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Record W2110230861 · doi:10.5194/bg-11-4251-2014

Physical controls on CH <sub>4</sub> emissions from a newly flooded subtropical freshwater hydroelectric reservoir: Nam Theun 2

2014· article· en· W2110230861 on OpenAlexafffund
Chandrashekhar Deshmukh, D. Serça, Claire Delon, Raphael Tardif, M. Demarty, Christian Jarnot, Yves Meyerfeld, Vincent Chanudet, P. Guédant, W. Rode, Stéphane Descloux, Frédéric Guérin

Bibliographic record

VenueBiogeosciences · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsGDG Environnement
FundersElectricité de FranceHydro-Québec
KeywordsEnvironmental scienceDaytimeDry seasonSubtropicsAtmospheric sciencesMethaneHydrology (agriculture)Water levelAmmoniaAnimal scienceChemistryEcologyGeologyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract. In the present study, we measured independently CH4 ebullition and diffusion in the footprint of an eddy covariance system (EC) measuring CH4 emissions in the Nam Theun 2 Reservoir, a recently impounded (2008) subtropical hydroelectric reservoir located in the Lao People's Democratic Republic (PDR), Southeast Asia. The EC fluxes were very consistent with the sum of the two terms measured independently (diffusive fluxes + ebullition = EC fluxes), indicating that the EC system picked up both diffusive fluxes and ebullition from the reservoir. We showed a diurnal bimodal pattern of CH4 emissions anti-correlated with atmospheric pressure. During daytime, a large atmospheric pressure drop triggers CH4 ebullition (up to 100 mmol m−2 d−1), whereas at night, a more moderate peak of CH4 emissions was recorded. As a consequence, fluxes during daytime were twice as high as during nighttime. Additionally, more than 4800 discrete measurements of CH4 ebullition were performed at a weekly/fortnightly frequency, covering water depths ranging from 0.4 to 16 m and various types of flooded ecosystems. Methane ebullition varies significantly seasonally and depends mostly on water level change during the warm dry season, whereas no relationship was observed during the cold dry season. On average, ebullition was 8.5 ± 10.5 mmol m−2 d−1 and ranged from 0 to 201.7 mmol m−2 d−1. An artificial neural network (ANN) model could explain up to 46% of seasonal variability of ebullition by considering total static pressure (the sum of hydrostatic and atmospheric pressure), variations in the total static pressure, and bottom temperature as controlling factors. This model allowed extrapolation of CH4 ebullition on the reservoir scale and performance of gap filling over four years. Our results clearly showed a very high seasonality: 50% of the yearly CH4 ebullition occurs within four months of the warm dry season. Overall, ebullition contributed 60–80% of total emissions from the surface of the reservoir (disregarding downstream emissions), suggesting that ebullition is a major pathway in young hydroelectric reservoirs in the tropics.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.201
Teacher spread0.194 · 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 designBench or experimental
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

Citations74
Published2014
Admission routes2
Has abstractyes

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