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Numerous scholars, domestically and internationally, have extensively researched the initiation and occurrence of landslides under intermittent rainfall. These studies have revealed the intrinsic relationship between rainfall intensity and landslide stability. This relationship indicates that landslide destabilization and failure involve the gradual spread of the plastic zone at the sliding surface until it penetrates through. The stability of these landslides was quantitatively evaluated using the overall safety factor. To improve the accuracy of landslide prediction and forecasting, the temporal and spatial relationships between landslide evolution characteristics and stability must be deeply investigated. By combining existing monitoring technology, revealing the temporal and spatial patterns of the overall safety coefficient of landslides, point safety coefficients, displacements, and other parameters, and proposing the criteria for the stability of landslides at each stage, we can provide reliable theories and methods for the accurate early warning and forecasting of landslides.
Using ABAQUS software, a finite element model for a traction landslide was established, considering the relationship between the spatial stress and time of the slope body under intermittent precipitation. Python was implemented for the secondary development of a time-history method for analyzing point safety factors. This method allowed us to calculate the spatial point safety coefficient cloud map of the different regions of a landslide section at any time and analyze the entire process of the initiation-deformation-failure of a traction landslide under intermittent rainfall.
The study yielded the following results: 1) Point safety coefficient time-range calculations visually described the evolution characteristics of the traction landslide sliding surface under intermittent rainfall, gradually moving from the foot to the top of the slope. The time-history varying characteristics of the three-point safety coefficient reflect the process of landslide initiation, deformation, and destabilization evolution stages, providing a sufficient basis for dividing the landslide traction, main slide, and locking sections. 2) Based on multidimensional parameters such as the overall safety factor, point safety factor, and displacement under intermittent rainfall, the combination of the point safety factor and deformation and time-history displacement parameters is shown to serve as a basis for judging the initiation, deformation, and destabilization of a traction landslide under intermittent rainfall. However, the overall safety factor cannot be used as the basis for judging. 3) According to the displacement variations and the numerical size of point safety coefficients of the three parts of a landslide (the traction, main slide, and locking sections), we jointly determine that a landslide has four states: stable, basically stable, less stable, and unstable. This analysis forms the criterion for determining the stable state of each stage of a traction landslide, and its reliability was verified through examples.
The above results prove that using the point safety coefficient to describe the landslide deformation and failure process is more specific and comprehensive than the overall safety coefficient. This finding provides a theoretical basis and engineering guidance for future early warning and forecasting of intermittent rainfall landslides in China.
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