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Record W2360433499

Analysis on Rainfall-Runoff Characteristics and Simulation of the Different Hydrologic Year Runoff of Xilin River Basin in Inner Mongolia Based on SWAT Model

2014· article· en· W2360433499 on OpenAlexaff
Duan Chao-y

Bibliographic record

VenueShuitu baochi yanjiu · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSurface runoffHydrology (agriculture)Inner mongoliaAridSnowmeltSWAT modelEnvironmental scienceDrainage basinStructural basinSoil and Water Assessment ToolGrasslandPhysical geographyChinaStreamflowGeologyGeographyGeomorphologyCartography
DOInot available

Abstract

fetched live from OpenAlex

Xilin River is a typical grassland river located in Inner Mongolia,which is a cold-arid-region in the north of China.Its basin was investigated and some necessary experiments were carried out by means of hydrological processes.The hydrological nonlinear system theory,geological statistics,remote sensing and geographic information system were used to determine the parameters that are required by SWAT.In conclusion,using SWAT to simulate the hydrological processes in the cold-arid-regions with a characteristic of snowmelt-runoff could represent different accuracies.The best fitting result between the observed and simulated data was obtained for the normal hydrologic years,the worst for the dry years,between which the accuracies were partial wet years wet yearspartial dry year.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2014
Admission routes1
Has abstractyes

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