Slope Movement Types and Processes
... Rockfalls are gravity-driven instabilities affecting steep slopes of soft and hard rocks ( [1][2][3]). Rockfall volumes span several orders of magnitude at the site scale, from about 10 −2 m 3 up to 10 2 m 3 or more ( [4][5][6]). ...
... ∈ [1,2,3,4,5,6,7,8,9,10,12,15] days and ∈ [1,3,5,7,9] days. These values are chosen inside the physical range of these parameters. ...
... ∈ [1,2,3,4,5,6,7,8,9,10,12,15] days and ∈ [1,3,5,7,9] days. These values are chosen inside the physical range of these parameters. ...
When rockfalls hit and damage linear stakes such as roads or railways, the access to critical infrastructures (hospitals, schools, factories …) might be disturbed or stopped. Rockfall risk management often involves building protective structures that are traditionally based on the intensive use of resources such as steel or concrete. However, these solutions are expensive, considering their construction and maintenance, and it is very difficult to protect long linear stakes. A more sustainable and effective risk management strategy could be to account for changes on rockfall activity related to weather conditions. By integrating sustainability principles, we can implement mitigation measures that are less resource-intensive and more adaptable to environmental changes. For instance, instead of solely relying on physical barriers, solutions could include measures such as restriction of access, monitoring and mobilization of emergency kits containing eco-friendly materials. A critical step in developing such a strategy is accurately predicting periods of increased rockfall activity according to meteorological triggers. In this paper, we test four machine learning models to predict rockfalls on the National Road 1 at La Réunion, a key road for the socio-economic life of the island. Rainfall and rockfall data are used as inputs of the predictive models. We show that a set of features derived from the rainfall and rockfall data can predict rockfall with performances very close and almost slightly better than the standard expert model used for operational management. Metrics describing the performance of these models are translated in operational terms, such as road safety or the duration of road closings and openings, providing actionable insights for sustainable risk management practices.
... Mountainous regions are home to 12% of the world's population and cover 24% of global land area (Hock et al., 2019). They are characterized by high elevations, sharp topographic gradients, and paraglacial environments; therefore, under the combined effects of tectonic activity and extreme precipitation, mountainous regions are also the origin of landslide hazards (Mani et al., 2023), including various types of movement processes (falls, slides, and flows) according to the classification system of Varnes (1978). In particular, it has been demonstrated in the scientific literature (e.g., Gariano and Guzzetti, 2016) that the magnitude and frequency of landslide occurrences have increased in high mountainous areas in recent years due to the coupling effects of population growth and climate change. ...
... According to the Varnes (1978) classification system, landslide hazards, including falls, slides, and flows, are expected to remain high in the study area because of the strong coupling of the endogenic and exogenic geological actions mentioned above. An existing inventory map elaborated from geological field surveys and a geologist's visual interpretation of optical images from unmanned aerial vehicle (UAV) and satellite measurements revealed that there were 87 landslide hazards in the study area ( Fig. 1(c)), including 50 slides, 29 falls, and 8 large-scale flows. ...
... The detected landslides were classified based on their geomorphological characteristics and divided into categories of falls, slides, and flows according to the Varnes (1978) classification system, thus producing an inventory map of the different types of landslides. The classification was achieved through an a priori inventory map of landslides ( Fig. 1(a)) and the geomorphological analysis of high-resolution UAV DOM and 3D model (Figs. ...
... Landslides are classified into four types based on their failure mechanism-slide, flow, fall, and complex. Slide failure mechanism involves the movement of soil and rock sliding through almost a planar or curved concave surface (Varnes, 1978). Slides usually occur in steep slopes having cohesive rock or soil. ...
... These topology-based features are input to the decision treebased shallow learner as in the first method. We included the TDA-based model considering its potential to handle other relevant classification problems in future versions of our tool, e.g., classifying landslide types (Cruden and Varnes, 1996;Varnes, 1978). Above listed methods could be used independently following similar script streams. ...
... For example, assessing landslide-prone regions as an alternative to landslide susceptibility measure using TDA. Also, TDA could be used to classify landslide types, according to the types described in (Cruden and Varnes, 1996) and (Varnes, 1978). Landslide type information plays a crucial role in landslide risk assessment which is usually missed in landslide databases (Loche et al., 2022). ...
Landslides are often catastrophic, causing loss of life and destruction of property and infrastructure. Landslide susceptibility and hazard modeling help mitigate these losses by finding regions prone to landslides and providing probabilistic forecasting of landslide occurrence in a region. However, these landslide susceptibility and hazard models' efficacy depends on the quality of existing databases that often lack crucial information, like the underlying trigger and failure mechanism of a landslide. In this Ph.D. project, we developed methods to identify landslide triggering and failure mechanism information using their geometric and topological properties. For identifying landslide trigger information, we developed three different methods based solely on landslide polygon shapefiles containing landslides' two-dimensional (2D) polygon shapes. The first method uses geometric properties of landslide polygons as a feature space for a machine learning classifier--random forest. In the second method, we transformed these 2D shapes into three-dimensional (3D) point clouds by incorporating the digital elevation data and then extracting landslides' topological properties by topological data analysis (TDA) of these 3D points clouds; and to classify landslides; we treat these topological properties as the feature space of a random forest classifier. The third method uses images of landslides as input to a convolutional neural network (CNN). We tested all three methods using two different testing schemes on six known trigger inventories spread over the Japanese archipelago. In the first scheme, we combine all inventories and then split the dataset into various combinations of training and testing. We train the method on five known triggered inventories in the second scheme and test it on the sixth inventory. Moreover, we implemented each method on an inventory without triggering information to showcase a possible real-world application. The TDA-based method is consistently the most accurate in the above analyses, ranging between 84% to 98% accuracy. To determine the failure mechanism, we explored various geometric and topological properties of landslide shape and found that topological properties are excellent predictors for identifying landslide failure mechanisms. Therefore, we developed a method for determining landslide failure types using landslide topology. First, we extracted the topological features of the landslide 3D shape using Topological Data Analysis and then fed these features as an input to the machine learning algorithm--random forest. We implemented the developed method on the Italian and the US data separately. The method achieves above 95 and 80 accuracies for each landslide failure type for the Italian and US data sets. The methods presented in this Ph.D. dissertation show strong performance in identifying landslide triggers and failure mechanisms. The methods are easy to use as they depend on landslide polygon as input and are transferrable to different regions of the world with adequate training data from areas with similar tectonic and climatic properties. We anticipate that the landslide community and modelers will find our method useful in determining landslides' trigger and failure mechanism. Moreover, we expect that the developed method will enhance the efficiency of landslide predictive models, such as landslide susceptibility and hazards models.
... Typically, each landslide failure type exhibits different geological, geometrical, and geotechnical properties (see Fig. 1). For instance, slides have conspicuous primary scarps and collapse along the planar or rotational surfaces 14 , flows such as mudflows exhibit visco-plastic or viscous/fluid kinematics caused by excess pore water pressure 15 , and rock falls entail the free falling of fragmented rocks from steep slopes 16 (see Note S1 and S2 for detailed explanations). Practitioners usually combine these different failure movements into one group within an inventory, despite their different properties [17][18][19] , since categorizing them manually requires comprehensive surveys (both in the field and remotely) and standardized classification protocols 12 , which are laborious and time-consuming. ...
... Drawing on the experiments of the sub-type classification (e.g., debris flows and earthflows) of landslide failures using the Italian and the US Pacific Northwest dataset (see Results, "Determining sub-type failure movements"), we recognize the substantial value in identifying and quantifying these sub-movements, bearing notable potential to enhance both landslide risk assessment and related hazard models 20 . The level of damage to infrastructure and the risk of human casualties vary depending on the intensity of the failure movement, which differs for each failure type 14 . For example, a slow-moving deep-seated rotational landslide (1.5 m/year to 16 mm/year) may not pose an immediate threat to the population, but it can cause extensive structural damage to buildings over a prolonged period 46,47 . ...
