NH3.2 | Large mass movements monitoring, modeling and early waning
Large mass movements monitoring, modeling and early waning
Co-organized by GM3
Convener: Giovanni Crosta | Co-conveners: Christian Zangerl, Irene Manzella
Orals
| Mon, 24 Apr, 10:45–12:30 (CEST), 14:00–15:45 (CEST)
 
Room 1.15/16
Posters on site
| Attendance Mon, 24 Apr, 08:30–10:15 (CEST)
 
Hall X4
Posters virtual
| Attendance Mon, 24 Apr, 08:30–10:15 (CEST)
 
vHall NH
Orals |
Mon, 10:45
Mon, 08:30
Mon, 08:30
Large mass movements in rock, debris and ice in glacial masses, represent enormous risks impacting on the socio economic tissue. These complex systems are difficult to describe, investigate, monitor and model. Hence a reliable model of these phenomena requires acquisition and analysis of all the available data. This is the key to support successive steps up to the management of Early Warning systems.
Large instabilities affect all the materials (rock, weak rocks, debris, ice), from low to high altitudes, evolving as slow or fast complex mass movements. This and the complex dependency on forcing factors result in different types and degrees of hazard and risk. Some aspects of these instabilities are still understudied and debated, because of the difficult characterization and few cases thoroughly studied. Regional and temporal distribution and relationships with controlling and triggering factors are poorly understood resulting in poor predictions of their behavior and evolution under present and future climate. Relationships among geological and hydrological boundary conditions and displacements are associated to mechanical controls, hydraulic response and evolution in space and time. Even for well studied and active phenomena warning thresholds are mostly qualitative, based on semi-empirical approaches and do not consider all available data. Then a multidisciplinary approach and a robust set of monitoring data are needed. Many modeling approaches can be applied to evaluate instability and failure, considering triggerings (e.g. rain, seismicity, eruption, snowmelt), failure propagation, leading to rapid mass movements (rock, debris, ice avalanches, flows). Nevertheless, the applied approaches are still phenomenological in most cases and have difficulty to explain the observed behavior. Impacts of such instabilities on structures represents a relevant risk but also an opportunity in terms of investigations and quantitative measurements of effects on structures (e.g. tunnels, dams, roads). Design of these structures and knowledge of their expected performance represent an important element.
We invite all the researchers to present case studies, sharing views and data, to discuss monitoring and modeling approaches and tools, to introduce new approaches for thresholds definition, including advanced numerical modeling, Machine Learning for streamline and offline data analyses, development of monitoring tools and dating or investigation techniques.

Orals: Mon, 24 Apr | Room 1.15/16

Chairpersons: Christian Zangerl, Irene Manzella
10:45–10:48
10:48–10:58
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EGU23-14887
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Virtual presentation
Vincent Drouin and Martina Stefani

Landslides pose a considerable risk over communities and infrastructure in Iceland. There have been large landslides in the recent years and a least one related to permafrost. Taking into account the changing climate, knowing past and active moving slopes increases preparedness for civil protection purposes. In order to have a better overview of the actual hazard, we mapped and classified all landforms reminiscent of landslides into a database. The mapping was done using aerial orthophotos, digital elevation models (DEM), and satellite interferometry (InSAR) velocity map. To begin with, this allows to extract statistics about the spatial distribution and size of various type of landslides. The largest landslide features mapped covers over 10 km2, the smallest below 100 m2. The most common type of large landform can be classified as complex: a mix of slide and slow flow. As expected, most landslides are located where there is steep topography: the West Fjords, the Trollaskagi peninsula, and the East Fjords. However, the distribution of landslide landforms is extremely varied within these areas. Some valleys show numerous landslides while other none. To help figuring out this heterogeneity, this database is put into relation with other type of geographical information: digital elevation models, lithology, bedrock geology, volcanic systems, faults, hydrology, permafrost, ground deformation velocities, constructions and infrastructures.

How to cite: Drouin, V. and Stefani, M.: A new landslide database for Iceland: what it tells us., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14887, https://doi.org/10.5194/egusphere-egu23-14887, 2023.

10:58–11:08
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EGU23-2084
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ECS
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On-site presentation
Silvan Betschart, Simon Loew, Neil Mancktelow, and Luiz Grafulha Morales

Many theories about processes and conditions of rock avalanches lack field evidence, due to difficulties in monitoring such events and the rarity of accessible locations to study corresponding structures in bedrock outcrops. This study provides a detailed investigation of the basal contact zone (including the rupture/sliding surface) of the Flims rock avalanche at two sites (from the proximal and distal release area) in terms of architecture, microfabric, and formation conditions. In addition, we compare our findings with shallow seismotectonic fault zones and derive indications for processes that have occurred before, during, and after the failure of the Flims rock avalanche.

 

Field observations document the wide natural variability of the basal contact zone architecture within the rock avalanche source area. The studied contact zone was formed at about 500 m depth as a stepped or undulating structure, few centimeters to several meters thick. It consists of chaotic breccia and locally features an up to 10 cm thick mesocataclasite, granular fault injections, and striated pavements indicating highly localized shear deformation. The pavements represent the main rupture/sliding plane of the rock avalanche and occur either as a sharp boundary to the intact bedrock or as parallel planes within mesocataclasite. In the proximal area of the source zone, a gradual increase of grain comminution towards the rock avalanche basal rupture/sliding surface suggests that most deformation and movement within the rock avalanche was concentrated in this narrow zone. In the more distal area, the deformation and movement were distributed on both the basal rupture surface and internal shear zones.

 

Microstructural investigations of the contact zone reveal deformations older than the mesocataclasite and pavement, including mylonites and calcite veins related to the previous tectonic history, and an old healed breccia, possibly formed during pre-failure damage in this zone. The architecture of the rock adjacent to the rupture/sliding surface observed in this study shows similarities to observations from shallow seismotectonic fault zones and high-strain and high-speed shear experiments. The analogies help to understand processes that led to the formation of the rupture plane and its increased mobility: Observations of cataclasite at the basal rupture zone suggest that the movement of the rock mass first was slow (< 0.4 m/s) and crushed the rock near the basal rupture surface by constrained comminution, inducing a granular flow. An acceleration of the slip rate to over 1 m/s led to dynamic weakening and the development of a distinct rupture/sliding surface. With the formation of a thin rupture surface, several coupled processes (grain boundary sliding, frictional heating, and thermal decomposition) might have caused a further decrease of the frictional resistance on this plane, resulting in increased mobility of the rock avalanche in the source area. Evidence for these processes is given by the occurrence of rounded nano-grain structures on the pavement of the basal rupture surface, which are possible remains of thermal decarbonation. This decarbonation implies a very local temperature rise due to frictional heating (> 720 °C), less than 10 µm away from the rupture surface.

How to cite: Betschart, S., Loew, S., Mancktelow, N., and Grafulha Morales, L.: Architecture, Microfabric and Formation Conditions of the Basal Contact Zone of the Flims Rock Avalanche (Switzerland), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2084, https://doi.org/10.5194/egusphere-egu23-2084, 2023.

