Controls on natural levée development in the Columbia River, British Columbia, Canada
Bibliographic record
Abstract
Abstract Natural levées of the Columbia River near Golden, British Columbia, were investigated to identify the mechanisms that control levée development and morphology. Topographic profiles of 12 levée pairs were surveyed, and measurements of water‐surface elevation, flow velocity, flow direction and turbidity were obtained during an average magnitude flood (1·2 years recurrence interval). Sedimentation rates and grain‐size distributions were measured from sediment traps placed along levée‐to‐floodbasin transects. Results show that water and sediment exchange between the channel and floodbasin was mainly by advection. During flooding, local floodbasins behave more as efficient water pathways than water storage features, resulting in down‐valley floodbasin flows capable of limiting basinward growth of levées. Levée shape results primarily from two independent factors: (1) maximum channel water stage, which limits levée height; and (2) floodbasin hydraulics, which control width. In the Columbia River, the competence of floodbasin flows results in relatively narrow and steep levées. Natural levées grow under two general conditions of deposition as governed by flood‐stage elevation relative to levée‐crest elevation: front loading and back loading. During large floods when crests are inundated, front loading preferentially aggrades the proximal portions of levées with sediment directly from the channel, thus increasing levée slope. During average or below‐average floods when many levée crests are not overtopped, back loading preferentially aggrades the distal levée areas and floodbasin floor, reducing levée slope. In the study area, a balance between front and back loading sustains these narrow and steep levée shapes for long periods, reflecting an equilibrium between hydraulic regime, floodplain morphology and deposition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".