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Record W2151967576 · doi:10.1002/esp.1004

Impact of hydroelectric power releases on the morphology and sedimentology of the bed of the Warche River (Belgium)

2004· article· en· W2151967576 on OpenAlexaff
Ali A. Assani, François Petit

Bibliographic record

VenueEarth Surface Processes and Landforms · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSedimentologyHydrology (agriculture)FluvialGeologyRiver bedOutcropChannelizedHydroelectricityBedrockSinuosityEnvironmental scienceGeomorphologyGeotechnical engineeringEcology

Abstract

fetched live from OpenAlex

Abstract The Butgenbach dam on the Warche River was built in 1932 in order to maintain a sufficient supply of water to the Robertville reservoir situated 7 km downstream, for the production of hydroelectricity. During winter months, releases are made almost every day from the Butgenbach dam. From a hydrological point of view, this has resulted in significantly reducing the number of discharges that are higher than bankfull. Despite the reduction in peak discharge, there is a significant increase in the number of efficient discharges (0·6 bankfull). The impacts of these hydrological modifications on the bed morphology and sedimentology below the Butgenbach dam have been studied and the following geomorphological modifications have been identified: a doubling of the width of the channel in 45 years, a reduction in the number of riffles and pools, an increase in the number of gravel bars and islets and an increase in bedrock outcrops in the channel. Moreover, the finest bed particles are mobilized by the almost daily releases, inducing a significant increase in bed‐material size sorting. The reduction of sinuosity and the disappearance of bed differentiation and riffle/pool sequences have produced a diminution of bed roughness and an increase of the competence of the river. Thus relatively small floods can remove the armoured layer. Copyright © 2003 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.364

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 science0.0000.000
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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2004
Admission routes1
Has abstractyes

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