11:08–11:18
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EGU23-3949
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ECS
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On-site presentation
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Cheng-Han Lin and Ming-Lang Lin

Deep-seated gravitational slope deformation (DSGSD) is a rock mass wasting process of high mountain slopes, featuring slow movement rate. Although DSGSD movement is slow, it can continue for a long period, producing large cumulative displacements and could transform to catastrophic rockslides. In Taiwan, DSGSD has often been reported in the slate belt of the Taiwan’s backbone Range because of the inherent cleavage characteristic. When the slate slope undergoing DSGSD, the geometry of cleavage structures will interact with topographic slope and manifest by different internal structures such as toppling features and flexural folding. This study investigates how the DSGSD influences the internal structures and present-day activity of slate slopes in the Chingjing region, Taiwan. We focus on where the cleavage dip direction is parallel to the topographic downslope direction. To describe the relationship between cleavage structure and DSGSD movement, we present 2D numerical simulation of simplified slopes using the distinct element modeling approach. The slope topography and cleavage geometry are based on the typical values of slate slope in the study area. The simulation shows that the rotation of the cleavage dip angle has correlated with the slope deformation mechanics at different locations. The toppling structure appears to the slope toe, and the cleavage remains the same dip angle at the crest. Three hinge lines can be identified at different depths of the slope, which suggests the location of potential basal shear bands within the slope. We also observe the distribution of the shear bands emerging at higher elevation as the deformation velocity decreases. Parametric study shows that deformation of internal structures can exist at depths of 60 m and more as a result of slope height, slope steepness and cleavage dip angle. On the other hand, this study retrieves slope kinematics by performing 2D decomposition of PS-InSAR products derived from Sentinel-1 data acquired in ascending and descending orbits. The result shows that surface displacement ranges in 5 - 10 mm/year in the period of 2015 - 2017, and the displacement rate increases to 10 - 30 mm/year in the period of 2018 - 2020. By detecting velocity change and identifying deformation dip vector, we explain the present-day activity of DSGSD and driving mechanisms in the study cases. Overall, based on mechanical modeling, our analyses demonstrate that a cataclinal slate slope can exhibit different internal structure patterns in different sectors during DSGSD. We also highlight the need for InSAR-assisted monitoring in the region lack of surface displacement data for deeper understanding of this long-term process and interactions between slope activity and potential driving force.

How to cite: Lin, C.-H. and Lin, M.-L.: Internal structure and present-day activity of deep-seated gravitational slope deformation (Chingjing, Taiwan), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3949, https://doi.org/10.5194/egusphere-egu23-3949, 2023.

11:18–11:28
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EGU23-14490
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ECS
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On-site presentation
Slow rock slope deformations promoting catastrophic collapses in tectonically active settings: the Tienchi case study (Taiwan)
(withdrawn)
Chiara Crippa, Federico Agliardi, Roberta Schibuola, Federico Franzosi, and Rou-Fei Chen
11:28–11:38
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EGU23-8130
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On-site presentation
Virginie Durand, Anne Mangeney, Pascal Bernard, Xiaoping Jia, Fabian Bonilla, Claudio Satriano, Jean-Marie Saurel, El Madani Aissoui, Aline Peltier, Valérie Ferrazzini, Philippe Kowalski, Frédéric Lauret, Christophe Brunet, and Clément Hibert

The quantification of the effects of external forcings such as seismicity and rainfall on slope destabilization is an open and important question. To investigate the role of these forcings, we analyze an unprecedented 10-year long catalog of the rockfalls occurring in the Piton de la Fournaise volcano crater. Indeed, the dense seismic network operated by the Piton de la Fournaise Volcano Observatory (La Réunion Island) makes it possible to precisely locate the rockfalls and recover the volume of each event. We use statistical tools originally developed for earthquakes to study the spatio-temporal evolution of the rockfall activity and to unravel the impact of the external forcings. Our results highlight the predominant effect of low amplitude seismicity on the slope destabilization, via a progressive damaging of the slopes. Moreover, we show that the efficiency and the time delay of this dynamic triggering depends on the stability state of the slopes, i.e. the distance to failure. To better understand our observations, we compare them with laboratory experiments on granular avalanches triggered by ultrasound.

 

How to cite: Durand, V., Mangeney, A., Bernard, P., Jia, X., Bonilla, F., Satriano, C., Saurel, J.-M., Aissoui, E. M., Peltier, A., Ferrazzini, V., Kowalski, P., Lauret, F., Brunet, C., and Hibert, C.: The competing roles of seismicity and rainfall in slope destabilization: rockfalls triggered on a metastable volcanic edifice, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8130, https://doi.org/10.5194/egusphere-egu23-8130, 2023.

11:38–11:48
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EGU23-8771
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ECS
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On-site presentation
Andrea Morcioni, Tiziana Apuani, Francesco Cecinato, and Manolis Veveakis

Large slope instability processes result from a complex interaction among different geological, geomorphological and climatic factors. A complex multidisciplinary approach is thus necessary to understand their behavior and develop modeling predictive tools. This work suggests a multi coupling method to predict stability and velocity of a landslide, giving critical values for measurable variables (i.e., piezometric level) up to which remediation actions can be deployed. The aim is to define a time‐dependent stability criterion that links the external forcing of a landslide with its internal response through a thermo-poro-mechanical mathematical model.

The presented model is based on the assumption that most of the landslide deformation is concentrated on a basal shear band representing the sliding surface: the landslide body is deemed as a rigid block sliding on a visco-plastic shear band with thermal softening and velocity hardening. When the landslide moves, it causes friction with mechanical dissipation that raises the basal temperature and reduces the shearing resistance of the shear-band material. This process can continue up to the point when the friction coefficient decreases uncontrollably due to a thermal runaway instability and the system become unstable, even without changes in the external factors.

The model is applied to the Ruinon Landslide located in the Central Italian Alps (upper Valtellina region). It represents one of the most active cases in the alpine region, with a main sliding surface located at a depth of approximately 70 m, for a total estimated volume of about 20 Mm3 threatening the national road SS300 that travels through the valley bottom. On the base of the available in situ monitoring data (Piezometers, Ground-Based Interferometric Radar), velocity–time curves correlate with the piezometric level trend, suggesting a key role of pore pressure as an accelerating factor for the landslide.

The workflow of the analysis involved different steps. A preliminary 3D FEM numerical analysis was performed to provide the stress-strain distribution along the slope. Then, to define the thermo-poro-mechanical behavior of the sliding surface and to calibrate the mathematical model, triaxial compression tests with thermal control were performed on rock samples representative of the shear band. The pore pressure data from in situ piezometers were introduced as input-data and the landslide basal temperature was calculated. Finally, the strain rate was simulated by the model and a process of validation was applied using field displacement histories recorded by the landslide monitoring system.

