Landslides on the radar: detection, monitoring, and runout hazard forecasting, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8647, https://doi.org/10.5194/egusphere-egu22-8647, 2022.

Satellite Remote Sensing Investigation of 21 July 2020 Shaziba Landslide, China

Wandi Wang1,2, Mahdi Motagh1,2, Sara Mirzaee3, Sigrid Roessner1 and Tao Li4

• Section 1.4 - Remote Sensing and Geoinformatics, GFZ German Research Center for Geosciences, Potsdam, Germany
• Institute of Photogrammetry and Geoinformation, Leibniz University Hannover, Hannover, Germany
• Department of Marine Geology and Geophysics, University of Miami, United States
• GNSS Research Center, Wuhan University, China

We present the results of remote sensing analysis of deformation related to the 21 July 2020 Shaziba landslide in China. The landslide, which occurred following the heavy precipitation from June to August 2020, is located at the Qingjiang River, approx. 30 km from Enshi City in Hubei Province of China.   It destroyed over 60 houses, and by blocking the course of the river, formed a landslide dam, which threatened the safety of people and infrastructure downstream. Although Shaziba landslide occurred in form of reactivation of an old landslide, the landslide prone slope was not instrumented prior to this most recent failure. Therefore, high-resolution remote sensing imagery was used as a very effective source of information for a detailed investigation of the evolution of this slope failure.  We collected the satellite remote sensing data covering a time period from June 2016 to July 2021 and comprise optical and radar data. Firstly, cross-correlation analysis using satellite optical imagery from Planet and Sentinel-2 systems was used to retrieve the lateral direction and magnitude of landslide movements. Next, multi-temporal interferometry (MTI) analysis based on Sentinel-1 and TerraSAR-X SAR data was exploited to obtain pre- and post-failure deformation. Results from different MTI techniques including Persistent Scatterer (PS), Small Baseline Subsets (SBAS), and Eigendecomposition based Maximum-likelihood-estimator of Interferometric phase (EMI) were compared to evaluate the most suitable method for InSAR time-series analysis of deformation related to the evolution of Shaziba landslide. Finally, several high-resolution DEMs derived from TanDEM-X (TDX) data were analyzed using repeat-pass interferometry and stacked together to compensate for the errors related to DEM alignment in order to precisely estimate the landslide volume. The results highlight how the integration of various remote sensing sensors helps to gain a better understanding of landslide evolution process and characterization. 

How to cite: Wang, W., Motagh, M., Mirzaee, S., Roessner, S., and Li, T.: Satellite Remote Sensing Investigation of 21 July 2020 Shaziba Landslide, China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5093, https://doi.org/10.5194/egusphere-egu22-5093, 2022.

Following intense precipitation records between mid-March and the beginning of April 2019, thousands of slope failures affected the mountainous regions in northeast and south of Iran. In particular, a catastrophic landslide occurred in Hoseynabad-e Kalpush village, in Semnan province in the Northeast of Iran, where more than 300 houses were damaged, of which 163 houses had to be evacuated due to the severity of the destruction and the danger to their residents. Several questions were raised in the aftermath of the disaster as to whether the landslide was triggered by the heavy precipitation only or by other factors such as additional load due to the increase of the hydraulic gradient and seepage from a nearby artificial reservoir built in 2013 on the opposite side of the slope. This paper provides multi-scale and multi-sensor remote sensing investigation for the pre-, co-, and post-failure slope stability of the Hoseynabad-e Kalpush landslide and assesses the role of potential external factors in triggering the 2019 catastrophic failure. C-band Sentinel-1A Interferometric Synthetic Aperture Radar (InSAR) measurements and very-high-resolution Planet scope imagery cross-correlation show a clear precursory and transient deformation in the lower part of the slope that culminated in a slope failure of more than 35 m in the upper part of the landslide in April 2019. The lower and middle parts of the landslide continued to move with a maximum displacement rate of 10 cm in the first 6 months. Satellite remote sensing results are integrated with rainfall data and in-situ records of the reservoir water levels to evaluate the role of meteorological and anthropogenic conditions in promoting slope instability. The outcomes of this study highlight how the complex interaction between climate and anthropogenic factors influence unstable hillslope conditions in space and time and the need for more integration of remote sensing measurements into early warning systems at regional and national scales. 