... Our findings in the US Pacific Northwest suggest that topological properties can reveal more than one physical process in a given landscape (for example, identifying coupled failures of slides following falls or slides following flows). This has significant implications for understanding complex landslide failures, which often arise from a combination of different failure movements, such as sliding, flowing, and falling, and may not be fully encompassed by conventional characterization and classification methods for large-scale analysis 13,14,41 . Traditional approaches may struggle to pinpoint the exact cause, leading to hindrances in prevention efforts. ...
The death toll and monetary damages from landslides continue to rise despite advancements in predictive modeling. These models’ performances are limited as landslide databases used in developing them often miss crucial information, e.g., underlying movement types. This study introduces a method of discerning landslide movements, such as slides, flows, and falls, by analyzing landslides’ 3D shapes. By examining landslide topological properties, we discover distinct patterns in their morphology, indicating different movements including complex ones with multiple coupled movements. We achieve 80-94% accuracy by applying topological properties in identifying landslide movements across diverse geographical and climatic regions, including Italy, the US Pacific Northwest, Denmark, Turkey, and Wenchuan in China. Furthermore, we demonstrate a real-world application on undocumented datasets from Wenchuan. Our work introduces a paradigm for studying landslide shapes to understand their underlying movements through the lens of landslide topology, which could aid landslide predictive models and risk evaluations.
... In particular, rainfall-induced shallow landslides have been reported to be a common and rather destructive threat to powerline pylons [27]. These types of landslides are characterized by shallow depth (up to 2 m, reaching the bedrock) but with a significant planimetric extension [41]. They are triggered by terrain saturation due to the rainfall infiltration processes [42] and include soil slips and earth flow, which, in the presence of large amounts of water (i.e., terrain saturation and overland flow), may evolve into debris flows [43]. ...
... The SLEM model does not explicitly consider the dependence on initial soil moisture because a complete saturation of the watershed basin is assumed. These conditions, although precautionary, are not representative of the partial saturation of the soils that, in many cases, guarantee their stability [41,71,[73][74][75]. The terrain imbibition is timedependent, and the complete saturation can only be reached in the long term and only for those areas morphologically predisposed to collect subsurface waters such as troughs and impluvium. ...
Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.
... A rockfall occurs when a portion of rock (referred to as a block) breaks away due to sliding, toppling, or falling from a vertical or nearly vertical cliff. It then descends the slope, either bouncing and flying in ballistic paths or rolling along talus or debris slopes 3 . This process involves the downhill motion of boulders (originating from natural inclines) or rock blocks (from man-made cuts), which, without adequate containment, can wreak havoc on structures in their trajectory or pose a significant hazard to public transportation routes [3][4][5][6][7][8][9][10] . ...
... It then descends the slope, either bouncing and flying in ballistic paths or rolling along talus or debris slopes 3 . This process involves the downhill motion of boulders (originating from natural inclines) or rock blocks (from man-made cuts), which, without adequate containment, can wreak havoc on structures in their trajectory or pose a significant hazard to public transportation routes [3][4][5][6][7][8][9][10] . ...
Rockfalls in mines represent one of the most hazardous events for miners, posing significant risks to safety, equipment, and operations. These incidents occur when rock or debris falls from the walls of a mine, often without warning, and can be triggered by geological factors, blasting practices, ground vibration, water infiltration, stress redistribution and timedependent behaviour of rock. Apart from this, the bench parameters, such as the slope angle of the bench, the friction angle of the material, bench height and width, affect the rockfall. The rockfall incidents history that occurred in the past several years suggest that rockfalls in opencast mines led to the fatal injuries of many individuals. The problems faced due to rockfalls are not repetitive, but they are disastrous in opencast mines once they occur. So, it is necessary to investigate the rockfall in an opencast mining industry. It is also observed from the literature that the kinetic energy of a rockfall helps determine the intensity of rockfall in a mine. Understanding these factors and implementing preventive measures and rapid response strategies is crucial in mitigating rockfall risks. Hence, this study investigates rockfall phenomena in a high wall open cast by determining the kinetic energy of a rockfall. A parametric study has been conducted to determine the effect of various bench parameters on the kinetic energy of rockfall. A predictive model is developed to determine the kinetic energy of rockfall concerning various factors affecting rockfall. The predictive model is also validated using three case studies of high opencast mines. The results from the predictive model and the numerical model for the case study mines match the predictive model that can predict the rock fall intensity for opencast mines. The study also aims to assess the potential risks posed to workers, equipment, and infrastructure in highwall opencast mines. The findings provide valuable insights for implementing appropriate safety measures and developing effective strategies to mitigate rockfall hazards.
... According to the classification of Varnes [12,44], and the reconnaissance in the field during the geological and geophysical prospecting phase, the landslide in the Tamban area in the detachment zone is translational, and the materials were transported and deposited in the accumulation zone at a distance of 330 m as debris flow with rubble materials from collapsed houses and highways (see Figures 4 and 5). Meteorological stations belonging to the National Institute of Meteorology and Hydrology (INAHMI) monitoring network did not record rainfall data on those days as they were not in operation. ...
... According to the classification of Varnes [12,44], and the reconnaissance in the field during the geological and geophysical prospecting phase, the landslide in the Tamban area in the detachment zone is translational, and the materials were transported and deposited in the accumulation zone at a distance of 330 m as debris flow with rubble materials from collapsed houses and highways (see Figures 4 and 5). ...
The recent landslide at the Tamban site, on 21 December 2021 (23:30 local time), provides relevant information on the trigger mechanisms and their relationship with geological factors. Therefore, the predominant aims of the current study were to identify the lithological units in the rocky substrate and subsoil from geophysical surveys, delineating the thickness of the tuff- and lapilli-supported fall layers. Additionally, we evaluated the deformation dynamics from probabilistic and deterministic analysis, where a plane with well-differentiated discontinuities of normal-type geological fault was evidenced. This deformation feature was associated with a planar-type landslide that reached a debris flow up to 330 m distance, with varied thicknesses. Furthermore, we conducted a probabilistic analysis, which started from the characteristics of the post-slide material analyzed through triaxial trials that were conducted to a retro-analysis in order to obtain the parameters of the moment the event occurred. With the base parameters to perform the landslide analysis and determine its safety factors in compliance with current regulations, a reinforced earth configuration was applied using the Maccaferri’s Terramesh method. Hence, it was possible to provide an analysis methodology for further geological scenarios of landslides that occurred in the province of Bolívar, the northern Andes of Ecuador.
... The northern Alps in central Japan are prone to landslide dams and dammed lakes due to their location along major tectonic lines and associated faults (Mizuyama et al. 2011). The characteristics of landslides and associated dammed lakes are related to the regional distribution of drainage areas, topography, and local rock types, as well as the texture and mineralogy of host rocks and sliding surfaces (Varnes 1978;Schäbitz et al. 2018). Landslide areas are generally identified by changed topography relative to adjoining topographic features, lineated or circular scarps, benched or hummocky topography, bulging and steepened toes, rotated landmasses, gullies, newly formed drainage, inclined or abnormal vegetation, etc. (Jibson 2009). ...
