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Record W2771850146 · doi:10.1002/rra.3235

The case of extreme hydrologic drought downstream from reservoirs in Quebec (Canada): The intermittent flow

2017· article· en· W2771850146 on OpenAlexaffabout
Ouassila Azouaoui, Ali A. Assani

Bibliographic record

VenueRiver Research and Applications · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsEnvironmental scienceFlow (mathematics)StreamflowHydrology (agriculture)Magnitude (astronomy)HydroelectricityDownstream (manufacturing)GeologyGeographyDrainage basinEcologyMechanicsPhysicsGeotechnical engineering

Abstract

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Abstract Intermittent flow is a hydrological phenomenon observed at all latitudes. This phenomenon is characterized by a complete or partial interruption of flow in time and/or space in channels. In Quebec, even though the climate is humid, intermittent flow occurs downstream from headwater reservoirs. These reservoirs store water during spring and summer (from April to September) and release it in winter to supply hydroelectric power plants located downstream. During the water storage period, intermittent flow is common (discharges falling to <1 L/s/km 2 ). The goal of the study is to analyse the characteristics (magnitude, frequency, and duration) of this flow downstream from 3 reservoirs built in the Saint‐Maurice River watershed, during the period from 1930 to 2010. Downstream, the contribution (magnitude) of intermittent flow to total altered flow is less than 2%. Intermittent flow frequency ranges from 24 to 65 days per year downstream from the 3 reservoirs. As far as duration is concerned, intermittent flow persists on average from 40 to 128 consecutive days. Canonical correlation analysis revealed that the frequency of intermittent flow is correlated with the North Atlantic Oscillation and its magnitude and negatively correlated with the Southern Oscillation.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score1.000

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 studies0.0020.002
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 head0.042
GPT teacher head0.294
Teacher spread0.252 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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