MétaCan
Menu
Back to cohort
Record W2311709439 · doi:10.2166/wst.2015.609

Evaluation of the applicability of the SWAT model in an arid piedmont plain oasis

2015· article· en· W2311709439 on OpenAlexaff
Yong Jun Wu, Changyou Li, Chengfu Zhang, Xiaohong Shi, Charles P.‐A. Bourque, Shengnan Zhao

Bibliographic record

VenueWater Science & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of New Brunswick
FundersNational Natural Science Foundation of China
KeywordsHydrology (agriculture)WatershedSoil and Water Assessment ToolAlluvial plainSWAT modelEnvironmental scienceAridCoastal plainWater balanceRidgeGeologyStreamflowGeographyDrainage basin

Abstract

fetched live from OpenAlex

Hetao Oasis is located in a typical piedmont alluvial plain bounded by the Langshan Mountain Range in the north, desert in the west, and the Yellow River in the south. Agricultural activities within the oasis significantly impact the hydrological cycle and water quality in downstream locations. The research uses the Soil and Water Assessment Tool (SWAT) for a piedmont plain by defining the watershed boundary as coinciding with the natural mountain ridge, the border between the oasis and the desert, and the Yellow River. The model simulates water discharge with coefficient of determination and a Nash-Sutcliffe model efficiency of 0.78 and 0.62 during model calibration, and 0.75 and 0.69 during model validation, suggesting that delineation of the watershed as carried out in this research is suitable for piedmont plain topography. From the results, the mountains contribute 28.4% to the water discharge at the outlet of the watershed, and water-use efficiency of irrigated water is about 40%, which is consistent with field-based measurements. Methodologies used in delineating watershed boundaries and parameterizing SWAT provide a solid foundation for water balance studies in other regions of the world with similar topography.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.034
GPT teacher head0.266
Teacher spread0.231 · 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.

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

Citations6
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueWater Science & TechnologySame topicHydrology and Watershed Management StudiesFrench-language works237,207