... Present-day geomorphic features such as slope steepness, aspect and curvature are important evidence of paleoevents during which a landslide occurred in the past. Geomorphic features observed during the field survey, such as depression on the ridge crest, uphill-facing scarps, and bulged lower parts of slopes (Varnes 1978;Jibson 1996) as well as degraded head scraps, tongue-like depositional bodies within the valley floor, steepened toes, and large boulders on low-gradient terrain (Clague 2015), indicate that the Nakatsuna landslide is a deep-seated gravitational paleoslide. The fault-bounded front, moderate relief, large-scale discontinuity, and low rock mass strength (Korup et al. 2007) are the main factors responsible for large-scale landslides and slope instability, which seems to be valid for the occurrence of the Nakatsuna Landslide. ...
Lake Nakatsuna, the central lake of the Nishina Three Lakes located in a narrow intermontane valley in the northern Japanese Alps, is thought to have formed by large landslides damming the paleo-Himekawa River at approximately 30 ka B.P. The mechanism of these large landslides in relation to geological and geomorphological attributes is less understood for the Nakatsuna Landslide. This paper focuses on the geomorphological evolution of Lake Nakatsuna in relation to the lithofacies of landslide blocks in tectonically active, hydrothermally altered, and weathered areas. Geomorphological and geological mapping, characterization of weathering grades and alteration intensity through field observation, petrographic observation, clay mineral analysis by XRD and major bulk geochemistry by XRF methods were adopted to establish the trends and intensity of source rock weathering and its relation to landslide mechanisms. Three paleo-landslide blocks have been identified from geomorphological field observations that may have formed the Lake Nakatsuna landslide dam. Petrographic observation reveals that approximately 30% of the mineral grains are slightly to moderately altered to form clay minerals (chlorite, kaolinite, illite, etc.) derived from hydrothermal alteration and weathering of rocks. CIA values range between 58 and 94 and reveal slight to strong hydrothermal activity. Along with the concentrations of abnormal geomorphic features such as steep slopes, isolated hills and depressions, and extremely loose sediments containing small and large blocks that have broken like a jigsaw puzzle in the hillslope and upper reach, it was determined that there was a large landslide that dammed the paleoriver and formed Lake Nakatsuna.
... Bunun için tip ve alan bakımından heyelan tanımlanması ve buna bağlı envanter oluşturulması önemlidir. Tarihsel seyri incelendiğinde heyelan tanımlanması ilk çalışmalarda; hava fotosu [6][7][8][9] ve uydu görüntülerinden [10][11][12] ilerleyen zamanlarda UAV insansız hava araçlarından elde edilen fotogrametrik DEM ve Lidar (Light Detection and Ranging) DEM'den (Digital Elevation Model) [13] yararlanılmıştır. Fotogrametrik DEM ve Lidar DEM yüksek veri kapasitesinin işlenmesinden dolayı küçük ölçekteki mekânların heyelan envanterinde daha fazla tercih edilmektedir. ...
... Etken faktörlerin çıktıları yamaç evriminin kestirilmesini sağlayarak heyelan duyarlılık ve tehlikesinin belirlenmesinde katkı oluşturmaktadır. Heyelanın zemin koşulları içindeki deseni pek çok çalışmada ortaya konulmuştur [5,7,26,[28][29][30]. Heyelan desenini iyi bir şekilde ortaya konulması için heyelan envanterinin titizlik ile hazırlanması gerekmektedir. ...
Yukarı Ceyhan Havzası topoğrafik ve litolojik geçişlerin sık olduğu bir bölgedir. Çalışmanın amacı yerleşmenin, tektonik aktivitenin ve yüzey şekillenmesinin yoğun olduğu sınırları belirlenen alanda heyelanların dağılımı ve temel karakteristiklerini etkileyen faktörleri detaylı bir şekilde incelemektir. Bu amaçla yüksek çözünürlüklü uydu görüntülerinden heyelan envanteri tanımlanmıştır. Envanterin doğruluğu arazi çalışmaları ile sağlanmıştır. Çalışma alanında 441 farklı tip heyelanın havzanın %3,6'sını kapladığı tespit edilmiştir. Heyelanların çoğunun ana tip olarak kayma tipinde olduğu (%70), bunun yanı sıra düşme ve akmalarda belirlenmiştir. Heyelanların büyüklük dağılımının 0,0005 km2-10,1 km2 arasında oldukça geniş olduğu ortaya çıkmıştır. Buna çeşitli jeolojik ve jeomorfolojik süreçlerin etkili olduğu ve farklı mekanizmaların rol oynadığı belirlenmiştir. Bu doğrultuda literatürdeki heyelan ile ilişkilendirilen topoğrafik faktörler ve jeolojik faktörler uzman tarafından çalışma sahasına özgü olarak değerlendirilmiştir. Buna göre eğim, yükselti, rölyef ve topoğrafik nemlilik indeksi topoğrafik faktörlerin heyelan tipine göre farklı seviyelerde heyelanı kontrol etmektedir. Paleo heyelanların dağ-ova arasındaki keskin rölyef geçişinde gelişmektedir. Havzada heyelanlar kumtaşı-çamurtaşı-kireçtaşı birimlerinde yoğunlaşmaktadır. Faya yakın zonda küçük heyelanlar bulunmasına rağmen 06 Şubat 2023 depremleri bu sınırlarda küçük düşmelere neden olmuştur. Heyelanlar dağılım topoğrafik ve jeolojik faktörlerin özelliğine göre değişiklik göstermektedir. Sonuç olarak heyelanların jeolojik, topoğrafik ve çevresel karmaşık etkileşimi sonucunda meydana geldiğini söyleyebiliriz. Bu nedenle çalışmaya ait analizler bölge için heyelan duyarlılık, tehlike ve risk çalışmalarında dikkate alınması açısından önemlidir.
... Although erosion rates on Mars are very low in the Amazonian, given the thin atmosphere and absence of liquid water (e.g., Golombek et al., 2006;Vaz et al., 2014), a period of three billion years would provide enough time to alter the appearance of these morphologically subtle surface features significantly. Finally, the formation of these scarps could be also related to slope gravitational processes (e.g., rotational sliding; Varnes, 1978), but our search for similar features on other steep-sided slopes in Tharsis (i.e., inside slope of volcanic calderas of Tharsis Montes or Olympus Mons) do not show any evidence of the formation of morphologically similar scarps on the caldera walls. Hence, this scenario seems to be also unlikely. ...
Endogenic processes have greatly affected the Martian surface, especially concentrating at several volcano-tectonic centers. The formation of Tharsis, a vast volcanic bulge, significantly influenced the western hemisphere of Mars. The associated loading stresses caused the formation of various sets of tectonic structures that might have remained active until today. However, surface evidence for very recent endogenic processes in Tharsis is sparse. Here, using the Context Camera (CTX) and High Resolution Imaging Science Experiment (HiRISE) images, we report the presence of fresh-appearing systems of local-scale scarps mostly developed at the southern edge of Tharsis, specifically at Claritas Rupes scarp. These scarps are spatially associated with depression centers situated at the base of Claritas Rupes, inside the Thaumasia Graben which is partially filled by volcanic deposits. The relationships between the studied scarps and present-day surficial processes and its deposits such as rockfalls indicate a young age of the scarps' development, namely, in the range of <1 Ma. The pristine topography (sharp and thin ridges), spatial distribution (association with depression centers), and regional geological context of Claritas Fossae lead us to interpret these scarps as surficial expressions of tectonic activity attributed to normal faulting. This could be related to Deep-seated Gravitational Slope Deformations (DGSDs) released by seismic activity related to ongoing subsidence of depression centers and/or reactivation of the listric normal Claritas Rupes fault. These observations imply that this region experienced long-lasting and multiple volcano-tectonic events and the formation of the youngest deformations could represent neotectonic activity, which has been active until recently, and possibly might be still ongoing.
