Steep Mountainous Areas Research Articles

Identification of Potential Landslides in the Gaizi Valley Section of the Karakorum Highway Coupled with TS-InSAR and Landslide Susceptibility Analysis

Landslides have become a common global concern because of their widespread nature and destructive power. The Gaizi Valley section of the Karakorum Highway is located in an alpine mountainous area with a high degree of geological structure development, steep terrain, and severe regional soil erosion, and landslide disasters occur frequently along this section, which severely affects the smooth flow of traffic through the China-Pakistan Economic Corridor (CPEC). In this study, 118 views of Sentinel-1 ascending- and descending-orbit data of this highway section are collected, and two time-series interferometric synthetic aperture radar (TS-InSAR) methods, distributed scatter InSAR (DS-InSAR) and small baseline subset InSAR (SBAS-InSAR), are used to jointly determine the surface deformation in this section and identify unstable slopes from 2021 to 2023. Combining these data with data on sites of historical landslide hazards in this section from 1970 to 2020, we constructed 13 disaster-inducing factors affecting the occurrence of landslides as evaluation indices of susceptibility, carried out an evaluation of regional landslide susceptibility, and identified high-susceptibility unstable slopes (i.e., potential landslides). The results show that DS-InSAR and SBAS-InSAR have good agreement in terms of deformation distribution and deformation magnitude and that compared with single-orbit data, double-track SAR data can better identify unstable slopes in steep mountainous areas, providing a spatial advantage. The landslide susceptibility results show that the area under the curve (AUC) value of the artificial neural network (ANN) model (0.987) is larger than that of the logistic regression (LR) model (0.883) and that the ANN model has a higher classification accuracy than the LR model. A total of 116 unstable slopes were identified in the study, 14 of which were determined to be potential landslides after the landslide susceptibility results were combined with optical images and field surveys. These 14 potential landslides were mapped in detail, and the effects of regional natural disturbances (e.g., snowmelt) and anthropogenic disturbances (e.g., mining projects) on the identification of potential landslides using only SAR data were assessed. The results of this research can be directly applied to landslide hazard mitigation and prevention in the Gaizi Valley section of the Karakorum Highway. In addition, our proposed method can also be used to map potential landslides in other areas with the same complex topography and harsh environment.

Human activities are intensifying the spatial variation of landslides in the Yellow River Basin

Human activities are a triggering factor for landslides in the Yellow River Basin (YRB, China). However, the extent to which the spatial distribution of landslides is affected by human activities is unclear. We constructed a human activity intensity index (HAII) based on nighttime light data and land cover data. Regression and dominance analyses were used to compare the effects of the HAII, precipitation, distance to river, distance to fault, topographic relief and slope on the landslides spatial density (LSD). The results showed that in the YRB, the HAII, as a dominance influencing factor, had a significant positive influence on the LSD. Moreover, regional differences in the human disturbance of nature intensify the spatial variation of LSD. To quantify the intensity of human disturbance to nature, a human-nature conflict index (HNCI) is constructed by quantifying the difference between the slope distributions of artificial and natural landscapes. The results show that in the middle section of the YRB, humans are developing more steep mountainous areas, leading to more dense landslides. This study provides a reference for landslide risk management and land use planning in the YRB.

Method for monitoring and forecasting landslide phenomenon based on machine learning

A landslide involves the downward movement of a mass of rock, debris, earth, or soil. Landslides happen when gravitational forces and other types of shear stresses on a slope surpass the shear strength of the materials. Additionally, landslides can be triggered by processes that weaken the shear strength of the slope's material. Shear strength primarily depends on two factors such as frictional strength, which is the resistance to movement between the interacting particles of the slope material, and cohesive strength, which is the bonding between those particles. A landslide is a terrible natural disaster that causes much damage to both human life and the economy. It often occurs in steep mountainous areas or hilly regions, ranging in scale from medium to large. It progresses slowly (20–50 mm/year), but when it occurs, it can move at a speed of 3 m/s. Therefore, early detection or prevention of this disaster is an essential and significant task. This paper developed a method to collect and analyze data, with the purpose of determining the possibility of landslide occurrences to reduce its potential losses.•The proposed method is convenient for users to grasp information of landslide phenomenon.•A machine learning model is applied to forecast landslide phenomenon.•Internet of things (IoT) system is utilized to manage and send a warning text to individual email address and mobile devices.