How to cite: Vassileva, M., Motagh, M., Roessner, S., and Akbari, B.: Evolution analysis of the April 2019 Hoseynabad-e Kalpush landslide in Iran inferred from  multi-sensor satellite remote sensing and in-situ measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10402, https://doi.org/10.5194/egusphere-egu22-10402, 2022.

A large, deep-seated ancient landslide body was partially reactivated close to the Aniangzhai village in the southwest of China on 17 June 2020. The catastrophic event occurred as a result of a  complex cascading event, started by a debris flow triggered by the heavy rainfall in the summer. The debris flows, coming from the northern Meilonggou Gully, created a dammed lake just under the ancient landslide body and blocked the Xiaojinchuan river, leading to an increase in the water level. Thereafter, the overflow of the barrier dam, influenced by the discharge of the surplus water from the nearby hydropower station to reduce the flood pressure, undercut the toe of the landslide, resulting in partial reactivation of this ancient landslide body.

This paper provided a comprehensive analysis of the evolution of this hazard chain using both radar and optical remote sensing techniques. 

Firstly, a horizontal displacement map is produced by cross-correlation technique using Planet data to retrieve co-failure motion. Results show that the horizontal displacement peaks at 14.7 m, and most of the large displacement, ranging from 12.5 m to 15.0 m, were found on the lower part of the slide compared to the middle and head parts in the large failure zone.

Next,  pre-failure slope stability analysis is performed using a stack of Sentinel-1 SAR data from 2014 to 2020.  InSAR time-series results show that the landslide has long been active before the failure. However, the rate of creep on this slow-moving landslide was not constant, rather it changed over time.  The 3-year wet period that followed a relative drought year in 2016 resulted in a 14% higher average velocity in 2018-2020, in comparison to the rate observed for 2014-2017. An accelerated creep was observed on the head part of the failure body since spring 2020 before the large failure.

Finally, X-band TerrASAR-X data, C-band Sentinel-1 data, and newly designed artificial corner reflectors are used to investigate the post-failure deformation rate. Corner reflectors are helpful auxiliaries for SAR and InSAR target analysis since they are identified as stable objects during radar acquisitions, especially in vegetated or agricultural landscapes, where the widespread loss of coherence between consecutive image acquisitions could happen. We evaluated the performance of newly designed miniature artificial cornel reflectors that are constructed for retrieving displacement signals from both ascending and descending TerraSAR-X satellites. The results indicate that the lower part of the ancient landslide body is still creeping. However, the average displacement rate of the active part has decreased since the catastrophic failure, although it is  still higher than the rate recorded in the precursory analysis prior to the failure between 2014 and 2020. Given the lack of in-situ monitoring data at Aniangzhai and other large landslides in high mountain areas all over the world, the uses of high resolution remote sensing data offer a unique opportunity to assess the state of landslide activities and their relation with different triggering factors.

How to cite: Xia, Z., Motagh, M., Li, T., and Roessner, S.: Pre-, co- and post-failure analysis of the Aniangzhai landslide on 17 June 2020 with satellite remote sensing and corner reflector InSAR (CR-InSAR), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4905, https://doi.org/10.5194/egusphere-egu22-4905, 2022.