... A call for modelbased debris flow impact assessment capability naturally arises from this development; however, debris flows are extremely complex multi-physics processes, and therefore hard to predict. As per Varnes classification [3], a debris flow is defined as moving mass of loose soil particles ranging from clays to rocks with high water content, driven by gravity. Further, the definition was modified to surging flow of saturated debris with very rapid to extremely rapid speed in a steep channel, which entrains material from the flow path [4], where debris is defined as mixture of materials, with higher percentage of coarse particles. ...
Debris fows are catastrophic landslides owing
to their very high velocities and impact. The number of such
fows is likely to increase due to an increase of extreme
weather events in a changing climate. At the same time,
risk reduction and mitigation plans call for a quantitative
assessment of the hazard. Numerical models are powerful
tools in quantifying debris fows in terms of fow height
and velocity with respect to both space and time, and to
derive mitigation-relevant diagnostics such as impacted area.
However, the current modelling practices possess critical
challenges that limit their application in a forward-directed
analysis to predict the debris fow’s impact. This work provides an overview of the past and current practices in debris
fow modelling, their potential use in simulation-based decision support and the challenges and future research scope
in computational debris fow modelling, based on the recent
literature.
... Synthetic-aperture radar interferometry (InSAR) is a crucial tool for identifying potential geological hazards over wide areas, especially slow-moving landslides (<60 mm/year) [1]. Compared to ground surveys and leveling measurements, it offers advantages such as extensive coverage, high efficiency, and cost-effectiveness. ...
Slow-moving landslides often occur in areas of high relief, which are significantly affected by tropospheric delay. In general, tropospheric delay correction methods in the synthetic-aperture radar interferometry (InSAR) field can be broadly divided into those based on external auxiliary information and those based on traditional empirical models. External auxiliary information is hindered by the low spatial–temporal resolution. Traditional empirical models can be adaptable for the spatial heterogeneity of tropospheric delay, but are limited by preset window sizes and models. In this regard, this paper proposes an improved tropospheric delay correction method based on the multivariable move-window variation model (MMVM) to adaptively determine the window size and the empirical model. Considering topography and surface deformation, the MMVM uses multivariate variogram models with iterative weight to determine the window size and model, and uses the Levenberg–Marquardt (LM) algorithm to enhance convergence speed and robustness. The high-precision surface deformation is then derived. Combined with hotspot analysis (HSA), wide-area potential landslides can be automatically identified. The reservoir area of the Baihetan hydropower station in the lower reaches of the Jinsha River was selected as the study area, using 118 Sentinel-1A images to compare with four methods in three aspects: corrected interferograms, derived deformation rate, and stability of time-series deformation. In terms of mean standard deviation, the MMVM achieved the lowest value for the unwrapped phase in the non-deformed areas, representing a reduction of 56.4% compared to the original value. Finally, 32 landslides were identified, 16 of which posed a threat to nearby villages. The experimental results demonstrate the superiority of the proposed method and provide support to disaster investigation departments.
... Types of landslides. Abbreviated version of Varnes' classification of slope movements(Varnes 1978) Complex: combination of two or more principal types of movement. ...
Landslides, among all, are hazardous natural disaster events. It is caused due to the creation of instability in the slopes of the terrain. In the past 20 to 30 years’ time span it has been observed that the frequency of landslides has increased tremendously due to urbanization and climate change. The landslide susceptibility maps could be used for planners to mitigate the destruction being caused by landslides beforehand. By this review article we want to put emphasis on use of new and advanced learning algorithms for preparation of landslide susceptibility maps. Few machine learning techniques like Random Forest (RF) artificial neural network (ANN) and Support vector machine (SVM) etc. have been giving very accurate maps for prediction of future natural hazard events. Himalayan region being topographically unstable has many complexities in doing study for a region. But based on the reviews of different studies it has been found that machine learning algorithms are very accurate in addressing the challenges being faced and gives vulnerable areas of landslide events through susceptibility maps. Ensemble techniques of different methodologies were found to be improving the accuracy of the landslide susceptibility assessment, but not many researches have done it. One of the most challenging tasks is to find the inventories of the landslide events. For which many organizations are working hard with the help of researchers to make a database for it. Still few researches are successful in prediction of temporal and spatial events of future landslides. Machine learning can act as a cutting edge in prevention of landslide vents ahead of time. This article tries to present the recent advancement of machine learning in the field of landslide susceptibility mapping. It also suggests a future perspective of more machine learning techniques like XGBoost that can be implemented in rough and complex topographic terrains of Himalayas.
... Rockslides Sandstone boulders from landslides are distinguished along the slopes and valley sectors (Fig. 7, G). More details of the slide types are described by Hungr et al (2014), who revised several aspects of the well-known classification of landslides developed by Varnes (1978). They modified the definition of landslide-forming materials to provide compatibility with accepted geotechnical and geological terminology of rocks and soils. ...
The Cerro Colorado Natural and Cultural Reserve, Córdoba, Argentina, is well known for its impressive rock paintings on
sandstone formations. While previous research in the area has focused mainly on archaeological sites, this study aims to pro
vide geomorphological data through an updated landform inventory and geomorphometric diversity index map, as the basis
for managing the geo-cultural heritage area and potential sites for geo-tourism and geo-education. ALOS PALSAR DEMs at
12.5 m spatial resolution were used as a primary data source for mapping the study area. Features were digitally drawn into a
geographical information system (GIS) and checked during a field survey. The results indicate that the landforms and points
of geological interest give this region high geodiversity, which underlines the importance of including a geoperspective in
the protection of nature and a sustainable use of the territory. The cavernous landforms contain native rock paintings, which
make them unique in the region. The conservation of archaeological sites requires geomorphological knowledge in order to
prevent degradation and loss of cultural and natural heritage. In addition to scientific interest, the history of the landscape
through its geodiversity is relevant for educational, communicational, and geo-tourism purposes.
Keywords Sandstone · Cerro Colorado · Geodiversity · Pre-Hispanic Rock Art · Córdoba · Argentina
... Tominaga, (2007) explica que a deflagração de movimentos gravitacionais de massa é condicionada por fatores geológicos e geomorfológicos, por aspectos climáticos, hidrológicos e da vegetação e pela ação do homem acerca do uso e ocupação do solo. Em relação aos tipos de movimentos de massa , Augusto Filho (1992) propôs, partindo das contribuições de Varnes (1978), uma classificação (Quadro 1) dos movimentos de massa ajustada à realidade ambiental brasileira (Brasil, 2013 ...
This research aims to conduct a survey on flooding, inundation, and gravitational mass movement processes in the urban area of Teresina, capital of Piauí state. The methodology is based on fieldwork, analysis of Google Earth Pro orbital images, application of SIG (QGIS) for mapping, bibliographic research, documentary and news portal analysis, and letters and reports from CPRM (2012; 2014; 2019). The results point to the inventory: 26 points of flooding, 15 of inundation, and 13 of mass movements in the urban area of Teresina; these points, in mapping, were added to the shapefiles of CPRM and resulted in the creation of two maps. The conclusions pointed to the possibility of demarcating new areas of high risk or high susceptibility to flooding and inundation processes. They also emphasize the importance of monitoring the environmental processes analyzed and the need to take measures such as signaling risk points and stabilizing unstable slopes related to mass movements.
... Landslides are natural hazards defined as the downward movement of a mass of rock, debris, or earth on a slope under gravity, affecting the population and its infrastructure (Varnes 1978;Cruden 1991). Landslides represent a substantial economic burden, causing the loss of human life around the world, representing the seventh worldwide largest killer among natural hazards and producing heavy economic damages in many countries (Donnini et al. 2020) and the fourth place in terms of the number of people affected by natural hazards around the world (Hidalgo and Vega 2021). ...