The outputs of the model well simulate the landslide velocity, reproducing the sliding behavior and its relationship with pore pressure. The developed time dependent stability criterion represents an innovative physics-based tool for analyze landslide evolution leading to early-warning and remediation strategies, that accounts for thermal and velocity sensitivity of shear band materials, as well as the effect of pore pressure in promoting the evolution of different creep stages. The validated model can be also used as a predictive tool, to forecast the behavior of landslides and establish a physically based early warning strategy taking into account future climate scenarios.

How to cite: Morcioni, A., Apuani, T., Cecinato, F., and Veveakis, M.: A thermo-poro-mechanical model to simulate and predict landslide evolution: a physics-based method applied to the Ruinon Landslide (Italian Alps), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8771, https://doi.org/10.5194/egusphere-egu23-8771, 2023.

11:48–11:58
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EGU23-4270
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ECS
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On-site presentation
Liang Wang, Simon Loew, and Qinghua Lei

Rock slopes usually exhibit progressive failure phenomena over a long period of time under the active Earth surface environment involving complex geological, mechanical, hydrological, and chemical interactions. Among these processes, weathering has been recognised as a ubiquitous and important factor that drives slope destabilisation. Rock masses in a slope may experience weathering-induced strength degradation of variable degrees depending on the morphology, lithology, depth, fracturing, and time, which can lead to the emergence of various rock slope failure patterns, e.g. planar and rotational slides, slumps, topples, and rock falls. After failure, the slope may transition from slow deformation to catastrophic collapse characterised by rapidly moving material flows of fragmented rocks. These complex processes are driven by various mechanisms operating across different timescales, which pose a great challenge for modelling the entire history of rockslide evolution. In this study, we develop a unified computational framework for simulating the pre- and post-failure behaviour of rock slopes subject to long-term weathering processes. This framework includes the following key features: (i) a coupled weathering-damage model is developed to capture the interplay of weathering-induced strength loss and damage-related strain softening; (ii) pre-existing faults are represented explicitly as thin weakness zones; (iii) an implicit time integration scheme is adopted to simulate the slope evolutionary behaviour across multiple timescales; (iv) a frictional velocity-weakening law is incorporated to capture the development of rapid mass flows; (v) the particle finite element technique is used to track the small to large deformation/motion of rock masses. We show that our model can realistically simulate the pre-failure progressive rock slope destabilisation, the catastrophic rock mass failure, and the post-failure transient runout, demonstrating the capability of our model in realistically capturing the initiation, evolution, and consequence of weathered rock slope failures. Our results provide useful insights into the interplay of natural weathering and brittle damage in rockslide evolution and the control of geological structures on pre- and post-failure patterns of rock slopes.

How to cite: Wang, L., Loew, S., and Lei, Q.: Modelling weathering-induced progressive rock slope failures, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4270, https://doi.org/10.5194/egusphere-egu23-4270, 2023.

11:58–12:08
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EGU23-14471
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Highlight
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On-site presentation
Daniele Giordan, Niccolò Dematteis, Fabrizio Troilo, and Valerio Segor

The study of glacier instabilities can be very useful, particularly when the activation of large ice avalanches can be dangerous for several elements at risk down-valley. This critical condition characterizes a growing number of glaciers in the Alps, where the distance between infrastructures, tourist areas and glaciers are minimal. The tragedy that occurred in Marmolada in 2022 is an example of the impact that an ice avalanche can have on a highly frequented area. In several recent studies, glacier-related instabilities are based on approaches similar to the ones adopted for landslides; in particular, the use of high-rate monitoring systems is fundamental for a characterization of the surficial movement of the glacier and its activity. The presence of an acceleration phase is often a precursor of the fall of the unstable ice chunk, and that is why the use of high-rate monitoring systems can be adopted for early warning purposes. The availability of similar data also allows a deeper knowledge of the processes that characterize the evolution of glaciers. Up to the present, the limited presence of permanent survey systems has prevented a more detailed study of the dynamics that control the evolution of glaciers. Recent monitoring solutions adopted to manage the ice-avalanche-related risk in the Alps represent an excellent opportunity to reduce this gap. The Grand Jorasses (Italian side of the Mont Blanc massif) open-field laboratory for the development of monitoring systems is an interesting example of this recent opportunity. The presence of cold (Whymper serac) and temperate (Planpincieux glacier) monitored glaciers is also important for better evaluating the impact of water at the bedrock-ice interface on the stability of hanging glaciers. The results obtained in the Grand Jorasses open-field laboratory pointed out the high complexity of temperate glaciers due to the variety of triggers that can activate large ice falls. The restricted access to the site for safety reasons limited the direct measurement of important parameters and led to the adoption of proximal remote sensing solutions. Thanks to the acquired data, a conceptual model of the glaciers' dynamics have been developed and adopted for better risk assessment.

How to cite: Giordan, D., Dematteis, N., Troilo, F., and Segor, V.: Dynamics of alpine glaciers large instabilities: results and open problems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14471, https://doi.org/10.5194/egusphere-egu23-14471, 2023.

12:08–12:18
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EGU23-1670
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ECS
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On-site presentation
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Daniel Hölbling, Lorena Abad, Raphael Spiekermann, Hugh Smith, and Andrew Neverman

Earthflows are complex landslide phenomena that can occur on gentle to moderate slopes in plastic, mixed, and disturbed earth with significant internal deformation. They exhibit a wide range of sizes (from tens of metres to kilometres in length) and can form complexes with slowly deforming bodies or fails along multiple shear surfaces, resulting in a lobate flow-like morphology. While they can show different movement rates, typical earthflows move slowly and intermittently with active and inactive states, whereby velocities are usually measured in meters per year. They mainly occur under saturated conditions, and trigger factors include prolonged or intense rainfall or snowmelt, stream erosion at the bottom of a slope, or the lowering of adjacent water surfaces and the related drawdown of the groundwater table. Earthflows can cause damage to infrastructure, affect the productivity of farmland, potentially dam rivers with subsequent flooding upstream, pose a risk to downstream areas, and impact water quality due to sediment input to streams.

Earthflows are usually mapped manually using orthophotos, but the quality of existing inventories differs significantly. Owing to their complexity, the semi-automated detection and delineation of earthflows is highly challenging. Boundaries are generally transitional rather than discrete, and a range of factors influence the internal homogeneity of the landslide body, such as topographic relief, landform properties, and scale. Terrain and topographic characteristics of earthflows, such as small scarps, hummocks, and flow lobe shadows, are difficult to discern based only on optical imagery; thus, the integration of high-resolution topographic data in the recognition process is important. While a human interpreter can use such specific topographic characteristics, implementing the required expert knowledge into automated mapping approaches based on remote sensing data is challenging.

