Long-runout mechanism and landsliding behaviour of large catastrophic landslide triggered by heavy rainfall in Guanling, Guizhou, China
Bibliographic record
Abstract
A large catastrophic landslide was triggered by a heavy rainfall on 28 June 2010 in Guanling, Guizhou, China. The landslide buried two villages and killed 99 people along the runout path. The landslide involved the failure of about 985 000 m 3 of sandstone from the source area, with a runout of about 1.4 km over a total vertical distance of about 420 m. To understand the possible long-runout mechanism and behaviour of the landslide, a detailed field survey of the landslide was conducted and samples were taken from the runout path. The shear behaviour of the sample based on a series of ring shear tests was examined, and numerical simulation of the landsliding behaviour by using a numerical runout model (DAN-W) was performed in which the shear strength obtained by ring shear tests was used. The experimental results reveal that the residual shear strength measured along the pre-existing shear surface is independent of the shear displacement rate under partially drained conditions, suggesting that the relationship between shear and normal stresses obeys the frictional model. A bulk basal friction angle of 14.4° at the base of the moving mass was then obtained from the test results. The simulated results show that the selected rheological model and parameters based on ring shear tests could provide the best performance in simulating the landslide. Therefore, it is expected that the model and parameters could improve the precision of hazard zonation for areas with geological, topographical, and climatic features similar to the Guanling landslide area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".