Study on the Impact Law of V-Shaped Gully Debris Avalanches on Double-Column Piers

The concrete piers in steep mountain areas are highly susceptible to damage disasters due to the impact of debris avalanches, which pose a serious threat to the safe operation of bridge structures. In order to investigate the impact load characteristics of debris avalanches on bridge pier structures in V-shaped valley mountain areas, Particle Flow Code 3D (PFC3D) models based on a discrete element method were applied in this study to establish a full-scale three-dimensional model of a debris avalanche in a V-shaped valley. By installing double-column piers in the influence zone of the debris avalanche, the impact force, accumulation morphology, motion characteristics of debris particles, internal force response of the double-column piers, and impact energy indicators were investigated. In addition, parameters such as the layout position of the piers and the impact angle of the debris were studied. The results showed that the particles at the front edge of the debris avalanche have a significant impact on the magnitude and distribution of the impact force on the piers. It is important to consider the layout position of the piers and the impact angle of the debris when designing bridge pier structures in high, steep mountain areas. There was a significant difference in the movement patterns between the particles at the front and rear edges of the landslide. The particles at the front edge had a higher velocity and stronger impact, while the particles at the rear edge had a slower velocity and were more likely to be obstructed by bridge piers, leading to accumulation. The obstruction effect of the piers on the debris particles was closely related to their positioning and the impact angle. Piers that were closer to the center of the valley and had a larger impact angle have a more significant obstruction effect, and the topography of the valley had a significant focusing effect on the debris avalanche, resulting in a greater impact force and energy on the piers located closer to the center of the valley. The impact force amplitude and duration of landslide debris on bridge piers showed a significant difference between the bottom and upper piers, as well as between the piers on the upstream and downstream sides. These research findings can provide valuable references for the design and disaster assessment of bridge piers for impact prevention in steep slopes and mountainous areas with deep ravines.

Mechanisms of Block Instability at the Toe of a Slowly Deforming Rock Slope

Steep alpine rock slopes undergoing deformation may give rise to concurrent landslide hazards of different type and magnitude. The underlying mechanisms of instability are often challenging to investigate due to their inherent complexity; furthermore, they can occur on poorly accessible terrain, preventing the collection of data by means of traditional field techniques or even inhibiting awareness of hazards. This paper focuses upon one such case, in which a major transportation corridor running along the floor of the Aosta Valley (Western Italian Alps) is affected by significant—and until recently unknown—rockfall hazards promoted by a previously collapsed rockslide still deforming slowly at elevations almost 600 m above the road. In particular, two large discrete blocks (volume > 103 m3) lie precariously at the toe of the slide and could fall downslope at extremely rapid velocity. The design of countermeasures for the stabilization or removal of these blocks would require the assessment of their mechanical interaction with the bedrock and degree of internal fracturing (i.e., possible pervasive damage within the blocks). We perform this task by first exploring potential kinematic styles and damage patterns at failure according to a series of preliminary finite-element models. We then use detailed displacement measurements from remote sensing and in situ monitoring, in conjunction with repeat topographic surveying from a terrestrial laser scanner (TLS) and a drone laser scanner (DLS), to reconstruct the actual kinematics of the blocks. The results substantiate the hypothesis that instability is primarily controlled by transient degradation of friction on a through-going basal rupture surface. Development of a large tensile fracture in one of the two blocks is inferred to be conditioned by increased non-planarity of the slipping joint in comparison with the other block. We highlight that optimized integration of cutting-edge rock slope investigation tools can help address otherwise unresolved key aspects of complex instabilities in steep mountainous areas.

UAV Seismic Source Traveltime Tomography Technology in Steep Mountainous Areas

Active source seismic exploration is one of the most important high-resolution methods to obtain information about underground structures in tunnel engineering, and the seismic source is the key equipment to acquire high-quality data. In steep mountainous areas with complex geological structures, surface undulation, and drastic changes, the use of traditional seismic sources with high cost can seriously affect the efficiency and accuracy of detection. In this paper, a survey experiment of tunnel engineering is carried out in Lijiang, Yunnan Province, completing a fast, high-quality seismic data acquisition through utilizing the convenient, environmentally friendly, and economical UAV (Unmanned Aerial Vehicle) seismic source as the shot and wireless node instrument as the receiver. The experiment shows that the UAV seismic source can achieve low-cost and environmentally friendly excitation of seismic waves in complex mountainous areas, making a breakthrough in seismic source equipment. We obtain a high-precision velocity model by traveltime tomography, identifying the thickness of the overburden layer in the study area, and providing an important reference for tunnel engineering.