In this study, we addressed these challenges and aimed to semi-automatically detect and map earthflows in the Tiraumea catchment, which is an upper catchment of the Manawatū catchment located in the Manawatū-Whanganui region of the North Island of New Zealand, using aerial photography and a photogrammetrically derived high-resolution digital surface model (DSM) within an object-based image analysis (OBIA) framework. A flexible segmentation approach was followed, creating different sizes of connected image objects at different hierarchical segmentation levels, whereby the earthflow boundaries were stepwise adapted and refined. Statistics derived from a range of terrain derivatives informed the selection of the most suitable derivatives for knowledge-based classification, which relied on specific earthflow characteristics, such as the connection to streams and the existence of bare ground, rushes, and surface water. The results show that the automated delineation of earthflow bodies is particularly difficult and requires further improvement. However, the mapping outcomes indicate potentially unknown earthflow locations that should be confirmed or refuted by local experts or in the field. An approach that combines semi-automated with manual feature detection could improve the entire mapping process and lead to acceptably accurate mapping results with the potential to greatly reduce the time and effort needed to generate earthflow maps.

How to cite: Hölbling, D., Abad, L., Spiekermann, R., Smith, H., and Neverman, A.: Semi-automated detection and delineation of earthflows in New Zealand using remote sensing - challenges and opportunities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1670, https://doi.org/10.5194/egusphere-egu23-1670, 2023.

12:18–12:30
Lunch break
Chairpersons: Christian Zangerl, Irene Manzella
14:00–14:03
14:03–14:13
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EGU23-6798
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On-site presentation
Kuo-Lung Wang, Jun-Tin Lin, and Yi-Hsuan Lee

In remote sensing of landslide investigation, the interpretation of optical image is the main method at present. However, when a disaster occurs, it is very difficult to obtain images without cloud coverage. For example, Typhoon Lubi in August 2021 and Typhoon Nissa in 2022 caused many landslides and road interruptions. However, due to the cover of clouds and fog, it was impossible to obtain satellite images in time to judge the scale of the disaster. Unmanned vehicles are also affected by weather factors, which greatly increases the risk of flight. Therefore, it is extremely necessary to develop disaster identification methods that are not affected by weather.

In this study, the long electromagnetic waves of synthetic aperture radar (SAR) are not affected by cloud and fog to develop a landslide detection model for radar images. The reference range of the location and scale of the landslide can be obtained under bad weather conditions to make up for the weather limitations when evaluating the scope of the disaster with optical images.

In this study, the NDSI&RVID method is used as the index for the identification and interpretation of the landslide area, and the analysis and discussion of the landslide area is carried out in combination with multi-time series and different orbital data. The effect of landslide identification is improved by three methods: single-sequence identification and interpretation stacking, multi-time-series index stacking, and multi-time-series image stacking. Among them, better interpretation results can be achieved by stacking multiple time-series images. It is recommended to use the number of 4 images before the disaster and 1 image after the disaster for data interpretation. Although the image pixel classification effect still needs to be improved, the identification rate for landslides of more than 10 hectares can reach more than 90%. In the absence of optical images, it has considerable reference value.

How to cite: Wang, K.-L., Lin, J.-T., and Lee, Y.-H.: The Feasibility Assessment of Quick Landslide Identification Methods After Hazards with Sentinel-1 SAR Imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6798, https://doi.org/10.5194/egusphere-egu23-6798, 2023.

14:13–14:23
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EGU23-7155
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ECS
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On-site presentation
Nirdesh Sharma and Manabendra Saharia

A landslide database is of utmost importance for hazard management as well as early warning systems. Historically landslides were manually identified by ground surveys or remote sensing data, but with development in satellite technology open-source satellite imagery has emerged as a preferred data source for landslide identification due to its cost effectiveness. On the other hand, an increase in computing power made computer vision methods especially deep learning popular for satellite image segmentation. Deep learning models require a large amount of data to reach operational performances, however there is very little labelled landslide data present. Labelling satellite imagery is costly and time consuming. Active learning remedies this by optimally selecting the data to label thereby maximizing the performance of the model given the limited data. In this study we present an active learning-based framework to train a segmentation model to identify landslides. The pre- and post-landslide images from sentinel 2 are merged with terrain features to create input data bands. The model is tested on a test database using metrics like IOU. The methodology has been developed with an application in India but can be applied globally.

 

How to cite: Sharma, N. and Saharia, M.: DL-AISLE: A Deep Learning framework using Active Learning on Satellite imagery for Landslide identification , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7155, https://doi.org/10.5194/egusphere-egu23-7155, 2023.

14:23–14:33
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EGU23-9298
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ECS
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On-site presentation
Zhuge Xia, Mahdi Motagh, Tao Li, Mimi Peng, and Sigrid Roessner

With the avalanche of satellite remote sensing sensors, significant efforts have been made to develop methods to integrate optical and SAR remote sensing efficiently to quantify the kinematics and lifecycle of landslides. In this study, we design a framework that integrates multi-sensor satellite remote sensing data to investigate post-failure kinematics of the 17 June 2020 Aniangzhai landslide in the Danba County of Southwest China. This ancient landslide was partially reactivated due to rapid river incision and toe erosion during a complex cascading event, which led to an evacuation and relocation of more than 20,000 people.

First, time series of Planet images are exploited using the sub-pixel offset tracking method to generate horizontal deformation. Then advanced Multi-temporal InSAR (MTI) techniques are utilized to analyze the line-of-sight (LOS) displacements for 16 months after the failure. Eventually, the dynamics of the post-failure mechanism are modeled by integrating optical and radar data using an exponential decay model with independent component analysis (ICA) and least squares methods. Besides, the performance of a newly designed corner reflector (CR), consisting of two sets of semi-circular metal plates with a radius of 30-40 cm, is evaluated using both TerraSAR-X (TSX) and Sentinel-1 SAR data.

Optical results show that the landslide underwent large deformation up to around 14.3 meters within 1.5 months after the failure, then the rate of deformation decreased slowly with time. InSAR analysis suggests that the LOS velocity reached a maximum of approximately 300 mm/year, indicating the active status of the ancient landslide body after failure. Using ICA decomposition, we extracted different features with various spatiotemporal patterns from the landslide body, which was then applied in data integration and 4D modeling of landslide kinematics. Our experiment using newly designed CRs indicates improvement in the background intensity in TSX images by around 30 dB, with signal-to-clutter ratio (SCR) exceeding 25 dB. The radar cross-section (RCS) of CRs in both TSX and S1 images remains relatively stable, ranging from 15-23 dB, making them suitable for CR-InSAR analysis.

How to cite: Xia, Z., Motagh, M., Li, T., Peng, M., and Roessner, S.: Characterizing 4D post-failure slope kinematics of the 2020 Aniangzhai landslide combining different remote sensing measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9298, https://doi.org/10.5194/egusphere-egu23-9298, 2023.