The increase in freely available optical satellite data with 10-15 m spatial resolution offers new opportunities to monitor slow-moving landslides and study their past movements through image cross-correlation in difficult-to-access regions around the world. Here, we explore this potential using Landsat-8 and Sentinel-2 optical satellite imagery to detect and quantify slope movements in the northwestern Argentine Andes over the past eight years. Our study takes advantage of the large spatial and temporal availability of optical satellite imagery, but we also show the caveats associated with cross-correlation for slow-moving targets. The northwestern Argentine Andes, particularly the mountain ranges that border the Central Andean Plateau (Altiplano-Puna Plateau), are predisposed to slope movements because of their steep hillslopes, weakened lithologies, sparse vegetation cover, and frequent rainfall events. Previous studies based on radar interferometry have identified several landslides moving at ~1 m/yr throughout our study area. We use these areas of known offset to identify optimal processing routines, evaluate their accuracy, and define the limitations of monitoring the movement of slow-moving landslides with optical imagery. We present approaches to pre- and post-correlation filtering to reduce noise and increase signal strength and further validate our results with high spatial resolution imagery (1-3 m). In this way, we aim to better constrain the distribution of slow-moving landslides throughout our study area and understand the driving factors of past and present slope movements at the regional scale.

How to cite: Mueting, A. and Bookhagen, B.: Cross-correlation of optical satellite data for the detection and monitoring of slow-moving landslides in northwestern Argentina, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4825, https://doi.org/10.5194/egusphere-egu22-4825, 2022.

Roads can both increase and decrease the likelihood of landslides occurring in a given region. This might be due to (i) mapping biases when compiling landslide inventories, (ii) the influence of the road on the landslide susceptibility. Here, we present a spatial statistical analysis of landslide proximity to roads across a range of geographic settings and landslide inventory types. We examine the proximity of landslide centroids to roads at regional to national scales using 12 diverse landslide inventories with variations in inventory type (6 triggered event, 6 multi-temporal), mapping method (1 field-based, 6 remote sensing, 5 a combination of mapping methods), and countries of origin distinguished by their human development index (HDI) (6 high and 6 low HDI). Each inventory contains 270 < n_Landslides < 81,000 landslides with inventory regional extents ranging from 80 km² < A_inventory < 385,000 km². We have developed a PyQGIS tool that calculates the distance between each landslide centroid and the closest road vector within the same watershed. From these distance values, we create a density distribution of landslides as a function of distance from roads for that inventory. We then compare each inventory’s density distribution of landslide-to-road distance to a set of randomly generated points and their distances to roads. For the 12 inventories, we find that the landslide density near roads compared to random points is greater in 3 inventories, equal in 3 inventories, and lower in 6 inventories. We find that a comparison between landslides and random points describes each inventory well in terms of road density. We divide the 12 inventories into 4 typologies with different potential explanations for each group. We believe there is evidence of mapping bias towards roads for the typology with 3 inventories that have greater landslide density (compared to random points), which suggests that a more nuanced use of road proximity within landslide susceptibility models should be adopted. Further research should be done to understand the interactions between landslides and proximity to roads at the regional to national scale.

How to cite: Malamud, B. D., Heijenk, R. A., Taylor, F. E., and Wood, J. L.: Road influences on landslide inventories, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7616, https://doi.org/10.5194/egusphere-egu22-7616, 2022.

Early warning for complex landslides is a difficult task since their evolution could depend on the combination of various predisposing and triggering geological (e.g. rock type, water circulation) and climatic factors (e.g. rainfall, snowmelt). Depending on the type of phenomenon, the temporal evolution of a landslide can be monitored in several ways, from classical to recent advances in remote sensing and in-situ measurements. The potential of real-time monitoring by ground-based radar interferometry (GB-InSAR) is exploited here to improve the understanding of the kinematic evolution of a complex landslide in the Italian Alps. To this end, the integrated use of long-term, spatially distributed GB-InSAR data and of a classical Robotic Total Station (RTS) monitoring is analyzed and discussed for the Sant’Andrea landslide, located in the municipality of Perarolo di Cadore (Belluno, Italy), a rotational slide in heterogeneous materials. Due to the landslide features, the use of these two different techniques is complementary: GB-InSAR measures a continuous field of motion, although along LOS, that is suitable for detecting unstable sectors and quantifying the space-time variations of the kinematics on the entire slope, whereas RTS is able to acquire tridimensional displacement data, very useful to monitor single points and to correctly interpret the GB-InSAR data. The landslide position, just upstream of the village center, represents a relevant hydrogeological risk for the inhabitants. This complex mass movement involves a clay-calcareous debris mass overlying an anhydrite-gypsum dolomitic bedrock. The kinematic activity exhibits an alternation of slow displacements, as long-term creep, and episodic or seasonal accelerations, strongly related to rainfall triggering in response to both heavy and lasting events. Based on the intensity and duration of rainfall, the significant accelerations are followed by a relaxation period with a slow regression of the displacement rate, usually without returning to the previous values.
The analysis carried out by combining the mapping of 3D point-based displacements and LOS surface velocity fields allows distinguishing mechanisms and sensitivity of the landslide sectors to rainfall inputs, as well as to understand the wide range of mechanical behaviors shown by the slope during the monitoring period. Such information aims to quantitatively evaluate the trigger-response signals to rainfall events to predict accelerating trends of the landslide displacements as well as possible failures. The proposed monitoring and modelling framework will be soon implemented in an operational early warning procedure using real-time, high-frequency GB-InSAR data together with RTS and weather forecasts, in accordance with local authorities of Civil Protection.