Community composition and diversity of land snails along an elevation gradient in the World Natural Heritage Site, Yakushima Island

Understanding alpine communities that form along elevation gradients is not only a major topic in community ecology but also provides biological conservation insights into recent environmental changes in alpine ecosystems. In this study, we investigated the community composition and diversity of land snails on Yakushima Island, Japan, which has steep mountainous areas and has been designated a World Natural Heritage Site. As a result of the survey, 3689 individuals of 42 species were recorded at 64 sites, and Bayesian hierarchical models were constructed using a species matrix and environmental data from remote sensing. We found that both land surface temperature, which correlated with elevation, and soil moisture index, which uncorrelated with elevation, altered community composition. Furthermore, species diversity was high at low elevations and decreased monotonically with increasing elevation. This diversity was related to the vegetation types. Thus, the results of these analyses imply that the land snail community on Yakushima Island varies along elevation. This study highlights the need to focus on changes in multiple environmental variables from a conservation perspective and the need to pay attention not only to alpine areas, but also to highly diverse low-elevation areas that are not legally designated as conservation areas.

Interferometric Synthetic Aperture Radar Applicability Analysis for Potential Landslide Identification in Steep Mountainous Areas with C/L Band Data

Landslides frequently occur in the mountainous area of southwest China, resulting in infrastructure damage, as well as a loss of life and property. The use of interferometric synthetic aperture radar (InSAR) technology has become increasingly popular due to its wide coverage, high precision, and efficiency in identifying potential landslides in steep mountainous regions to mitigate risks. This study focused on the Mao County region in China and utilized a small baseline subset of InSAR (SBAS−InSAR) technology with Sentinel-1 and ALOS-2 data to identify the potential landslides and analyze their applicability. To ensure accuracy, the findings were verified using optical image and field surveys. Additionally, a comparative analysis was performed on C-band and L-band SAR data to examine differences in the coherence, geometric distortion, and displacement results, revealing that the L-band has clear advantages in the coherence, suitable observation coverage, and displacement results, while C-band can detect relatively slight displacements. This study aimed to determine the applicability of different SAR satellites for early landslide identification in steep mountainous areas, which can serve as a technical reference for selecting appropriate SAR data and enhancing InSAR identification abilities for potential landslides in the future.

Research on General Model of Railway Route Selection in CSM Areas Using the Sichuan–Tibet Railway and Other Typical Mountain Railways as Case Studies

In recent years, China’s rail network has been expanding to western China. Most of western China is a complicated and steep mountainous area with complex terrain and a harsh natural environment. Many engineering geological problems and unfavorable geological hazards have been encountered in railway construction in this area. Railway route selection in complex and steep mountainous (CSM) areas has become one of the fundamental issues in railway design. In view of the existing literature, this paper is aimed to summarize the characteristics and difficulties of railway route selection in CSM areas. In view of the low efficiency of railway route selection in CSM areas, a set of general models for railway route selection in CSM areas is established in the present study. A new multifactor interactive matrix dynamic weight approach is proposed in this model, and the corresponding evaluation index system is then developed. This methodology has been successfully applied in two typical CSM railway route selection cases, which proves the validity and applicability of this novel approach. This scrutiny provides a newly solid reference for the route selection method of the railway in CSM areas and gives a new direction for the evaluation and decision-making of other complex system engineering problems.

Test Analysis of 220 kV Rotating Transmission Angle Tower

As the requirements for the protection of environmental water in the construction of transmission lines have increased, the position of the tower in steep mountainous areas often fails to meet the requirements because of the difference in tower legs, which causes damage to the original landform, thus resulting in the change of the path and the increase of the project investment. In this paper, we optimize the design of a rotating steel tower to adapt to the steep terrain of mountainous areas and reduce the base surface opening. The feasibility of the proposed rotating tower optimization design is demonstrated by analyzing the real test data of the rotating tower.