14:33–14:43
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EGU23-11251
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On-site presentation
Meei-Ling Lin, Sheng-Yu Chiu, Kuo-Lung Wang, and Yo-Ming Hsieh

The deep-seated landslides often caused severe hazard due to the large area and landslide mass associated with the landslide movement. Thus, monitoring the landslide movement is an important task for landslide hazard management. The Microelectromechanical Systems (MEMS) technique developed rapidly in recent years provides the ability of low-cost sensors and easy installation for monitoring of the landslide movement in field. Typically, the landslide movement monitoring using MEMS is based on the tilt angle determined from the measured ground acceleration variations in three directions, and being subjected to the signal noise. We adopt Moving Window Fast Fourier Transform and other seismic wave analysis in this study to improve resolution of the seismic signals and achieve a sound detection of deep-seated landslide movement. The MEMS was installed at the Lantai deep-seated landslide study area, which measured the ground accelerations mid-slope of the landslide. The seismic signals recorded for eleven earthquake events and three heavy rainfall events are selected for analysis. It was found that the signal frequency can be separated from the system responses and related to the landslide movement. Validations were conducted by comparing the analysis results to the field monitoring data of in-place inclinometer and borehole extensometer while available. It is suggested that the landslide movement can be identified with seismic signal at approximately 17 Hz, and the results are consistent for both earthquake-induced and rainfall-induced events. 

How to cite: Lin, M.-L., Chiu, S.-Y., Wang, K.-L., and Hsieh, Y.-M.: Detecting Deep-seated Landslide Movement Using Seismic Signal Analysis of MEMS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11251, https://doi.org/10.5194/egusphere-egu23-11251, 2023.

14:43–14:53
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EGU23-12150
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ECS
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On-site presentation
Hsien-Li Kuo, Guan-Wei Lin, Ting-Yu Lin, and Chung‑Ray Chu

Monitoring the creeping indications of landslides could provide valuable information for hazard prevention. The DIC methods allow to measure horizontal ground deformation with optical images. The surface moving information of landslide could offer the necessary data to infer the geometry including landslide sliding surface and volume of landslides.

This study focuses on a deep-seated landslide in Guanghua area which has been creeping since 2006 in northern Taiwan and there were sporadic collapse events in this slope area during recent years. The satellite images from 2016 to 2022 were collected and applied in Sliding Time Master Digital Image Correlation Analyses (STMDA) procedure to obtain the surface deformation of the landslide. The results including surface displacement and moving direction highly coincided with other monitoring data from on-site instruments. The landslide depth derived from surface displacements is about 20 m. The achievements reveal that using DIC method help to understand the landslide creeping process and the geometry distribution of potential landslide

How to cite: Kuo, H.-L., Lin, G.-W., Lin, T.-Y., and Chu, C.: Using Digital Image Correlation (DIC) method to monitor the creeping indication and infer the geometry of landslides, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12150, https://doi.org/10.5194/egusphere-egu23-12150, 2023.

14:53–15:03
|
EGU23-13439
|
On-site presentation
Halldór Geirsson, Thorsteinn Sæmundsson, Jóhanna Malen Skúladóttir, and Nicolai Jónasson

Landslides show various characteristics of spatio-temporal distribution of movement. For example, nearby parts of the same landslide may respond differently to heavy rainfall. We report here on measurements of various episodic and transient movements, using low-cost continuously recording GNSS instruments, in two landslides areas in Iceland.

 

In the Tungnakvíslarjökull landslide, which lies on the west flank of the Katla Volcano in south Iceland, two GNSS instruments were installed in 2019 and 2020, at 830 and 650 m a.s.l. height, respectively. This landslide mass has subsided gradually by approximately 200 m in the past 70 years and has a scarp approximately 1.5 km long. The GNSS stations show movements of several decimeters per year, with most movement confined to late summer and fall each year. The lower station of the two shows distinct "jerky" motion, with instantaneous movements of 5-15 cm each time. These offsets are sometimes accompanied by regionally located seismic events occurring within seconds of the offsets. The upper station, however, moves more continuously. The landslide region experiences heavy rain in the fall season, however, also in the spring when little movement is observed. One possibility explaining the lack of motion in the spring time that frozen surface layers in spring to mid-summer may hinder precipitation from entering the landslide mass.

 

The Almenningar landslide region in north Iceland is composed of three main landslides spanning ~5 km distance. The fastest moving part is ~0.3 km wide and moves by ~1 m per year. A main road traverses the landslide area and needs frequent repairs because of differential motion. In the summer of 2022, nine continuously running GNSS stations were installed along the main road in the landslide region at 50 – 60 m a.s.l. height, with eight stations located in active parts, and one acting as a local reference station for monitoring purposes. Since the installation, three distinct movement episodes have been recorded, all following heavy rain, recorded by local and regional meteorological stations. However, different segments of the landslide area respond differently to the rain forcing, starting and stopping at different times, with some stations showing abrupt start with near-exponential decay, while some show gradual acceleration, followed by deceleration. We suggest that hydrological pressure inside the landslide governs much of its behavior.

 

In summary, the continuous low-cost GNSS observations complement spatially dense deformation techniques, such as using InSAR, differential DEM, or feature tracking. The continuous GNSS monitoring allows for great potential in understanding the time-dependent mechanics of landslides, and contributing to early warning of excessive motion.

How to cite: Geirsson, H., Sæmundsson, T., Skúladóttir, J. M., and Jónasson, N.: Seasonal and precipitation-triggered movements of the Almenningar and Tungnakvíslarjökull landslides, Iceland, monitored by low-cost GNSS observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13439, https://doi.org/10.5194/egusphere-egu23-13439, 2023.

15:03–15:13
|
EGU23-2422
|
ECS
|
On-site presentation
|
Qinghua Lei, Didier Sornette, Haonan Yang, and Simon Loew

Catastrophic rock slope failures pose great threats to life and property, but remain difficult to predict. Over the past decades, great efforts have been devoted to develop and deploy high-precision monitoring technologies to observe unstable rock slope movements. However, only a limited number of large rock slope failures have been so far successfully mitigated. Here, we present a novel predictive framework to quantitatively assess the slope failure potential in real time. Our method builds upon the physics of extreme events in natural systems: the extremes so-called “dragon-kings” (e.g. slope tertiary creeps prior to failure) exhibit statistically different properties than other less intense deformations (e.g. slope secondary creeps). We develop robust statistical tools to detect the emergence of dragon-kings during rockslide evolution, with the secondary-to-tertiary creep transition quantitatively captured. We also construct a phase diagram characterising the detectability of dragon-kings against “black-swans” and informing on whether the slope evolves towards a catastrophic or slow landslide. We test our method on both synthetic and real datasets, demonstrating how it might have been used to forecast three representative historical rockslide events at Preonzo (Switzerland), Veslemannen (Norway), and Moosfluh (Switzerland). Our method, superior to the conventional velocity threshold approach, can considerably reduce the number of false alarms and identify with high confidence the presence of true hazards of catastrophic rock slope failures. Our work adds a new conceptual framework and operational methodology with a significant potential to reduce landslide risks and support existing early warning systems.

