Hydrodynamics of a large lake with complex geometry and topography: Lake of the Woods
Bibliographic record
Abstract
We developed a high-resolution (250 m) three-dimensional hydrodynamic model of Lake of the Woods (LoW) to study surface seiches, lake circulation, and water temperature. LoW spans over two different geological regions, experiences wind variability, encompasses >14,500 islands and includes twelve hydraulically connected sub-basins. The complex geometry and topography are unique for this large lake that suffers from seasonal algal blooms. The model uses a spatially and temporally variable wind field, heat fluxes, riverine inflows obtained from a watershed model, outflows at Kenora and Norman dams, and was run for the spring-summer of 2017 and 2018. The predominant physical processes in LoW are surface seiches, and wind and rivers drive mean lake-wide circulations and mixing. The observed periods of seiches in the lake are 9.5, 3.4, 2.3, and 1.3 h, attributed to horizontal modes 1, 3, 6, and 12, respectively. Amphidromic structures show that sub-basin seiche's responses to wind may be limited to one sub-basin; however, lake-wide responses were also observed, which suggests the seiche-induced oscillatory velocities can impact transport paths. The mean water temperature is variable spatially, ranging from <15 °C in early June to ∼25 °C in July-August. Sabaskong Bay experienced warmer summer water temperatures with unidirectional mean flows to the lake. Main water transport is towards the northeast. Modelled conservative tracers, consistent with observations, show that the Rainy River plume extent covers Big Traverse, Morson, and Little Traverse Bays. The modelled seasonal hydraulic retention times in southern bays are <150 days and are much longer in northern bays.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".