Reducing Local Correlations Among Causal Factor Classifications as a Strategy to Improve Landslide Susceptibility Mapping

Xiao, Ting; Yu, Lanbing; Tian, Weiming; Zhou, Chang

doi:10.3389/feart.2021.781674

Cited by 14 publications

(8 citation statements)

References 46 publications

(40 reference statements)

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“…Advanced technology is the key to obtaining the meso-structure and micro-structure of intact glacial till. In recent years, with the development of computer technology and numerical calculation methods, a variety of methods have emerged in the field of analysis and research on the meso-structure and micro-structure of rock and soil [35][36][37], such as SEM techniques, statistical methods, fractal theory, and CT scanning methods. The CT scanning technology and scanning electron microscope technology used in the study of the meso-structure and micro-structure characteristics of intact glacial till are the most advanced methods for studying the structure of rock and soil mass.…”

Section: Discussionmentioning

confidence: 99%

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

2022

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Glacial till is a special soil in alpine mountainous areas, which often induces geohazards such as debris flows and landslides due to the influence of special geological environmental conditions in alpine mountainous areas. The change in the structure of glacial till is the main cause of geohazards. Glacial till structure is one of the important factors affecting the mechanical properties of soil. It can explain the mechanical phenomena of soil engineering and establish the quantitative relationship between soil structure and macro–mechanical properties. However, there are few systematic research results on its structure. For this reason, the intact glacial till in the Moxi River Basin, South of Kangding City, Tibetan Autonomous Prefecture of Garzê, Sichuan Province was taken as the research object, and the meso-structure and micro-structure of intact glacial till were studied using CT scanning and scanning electron microscopy (SEM). The meso-structure and micro-structure images of the interior of intact glacial till were obtained and the porosity, particle shape, directivity and structural unit were analyzed. The results show that: (1) the average porosity of longitudinal and transverse sections of intact glacial till are 24.92% and 24.35%, respectively, and the difference is not significant; (2) the average circularity of the particles in the longitudinal and transverse sections is 0.836 and 0.802, respectively, and the average aspect ratio is 2.5 and 3.7, respectively. The shape of the particles in the longitudinal section is more circular than in the transverse section, and the orientation of the particles in the transverse sectional direction is more obvious; (3) the main mineral components of the glacial till sample are mica, feldspar and quartz. In the process of transportation and deposition, the mineral particles undergo different degrees of grinding, crushing and dissolution. The particles are mainly formed by calcareous cementation, and the cementation is dense. The structure is mainly a skeleton structure composed of fine particles that are wrapped or filled. These findings provide the scientific basis for highway-, railway- and hydro-power-station construction and disaster prevention and mitigation in the alpine mountainous area.

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Section: Discussionmentioning

confidence: 99%

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

2022

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“…Quantitative Study of the Microparameters. At present, with the development of computer technology, many numerical calculation methods have been introduced to analyze the evolution process [22,23] and regional distribution of natural hazards [24,25]. Compared to the continuum mechanics methods [26,27], PFC can be used to study the mechanical properties and behavior of the elements from the perspective of microstructure [28,29].…”

Section: 2mentioning

confidence: 99%

Cross-Scale Study of the High-Steep Reservoir Banks under Different Mechanical States

et al. 2022

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The deformation of high-steep rocky banks is caused by the self-weight of overlying rock mass and the fluctuation of reservoir water. In this paper, the newly developed testing equipment and the particle flow code (PFC) were used to complete the cross-scale study of the high-steep rocky banks under different mechanical states. The test conditions involved the dry state, saturated state, and hydraulic coupling states under different confining pressures. Combined with the micrographs of the fractured surface under different mechanical states, it can be found that the participation of the water could reduce the bond contact and accelerate the deformation of the particles, ultimately leading to an increase in the plastic deformation and a decrease in the peak strength of the rock mass. Compared to the saturated state, the water in the hydraulic coupling state was not transferred though the storage space was compressed; thus, the water pressure would further promote the extension of the microcracks. When considering the fluctuations of the reservoir water, the changes in the mechanical state may accelerate the degradation rate of the rock mass. The related methods can provide data support and a theoretical basis to the evolution trend of high-steep rocky reservoir banks.

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“…As one of the most landslide-prone areas in China, the Three Gorges Reservoir Area (TGRA) has been given much attention concerning severe landslides [6]. One main reason is that the construction of the Three Gorges Dam (TGD) has significantly changed the regional hydrogeological conditions [7,8].…”

Section: Introductionmentioning

confidence: 99%

Using Complementary Ensemble Empirical Mode Decomposition and Gated Recurrent Unit to Predict Landslide Displacements in Dam Reservoir

Yang

Xiao

Huang³

2022

Sensors

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It is crucial to predict landslide displacement accurately for establishing a reliable early warning system. Such a requirement is more urgent for landslides in the reservoir area. The main reason is that an inaccurate prediction can lead to riverine disasters and secondary surge disasters. Machine learning (ML) methods have been developed and commonly applied in landslide displacement prediction because of their powerful nonlinear processing ability. Recently, deep ML methods have become popular, as they can deal with more complicated problems than conventional ML methods. However, it is usually not easy to obtain a well-trained deep ML model, as many hyperparameters need to be trained. In this paper, a deep ML method—the gated recurrent unit (GRU)—with the advantages of a powerful prediction ability and fewer hyperparameters, was applied to forecast landslide displacement in the dam reservoir. The accumulated displacement was firstly decomposed into a trend term, a periodic term, and a stochastic term by complementary ensemble empirical mode decomposition (CEEMD). A univariate GRU model and a multivariable GRU model were employed to forecast trend and stochastic displacements, respectively. A multivariable GRU model was applied to predict periodic displacement, and another two popular ML methods—long short-term memory neural networks (LSTM) and random forest (RF)—were used for comparison. Precipitation, reservoir level, and previous displacement were considered to be candidate-triggering factors for inputs of the models. The Baijiabao landslide, located in the Three Gorges Reservoir Area (TGRA), was taken as a case study to test the prediction ability of the model. The results demonstrated that the GRU algorithm provided the most encouraging results. Such a satisfactory prediction accuracy of the GRU algorithm depends on its ability to fully use the historical information while having fewer hyperparameters to train. It is concluded that the proposed model can be a valuable tool for predicting the displacements of landslides in the TGRA and other dam reservoirs.

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Reducing Local Correlations Among Causal Factor Classifications as a Strategy to Improve Landslide Susceptibility Mapping

Cited by 14 publications

References 46 publications

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province

Cross-Scale Study of the High-Steep Reservoir Banks under Different Mechanical States

Using Complementary Ensemble Empirical Mode Decomposition and Gated Recurrent Unit to Predict Landslide Displacements in Dam Reservoir

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