How to cite: Lei, Q., Sornette, D., Yang, H., and Loew, S.: Dragon-king detection for real-time forecast of catastrophic rock slope failures, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2422, https://doi.org/10.5194/egusphere-egu23-2422, 2023.

15:13–15:23
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EGU23-14398
|
ECS
|
On-site presentation
Adriaan van Natijne, Thom Bogaard, and Roderik Lindenbergh

Landslides are a major geohazard in hilly and mountainous environments. We focus on slow-moving, deep-seated landslides that are characterized by gradual, non-catastrophic deformations of millimeters to decimeters per year and cause extensive economic damage. Where landslide hazard mitigation is impossible, Early Warning Systems are a valuable alternative to reduce landslide risk. Recent studies have demonstrated the effective application of machine learning for deformation forecasting to specific cases of slow-moving, non-catastrophic, deep-seated landslides. To test to what extent a combination of data-driven machine learning techniques and remote sensing observations can be used for landslide deformation forecasting, we developed a machine learning based nowcasting model on the multi-sensor monitored, deep-seated, Vögelsberg landslide, near Innsbruck, Austria. Our goal was to link the landslide deformation pattern to the conditions on the slope, and to produce a four-day, short-term forecast, a nowcast, of deformation accelerations.

Precipitation, snowmelt, soil moisture, evaporation, and temperature were identified as hydro-meteorological variables with high potential for forecasting deformation acceleration. Time series of those variables were obtained from remote sensing sources where possible, and otherwise from reanalysis sources as surrogate for data that is likely to be available in the near future. Deformation, the result of slope instability, was monitored daily by a local, automated total station of the Division of Geoinformation of the Federal State of Tyrol.

The five years of daily deformation and hydro-meteorological observations at the Vögelsberg landslide is quite limited for a machine learning model. To limit the complexity of the model, and the number of parameters to be optimized, the model was designed to mimic a bucket model, a simple hydrological model. A shallow neural network based on Long-Short Term Memory, was implemented in TensorFlow, as custom sequence of existing building blocks. In addition, a traditional neural network and recurrent neural network were tested for comparison.

Thanks to the limited complexity of the model, the major contributors could be determined by trial-and-error of nearly 150 000 model variations. Models including soil moisture information are more likely to generate high quality nowcasts, followed by models based solely on precipitation or snowmelt. Although none of the shallow neural network configurations produced a convincing nowcast deformation, they provide important context for future attempts. The machine learning model was poorly constrained as only five years of observations were available in combination with the four acceleration events that occurred in these five years. Furthermore, standard error metrics, like mean squared error, are unsuitable for model optimization for landslide nowcasting.

We showed that landslide deformation nowcasting is not a straightforward application of machine learning. The complexity of the machine learning model formulation at the Vögelsberg illustrates the necessity of expert judgement in the design and evaluation of a data-driven nowcast of slow deforming slopes. A future, successful nowcasting system will require a simple, robust model and frequent, high quality and event-rich data to train upon.

How to cite: van Natijne, A., Bogaard, T., and Lindenbergh, R.: Challenges for satellite-based deep-seated landslide nowcasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14398, https://doi.org/10.5194/egusphere-egu23-14398, 2023.

15:23–15:33
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EGU23-14542
|
On-site presentation
Jean-Philippe Malet, Catherine Bertrand, Clément Hibert, Mathilde Radiguet, Thomas Lebourg, Stéphanie Gautier, Grégory Bièvre, Maurin Vidal, Xavier Wanner, Candide Lissak, Benjamin Vial, Nicolas Châtelain, Romain Besso, Sandrine Baudin, and Anne Boetsch

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.

How to cite: Malet, J.-P., Bertrand, C., Hibert, C., Radiguet, M., Lebourg, T., Gautier, S., Bièvre, G., Vidal, M., Wanner, X., Lissak, C., Vial, B., Châtelain, N., Besso, R., Baudin, S., and Boetsch, A.: The OMIV service: acquiring and sharing long-period instrumental time series for documenting landslide activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14542, https://doi.org/10.5194/egusphere-egu23-14542, 2023.

15:33–15:45

Posters on site: Mon, 24 Apr, 08:30–10:15 | Hall X4

Chairperson: Christian Zangerl
X4.29
|
EGU23-6748
|
ECS
Jiaming Yao, Hengxing Lan, Langping Li, Yiming Cao, Yuming Wu, Yixing Zhang, and Chaodong Zhou

Large paleolandslides are developed in the upper reaches of Jinsha River, which seriously threaten the safety of nearby residents and engineering facilities. It is important to study the movement characteristics of these landslides. In this work, we inspect the deformation characteristics of a rapid landsliding area along the Jinsha River by using multi-temporal remote sensing, and analyzed its future development. Surface deformations and damage features between January 2016 and October 2020 were obtained using multi-temporal InSAR and multi-temporal correlations of optical images, respectively. Deformation and failure signs obtained from the field investigation were highly consistent. Results showed that cumulative deformation of the landsliding area is more than 50 cm, and the landsliding area is undergoing an accelerated deformation stage. The external rainfall condition is an important factor controlling the deformation. The increase of rainfall will accelerate the deformation of slope. The geological conditions of the slope itself affect the deformation of landslide. Due to fault development and groundwater enrichment, slopes are more likely to slide along weak structural plane. The Jinsha River continuously scours the concave bank of the slope, causing local collapses and forming local free surfaces. Numerical simulation results show that once the landsliding area fails, the landslide body may form a 4 km long dammed lake, and the water level could rise about 200 m.

How to cite: Yao, J., Lan, H., Li, L., Cao, Y., Wu, Y., Zhang, Y., and Zhou, C.: Characteristics of a rapid landsliding area along Jinsha River revealed by multi-temporal remote sensing and its risks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6748, https://doi.org/10.5194/egusphere-egu23-6748, 2023.

X4.30
|
EGU23-5022
|
ECS
Edoardo Carraro, Yenny Alejandra Jimenez Donato, Francisca Antonia Soto Bravo, Robert Kanta, Philipp Marr, and Thomas Glade

Landslides are one of the most important and frequent geological hazards worldwide. Among the many different types and processes, slow and very slow mass movements are often underestimated, even if they can impact local infrastructures and permanently affect agricultural practices and land use planning. Slow-moving landslides are common in clay-rich layers and areas that are typically characterized by mechanically weak materials. In the field of slow-moving landslide monitoring, understanding the factors driving the slope instability is the key to assessing the landslide hazard and to supporting local authorities in hazard management.

In this study, the first results of an ongoing monitoring setup for a complex, slow-moving earth-slide system in Lower Austria are presented. The Brandstatt landslide is located in a complex geological transition zone between the Flysch and Klippen zones, which is known to be prone to shallow and deep landslides because its susceptibility to sliding processes has been investigated in recent years. Considering the predisposing conditions (geological and climatic settings), the unstable slope can be considered as a representative site of complex landslide processes in this region.

