Effects of human activity on erosion, sedimentation and debris flow activity – A case study of the Qionghai Lake watershed, southeastern Tibetan Plateau, China
Bibliographic record
Abstract
We report the results of a study of the Qionghai Lake watershed, located on the southeastern edge of the Qinghai–Tibetan Plateau, China, designed to investigate the effects of human activity on changes in soil erosion intensity, debris flow activity and lacustrine sedimentation. The results indicate that the mean denudation rate of the watershed was about 0.82 mm/yr during the Holocene. However, since 1952, the rate has increased to 1.82 mm/yr, accompanied by a greatly increased sedimentation rate in Qionghai Lake. The increased denudation rate was accompanied by increases in population and the related intensified exploitation of land resources, including deforestation and an increase in the area of cultivated land. In addition, the increasing rate of denudation and lacustrine sedimentation is closely linked to the increased frequency of flooding and debris flows in the watershed. Based on our results, we estimate that the longevity of Qionghai Lake is about 1200 years in the case of natural evolution; however, this is reduced to 540 years in the context of continued intensive human activity in the region. These findings are important for the mitigation of mountain hazards such as debris flows and for the promotion of sustainable economic development in the Qionghai Lake area. They also provide a basis for obtaining an improved estimate of changes in denudation rate on the southeastern edge of the Qinghai–Tibet Plateau.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".