Chain effects of landslide activity intensity decay on landslide sediment transfer and debris flow activity
Bibliographic record
Abstract
In earthquake-affected zones, the spatiotemporal succession of landslide activity intensity influences the capacity of the landslide sediment supply for debris flows, thereby affecting their activity. However, the driving mechanisms behind the spatiotemporal succession of landslide activity intensity remain unclear. In particular, the chain effects of this evolution on landslide sediment transfer and debris flow activity are not fully understood. In this study, we monitored the prolonged changes in landslide activity intensity and landslide sediment transfer potential. we subsequently analyzed the driving mechanism of the succession of landslide activity intensity and observed the close relationship between the succession of landslide activity intensity and sediment transfer as well as debris flow activity. In the first 5 years following the Wenchuan earthquake, intense tectonic activity and extreme rainfall events dominated the landslide destabilization probabilities, resulting in exceptionally high sediment transfer potential in the Yingxiu–Caopo regions, Sichuan Province, China. Subsequently, the combined impacts of rainfall, curvature, slope, and aspect gradually increased, resulting in the regions with higher landslide activity intensity progressively advancing to these nonriparian regions, which consequently induced a corresponding change in areas with higher landslide sediment transfer potential. The spatiotemporal evolution of landslide activity intensity has led to a linear decay in the potential for landslide-derived sediment supply to channels, consequently resulting in a corresponding linear decline in debris flow activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".