Landslide movements monitoring includes a combination of surface and subsurface methods to investigate the spatio-temporal evolution of factors that prepare, trigger, and control landslide dynamics. Geological characterization of the subsurface was obtained through a dynamic penetration test (DPH) campaign and percussion drilling. In addition, the subsurface displacements and potential shear planes were evaluated using repeated inclinometric measurements. A meteorological station is also installed on-site, as well as piezometers and time-domain reflectometry (TDR) sensors in selected locations on the slope. These instruments provide high temporal resolution data, which are automatically transmitted to a server for the real-time monitoring of hydrometeorological conditions. However, the monitoring strategy to detect surficial changes is currently limited to the application of Terrestrial Laser Scanning (TLS) because an Unmanned Aerial Vehicle (UAV)-based Structure from Motion (SfM) is not possible for vegetation cover issues.

The current results suggest the following: i) the connection between soil properties, soil moisture, and changes in groundwater level in the evolution of the slope instability, ii) potential shear surfaces within the shallow layers of the unstable slope, and iii) the importance of combining hydrological and geotechnical monitoring to set up an integrated network for landslide interpretation. Accordingly, obtaining information from a multi-parameter monitoring system is fundamental to identifying the relationship between the triggering and kinematic mechanisms of a complex, slow-moving landslide. However, the nonlinear behavior of slow movements restricts the temporal capability to properly understand the processes of complex mass movements. Consequently, landslide dynamics need to be further understood to establish a long-term monitoring system.

How to cite: Carraro, E., Jimenez Donato, Y. A., Soto Bravo, F. A., Kanta, R., Marr, P., and Glade, T.: Insights from a combination of surface and deep measurements to set a long-term monitoring system of a complex, slow-moving landslide in Lower Austria (Austria), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5022, https://doi.org/10.5194/egusphere-egu23-5022, 2023.

X4.31
|
EGU23-7442
|
ECS
Francesco Seitone, Victor Buleo Tebar, Michele Camillo Gabriele Licata, Mauro Bonasera, Alessio Argentieri, Giovanni Rotella, and Giandomenico Fubelli

On large landslide areas, two-dimensional and three-dimensional geological-technical models realization require a large number of subsurface data.

We investigate a complex landslide system located in San Vito Romano, Central Italy, 40 km east from Rome where a large number of boreholes, piezometers and geophysical surveys are available.  

The purpose of this work is the San Vito Romano landslide characterization in order to create a simplified graphic 3D model and to support a monitoring plan. The aim is also to support local authorities in civil protection activities.

The geological context is characterised by a Tortonian sequence of turbidite deposits, characterised by marls and arenaceous intercalations, forming a monocline with 15-20° dip-direction eastward, parallel to slope inclination. Moreover, a complex hydrogeological system characterises the groundwaters.

This landslide has a spatial extent of about 0.5 km2 and it has been studied for lot of years. It affects San Vito Romano’s new town (built from the 60s) and it has been interpreted as a large rock translational slide. From a geomorphological point of view the village is located along a cuesta. Human activities consist in buildings, roads and public services, built over the years, even in the recent past.

A multitude of technical reports were carried out in this area during the last decades: geological surveys for building projects, geotechnical surveys for landslide monitoring planning, academic studies and field survey to understand the geomorphological slope evolution, hydrogeological and geophysical survey.

All the available surveys were censored in order to create a large database in GIS environment. The database containing all the information from 80 linear and punctual surveys.

Therefore, a boreholes surveyed quick interpretation was carried out. First, the stratigraphy was simplified into three different lithological units: loose material belonging to the landslide, bedrock involved in the gravitational process and bedrock in place. The stratigraphic and geotechnical data were implemented by the seismic data.

A Digital Terranean Model was created using contour lines and elevation points from a 1:2000 scale local topographic map.

All available data has been entered into AutoCAD Map 3D and georeferenced in GIS environment. 7 E-W and 8 S-N cross sections were realized allowing a first two-dimensional landslide system interpretation. Finally, the cross sections were correlated to create a single simplified three-dimensional subsurface model.

This model shows at least three surfaces of rupture at different depth and the geological setting of the wide translation slide. Moreover, it could be implemented with new data and it could be imported into slope stability and hydrogeological modelling software for numerical analysis.

How to cite: Seitone, F., Buleo Tebar, V., Licata, M. C. G., Bonasera, M., Argentieri, A., Rotella, G., and Fubelli, G.: The large San Vito Romano (central Italy) landslide system 3D geological-technical model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7442, https://doi.org/10.5194/egusphere-egu23-7442, 2023.

X4.32
|
EGU23-16666
Ji-Shang Wang, Tung-Yang Lai, Chyan-Deng Jan, Guei-Lin Fu, Cheng Hsiu Tsai, and Wei-Ze Liou

The landslide prone area, Xingzhuang has been identified as a deep-seated landslide prone area by Taiwan authorities. Where covers a 10.3 hectares’ area with an average slope of 22.8 degrees and 20 buildings around the slope toe. The majority lithology of upper slope is sand-shale interbedded with highly sand contented, which differs from lower slope in shale with mud contented. In order to grasp the activities of this area, we have installed a real-time compound monitoring station including GNSS, biaxial tiltmeter, ground water level meter, and rain gauge.

The rainfall depth of 2021 and 2022 was 4,175 mm and 1,691 mm respectively. The difference was larger than 2400 mm in our study area which might induced the different activity behaviors. In this study, we discussed the relations of slope activity and hydrological parameters in last two years. The results show (1) The variation of X-direction of tiltmeter were about 7,500 and 3,500 (sec) in 2021 and 2022, respectively. The variation of Y-direction of tiltmeter were about 6,500 and 4,500 (sec) in 2021 and 2022, respectively. (2) In the same 6-hours rainfall intensity, the 6 hours tilt-angle of X and Y direction in 2021 were both two times of 2022. (3) In the same ground water level, the 6 hours tilt-angle of X and Y direction in 2021 were about 2 and 1.5 times of 2022, respectively. (4) In the same variation of 6-hours ground water level, no matter raising or decline ground water level the 6 hours tilt-angle of X and Y direction in 2021 were about 2.2 and 1.5 times of 2022, respectively. And the change rate of the 6 hours tilt-angle would be accelerated when the 6-hours variation of groundwater level was higher than 0.4 meters. On the whole, the rainy year would induce more active than dry year.

How to cite: Wang, J.-S., Lai, T.-Y., Jan, C.-D., Fu, G.-L., Tsai, C. H., and Liou, W.-Z.: Difference between rainy and dry year in Relations of activity and hydraulic parameters of landslide prone area: A case study in Xinzhuang, Southern Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16666, https://doi.org/10.5194/egusphere-egu23-16666, 2023.

