Fate of Artificially Injected Oxygen in the Hypolimnion of a Two‐Basin Lake: Amisk Lake, Revisited
Bibliographic record
Abstract
Abstract Bubble‐plume diffusers are increasingly used to add dissolved oxygen (DO) to the hypolimnion of lakes and reservoirs. Bubble plumes are successful at replenishing hypolimnetic DO, but they also introduce mixing energy that induces subtle changes in the thermal structure of the reservoir, driving changes in plume behavior. To account for this complex plume‐reservoir interaction, a double bubble‐plume model is coupled with a three‐dimensional hydrodynamic model. The coupled model is used to reassess a field‐scale analysis of the bubble‐plume diffuser in two‐basin Amisk Lake, aiming at evaluating the relative role of bubble‐induced circulation and internal‐seiching in driving inter‐basin transport under stratified conditions. A large‐scale plume‐induced circulation was previously thought to be the main driver of inter‐basin oxygen transport. This interpretation was based on the attribution of the time‐averaged circulation in the channel due to plume operation. However, the intrinsic complexity of the hydraulic system and the sparseness of the field data introduced large uncertainties in the previous analysis. Here, we demonstrate that the time‐averaged circulation is primarily the result of wind‐driven internal seiches. Oxygen exchange is shown to be controlled by the interaction between internal seiche‐driven horizontal transport along the channel, and, the rate at which added oxygen reaches the layers above the sill, which is mainly controlled by plume‐induced circulation. Internal‐seiche driven transport through basin constrictions will vary depending on the magnitude of the wind forcing, depth of the thermocline and the channel geometry. These results highlight the importance of understanding water movement prior to introducing restoration actions in lakes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".