How to cite: Catani, F., Carraro, E., Galgaro, A., and Nava, L.: Integration of ground-based radar interferometry (GB-InSAR) and weather forecasts for real-time monitoring: kinematic evolution and early warning of the Sant’Andrea landslide (Eastern Italian Alps), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11731, https://doi.org/10.5194/egusphere-egu22-11731, 2022.

Large rock-ice avalanches have been observed in the past in the Mont Blanc Massif area, notably from the Grand Pilier d’Angle in 1920 and from the Brenva spur in 1997, which involved millions of cubic meters of material. More recently, a rockslide detached from the Brenva spur in 2016, involving 35000 m³ of material. In the context of monitoring, in the fall of 2020 and 2021, two Lidar campaigns were performed to obtain 3D models of the rock face and monitor future rockfall activity. Moreover, point clouds were obtained from the Structure from Motion technique, using aerial photos from helicopter. Comparing the point clouds of 2020 and 2021 in CloudCompare software, only a few small rockfalls of 10-30 m³ were observed. The three-dimensional model of the rock wall was used as an input for the structural analysis of the Brenva Spur and Grand Pilier d'Angle, using Coltop3D software. The analysis showed that the same families of discontinuities characterizing the Brenva Spur are also found in the Grand Pilier d’Angle and other granitic crops at lower altitudes, indicating that they all belong to the same regional set of discontinuities. To monitor the collapses of the Brenva spur, an accelerometer was installed in 2017 on the wall and a high-resolution camera was placed at a distance of about 6 km. In June and July 2018, two rockfalls and one rockslide were detected, by both the accelerometric signal and the visual inspection of the photos. A spectrogram was therefore created, which showed that both high and low-frequency contents are present. Low frequencies may correspond to the sliding and high frequencies may correspond to rock bounces.

How to cite: Vicari, J. H., Fei, L., Bertolo, D., Choanji, T., Derron, M.-H., Ferretti, G., Jaboyedoff, M., Thuegaz, P., Troilo, F., Uhlmann, D., and Wolff, C.: Rock instability hazard in high mountain area: the example of the Brenva spur (Mont Blanc massif), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8842, https://doi.org/10.5194/egusphere-egu22-8842, 2022.

Slow-moving landslides play an important role in both theoretical slope evolution and practical landslide hazard and risk research. Their process rates impede the quantitative analysis of related dynamics over short time periods, given that the actual changes are often lying within the error margins of the respective methodological approaches. In this study, current results are presented for a long-term monitoring setup of a slow-moving earth slide – earth flow system in the Flysch and Klippen Zone of Lower Austria. The aim is to further assess surface and subsurface characteristics, their interrelations, and implications on spatio-temporal landslide dynamics.

The research strategy comprises the utilization and analysis of both surface and subsurface monitoring data. The methodology includes the application of Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) based Structure from Motion (SfM). Geotechnical methods, such as penetration tests, percussion drilling and inclinometer measurements are used to gain information about subsurface characterization. A meteorological station and piezometer measurements provide information on hydro-meteorological conditions. Surface monitoring data is available since 2015, subsurface monitoring started in 2018.

