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Record W2109106795 · doi:10.1002/hyp.10071

River evaporation and corresponding heat fluxes in forested catchments

2013· article· en· W2109106795 on OpenAlexafffundabout
Audrey Maheu, Daniel Caissie, André St‐Hilaire, Nassir El‐Jabi

Bibliographic record

VenueHydrological Processes · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité de MonctonUniversity of New BrunswickFisheries and Oceans CanadaInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEvaporationEnvironmental scienceHydrology (agriculture)STREAMSFlux (metallurgy)Heat fluxHumidityAtmospheric sciencesHeat transferGeologyMeteorologyGeography

Abstract

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Abstract River water temperature is a very important variable in ecological studies, especially for the management of fisheries and aquatic resources. Temperature can impact on fish distribution, growth, mortality and community dynamics. River evaporation has been identified as an important heat loss and a key process in the thermal regime of rivers. However, its quantification remains a challenge, mainly because of the difficulty of making direct measurements. The objectives of this study were to characterize the evaporative heat flux at different scales (brook vs river) and to improve the estimation of the evaporative heat flux in a stream temperature model at the hourly timescale. Using a mass balance approach with floating minipans, we measured river evaporation at an hourly timescale in a medium‐sized river (Little Southwest Miramichi) and a small brook (Catamaran Brook) in New Brunswick, Canada. With these direct measurements of evaporation, we developed mass transfer equations to estimate hourly evaporation rates from microclimate conditions measured 2 m above the stream. During the summer 2012, river evaporation was more important for the medium‐sized river with a mean daily evaporation rate of 3.0 mm day −1 in the Little Southwest Miramichi River compared with that of 1.0 mm day −1 in Catamaran Brook. Evaporation was the main heat loss mechanism in the two studied streams and was responsible for 42% of heat losses in the Little Southwest Miramichi River and 34% of heat losses in Catamaran Brook during the summer. Copyright © 2013 John Wiley & Sons, Ltd.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations41
Published2013
Admission routes3
Has abstractyes

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