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Record W4214874581 · doi:10.2172/883215

Hydroacoustic Evaluation of Juvenile Salmonid Passage at The Dalles Dam Sluiceway, 2005

2006· report· en· W4214874581 on OpenAlexaff
Gary E. Johnson, Fenton Khan, John B. Hedgepeth, Robert P. Mueller, Cynthia L. Rakowski, Marshall C. Richmond, John A. Serkowski, John R. Skalski

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsDalsa Corporation
Fundersnot available
KeywordsSluiceSpillwayFish <Actinopterygii>OutflowHydrology (agriculture)Marine engineeringEnvironmental scienceHydropowerEngineeringFisheryGeographyGeotechnical engineeringMeteorologyArchaeology

Abstract

fetched live from OpenAlex

The U.S. Army Corps of Engineers Portland District engaged the Pacific Northwest National Laboratory to evaluate fish passage at The Dalles Dam powerhouse in 2005. The goal of the study was to provide information on smolt passage that will inform decisions on long-term measures and operations to enhance sluiceway passage and reduce turbine passage to improve smolt survival at the dam. The study addressed one of the main programs dedicated to improving juvenile salmonid survival at The Dalles Dam: Surface Flow Bypass. The study objectives (see below) were met using a combination of hydroacoustic and hydraulic data. The study incorporated fixed-location hydroacoustic methods across the entire powerhouse, with especially intense sampling using multiple split-beam transducers at all sluiceway portals. We did not sample fish passage at the spillway in 2005. In the sluiceway nearfield, we used an acoustic camera to track fish movements. The fish data were interpreted with hydraulic data from a computational fluid dynamics (CFD) model. Fish passage data were collected in the framework of an “experiment” using a randomized block design (3-day treatments; two treatments) to compare two sluiceway operational configurations: Sluice 2+5 and Sluice 2+19 (six gates open for each configuration). Total project outflow was 76% of the 10-year average for spring and 71% of the 10-year average for summer. Based on these findings, we make the following recommendations: 1) The sluice should be operated 24 h/d from April until November. 2) Open six rather than three sluice gates to take advantage of the maximum hydraulic capacity of the sluiceway. 3) Open the three gates above the western-most operating main turbine unit and the three gates at MU 8 where turbine passage rates are relatively high. 4) Operate the turbine units below open sluice gates as a standard fish operations procedure. 5) Develop hydraulic and entrance enhancements to the sluiceway to tap the potential of The Dalles Dam sluiceway to be highly efficient and effective at passing juvenile salmonids. 6) Consider the following elements for surface flow bypasses during design of any sluiceway enhancements at The Dalles Dam: Form an extensive surface flow bypass flow net (surface bypass discharge greater than ~7% of total project discharge) at both west and east ends of the dam; Create a gradual increase in water velocity approaching the surface flow bypass (ideally, acceleration < 1 m/s per meter); Make water velocities at an entrance high enough (> 3 m/s) to entrain the subject juvenile fishes, e.g., 10,000 cfs or so; Adapt the shape and orientation of the surface entrance(s) to fit site-specific features, i.e., test a Removable Sluiceway Weir. 7)The Dalles Dam sluiceway has potential to be highly efficient and effective at passing juvenile salmonids. We recommend tapping this potential with enhancements to the sluiceway.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

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 head0.032
GPT teacher head0.280
Teacher spread0.248 · 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 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

Citations9
Published2006
Admission routes1
Has abstractyes

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