Results suggest that a) very high-resolution surface data is necessary to capture real surface changes and that TLS is more suited for processes such as these than UAV based SfM, b) the interpretation of morphological features based on multi-temporal mapping can increase the DoD based level of surface change detection, c) only prolonged observation periods can reveal interrelations on surface and sub-surface dynamics and d) that in-depth knowledge on the study area is important to interpret results and that the impact of natural, but especially artificial disturbances of the hillslope system more or less temporarily close to recent process activities remains difficult to evaluate.

Current monitoring results reveal the complexity and non-linearity of slow-moving, complex landslide behaviour. Both high spatial and temporal resolution of on-going monitoring data enables an assessment of low rates and changes. However, the slower the process, the longer the observation needs to be. Otherwise the actual process dynamics might be misinterpreted, e.g. the data might be superimposed by technical restrictions. 

How to cite: Stumvoll, M. J., Philipp, M., Robert, K., Jiménez, A., and Thomas, G.: Complex, slow-moving landslide dynamics: implications from a long-term monitoring setup on the Hofermühle landslide in Lower Austria, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8599, https://doi.org/10.5194/egusphere-egu22-8599, 2022.

The paper focuses on presenting a methodology that can be used to rapidly assess and map kinematics of landslides when these occur in areas with dense vegetation cover. The method is based on using aerial imagery collected with UAV (Unmanned Aerial Vehicle) and their derived products obtained by applying the Structure from Motion (SfM) technique. The landslide occurred on May 3, 2021, and is located in the Livadea village, Curvature Subcarpathians (Romania). It affected several houses from the vicinity, and the people were relocated because of the high probability of landslide reactivation. To mitigate the consequences of this landslide, a preliminary investigation, based on three UAV surveys and field geological-geomorphological surveys, was carried out to delineate active parts of the landslide and to define evacuation measures. Three UAV flights (May 6, May 25 and July 10) were performed using DJI Phantom 4 and Phantom 4 RTK drones. Because it is a heavily forested area, a semi-automated processing of the landslide kinematics and change detection analysis were not possible. The landslide displacement rates and the changes in terrain morphology between flights were assessed by manual interpolating of collected landmarks on all three UAV flights. Tilted trees were used to estimate the landslide direction and evolution. The results show an average displacement of 9.55 m (minimum 1.2 m, maximum 20.6 m) between the first and the second flight and an average of 19.27 m (minimum 1.98 m and maximum 46.3 m) between the second and the third flight, respectively. This approach proved quick and efficient for rapid landslide investigations when fast response and measures are necessary to reduce landslide consequences.

Acknowledgement

This work was supported by a grant of the Romanian Ministry of Education and Research, CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2019-5152, within PNCDI III (project coordinator Ionuț Șandric, https://slidemap.gmrsg.ro) and by the project PN19450103 / Core Program (project coordinator Viorel Ilinca).

How to cite: Ilinca, V., Șandric, I., Chițu, Z., Irimia, R., and Gheuca, I.: UAV applications to assess short-term dynamics of slow-moving landslides under dense forest cover, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1104, https://doi.org/10.5194/egusphere-egu22-1104, 2022.

The Danube Bend is one of the environmental hotspots of Northern Hungary.
Numerous geodynamic, geomorphological, fluvial and anthropogenic processes contribute to the formation of spectacular and dynamic landscapes, which result in mass movements of varying magnitude, threatening the transport infrastructure crossing the area. The combination of continuous uplift and the incision of the Danube, the largest river in Central Europe, has created steep slopes in critical or sub-critical state for mass movements. Recent landslides, which have brought road and rail traffic to a standstill for considerable periods, have shown that research into the (in)equilibrium of slopes is an important issue.

