Triggering mechanism and reactivation probability of loess-mudstone landslides induced by rainfall infiltration: a case study in Qinghai Province, Northwestern China

Mu, Wenping; Wu, Xiong; Qian, Cheng; Wang, Kang

doi:10.1007/s12665-019-8767-1

Cited by 16 publications

(7 citation statements)

References 52 publications

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“…Xu et al [17,18] studied the effect of periodic water circulation on rock mass by P-Wave Velocity and found that the water-rock interaction changed the porosity of the rock pores and then affected its mechanical properties. Mu [19] studied the triggering mechanism and reactivation probability of a loess-mudstone landslide induced by rainwater infiltration, and concluded that shear strength of media is very sensitive to water content because of water-rock interaction, and landslide reactivation is controlled by the water sensitivity of media, especially the original sliding zone.…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence of Water–Rock Interaction on the Stability of Schist Slope

et al. 2020

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(1) The studies on the influence of rainfall on slope stability mainly focus on rainfall characteristics and the variation of strength parameters. Few studies pay attention to the micro structure changes of rock mass under long-term rainfall conditions, and the influence of failure mode. (2) Based on nuclear magnetic resonance (NMR) and electron microscopic imaging (Emmi) technology, the micro structure changes and macro deformation characteristics of the schist, under long-term immersion in different liquids are analyzed. (3) After soaking in the deionized water, the uniaxial compression strength of the intact specimen is slightly lower than that of the untreated specimens, but the test process in the elastic compression stage is considerably prolonged, and the failure modes show both shear and slip at the same time. While after soaking in acid solution, the fracture of rock samples with initial cracks can be obviously reduced and healed, which is consistent with the change of micro pore structure. The uniaxial strength and modulus of the intact samples are significantly lower, and only slip failure mode occurred. (4) It shows that water–rock interaction is an important factor influencing the stability of slope besides the external rainfall force, which affects the structural characteristics and mechanical properties of rock.

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Section: Introductionmentioning

confidence: 99%

Study on the Influence of Water–Rock Interaction on the Stability of Schist Slope

et al. 2020

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“…All the parameters used in this study contributed to the landslides' occurrence. According to various studies, moisture (precipitation) and topographical properties play a significant role in triggering landslides [76][77][78][79]. The excessive moisture in the soil increases the pore pressure, which decreases the shear strength of the soil and leads to slope failure [78].…”

Section: Landslide Early Warning System (Lews) and Land System Proces...mentioning

confidence: 99%

Management of Landslides in a Rural–Urban Transition Zone Using Machine Learning Algorithms—A Case Study of a National Highway (NH-44), India, in the Rugged Himalayan Terrains

Fayaz

Meraj²,

Khader

et al. 2022

Land

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Landslides are critical natural disasters characterized by a downward movement of land masses. As one of the deadliest types of disasters worldwide, they have a high death toll every year and cause a large amount of economic damage. The transition between urban and rural areas is characterized by highways, which, in rugged Himalayan terrain, have to be constructed by cutting into the mountains, thereby destabilizing them and making them prone to landslides. This study was conducted in one most landslide-prone regions of the entire Himalayan belt, i.e., National Highway NH-44 (the Jammu–Srinagar stretch). The main objectives of this study are to understand the causes behind the regular recurrence of the landslides in this region and propose a landslide early warning system (LEWS) based on the most suitable machine learning algorithms among the four selected, i.e., multiple linear regression, adaptive neuro-fuzzy inference system (ANFIS), random forest, and decision tree. It was found that ANFIS and random forest outperformed the other proposed methods with a substantial increase in overall accuracy. The LEWS model was developed using the land system parameters that govern landslide occurrence, such as rainfall, soil moisture, distance to the road and river, slope, land surface temperature (LST), and the built-up area (BUA) near the landslide site. The developed LEWS was validated using various statistical error assessment tools such as the root mean square error (RMSE), mean square error (MSE), confusion matrix, out-of-bag (OOB) error estimation, and area under the receiver operating characteristic (ROC) curve (AUC). The outcomes of this study can help to manage landslide hazards in the Himalayan urban–rural transition zones and serve as a sample study for similar mountainous regions of the world.

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“…Sandstone forms a permeable layer, the mudstone is relatively water-resistant, and the contact zone between the two is made up of a highly watersaturated zone [25]. Studies have revealed that the presence of stagnant water in the residual soil layer and the increase in pore water pressure were the main reasons for rainfallinduced landslides [26]. The geological structure of Longquan Mountain is predominantly composed of a soft rock "red layer."…”

Section: Study Area Descriptionmentioning

confidence: 99%

“…Continuous rainfall is the primary cause of red bed landslides [26]. As shown in Figure 14, the field measurement date was February 2, 2021.…”

Section: Geofluidsmentioning

confidence: 99%

Research on Internal Structure and Mechanism of Landslide Based on Hydrogeophysical Investigation (Quan’an Landslide, Southwest China)

Wang

et al. 2022

Geofluids

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The survey area is located in the planning area of Longquan national urban park, with frequent human activities, numerous water conservancy, transportation projects, and frequent geological disasters such as landslides. The Red Mudstone has low strength and easy to soften in the case of water, and it is very prone to landslide in rainy season. At present, there are many studies on Red Mudstone Landslides, but most of them are analyzed by geological means, and the monitoring process is also dominated by surface deformation and settlement; there is less analysis with hydrogeological that is caused by rainfall and human activities. For Red Mudstone Landslides, to effectively reveal and analyze the process of the Slip Mechanism, we need to carry out the characteristics of hydrogeological structure and underground physical structure, and compare with surface monitoring and point geological structure. In this study, a one-year field survey and hydrogeophysical survey were carried out. Combined with the characteristics of environmental geology, the geophysical forward modeling problem based on finite element method was used to verify the influence of rainfall on the electrical characteristics of underground media. The smoothness constrained least square method and three-dimensional unstructured grid method are used to interpret the ERT data, analyze the abnormal patterns of electrical structure of landslide in different seasons, and correspond well with the GPR data. According to the characteristics of surface vegetation and weathering, as well as the displacement and settlement monitoring after landslide, the spatial characteristics of red bed landslide are revealed, and the relationship between landslide, rainfall, and human activities is clarified.

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Triggering mechanism and reactivation probability of loess-mudstone landslides induced by rainfall infiltration: a case study in Qinghai Province, Northwestern China

Cited by 16 publications

References 52 publications

Study on the Influence of Water–Rock Interaction on the Stability of Schist Slope

Study on the Influence of Water–Rock Interaction on the Stability of Schist Slope

Management of Landslides in a Rural–Urban Transition Zone Using Machine Learning Algorithms—A Case Study of a National Highway (NH-44), India, in the Rugged Himalayan Terrains

Research on Internal Structure and Mechanism of Landslide Based on Hydrogeophysical Investigation (Quan’an Landslide, Southwest China)

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