This scientometric analysis significantly advances the understanding of landslide risk assessment and economic losses, focusing on scientometric insights. This study aims at analyzing the global trends and structures of landslide risk and economic loss research from 2002 to 2023 using scientometric techniques such as co-authorship, co-word, co-citation, cluster analysis, and trend topics, among others. Thus, analysis of 92 studies gathered from Scopus and Web of Science databases reveals a continuous growth in environmental, social, and quantitative research topics. Predominant contributions hail mainly from China and Italy. The research identifies critical themes, including risk analysis, vulnerability, fragility, and economic losses. The current identified research combines advanced statistical methods, including logistic regression, with climate change scenarios and susceptibility assessments to reveal intricate connections between climatic shifts, hydrogeological hazards, and their economic and environmental impacts. This study provides researchers and practitioners with a comprehensive understanding of the status quo and research trends of ontology research landslide risk and its economic losses. It also promotes further studies in this domain.
... Mining-induced catastrophic landslides, especially rock topples, are common in mountainous terrain. Rock toppling can be classified as one of the fundamental forms of slope movement (Hungr et al. 2014;Varnes 1978). This type of movement involves a forward rotation, causing a rock mass to detach from the slope. ...
The spatial and temporal evolution of mining-induced landslides is a topic of global interest. Their accurate hazard zonation is crucial, particularly in areas characterized by joints that split rock mass into arbitrary-shaped blocks and influence their behavior. An increasing number of dynamic models are being utilized to enhance the probabilistic prediction of landslides. However, the validation and parameter calibration of such events face uncertainties in accuracy primarily due to mechanical properties and valley morphology (such as geometric shape and bed inclination). The study examines the dynamic process and mechanism of rock topples by investigating the Yiziyan rock toppling incident on June 20, 2023, in Guizhou, China. Our analysis is based on an integrated multi-source data approach, including an Uncrewed Aerial Vehicle (UAV) survey, particle size distribution, and numerical modeling corroborated by field investigation and video footage analysis. The particle size distribution is studied along the runout path of the Yiziyan rock topple through field investigations supplemented with high-resolution image analysis by a UAV. We then performed a sensitivity analysis to calibrate the numerical parameters for Discrete Element Modeling to examine the effectiveness of analyzing and forecasting typical topple events in areas with similar geological characteristics. The massive tensile cracks in the study area increase the possibility of rock failure events, therefore, we have acquired and outlined the early warning data acquired from the on-site monitoring devices into constant deformation, accelerated deformation, and critical deformation. The data analysis demonstrates a continuous deformation followed by ultimate failure and indicates the potential failure type that may occur. Furthermore, we conducted a forward simulation to predict the runout and impact of a potential rock failure event to demarcate the potential risk zone in the study area. The study aims to improve hazard prediction and mitigation in mining-affected areas by understanding failure mechanisms and dynamic processes related to topple-runout movement. It demonstrates the effectiveness of integrating multi-source data for better topple runout and particle size distribution analysis. The study establishes calibrating numerical parameters that improve hazard assessments, predictive modeling, and mitigation of potential geological hazards, contributing to safer mining operations and hazard mitigation strategies in similar geological contexts.
... Mass movements can vary, based on the involved material, their kinematics, and velocity [4][5][6]. In some cases, these phenomena have proven to be catastrophic events causing numerous victims and considerable damage; in other cases, due to their extremely low velocity (mm or cm per year), landslides can remain unknown or very difficult to recognize for a long time. ...
Landslides play a significant role in the morpho-evolutional processes of slopes, affecting them globally under various geological conditions. Often unnoticed due to low velocities, they cause diffuse damage and loss of economic resources to the infrastructure or villages built on them. Recognizing and mapping mass movements is crucial for mitigating economic and social impacts. Conventional monitoring techniques prove challenging for large areas, necessitating resource-intensive ground-based networks. Leveraging abundant synthetic aperture radar (SAR) sensors, satellite techniques offer cost-effective solutions. Among the various methods based on SAR products for detecting landslides, multi-temporal differential interferometry SAR techniques (MTInSAR) stand out for their precise measurement capabilities and spatiotemporal evolution analysis. They have been widely used in several works in the last decades. Using information from the official Italian landslide database (IFFI), this study employs Sentinel-1 imagery and two new processing chains, E-PS and E-SBAS algorithms, to detect deformation areas on the slopes of Calitri, a small town in Southern Italy; these algorithms assess the cumulated displacements and their state of activity. Taking into account the non-linear trends of the scatterers, these innovative algorithms have helped to identify a dozen clusters of points that correspond well with IFFI polygons.
... Usually, due to the load carrying capacity of the river, large boulders are deposited earlier, while cobbles and sand particles are deposited at the toe of the river, usually forming an alluvial fan (Figure 3(d)). Slope wash deposits are accumulated materials formed by mass movements on rock slopes, including rock falls, debris slides, and debris flows (Varnes 1978). Due to mineralogical variation, these deposits are covered with vegetation. ...
The study for the design of tunnels in similar geological settings, providing insights into potential challenges that may arise during excavation and offering strategies for mitigating risks in District Kalam on the Ushu River, Khyber Pakhtunkhwa, Pakistan. The methodology involved geological mapping, rock sampling, discontinuity surveys, and laboratory testing for empirical analysis of tunnel parameters at the Weir House, Powerhouse, and tunnel alignment locations. Empirical analysis of tunnel parameters using three rock classification systems, rock mass rating (RMR), rock quality tunneling index, and rock mass index (RMi). Based on the classification, the rock quality was found to be fair, indicating favorable rock properties. The Q-system rated the rock as poor to fair, suggesting low discontinuity intensity, medium rock strength, or medium deformation modulus. According to the RMi, rock was rated as medium to strong, indicating low discontinuity intensity, high rock strength, or low deformability. The support design for the tunnel is based on empirical analysis, it recommends support design for the tunnel reinforcement elements such as rock bolts, wire mesh, and shotcrete lining. Overall, the tunnel is stable and does not have complex structure and weak zones.
... Different types of landslides can be distinguished depending on the movement type and materials involved. Here we will refer to the classification of Varnes (1978). ...
The occurrence of multiple precipitation events not‐independent in time, that is, a temporal clustering, is an example of a temporal compounding event. This type of forcing is of great relevance for the occurrence of different natural hazards, like floods and deep‐seated landslides, for which previous soil saturation plays an important role in shaping the associated hazard. Using ERA5‐Land data set and E‐OBS, we firstly investigate the spatial and temporal characteristics of temporal clustering of precipitation over the Italian territory, and we relate it with two oscillation patterns, namely North Atlantic Oscillation (NAO) and Mediterranean Oscillation Index (MOI), and with common synoptic conditions. Then, we explore the role of temporal compounding of precipitation in the generation of different movement types (complex, debris flow, fall, flow, and sliding) using the database of landslides from the Aree Vulnerate Italiane project (in Italian AVI, meaning Areas Affected by Landslides or Floods). From this study it emerges that below average values of NAO and MOI increase the probability of having clustered precipitation events. For all types of landslides, except rock falls, we observed that the majority of the events are preceded by a temporal clustering of precipitation, over longer time windows for complex events, shorter for debris flows. For rock falls, we found also a link with low minimum temperature and freeze‐thaw cycles for winter events and high maximum temperature for summer events. This work contributes to the investigation of temporal clustering of precipitation in connection with natural hazards characterized by a mechanism of saturation.
... It contains more than 279 landslides of different sizes, of which 210 were triggered and 69 reactivated. According to the classification of Varnes (1978), the inventory can be divided into three categories: rotational, translational, and creep related. In the study area, the main movements (82%) correspond to rotational landslides, 13% correspond to translational landslides, and the remaining movements (5%) are creep related. ...