For this study, a variety of remote sensing observations have been integrated, including satellite and UAV imagery, LiDAR data and derived data, as well as field observations Workflows such as laser scanning and Structure from Motion to create digital surface and digital terrain models with an accuracy of tenths of a metre horizontally and a few centimetres vertically.
Vegetation is also an important issue, as it can partly stabilise slopes and can provide protection, so detailed mapping has also been carried out. Geomorphological observations, satellite and recent UAV imagery were used to map the potential for mass movements, and a rough estimate of the amount of loose material available for mass movements was made. The results provide important spatial and temporal input for road safety and the maintenance and safe upkeep of roads and railways.

_{MÁV Hungarian State Railways is thanked for providing facilities and data.}

_{FV is supported by EFOP-3.6.3-VEKOP-16-2017-00001: Talent Management in Autonomous Vehicle Control Technologies – (financed by the Hungarian Government & the European Social Fund).}

_{BK is supported by the NRDI Fund of Hungary, Thematic Excellence Programme no. TKP2020-NKA-06 (National Challenges Subprogramme) funding scheme.}

How to cite: Székely, B., Rozman, G., Bitiukova, E., Vörös, F., and Kovács, B.: Assessing the potential for mass movements of the Danube Bend (Hungary) endangering transport infrastructure: an integration of field observations and UAV and other imagery, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3282, https://doi.org/10.5194/egusphere-egu22-3282, 2022.

In recent years, rapid climatic changes and their impact is widely visible and recognizable around the world. One of the effects of global warming is reduced snow cover in high-mountain areas. Such a situation leads to the case, where retaining snow cover suitable for the skiing activities is crucial. As a solution, heavy artificial snow with high water content is used. To prolongate the skiing season additional snow is produced and stored as a thick cover on the hillsides.  Such a heavy load leads to a situation, where slow-developing landslides with a tendency for rapid movements can occur. Such a situation can be potentially dangerous not only for the infrastructure but also for the humans themselves. Such a situation was observed in a study site in Cisiec (Silesian Voivodeship, Southern Poland), we're slowly developing landslide strongly affected the infrastructure on a small skiing resort. For a fuller understanding of the problem, precise geophysical imaging is required to distinguish of main triggering factors, as well as the anthropogenic impact on the landslide itself. In the presented study, the authors propose an integrated geophysical approach utilizing imaging techniques such as seismic reflection imaging and tomography, seismological monitoring, Electrical resistivity tomography (ERT), Audio-Magnetotellurics (AMT), laser scanning and photogrammetry for the monitoring time evolution of anthropogenically developed landslide. The integration of the results allows for obtaining a more certain image of the subsurface and its time evolution necessary for the studied problem. By using the uncertainty driven approach, where data is correlated with preserved information about its uncertainty, multiple interpretation mistakes can be solved. As a result, the authors were able to estimate the seasonal evolution of the landslide in relationship to the anthropogenic load on the hillside.

This research was funded by the National Science Centre, Poland (NCN) Grant 2020/37/N/ST10/01486.

How to cite: Marciniak, A., Majdański, M., Kowalczyk, S., Górszczyk, A., Gajek, W., Oryński, S., and Stan-Kłeczek, I.: Integrated time-lapse geophysical imaging and remote-sensing study of the antropoghenic triggering of the landslides, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1342, https://doi.org/10.5194/egusphere-egu22-1342, 2022.

Exceptional rainfalls (up to 200 mm in 72 h) in W-Germany, the Netherlands and Belgium led to severe flooding on 14-15 July 2021. In Germany the Ahr valley (Eifel mountains) was hit heavily, leading to 134 fatalities and substantial loss of property and infrastructure. Besides the damage in the floodplains, multiple shallow landslides were triggered along the Ahr embankments. Furthermore, the flood caused undercutting of several old landslide bodies. One such landslide in Devonian Schist bedrock is located at a narrow, bended stretch of the Ahr, near the town of Müsch. A complete failure has the potential to dam the river posing a considerable hazard.

The main objectives of this study are to gain an in-depth understanding of the landslide causes and its transient activity. These objectives are tackled by a multi-method approach: landslide mapping, analysis of pre- and post-event airborne laser scanning (ALS) and terrestrial laser scanning (TLS) data, electrical resistivity tomography (ERT), seismic refraction tomography (SRT), passive seismic monitoring, geotechnical analysis and interviews with local inhabitants.

