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Record W2116689256 · doi:10.1139/l08-087

Modeling of salinity intrusion under different hydrological conditions in the Arvand River Estuary

2008· article· en· W2116689256 on OpenAlexvenueno aff
Fatemeh Zahed, Amir Etemad‐Shahidi, Ebrahim Jabbari

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsEstuaryHydrology (agriculture)SalinityEnvironmental scienceDischargeIntrusionWater dischargeWater qualityClosure (psychology)Momentum (technical analysis)Saltwater intrusionGeologyDrainage basinOceanographyGeotechnical engineeringGroundwaterAquiferGeographyEcology

Abstract

fetched live from OpenAlex

Arvand River Estuary is the most important inland water body of Iran and its discharge has been reduced in the last decades due to construction of several dams. Hence, a two-dimensional laterally averaged time dependent hydrodynamic and water quality model called CE-QUAL-W2 was applied to this estuary to assess the impacts of river discharge reduction. The model was first implemented with three different closure schemes for parameterization of vertical transport of mass and momentum. It was found that the W2N scheme performs better than the other schemes in predicting the vertical salinity structure. The model was then used for prediction of salinity intrusion in different hydrological conditions and a simple equation was obtained for estimation of the intrusion length as a function of upstream freshwater discharge.

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)0.001
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.016
GPT teacher head0.181
Teacher spread0.165 · 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

Citations31
Published2008
Admission routes1
Has abstractyes

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