About 270 landslides have been triggered in the Mila region (northeast Algeria) linked to the 7 August 2020 Mw 5 earthquake,
but they have not been analyzed and mapped throughout the region. As a consequence, the potential link between the
earthquake, faults, and the set of large landslides registered subsequently in the same region has not yet been studied,
understood, and mapped. However, the geology and morphology of large and deep landslides lying dormant in the region,
which could be reactivated in case of seismic activity, are located close to faults and present the same morphological
characteristics as landslides triggered by the main shock. The aim of this paper is to present the relationship between
the seismotectonic and large landslide distribution and to compare landslide susceptibility maps by the application of
geographical information system (GIS)-based frequency ratio (FR) and weighting of evidence (Wi) statistical methods. A
landslide inventory map was developed using interferometric synthetic aperture radar (InSAR) post-seismic deformation
maps, aerial photographs, and field survey investigations. The analysis of the spatial distribution of large landslides, together
with information on aftershocks and electrical resistivity tomography (ERT) sections, shows that the spatial distribution
of large landslides is consistent with epicenter locations along a NW–SE axis and two NE–SW axes. Evidence of NE–SW
faults related to a N120E striking dextral strike–slip fault is also discussed. Various factors are shown to be associated with
landslide occurrence, such as lithology, distance to fault, slope degree, slope aspect, distance to rivers, drainage density,
elevation, rainfall, peak ground acceleration (PGA) in soil and rock estimated according to the Mila earthquake (Mw = 5),
and epicentral distance. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve approach
was used to confirm and validate the accuracy of the two models. The obtained AUC values were 89.05% and 87.57% for
the FR and Wi models, respectively, indicating high levels of prediction accuracy. The large landslides triggered in the Mila
region are found to be directly related to the seismotectonic structure, and a seismic sequence interspersed with moderate
earthquakes over a short period. The results are presented as a landslide susceptibility map showing areas highly vulnerable to
landslides and those with moderate and low vulnerability. It is expected that this will be very helpful for landslide prevention
and infrastructure planning in Mila City.
... The city has a population of about 2,967,310 (updated November 2023 [83]), with a very high population density of about 2535 inhabitants/km 2 (updated February 2023 [83]). The island of Ischia is the most exposed to both seismic and landslide events due to unstable slopes [92], along which rainfall can easily wash away the surface debris downstream [84,[93][94][95][96][97][98][99]. ...
A multi-hazard analysis (seismic, landslide, flood) is conducted to verify the impact on the road network. The ENEA CIPCast platform is an innovative Decision Support System (DSS) that is used to implement the analyses using GIS. Using analytical and geoprocessing tools, the hazards were assessed and mapped. The overlapping of different geospatial layers allowed the implementation of a specific hazard map for the road network. Multi-hazard values were obtained using an appropriate matrix of single values, which were classified, and then summarized into four classes of values. The analyses were conducted at the regional (Campania region), provincial (Metropolitan City of Naples), and local scales (island of Ischia and municipality of Casamicciola Terme). In particular, the landslide event that struck Ischia island on 26 November 2022 and the municipality of Casamicciola Terme was considered as a case study to determine the impact on the road network, infrastructures, buildings, and jeopardizing inter-municipal connections. The results are mainly visualized through map processing and statistical summaries of the data. The management of the landslide debris, which can contain a multitude of fractions (waste, biomass and vegetation, sludge, soil, and rocks transported downstream by water), was also explored. This is a frontier issue for which international manuals and guidelines, as well as national and emergency acts, have been examined. A specific protocol for the sustainable management of the debris generated by floods and landslides is needed, and discussed in the present paper, to overcome emergencies after catastrophic events.
... Field observations had also indicated creeping in the form of tilting of trees and cracks on the road passing through the landslide (Fig. 2d). Notably, such creeping has been attributed as indications of progressive strain development in many studies (Terzaghi 1950;Varnes 1978). ...
The NW Himalaya has been subjected to frequent disastrous landslides of different types owing to frequent extreme rainfall events and rock mass shearing caused by structural and/or lithological contrast. Though majority of the landslides in the NW Himalaya are of complex type comprising debris and loose rock mass that may result into debris flow and/or rockfall, their potential behavior is rarely explored. The present study aims to evaluate the recurrence of one such complex landslide (0.23 Mm²) of Yamuna Valley, NW Himalaya that is subjected to rock mass shearing and the region accommodating this landslide receives frequent extreme rainfall events. A huge slope failure in this landslide occurred on 12 September, 2017 damaging a ~ 400 m stretches of the National Highway (NH) road. The landslide location has strategic significance, since up to 0.3–0.4 million pilgrims travel annually on the road passing through the landslide slope. To evaluate the potential behavior of landslide and to understand the factors causing this landslide (pre-failure analysis), slope stability analysis and rockfall simulation were performed. Pre-failure analyses indicated that the maximum shear strain of 0.14–0.18 and total displacement of 2–8 m likely developed parallel to the slope. The possibility of rainfall triggering is explored in view of increasing rainfall, soil moisture, and surface runoff conditions. Tectonic influences are also evaluated using joints and fracture patterns in rock mass. Post-failure analysis showed that though the maximum shear strain and the total displacement had reduced to 0.07–0.15 and 2–5 m, respectively after the failure, the slope is still unstable. Rockfall simulation revealed the potential for rockfalls having energy and velocities in the range of 900–4000 kJ and 18–75 m/s, respectively.
Seismic signals, with their remote and continuous monitoring advantages, have been instrumental in unveiling various landslide characteristics and have been widely applied in the past decades. However, a few studies have extended these results to provide geologists with pre-survey information, thus enhancing the understanding of the landslide process. In this research, we utilize the deep-seated Cilan Landslide (CL) as a case study and employ a series of seismic analyses, including spectrogram analysis, single force inversion, and geohazard location. These techniques enable us to determine the physical processes, sliding direction, mass amount estimation, and location of the deep-seated landslide. Through efficient discrete Fourier transform for spectrograms, we identified three distinct events, with the first being the most substantial. Further analysis of spectrograms using a semi-log frequency axis generated by discrete Stockwell transform revealed that Event 1 consisted of four sliding failures occurring within thirty seconds with decreasing sliding mass. Subsequent Events 2 and 3 were minor toppling and rockfalls, respectively. Geohazard location further constrained the source location, indicating that Events 1 and 2 likely originated from the same slope. Subsequently, the sliding direction retrieved from single force inversion and volume estimation was determined to be 153.67º and 557,118 m3, respectively, for the CL. Geological survey data with drone analysis corroborated the above seismological findings, with the sliding direction and source volume estimated to be around 148° and 664,926 m3, respectively, closely aligning with the seismic results. Furthermore, the detailed dynamic process observed in the spectrogram of Event 1 suggested a possible failure mechanism of CL involving advancing, retrogressing, enlarging, or widening. Combining the above mechanism with geomorphological features identified during field surveys, such as the imbrication-like feature in the deposits and the gravitational slope deformation, with event video, infers the failure mechanism of retrogression of the Event 1 after shear-off from the toe. Then, the widening activity was caused by the failure process for subsequent events, as Events 2 and 3. This case study underscores the significance of remote and adjacent seismic stations in offering seismological-based landslide characteristics and a time vision of the physical processes of landslides, thereby assisting geologists in landslide observation and deciphering landslide evolution.
