软岩浅层滑坡的土壤工程特性及破坏机理

CATENA, Volume 181, October 2019, Article 104093    

Jiewei Zhan, Qing Wang, Wen Zhang, Yunlong Shangguan, Jianping Chen    

摘要：Tertiary soft-rock strata exposed on the eastern side of Changbai Mountain are landslide-prone strata. In recent years, shallow landslides have frequently occurred along the highway in this region, leading to great challenges in highway construction and safe operations. National Highway 302, which is under construction, crosses an old landslide group close to the village of Xinyan. A shallow landslide that recently occurred in this section, the Xinyan landslide, which occurred in a road embankment composed of soft-rock materials, is studied herein as a case study. The field survey identifies the geological characteristics and current conditions of the landslide area and confirms an inheritance relationship between the Xinyan landslide and previous landslides. Through a laboratory geotechnical test, mineral composition analysis and microstructure analysis of landslide soils, it is found that the examined soft-rock materials exhibit both dispersion and expansion. The coupling effect of soil expansion and dispersion contribute to the formation of seepage channels and to the degradation of soil properties. Under the combined effects of these factors, local shear failure first occurs at the weakest toe of the embankment. Then, unloading effects and strain softening lead to the progressive propagation and expansion of the sliding surface. Finally, the failure of the Xinyan landslide enters a progressive failure mode from the slope toe to the interior area. Therefore, this study reveals that expansibility, dispersivity, extremely low shear strength levels, softening behavior and preferential flows are the main causes of the repeated failure of the gentle soft-rock slopes in this region. These results may serve as a good reference for the prevention and treatment of similar soft-rock landslides occurring in the Yanbian region or worldwide.    

A PFE/IE – SPH joint approach to model landslides from initiation to propagation    

模拟滑坡从开始到传播的PFE/IE – SPH联合方法  

Computers and Geotechnics, Volume 114, October 2019, Article 103153    

Chuan Lin, Manuel Pastor, Tongchun Li, Xiaoqing Liu, Taozhen Sheng    

摘要：Landslide is a complicated natural disaster that can be divided into multiple stages such as initiation and propagation. Researchers have been attempting to reveal the characteristics of each stage by practicing various modelling methods. This paper attempts to discover whether the combination of two popular approaches, including the Partitioned Finite Elements and Interface Elements method (PFE/IE) and the depth-integrated SPH model would bear a more reliable estimation. In the first stage, the PFE/IE method is practiced to investigate the triggering of slopes. The outcome from the first stage, including the contact force and the material parameters under limit state, are then utilized as the initial condition in the analysis of the subsequent propagation stage. In the propagation stage, the depth-integrated SPH model is used to explore the landslide propagation. Consequently, the SPH model is capable of dealing with large deformation problems that occur during the landslide movement process. Two benchmark tests are performed to verify the accuracy and feasibility of applying the hybrid model to study the landslide initiation. After the justification of the PFE/IE approach, it is then combined with the SPH model by an appropriate interpolation method. The presented PFE/IE-SPH joint approach is employed to evaluate the safety margin of a practical slope, as well as the potential effect region if the landslide occurs. The simulated result from the joint approach demonstrates its capability of providing references for the mitigation and protection measures.    

Characteristics of landslide-debris flow accumulation in mountainous areas    

山区滑坡碎屑流积聚特征  

Heliyon, Volume 5, Issue 9, September 2019, Article e02463    

Zhang Qing-zhao, Pan Qing, Chen Ying, Luo Ze-jun, Zhou Yuan-yuan    

摘要：Landslide-debris flow is a sudden geological hazard in mountain areas, which is characterized with large scale, fast speed and wide impact range, and often causes disastrous accidents. In this study, an indoor sliding chute test was used to study the movement process of the landslide-debris flow and its accumulation pattern in the valley, taking into account the initiated gradient and particle size distribution. Besides, the model test was reproduced by PFC and the numerical models were constructed to fit the actual situation of landslide-debris flow. The results show that the collision of particles occurs during the movement of landslide-debris flow, and obvious sorting phenomena occur in the final deposit. Coarse particles distribute in the front and surface of the deposit while fine particles distribute in the back and bottom. The initiated angle has a certain effect on the morphology of the deposit: larger initiated angle makes the deposit closer to the opposite bank of the valley. Particle gradation has a significant impact on the form and distribution of deposit as well, with the increase of the proportion of coarse particles, the deposit of fine particles shrinks to the center of the rear edge, the profile of the deposit is more flat and uneven, the deposit is closer to the opposite bank of the valley, and the angle of the deposit profile increases significantly.    

Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data    

基于无人机数据与对象图像分析的浅层滑坡制图  

Engineering Geology, Volume 260, 3 October 2019, Article 105264    

Resul Comert, Ugur Avdan, Tolga Gorum, Hakan A. Nefeslioglu    

摘要：The Black Sea Region of Turkey is one of the most landslide prone areas due to its high slope topography, heavy rainfall, and highly weathered hillslope material conditions. Preparation of landslide inventory maps is the first step in producing landslide susceptibility maps. Ground-based methods for mapping landslide occurrences are time-consuming and expensive. Additionally, landslide mapping based on satellite imageries and aerial photographs has some limitations, including climatic conditions, cost, and limited repetitive measurement capacity. Visual interpretation-based landslide mapping, which is based on satellite imageries and aerial photographs, is a time-consuming procedure that requires an experience-based expert opinion. Therefore, the data acquisition based on unmanned aerial vehicle (UAV) and landslide event inventory maps using an object-based classification approach can be superior to other methods in terms of speed and cost. In this study, we developed a semiautomatic model using object-based image analyses for rapid mapping of shallow landslides from the data obtained from UAVs after major landslide events in the Black Sea Region of Turkey. For this purpose, two test sites—Kurucasile (Bartin) and Cayeli (Rize)—were selected. Landslide mapping models were developed in the investigation sites, and the performance of the models was evaluated. The landslides' data obtained with the developed models were compared to the landslides' data produced by the experts. The comparison process revealed that landslides mapped by using UAV data have an accuracy rate higher than 86% according to the number of landslides and 83% according to the landslide area.    

Landslide susceptibility hazard map in southwest Sweden using artificial neural network    

基于人工神经网络的瑞典西南滑坡易发性灾害制图  

CATENA, Volume 183, December 2019, Article 104225    

Abbas Abbaszadeh Shahri, Johan Spross, Fredrik Johansson, Stefan Larsson    

摘要：Landslides as major geo-hazards in Sweden adversely impact on nearby environments and socio-economics. In this paper, a landslide susceptibility map using a proposed subdivision approach for a large area in southwest Sweden has been produced. The map has been generated by means of an artificial neural network (ANN) model developed using fourteen causative factors extracted from topographic and geomorphologic, geological, land use, hydrology and hydrogeology characteristics. The landslide inventory map includes 242 events identified from different validated resources and interpreted aerial photographs. The weights of the causative factors employed were analyzed and verified using accepted mathematical criteria, sensitivity analysis, previous studies, and actual landslides. The high accuracy achieved using the ANN model demonstrates a consistent criterion for future landslide susceptibility zonation. Comparisons with earlier susceptibility assessments in the area show the model to be a cost-effective and potentially vital tool for urban planners in developing cities and municipalities.    

Superpixel-based automatic image recognition for landslide deformation areas    

基于超像素的滑坡变形区域的自动图像识别  

Engineering Geology, Volume 259, 4 September 2019, Article 105166    

Yang Yang, Shuliang Song, Fucai Yue, Wen He, Wen Nie    

摘要：Obtaining continuous landslide deformation information is important for analyses of landslide processes. This paper proposes a landslide deformation area image recognition method. Using this method, the landslide area can be automatically identified, and continuous landslide deformation data can be obtained. This novel method is implemented using Python and the OpenCV open source libraries, and it is validated using video data of rainfall-induced landslide experiments. The results indicate that the image recognition method can identify the landslide features in video monitoring images with high accuracy. An analysis of the error in the recognition results shows that the environmental changes in light intensity and specular reflections are the main causes of the recognition errors. The new image recognition method is straightforward and can be applied to bare slopes, especially man-made slopes.    

A unified landslide classification system for loess slopes: A critical review    

黄土滑坡的统一分类体系评述  

Geomorphology, Volume 340, 1 September 2019, Pages 67-83    

摘要：Over the last few decades, many landslide classification systems have been developed. Inconsistencies across these systems have inevitably led to ambiguity, confusion, and contradictions. Specifically, there has been no consensus on what types of slope movements and failures constitute landslides. As a result, landslide classification systems based on the same criteria do not always include the same types of slope failures. On the other hand, general landslide classification systems do not take into account the unique characteristics of slope failures in loess, which covers about 6.7% of the Earth's land surface. Most literature on loess is in Chinese and the nomenclature, both within the Chinese literature and between the Chinese and English literature, is often not readily comparable. Therefore, there is a need for a consistent and comprehensive system for classification of loess-slope failures to be developed to better manage these particular geohazards as the presence and interactions of humans with the environment in loess areas continue to increase. In this paper, a critical review of landslide classification systems was conducted to identify their limitations, as well as their relevant criteria for classifying loess-slope failures. Understanding the mechanisms underlying the failure of loess slopes is critical for creating a realistic and comprehensive classification system for slope failures. The classification systems of loess-slope failures unified in this paper are based on detailed analyses of the possible mechanisms underlying each class of failure. The primary classification criteria are types of movement and materials, with other descriptive criteria used to explain differences among different classes. For each class, one or two typical case histories are presented. A comprehensive collection of the literature reviewed in this study will facilitate future research on loess geohazards.