Identifying Potential Landslides in Steep Mountainous Areas Based on Improved Seasonal Interferometry Stacking-InSAR

Landslides are a major concern in the mountainous regions of southwest China, leading to significant loss of life and property damage. Therefore, it is crucial to identify potential landslides for early warning and mitigation. stacking-InSAR, a technique used for landslide identification in a wide area, has been found to be faster than conventional time-series InSAR. However, the dense vegetation in southwest China mountains has an adverse impact on the coherence of stacking-InSAR, resulting in more noise and inaccuracies in landslide identification. To address this problem, this paper proposes an improved seasonal interferometry stacking-InSAR method. It uses Sentinel-1 satellite data from 2017 to 2022. The study area is the river valley section of the G213 road from Wenchuan County to Mao County. The study reveals the characteristics of seasonal decoherence in the steep mountainous region, and identifies a total of 21 potential landslides using the improved method. Additionally, optical satellite imagery and LiDAR data were used to assist in the identification of potential landslides. The results of the conventional stacking-InSAR method and the improved seasonal interferometry stacking-InSAR method are compared, showing that the latter is more effective in noise suppression caused by low coherence. Their standard deviations were reduced by 46%, 22%, 10%, and 14%, respectively, using the quantitative statistics for the four tested areas. The proposed method provides an efficient and effective approach for detecting potential landslides in the mountainous regions of southwest China. It can serve as a valuable technical reference for future landslide identification studies in this area.

Experimental Investigation of the Bearing Performance and Failure Characteristics of Double-Row Pile-Slab Structures in Steep Mountainous Areas

Considering the pile-slab subgrade project of the Hangzhou-Huang Shan Passenger Dedicated Line as the basis, this paper conducts a 1:10 large-scale indoor model test for the horizontal bearing capacity of the pile-slab structure in steep mountainous areas to study the distribution of the pile-slab structure stress, soil pressure and structural deformation and analyze the failure mode of the structure and slope. The research shows that when the subgrade with a double-row pile-slab structure is subjected to horizontal loading in the steep slope section, the steel bars of the pile body above the sliding surface are compressed, and the steel bars of the pile body below the sliding surface are under tension. With the increase in the horizontal load, the stress of the pile body steel bar remains basically unchanged or shows a steady increase and finally sharply increases. The deformation of the bearing plate is dominated by the horizontal displacement, and the horizontal displacement reaches 7.25 mm when the plate is broken. In addition, warping deformation of the inner high and outer low occurs. When the horizontal load reaches 157 kN, shallow damage and local collapse of the slope occur, and transverse and diagonal cracks occur at the top of the pile and near the sliding surface of the pile. During the test, the pile-slab structure always deforms more than the slope, and the overall stability of the structure is good. The test is suitable for sections where the remaining sliding force is less than 770 kN/m (equivalent to a slope length of 79.123 m).

Case study on viability of using head-separated micropiles as foundation system for check dams

Check dams constructed in steep mountainous areas require the rationalization of the dam body and foundation system. In general, soil cement replacement or caissons are often adopted for foundations. In such cases, reducing the construction effort is a critical issue. To address this, the authors studied the viability of a new type of check dam foundation consisting of a group of micropiles whose heads are structurally disconnected from the dam body. The system, coined a head-separated micropile group (HMG) foundation, enables the saving of labor and a reduction in the cross-sectional forces applied to the micropiles. Firstly, a full-scale loading test of the HMG was conducted. Then, a finite element model was formulated and its parameters fitted to make it suitable for reproducing the experimental results. Finally, using the FE model, the performance of a typical rigidly connected micropile foundation and that of the HMG system were compared in terms of the bearing capacity and displacement of the check dam body. The results confirmed that, although its displacement was 1.25 times larger than that of the rigidly connected foundation, the HMG system led to a factor of safety of 3.5 against micropile buckling.

InSAR Spatial-Heterogeneity Tropospheric Delay Correction in Steep Mountainous Areas Based on Deep Learning for Landslides Monitoring

InSAR Spatial-Heterogeneity Tropospheric Delay Correction in Steep Mountainous Areas Based on Deep Learning for Landslides Monitoring

An Integrated Model for the Geohazard Accident Duration on a Regional Mountain Road Network Using Text Data

A mountainous road network with special geological and meteorological characteristics is extremely vulnerable to nonrecurring accidents, such as traffic crashes and geohazard breakdowns. Geohazard accidents significantly impact the operation of the road network. Timely and accurate prediction of how long geohazard accidents will last is of significant importance to regional traffic safety management and control schemes. However, none of the existing studies focus on the topic of predicting geohazard accident duration on regional large-scale road networks. To fill this gap, this paper proposes an approach integrated with the Kaplan–Meier (K-M) model and random survival forest (RSF) model for geohazard accident duration prediction based on text data collected from mountainous road networks in Yunnan, China. The results indicate that geohazard accidents in road networks have a strong aggregation in tectonically active, steep mountainous, and fragmented areas. Especially the time of the rainy season, and the morning peak, brings high incident occurrences. In addition, accident type, secondary accidents, impounded vehicles or personnel, morning rush hour, closed roads, and accident management level significantly affect the duration of road geohazards. The RSF model was 0.756 and 0.867 in terms of the C-index and the average area under the curve, respectively, outperforming the traditional hazard model (Cox proportional hazards regression) and other survival machine learning models (survival support vector machine). Without censored data, the mean absolute error and mean squared error of the RSF model were 11.32 and 346.99, respectively, which were higher than the machine learning models (random forest and extreme gradient boosting model).