Loess on the Earth occupies an area of more than 13 million km ² . The greatest spread of loess is in Europe and Asia (mainly south of 62°N), where vast areas are composed of loess from the surface, the thickness of which varies in Europe from a few meters to 20–30 m, and in the Caucasus, in intermountain hollows of Central Asia, China-from 50–60 m to 100 m and more. The peculiarity of loess is its predisposition to the development of subsidence-compaction during moistening under the action of both their own weight and external loads. As a result, in the areas of loess distribution, in addition to classical landslide forms, a special type of landslides is often observed, in the formation of which subsidence plays a significant role. The main factors in the formation of “subsidence landslides” are a decrease in the strength of loess as a result of increasing water cut. Underground water moistens the loess thickness from below to the state when its structure breaks under its own weight and subsidence begins with the formation of cracks on the day surface. Further moistening and destruction of the loess structure continues at the expense of both groundwater and atmospheric water absorbed through cracks. Such combination of conditions determines further development of subsidence phenomena and subsequent landslide deformations. The rate of displacement of such landslides depends on the extent and rate of subsidence development at the base of the slope. “Subsidence landslides” can be defined as a type of complex landslides.
Taiwan is at the junction of tectonic plates, with high mountainous terrain and abundant rainfall due to the rich moisture of the subtropical monsoon zone, which makes the already dangerous slopes even more unstable. By applying the digital camera measurement approach, with its moderate installation cost, high security, and mobility, it is possible to capture and monitor the hillside over an extended period, guaranteeing its stability. Photogrammetry is a recent technology that has gained popularity in many fields. Image analysis, achieved by capturing photographs, is a growing trend. It offers a cost-effective way of transmitting information in automated Internet of Things (IoT) systems, reducing human and financial resources. Therefore, this study aims to utilize close-range photogrammetry to analyze both 2D and 3D image data. Besides, this study encompasses thermal images, enabling researchers to evaluate observed objects' temperature differences quickly. Thus, this study aims to superimpose temperature information from thermal images onto optical images, in order to analyze slope information. It focuses on creating on-site cameras that use both optical and thermal imaging, building a three-dimensional point cloud using optical systems, investigating image displacements, and tracking unstable areas using thermal imaging. Additionally, the research explores the potential of AI interpretation to aid in this process. The laboratory and the preliminary field test support the feasibility of the proposed system and interpretation methods.
Hazards created by the landslide damming of rivers have become common in tectonically active mountainous areas. However, it remains unclear how tectonic effects may influence the formation and characteristics of landslide dams. The purpose of this paper is to explore how tectonic effects impact the drivers, geomorphic features, and activity characteristics of landslide dams along a fault zone. We investigated 83 landslide dams clustered along a fault zone in the Bailong River Basin. Most of the dams are located in areas of high tectonic stress, resulting from the rapid river incision and destruction of slope structure caused by intense tectonic activities in these areas. Statistical analysis, InSAR monitoring, and field investigation revealed that different tectonic effects were associated with significant differences in the geomorphic features, activity characteristics, and controlling factors of the landslide dams. Thus, we identified three distinct patterns of landslide dams in tectonically active mountainous areas: (1) Topography-driven landslide dams are caused by rapid rock uplift and river incision. Here, the steep terrain enhances the development of small landslides, the narrowness of the channels favors river damming, and the residual deposits on the hillslope remain active. (2) Tectonic activities promote the development of structural planes in the rock mass and reduce its strength, ultimately forming structural plane-controlled landslide dams. Although their volumes are not very large, the strong erosion resistance of rockslides can cause river damming and maintain the stability of deposits. (3) Fractured rock mass-controlled landslide dams are composed of broken rock and fault gouge. The extremely low strength of these materials allows them to form very large landslides that can easily dam the river, and maintain a slow-moving state. Through a geomorphological and geological model, our study offers new insights and enhances the understanding of the formation and characteristics of landslide dams induced by tectonic activity in mountainous regions.
The present study deals with the field observations and results obtained from the Geotechnical investigations and Ground Penetrating Radar survey carried out on Thatri landslide. Thatri township is situated on the left bank of the Chenab River along NH-244, 43 km from district headquarter Doda, Jammu and Kashmir. The landslide occurred on 2nd February, 2023 damaged 21 buildings, affected about 150 people and created situation like Joshimath tragedy. Detailed field investigations on lithology, sub-surface structure determined by GPR investigations and geotechnical parameters of the soil revealed that the leading edge of the slide caused most damage due to cracks developed in the slope wash deposits followed by subsidence and down slope movement of a portion of the township (Nai Basti). The study revealed that percolation of water from soak pits, sewerage, and rain water into the terrace deposits comprising of clays, silt, sand and gravels was the major triggering factors.
The study investigates an earth slide type rain-induced landslide that occurred at Madithorai, Nilgiris District, India in 2009. It consists of detailed field investigations such as topographical survey and borehole investigation, laboratory and numerical investigations. Based on the topographical survey the slope was modelled in SEEP/W programme to perform the uncoupled transient seepage analysis. The cumulative rainfall of 586 mm was given as an input for a duration of 5 days that caused landslide at Madithorai. The results of transient seepage analysis were used to determine the stability of the slope based on the infinite slope method for unsaturated soil. Based on the analysis the failure mechanism of Madithorai landslide was observed. The influence of antecedent rainfall using three different idealized 5-day antecedent rainfall was studied. A threshold intensity was established from the different 5 days antecedent rainfall and the corresponding factor of safety which can be used as for landslide early warning. The factor of safety from deterministic analysis was greater than one which does not imply that the slope is stable. Therefore, the performance of the slope was studied based on the reliability index and probability of failure using the Monte Carlo simulation. The results highlight that the slope is in hazardous condition with a reliability index of 1.15 and the probability of failure of 11.7%. Hence, it is recommended to adopt a landslide early warning system and suitable remedial measures at Madithorai location.
The Himalayan region encompasses nearly 12% of the total geographical area of India and exhibits a high susceptibility to landslides owing to its delicate lithology, intricate geology, and steep slopes. Over the past few decades, GIS-based hydrological, data-driven, and physical-based models have been used extensively to identify landslide-prone areas. On the other hand, not much is known regarding the reliability and applicability of these options. This paper explores rainfall thresholds, InSAR (Interferometric Synthetic Aperture Radar) analysis, and site-based monitoring in the context of rainfall-induced landslides. Hence, the article offers a holistic view of these practices. The rainfall thresholds are determined for the Mandi region which can further aid in landslide forecasting and provide an early warning if that threshold is breached. In the absence of rainfall and other ground features, InSAR analysis monitors ground deformation in real-time. However, site-based monitoring methods can be employed for a specific area with a high hazard probability, as detected from susceptibility mapping. Furthermore, by integrating real-time data from subsurface systems with predictive machine learning (ML) algorithms, the monitoring system can forecast landslides and raise alerts as per significant movements. This paper offers an overview of all these techniques, focusing on real-world case studies.
A large number of local people and property losses have been reported in the Rangamati Hill Tracts (RHT) of Bangladesh due to the 17 June 2017 Landslide event. This chapter investigated the actual causes of this landslide event which focuses on the coupling effects of earthquake-rainfall-induced landslide activities that occurred in this area. To know this scenario better, the study considered freely available earth observation multi-temporal Landsat satellite scenes for landslide-induced change assessment. In addition, thirteen associated conditioning factors were integrated within the GIS environment by adopting a multicriteria analytical hierarchy process (AHP) approach to prepare a landslide hazard risk (LHR) map of the study area. The study results quantified 3.81, 3.00, and 8.90% of areas as very high-risk, high, and moderate LHR categories. Moreover, the results also revealed that multiple issues (i.e., earthquakes, heavy rainfall, hill cutting, deforestation, and haphazard human settlement construction on the hill slope) are the main catalysts behind this landslide event. Finally, the study recommends integrated Remote sensing, GIS, and AHP techniques for future landslide risk assessment across the globe.
