Investigation on the Failure Mechanism of Rainfall-Induced Long-Runout Landslide at Upputhode, Kerala State of India

Andrewwinner, Rajkumar; Chandrasekaran, S. S.

doi:10.3390/land10111212

Cited by 8 publications

(5 citation statements)

References 65 publications

(83 reference statements)

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“…Furthermore, the higher hydraulic conductivity of coarser soils results in a faster raising of the wetting front, which reaches the bottom of the soil layer in a shorter amount of time, changing the zero-pore water pressure to a positive pressure, and destabilizing the slope. Andrewwinner et al [105] used a finite-difference model to analyze a rainfall-triggered landslide that occurred on silty sand with a considerable amount of kaolinite clay, and identified a local rainfall threshold of a daily rainfall intensity of 142 mm without an antecedent rainfall. Alternatively, an antecedent rainfall of 151 mm within 5 consecutive days can initiate a landslide, where the failure increase in pore water pressure is due to prolonged rainfall.…”

Section: Discussionmentioning

confidence: 99%

The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)

Luino

Graff

Biddoccu³

et al. 2022

Land

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Shallow landslides due to the soil saturation induced by intense rainfall events are very common in northern Italy, particularly in the Alps and Prealps. They are usually triggered during heavy rainstorms, causing severe damage to property, and sometimes causing casualties. A historical study and analysis of shallow landslides and mud-debris flows triggered by rainfall events in Lombardy was carried out for the period of 1911–2010, over an area of 14,019 km2. In this study, intensity–duration rainfall thresholds have been defined using the frequentist approach, considering some pedological characteristics available in regional soil-related databases, such as the soil region, the textural class, and the dominant soil typological units (STU). The soil-based empirical rainfall thresholds obtained considering the soil regions of the study area were significantly different, with a lower threshold for landslide occurrence in the soil region M1 (Alps), where soils developed over siliceous parent material, with respect to the whole study area and the soil region M2 (Prealps), where soils developed over calcareous bedrocks. Furthermore, by considering textural classes, the curves were differentiated, with coarse-textured soils found more likely to triggerlandslides than fine soils. Finally, considering both texture and main soil groups, given the same rainfall duration, the rainfall amount and intensity needed to initiate a landslide increased in the following order: “coarse-skeletal” Cambisols < Umbrisols < Podzols < “fine” Cambisols. The results of this study highlighted the relevant role of pedological conditioning factors in differentiating the activation of rainfall-induced shallow landslides in a definite region. The information on soils can be used to define more precise rainfall–pedological thresholds than empirical thresholds based solely on meteorological conditions, even when they are locally defined. This knowledge is crucial for forecasting and preventing geo-hydrological processes and in developing better warning strategies to mitigate risks and to reduce socio-economic damage.

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Section: Discussionmentioning

confidence: 99%

The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)

Luino

Graff

Biddoccu³

et al. 2022

Land

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“…The sandstone and coal have a medium permeability, which provided a good channel for the groundwater activity, forming a better aquifer and causing the mudstone to always be subjected to water infiltration. In the process of raising the static groundwater level in the end wall, the pore water pressure increased, reducing the suction of the soil matrix and resulting in a decrease in the soil shear strength (Andrewwinner and Chandrasekaran, 2021). The Mohr circle for the stress of the soil became smaller, and the shear strength decreased.…”

Section: ) Influence Of the Fault Fracture Zone On The End-wall Stabi...mentioning

confidence: 99%

Landslide mechanism and stability of an open-pit slope: The Manglai open-pit coal mine

Chen

Shu²,

Liu³

et al. 2023

Front. Earth Sci.

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A clear understanding of landslide mechanisms and stability analyses is of great significance for landslide monitoring, prediction, and control. A large-scale end wall landslide occurred and its area reached 47,752 m2 on August 7–20, 2020, in the Manglai open-pit coal mine, China. In this paper, the engineering geological survey, mechanical test, large-deformation finite element numerical method, limit equilibrium method and analytical formula are used to analyze how the groundwater level rise caused this end wall failure and landslide. The engineering geological conditions, hydrogeological conditions, landslide activity signs and physical and mechanical parameter calibration of the sliding mass are investigated in detail and tested. Three-dimensional and two-dimensional numerical models of slopes are established, and an analytical formula calculation method to calculate the factor of safety (FoS) is proposed when sliding cracks are located on the top and toe of a slope. The results indicate that the fault fracture zone, soft strata, continuous heavy rainfall, and groundwater were the main contributors to this landslide. The three-dimensional numerical calculation results are consistent with the deformation and failure process of the slope observed in the field, which shows a retrogressive progressive failure mode. The calculation results of SLOPE/W and the analytical formula are consistent; i.e., when the groundwater level rises to +950, the stability of the end wall reaches the critical stability state. With the passage of time, the creep of the sliding surface accelerates until the entire end wall landslide.

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“…Landslide instability and damage cause heavy losses and disasters. The EM-DAT catastrophe database estimates that 8,658 persons perished as a direct result of landslide activity throughout the globe during 1990 and 1991 [ 1 ]. “The Durham Fatal Landslide Database” (DFLD) database indicates that the death toll from landslide events between 1980 and 2000 was about 72,000 worldwide, or about 3,400 per year, a figure that is considered a significant underestimation of landslide hazard outcomes because the underreporting of small events (events with very low mortality rates) and events that occur in very remote areas keeps the count far below the actual number [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Stability Analysis of Geotechnical Landslide Based on GA-BP Neural Network Model

Zhao

2022

Computational and Mathematical Methods in Medicine

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Rock and soil landslides, a regular geological disaster in engineering construction, endanger national property and, in severe circumstances, result in a huge number of casualties. A set of methods for landslide stability analysis and prediction has been established, with the academic idea of “geological process mechanism analysis-quantitative evaluation” at its core, combined with detailed field investigation of geological hazards, forming a relatively complete technical route for research on landslide stability analysis. The work of this paper can be summarized as follows: (1) Introduce the research status of geotechnical landslide stability at home and abroad and the current development trend of neural network. (2) Through the collected sample database, take the training function and the number of hidden layer neurons as variables to optimize the BP neural network, and combine the optimized BP neural network with the genetic algorithm to construct the GA-BP neural network. (3) The stability coefficients of the BP neural network, the genetic algorithm based back propagation neural network (GA-BPNN), and the limit equilibrium technique are analyzed and compared. The findings imply that landslide stability can be assessed using neural networks. GA-BPNN is a viable alternative to back propagation neural network (BPNN). The algorithm is more accurate, has a faster convergence rate, and is more stable.

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Investigation on the Failure Mechanism of Rainfall-Induced Long-Runout Landslide at Upputhode, Kerala State of India

Cited by 8 publications

References 65 publications

The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)

The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)

Landslide mechanism and stability of an open-pit slope: The Manglai open-pit coal mine

Stability Analysis of Geotechnical Landslide Based on GA-BP Neural Network Model

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