A Synthetic Algorithm on the Skew-Normal Decomposition for Satellite LiDAR Waveforms

Full-waveform satellite LiDAR can be used to retrieve the terrestrial surface information by decomposing its received waveforms. However, it is challenging to accurately extract the parameters of each component from a non-Gaussian overlapped waveform, which happens in steep mountain or urban areas. Therefore, a synthetic algorithm with the boosted Richardson–Lucy (RL) deconvolution, layered extraction, and gradient descent is proposed to implement the skew-normal decomposition for the received waveforms. To validate the performance of the proposed algorithm, we developed waveform decomposition experiments for three types of data, including known-parameter waveforms, simulated waveforms, and Global Ecosystem Dynamics Investigation (GEDI) satellite LiDAR waveforms. Meanwhile, we figured out the evaluation metrics involving correlation coefficients (CCs); root mean square errors (RMSEs); extracted parameter errors; and successful, missing, and unwanted rates for the decomposed waveforms. Through comparing the decomposed results of the proposed algorithm and the classical direct Gaussian decomposition (DGD) algorithms, we discovered that 1) the average CC has a growth of 4% and the average RMSE has a reduction of 60%; 2) the average errors of extracted amplitude, peak position, and pulsewidth have mitigated with 3.9%, 2.2%, and 5.1%, respectively; and 3) the successful detection rate increases by 40% and the unwanted and the missing rate decrease by 5% and 35% for the 2000 groups of known-parameter waveforms. In addition, the average CCs have slight growth of 3% and 1.2%, and the average RMSEs have significant reductions of 43% and 49% for the simulated and GEDI LiDAR waveforms, respectively. This research provides a preferable waveform decomposing approach conductive to characterizing the terrestrial information from the overlapping skew-normal full waveforms.

DISTRIBUTION AND EVOLUTION OF ICE APRONS IN A CHANGING CLIMATE IN THE MONT-BLANC MASSIF (WESTERN EUROPEAN ALPS)

Abstract. Ice Apron (IA) is a poorly studied ice feature, commonly existing in all the world’s major mountain regions. This study aims to map the locations of the IAs in the Mont Blanc massif (MBM), making use of the very high-resolution optical satellite images from 2001, 2012 and 2019. 423 IAs were identified and accurately delineated in the MBM on the images from 2019, and their topographic characteristics were studied. We generated our own Digital Elevation Model (DEM) at 4 m resolution since the freely available products predominantly suffer from significant inconsistencies, especially in steep mountain areas. Results show that most IAs exist at elevations above the regional Equilibrium Line Altitude (ELA), on steep slopes, on concave surfaces, on northern and southern aspects and on the most rugged terrains. They are also commonly associated with steep slope glaciers as 85% of them occur on these glaciers’ headwalls. A comparison between 2001 and 2019 shows that IAs have lost around 29% of their area over a period of 18 years. This is significant and the rate of area loss is very alarming in comparison with the larger glacier bodies. We also studied the effect of topographic parameters on the area loss. We found that topographic factors like slope, aspect, curvature, elevation and Terrain Ruggedness Index (TRI) strongly influence the rate of area loss of IAs.

Reconstruction and Evaluation of DEMs From Bistatic Tandem-X SAR in Mountainous and Coastal Areas of China

TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) mission is designed to generate 3-D images of the Earth as the first bistatic synthetic aperture radar (SAR). However, few quantitative studies of TanDEM-X digital elevation model (DEM) quality validation have been conducted specifically in China. This article presents an iterative method to generate high-resolution TanDEM-X DEMs and assesses the vertical accuracy with high-accuracy GPS observations, 1 arc second global DEMs available [Advanced Land Observing Satellite World 3-D-30 m v2.2, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) v3, Shuttle Radar Topography Mission (SRTM) v3.1, NASADEM, and X-band SRTM], and TanDEM-X 90 m DEM. The results demonstrate remarkable elevation quality and consistency in coastal areas with root mean square error of 1.7 m and 90% linear error (LE90) of 0.4 m, whereas 3–4 times weaker accuracies in steep mountainous areas. A positive bias of 1–2 m for an overall LE90 measure exists in the dense vegetation and steep-slope mountainous areas. TanDEM-X DEM-based SAR interferometry deformation uncertainty simulation indicates a low or even negligible topographic error contribution of 2–4 mm in mountainous areas and less than 1 mm in coastal areas. It indicates that the TanDEM-X DEM performs better than other global DEMs overall and shows a better elevation consistence with SRTM C-band DEM in the coastal area. As an excellent source of up-to-date information, the TanDEM-X DEM are expected be an advantage for understanding dynamic land use changes and improving identification and delineation of coastal lands, mountainous landslides, and earthquakes disasters.

Modeling soil erosion using RUSLE and GIS at watershed level in the upper beles, Ethiopia

Soil erosion by water often described as the most worst form of land degradation with serious environmental and socioeconomic ramification, which accelerated by human-induced activities and impacts agricultural productivity, water resources sustainability, and ecological conservations. Despite, the significant amount of research on the topic, location-specific soil erosion studies are still limited in Ethiopia, particularly in the study region. Therefore, this study investigates the spatial pattern of soil erosion risk and map the annual soil loss rate in the Upper Beles watershed of the Blue Nile Basin, Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) model, coupled with geographical information system (GIS), has been adopted for soil loss estimation. The respective model factors were derived from rainfall, soil, land use/cover, and digital elevation model data. The raster layers of rainfall erosivity, soil erodibility, topographic, cover management, and conservation practices were processed and multiplied together in the GIS platform. The order of magnitude of the estimated soil loss was within the range of zero in bare areas and watercourses to well over 50 t ha−1 yr−1 in degraded slope and steep mountain areas. The resulting average annual soil loss was founded to be 13.2 t ha-1 yr-1, which exceeded the soil loss tolerances of Ethiopia's northern highlands. Based on soil erosion risk's spatial distribution, 58.2% of the watershed has suffered soil loss less than 5 t ha−1 yr−1. Result shows that high soil erosion prevails at steep slopes and mountainous areas with no vegetation covers and extensively cultivated areas. The RUSLE and GIS-based approach provides a reliable estimation of soil loss that helps identify the priority area for effective planning and implementation of sustainable soil management practices to reduce soil erosion, particularly for the sustainability of the Grand Ethiopian Renesance Dam (GERD) located at the downstream.

Channelized and unchannelized collapses of granular columns on a horizontal surface

Columnar dangerous rock mass is widely developed in many high and steep mountain areas around the world. It often collapses, disintegrates and produces debris flow, which is disastrous. The collapse process of the columnar dangerous rock mass is very similar to the collapse of granular column. In this paper, we report the results of an experimental investigation of the flow induced by the collapse of a column of granular material over a horizontal surface. Two different setups are used, namely, a channelized granular column collapse (i.e., two-dimensional) and an unchannelized granular column collapse (i.e., three-dimensional), allowing us to compare channelized and unchannelized collapses flows. The experimental data suggest that our experimental findings were markedly different from those reported by previous authors (i.e., include the channelized and unchannelized collapse flows showed differences in energy conversion and dissipation). In channelized collapse flows, the maximum vertical speed appears in the free fall regime, while, the maximum speed in the vertical direction of unchannelized collapse flows appears in the spreading regime. During the whole collapse process, i.e., in channelized and unchannelized collapse flows, the conversion of potential energy and kinetic energy does not occur uniformly, and the maximum kinetic energy of the channelized collapse flows is higher than that of the unchannelized collapse flows, and compared with the unchannelized collapse flows, the dissipation energy in the channelized collapse flows is lower. A series of experiments was performed to predict the behaviour of different granular columns (characterized by different initial aspect ratio (a), varying from 1 to 4). The data obtained from 2D experimental model and 3D experimental model have certain amount of difference, such as the particle runout distance (d1), the maximum central height (h2), and the deposition angle (i.e., β1, β2). These differences show that the 2D experimental model does not fully represent the 3D conditions (i.e., the role of side-walls on the channelized collapse flows characteristic is non-negligible). Accordingly, care must be taken when validating 3D models with 2D experimental data. The movement of the tower dangerous rock masses with collapse failure mode could be evaluated using this channelized and unchannelized granular column experimental results.