The old landslide is 100 m wide and 200 m long. Preliminary analysis of ERT and SRT indicate a landslide depth of 20-30 m, leading to an overall landslide volume of 400,000 - 600,000 m³. ERT further shows underlying bedrock properties and water saturated zones. An old dumpsite as well as an ancient railway, now used as forest trail, cutting through the landslide horizontally are clearly shown as resistive zones. Analysis of ALS data shows that so far only the frontal part at the Ahr banks has been active and has lost about 6300 m³ due to fluvial erosion and landsliding. Field mapping shows clear signs of retrogressive landsliding. From October 2021 onwards the landslide body has been equipped with five geophones to record both subtle changes in ground rheology and discrete events of rock bridge failure due to incremental mass movement. Currently most seismic signals at the slope can be allocated to daily traffic and road construction in the area.

The combination of geophysical and remote sensing methods enables a profound insight into the mechanisms and present processes of the Müsch landslide. Based on this, we will be able to assess the probability for a reactivation of the whole landslide body, which could trigger cascading hazards affecting a much larger region. An improved monitoring concept will be developed which can be adopted to similar structures in the Ahr valley and beyond. 

How to cite: Wenzel, T., Bell, R., Dietze, M., Schrott, L., Beer, A., Braun, A., and Fernandez-Steeger, T.: Hillslope failure due to stream undercutting: The 2021 flood event in the Ahr-valley and resulting mass movements – a multi-method approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7116, https://doi.org/10.5194/egusphere-egu22-7116, 2022.

Distributed Acoustic Sensing (DAS) is becoming increasingly popular due to its high spatial and temporal resolution. DAS holds great potential for geohazard applications as, in principle, anything affecting the strain on a fibre optic cable section can be measured. Examples are passing seismic surface waves and ambient temperature changes.  This presentation demonstrates the feasibility of DAS for quick clay monitoring, and presents data from a field trial in Rissa, Norway.

In Norway, almost all landslides in clays that have serious consequences are caused by the instability of quick clay. Examples include the landslides Trögstad (1967), Rissa (1978), and recently Gjerdrum (2020).

A research field site was established at Rissa by the Centre for Geophysical Forecasting (CGF). Long term monitoring with DAS over several months is carried out to monitor changes in the geophysical parameters of the soil before and after road construction work.

Due to the close relation between elastic parameters controlling seismic wave propagation and the petrophysical properties of the sediment, which determine the strength, DAS measurements from seismic waves, mainly Rayleigh waves, can be used to investigate the soil stability.

The Rayleigh waves of interest travel with a velocity that is approximately 0.9 times the shear wave velocity (Vs) and may have wavelengths of only a few meters. The shear modulus, which is the main geomechanical parameter controlling the stability and shear strength, can be approximately inferred from Vs. Therefore, observation of changes in Vs can be used to detect changes in shear strength of clay formations.

One of the main challenges for this application lies in the detection of seismic surface waves of shorter wavelengths. Commonly used methods for quick clay monitoring suffer either from lower spatial resolution or limited area coverage, and we also seek to address these challenges.

Alcatel Submarine Network Norway developed an interrogation technology (OptoDAS) enabling long-range measurement over 100km. Spatial sampling intervals as small as 1m can be chosen. It is, however, the gauge length and the spatial sampling that determines the spatial resolution. The gauge length varies from 40m to 2m, and is analogous to receiver (group or node) separation in conventional seismic methods. 

Due to the inherent properties of DAS interrogation the SNR is lower for very small gauge lengths. Although the data quality is adequate, we strive to improve the SNR further to make DAS well suited for the analysis of seismic waves with wavelengths even shorter than 4m.

A cost-effective solution for increasing the data quality could be found by introducing fibre loops into the acquisition design. The gain of these optimization will be presented, and it will be demonstrated that data quality can be improved by stacking over multiple similar fibre optic pathways.