The Himalayan region of India, in particular, faces an escalating slope instability due to landslides, posing significant pressure on rapid developmental activities. In this chapter, the study focuses on generating a comprehensive landslide susceptibility map (LSM) to analyze and detect the most crucial zones susceptible to landslides for the biggest hydroelectric project undertaken in India- Subansiri lower hydroelectric project situated on the intensive slopes of the Himalaya which is under a constant threat of recurring landslides utilizing a Geographical Information System (GIS) based Analytical Hierarchy Process (AHP) model. The LSM was created by considering a range of 9 geo-environmental parameters like slope, aspect, lithology, lineament density, geomorphology, drainage density, NDVI, LULC, and Road (Euclidean distance) to identify areas susceptible to future landslides and to delineate potential hazard zones. Using the Receiver Operating Characteristic (ROC) curve model, the AHP model was validated and yielded accuracy rates of 79.2%, 79.8%, and 79.2% for the geometrical-interval, quantile, and natural breaks (Jenks) classification models, respectively. A predictive numerical rockfall model Rapid Mass Movement Simulation (RAMMS) was employed to detect the runout trajectories and spatial extent of rockfall around the vicinity of the dam. The velocity of the estimated future rockfall was detected to be 9.84 ms−1, Jump height of 1 m, and kinetic energy of 132.80 kJ. The study’s outcomes hold practical implications for infrastructure development and management in landslide-prone regions, as the susceptibility map can aid in the implementation of effective risk mitigation strategies.
This study presents a geospatial assessment of potential landslide hazards in the Bandarban District of the Chittagong Hill Tracts (CHT) in Bangladesh. Landslides are a severe threat to mountainous regions, causing loss of life and significant economic damage worldwide. The study employs a Geospatial weighted overlaying technique, assigning values on a scale of 1–5 and 100 for factors influencing landslides. These factors encompass historical landslide occurrences, land use patterns, rainfall, elevation, slope characteristics, soil types, geological features, distances to rivers, roads, stream orders, and socio-economic variables like household density, population density, income levels, and education. These values are determined in consultation with local communities and domain experts. The geospatial model categorizes the Bandarban District into five distinct levels of landslide hazards, ranging from “Very High Hazard” to “Very Low Hazard.” “Very Low Hazard” areas, constituting 13.39% of the total hazard area, pose the least risk but still require basic preparedness measures and educational initiatives. “Low Hazard” areas, covering 36.04% of the hazard area, necessitate lower mitigation priority but ongoing awareness and preparedness efforts. The “Moderate Hazard” areas, making up 39.39% of the hazard area, require a multi-faceted approach for risk reduction, including land-use regulations, reforestation, and community-based disaster risk reduction programs. “High Hazard” areas, though smaller at 11.00% of the hazard area, demand immediate attention with actions such as engineering solutions, land use planning, and proactive disaster preparedness. The “Very High Hazard” area, representing only 0.18% of the hazard area, requires the most urgent focus for mitigation measures.
The Jiaju landslide is a large soil‒rock palaeolandslide in the Danba section of the Upper Dadu River in southwestern Sichuan Province, China. In this work, geological investigations, long-term comprehensive monitoring, experiments, and numerical simulations were used to determine the formation mechanism and evolution of this landslide. A complex armchair-shaped terrain with a substantial height difference between the rear and the foot of the slope, multiple structural defects within the landslide-accumulation region, and a coupling effect among multiple factors controlling river erosion and human activity were identified. The dynamic landslide deformation process was recorded by the integration of global positioning system (GPS) and inclinometer data, and the kinematic behaviour of the landslide was simulated using a Fast Lagrangian Analysis of Continua in 3 Dimensions (Flac3D) model in three stages. (1) During the last rapid uplift of the Tibetan Plateau and strong river erosion, the Jiaju bank slope was deformed and failed, forming a massive, thick palaeolandslide with a volume of approximately 2.76 × 107 m3. (2) The structure of the landslide materials deteriorated, and the weak structural plane was softened by groundwater and surface loading. The landslide was reactivated, with deformation and failure occurring through sliding and fracturing. (3) The landslide exhibited creep deformation with multistage and multilayer sliding surfaces via front-slope toe excavation and river-level fluctuations.
Real-world hazard evaluation poses many challenges for the development and application of numerical models of debris flows. In this chapter we provide a conceptual overview of physically based, depth-averaged models designed to simulate debris-flow motion across three-dimensional terrain. When judiciously formulated and applied, these models can provide useful information about anticipated depths, speeds, and extents of debris-flow inundation as well as debris interactions with structures such as levees and dams. Depth-averaged debris-flow models can differ significantly from one another, however. Some of the greatest differences result from simulation of one-phase versus two-phase flow, use of parsimonious versus information-intensive initial and boundary conditions, use of tuning coefficients versus physically measureable parameters, application of dissimilar numerical solution techniques, and variations in computational speed and model accessibility. This overview first addresses these and related attributes of depth-averaged debris-flow models. It then describes model testing and application to hazard evaluation, with a focus on our own model, D-Claw. The overview concludes with a discussion of outstanding challenges for development of improved debris-flow models and suggestions for prospective model users.
The current study aims at GIS-based multicriteria decision analysis to generate a landslide-susceptible map from Baramulla to Uri Road segment along NH-1, Kashmir Himalaya, India. The landslide causative factors examined to generate our AHP matrix are slope gradient, elevation, slope aspect, curvature, distance to drainage, distance to roads, distance to lineaments, geology, land use/land cover, and Rainfall. The study mapped and identified the active landslides along NH-1 through extensive field investigations and other secondary data sources. The landslide events were dominated by rockfall and debris slides. Based on their importance in landslide occurrences, the thematic layers were given relative relevance scores using Saaty's scale. Besides, the Analytic Hierarchy Process was employed to normalize the relative weights and attributes of the various thematic layers. In addition, all thematic data layers were combined using a weighted linear approach to generate the landslide susceptibility map. Furthermore, the resultant landslide susceptibility map was classed into five categories viz., very high (24.18%), high (30.24%), medium (28.61%), low (15.28%), and very low (1.69%). The study reveals that 54.42% of the area falls under the high and very high susceptible zones. Likewise, 78.9% of overall model accuracy of final landslide susceptible zonation map was computed using the area under curve method. Moreover, this study would aid infrastructural, geo-environmental, and landslide hazard planning in the studied region.
The present work aims to highlight a particular event where there was a concomitance of particular hydrogeological and climatic conditions, unfortunately in a scenario which could be repeated. In fact, the south-eastern slope of Mount Vermenone (Central Apennines, Italy) was affected by a severe landslide movement of debris flow type. The phenomenon was triggered in the mid-high portion where a vast and thick debris accumulation (coarse, loose, and weakly cemented materials) was present. The aforementioned materials, in addition to being located on a steep slope, were frequently in a condition of water saturation during the winter, given the presence of springs and the characteristic impluvial form in which they were concentrated. In January 1997, a rapid snowmelt increased the water saturations in the thick debris, so that the materials became unstable on the slope and the movement is quickly activated. A fast and dense debris flow was triggered, moving along the steep slope down to the main valley floor: Here, the high energy flow did not stop but continued, spreading its accumulation almost to the built-up area. Only after several days and months the stream was able to resume its course, incising the huge mass of alluvial materials that can still be seen today at the edge of the plain. In addition, the groundwater resource also has been compromised as some springs in the area have changed their regime or even disappeared. The event was of considerable impact, and given its exceptional nature, studies on the dynamics of the landslide phenomenon were carried out. These in particular were conducted on the possibility of reactivations and also toward the monitoring of the adjacent areas. In this regard, a first response from the installed instruments was that no movement was recorded, and therefore, we are facing a very high threshold before triggering, probably due to the high permeability of the materials.
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