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Record W2079344556 · doi:10.1177/0959683615574893

Effects of human activity on erosion, sedimentation and debris flow activity – A case study of the Qionghai Lake watershed, southeastern Tibetan Plateau, China

2015· article· en· W2079344556 on OpenAlexaff
Ningsheng Chen, Mingli Chen, Jun Li, Na He, Mingfeng Deng, Javed Iqbal Tanoli, Ming Cai

Bibliographic record

VenueThe Holocene · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsLaurentian University
Fundersnot available
KeywordsDenudationWatershedSedimentationDebris flowErosionDebrisPlateau (mathematics)GeologyHydrology (agriculture)Physical geographyContext (archaeology)LandslideDeforestation (computer science)Environmental scienceSedimentGeomorphologyOceanographyGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.240
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2015
Admission routes1
Has abstractyes

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