Results will be presented for seismic signals from passive sources – such as passing cars on the nearby road, and from an active source, a seismic hammer and plate shot.

The pros and cons of using long-range high-resolution DAS technology for soil monitoring will be discussed along with potential areas for future advances.

How to cite: Wienecke, S., Jacobsen, J., Brenne, J.-K., Landrø, M., Dong, H., Rørstadbotnen, R. A., Kakhkhorov, U., and Growe, K.: Distributed acoustic sensing for quick clay monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6538, https://doi.org/10.5194/egusphere-egu22-6538, 2022.

Radio-Frequency Identification (RFID) shows great potential for earth-
sciences applications, notably in landslide surface monitoring at high spatio-
temporal resolution [1] with meteorological robustness [2]. Ten 865MHz
RFID tags were deployed on part of a landslide and continuously moni-
tored for 8 months by a station composed of 4 reader antennas. 2D rela-
tive localization was performed using a Phase-of-Arrival approach [3], and
compared with optical reference measurements. The centimeter-scale ac-
curacy of this technique was confirmed theoretically by developing a mea-
surement model that includes multipath interference and system sensitiv-
ity kernel. Although horizontal localization shows promising results, ver-
tical displacement monitoring presents intrinsic error sources that greatly
decrease accuracy in this direction. This study confirms that 2D landslide
displacement tracking is feasible at relatively low station and maintenance
cost (Charlety et al.,2021, submitted).

References

[1] M. Le Breton, L. Baillet, E. Larose, E. Rey, P. Benech, D. Jongmans, F. Guy-
oton, and M. Jaboyedoff, “Passive radio-frequency identification ranging, a
dense and weather-robust technique for landslide displacement monitoring,”
Engineering geology, vol. 250, pp. 1–10, 2019.
[2] M. Le Breton, L. Baillet, E. Larose, E. Rey, P. Benech, D. Jongmans, and
F. Guyoton, “Outdoor uhf rfid: Phase stabilization for real-world appli-
cations,” IEEE Journal of Radio Frequency Identification, vol. 1, no. 4,
pp. 279–290, 2017

How to cite: Charléty, A., Larose, E., Le Breton, M., Baillet, L., and Helmstetter, A.: 2D Phase-based RFID localization for on-site landslide monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1156, https://doi.org/10.5194/egusphere-egu22-1156, 2022.

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.

How to cite: Ducasse, J., Bertrand, C., Maillard, O., Malet, J.-P., Lajaunie, M., Benarioumli, S., Bataillès, C., and Lespine, L.: Hydrogeological modelling of the Viella landslide (Hautes-Pyrénées) for hazard understanding, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4525, https://doi.org/10.5194/egusphere-egu22-4525, 2022.

In the stability analysis of landslides, it is required to consider the rainfall intensity, geographical features and hydromechanical behavior in unsaturated layers. The actual landslide can be simulated rigorously by 3D analysis. The unsaturated shear strength can be evaluated from soil water retention curves based on the suction stress which has generalized Bishop’s effective stress. The unsaturated soils become unstable as the saturation ratio increases and subsequently the effective stress decreases. The assessment of landslide stability is based on the effective stress theory in unsaturated soils.

By the GIS based analysis system, the slope stability is estimated for wide mountain area in Korea. From digital map data, the contour map and elevation are extracted and the mesh is created as a preprocess. In each cell, the infiltration and stability analysis are performed step by step. In the area of actual landslides, the infiltration analysis on transient flow has been performed one dimensionally for the actual rainfall record. The stability analysis is subsequently performed three dimensionally based on the unsaturated effective stress principle. It is verified that the 3D stability analysis can simulate the actual landslide rigorously.

 Acknowledgements This research is supported by grant from Korean NRF (2019R1A2C1003604), which are greatly appreciated.

How to cite: Oh, S., Kim, S. J., and Son, K. I.: 3D Analysis of Stability for Rainfall Induced Landslides in Unsaturated Soils, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2126, https://doi.org/10.5194/egusphere-egu22-2126, 2022.