X4.33
|
EGU23-16680
Rou-Fei Chen, Chris Li, Tzung-Ting Chen, and Yi-Chung Chen

Since its opening to traffic, the Southern Cross-Island Highway has been playing an important role in linking Southern and Eastern cities in Taiwan. Nevertheless, Southern Cross-Island Highway was firstly struck by the 1999 Ji-ji Earthquake, which resulted in collapses along the route, and then Typhoon Morakot, which caused damages of 22 bridges and a number of deep-seated landslides between Meishan of Kaohsiung and Siangyang on the East. A long-term road reconstruction and improvement project of Southern Cross-Island Highway was therefore initiated in 2009. In August 2021, the torrential rain triggered a deep-seated landslide located in the upstream of Yusui Stream and an enormous amount of debris was brought to the downstream and crashed Minbaklu Bridge between Meishan and Siangyang. Although the Directorate General of Highways cleared the route and built a temporary steel bridge for people to pass through, this incident has highlighted the fact that the road breaks when plum rain or torrential rain occurs. This project has adopted optical satellite imagery, aerial LiDAR and UAV, technologies that complement each other with their respective benefits and drawbacks. Aerial LiDAR can remove vegetation and present the real ground surface, enabling researchers to calculate the volume of landslide materials of Yusui Stream and Putanpunas Stream using LiDAR derived DTM (digital terrain model) constructed based on the images collected between 2016 and 2022. The three-dimensional terrain interpretation and landslide volume calculation results reveal that the landslide surface area had been continuously increased over the last six years due to abundant rainfall brought by typhoons and torrential rain, causing an enormous volume of debris falling into the main river channel and piled up at its confluence with Laonong River. Nevertheless, the interpretation can be hard in areas with small-scale shallow landslide due to smaller changes to the surface elevation. Optical satellite imagery before and after the sliding is therefore required to quantify the change of landslide volume, helping to determine potential landslide and accumulation areas even more effectively.

How to cite: Chen, R.-F., Li, C., Chen, T.-T., and Chen, Y.-C.: Applications of multi-scale remote sensing data to determine potential landslides in the Laonong watershed areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16680, https://doi.org/10.5194/egusphere-egu23-16680, 2023.

X4.34
|
EGU23-14912
|
ECS
Severin Simma, Reinhard Gerstner, Gerald Valentin, Franz Goldschmidt, and Christian Zangerl

We present a study focusing on the geologic-geometrical characterization of an approximately
1,5 km² large, deep-seated rock slide at the south-eastern slope of the Wasserradkopf (3032
m a.s.l.) located in the high alpine environment of the Hohe Tauern National Park (Carinthia,
Austria). The rocks composing the Wasserradkopf belong to the “Bündnerschiefer”, which
mainly consist of a highly schistose rock mass.
Within our study, we performed a lithological and structural characterization, detailly mapped
the geomorphological features, and incorporated high resolution INSAR data in order to
demonstrate the structural control on the rock slide process.
Firstly, we conducted a geological field survey with the aim of creating a geological map of the
study site. Petrographic investigations on the microscope helped to classify the mapped
lithologies according to their mineralogy. Additionally, we recorded discontinuities to identify
the structural inventory of the rock mass hosting the rock slide allocate the discontinuities to
discontinuity sets.
Secondly, we characterized and mapped the geomorphological features, i.e., scarps, counter
facing scarps and horst and graben structures on the rock slide surface to identify the unstable
areas and distinguish individual rock slide slabs.
Finally, we assessed the INSAR data to quantify the movement in the outlined unstable areas.
By mapping areas of differential deformation rates, we confirm the presence of individual rock
slide slabs.
The preliminary results show that dominant brittle structures, which are represented by two
subvertical NNE-SSW and WNW-ESE striking joint sets, and several NE-SW striking steep
standing faults provide a favorable structural predisposition in interplay with the moderately
out-slope dipping schistosity for a rock slide mechanism to develop. Moreover, we correlate
the differential movement rates observable in the INSAR data with the individual rock slide
slabs identified by geomorphologic mapping.
By this combination of geological, geomorphological and advanced remote sensing techniques
we demonstrate the structural influence on the rock slide process and unravel its internal
deformation and kinematics.

How to cite: Simma, S., Gerstner, R., Valentin, G., Goldschmidt, F., and Zangerl, C.: Geomorphological-geological characterization of an active, deep-seated rockslide in a heavily foliated rock mass – Wasserradkopf, Austria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14912, https://doi.org/10.5194/egusphere-egu23-14912, 2023.

Posters virtual: Mon, 24 Apr, 08:30–10:15 | vHall NH

Chairperson: Irene Manzella
vNH.4
|
EGU23-10134
|
ECS
|
Thyago Anthony Soares Lima and Antonio Rodrigues de Oliveira Filho

Mass movements result in great loss of life and property. This damage can be mitigated if the cause and effect relationships of the events are known. In this study, we use the analytical hierarchy process methods (AHP) to produce susceptibility to mass movement in the neighborhood of Fernão Velho, in the city of Maceió, capital of the state of Alagoas, northeastern Brazil . The study was conducted using remote sensing data, field surveys, and geographic information system (GIS) tools. That influence the occurrence of mass movement, such as elevation, slope aspect, slope gradient, density of buildings/cuts and embankments, lithology, distance from the lineament, soil, precipitation, land use/land cover (LULC) and influence of the railway line. Then the susceptibility to mass movement was established based on the assigned weight and ranking given by the AHP method. The result of the analysis was verified using existing mass movement occurrence sites, where it was obtained through the ROC index, an AUC of 86% , and a confidence interval of 82% , having an accuracy rate of 90% . The map of susceptibility to mass movement obtained is useful for prevention and mitigation of risks to the phenomenon, and proper planning for land use and construction in the future, serving as support for planning and decision-making by the civil protection of the municipality. 


Keywords: mass moviment susceptibility, analytic hierarchy process, GIS, remote sensing

How to cite: Soares Lima, T. A. and de Oliveira Filho, A. R.: Analytical Hierarchy Process for Mass Moviments Susceptibility Mapping in Fernão Velho, Maceió, Northeast Brazil, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10134, https://doi.org/10.5194/egusphere-egu23-10134, 2023.

vNH.5
|
EGU23-13358
longqi li

The 2020 December 5th Qingliucun landslide in western China presents a high locality and complex movement features. Its landslide source sits at the margin of a platform of a hillslope, which suffers from repeated earthquake and snow-water infiltration. The data from Insar and monitoring devices reveal that this landslide body have deform for 6 years and present a stepped three-phase failure process. The PFC simulation is also used to reproduce the failure process and motion features. It is found that several earthquakes result in the initiation of this landslide body and the snow-water infiltration plays a direct role in triggering this landslide by weakening the strength of soils. The landslide body scrape the slope mass during its transfer and block the river near the toe of the hillslope. The huge energy of landslide body is consumed during this process as verified by PFC simulation. The results can offer a good guidance to the hazard mitigation of this kind of landslide.

How to cite: li, L.: The failure pattern and transfer features of the 2020 Qingliucun landslide, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13358, https://doi.org/10.5194/egusphere-egu23-13358, 2023.