A threshold in submarine channel curvature explains erosion rate and type
Bibliographic record
Abstract
Submarine channels are conduits for sediment-laden flows called turbidity currents, which play a globally significant role in the offshore transport of sediment and organic carbon and pose a hazard to critical seafloor infrastructure. Time-lapse repeat surveys of active submarine channels have recently shown that upstream-migrating knickpoints can dominate channel evolution. This finding contrasts with many studies of ancient outcrops and subsurface geophysical data that inferred channel bends migrate laterally, as occurs in meandering rivers. Here, we aim to test these two contrasting views by analysing two high-resolution repeat seafloor surveys acquired 13 years apart across the entirety of an active submarine channel in Knight Inlet, British Columbia. We find that two main mechanisms control channel evolution, with the normalised channel radius of curvature (specifically, R* - channel radius of curvature normalised to channel width) explaining which of these mechanisms dominate. Pronounced outer bend migration only occurs at tight bends ( R* <1.5). In contrast, at broader bends and straighter sections ( R* >1.5), erosion is focused within the channel axis, where upstream-migrating knickpoints dominate. High centrifugal accelerations at tight bends promote super-elevation of flows on the outer channel flank, thus, enhancing outer bend erosion. At R* >1.5, flow is focused within the channel axis, promoting knickpoints that migrate upstream at an order of magnitude faster than the rate of outer bend erosion at tight bends. Despite the dominance of knickpoints in eroding the channel axis, their stratigraphic preservation is very low. In contrast, the lateral migration of channel bends results in much higher preservation via lateral accretion of deposits on the inner bend. We conclude that multiple mechanisms can control evolution at different channel reaches and that the role of knickpoints has been underestimated from past studies that focused on deposits due to their low preservation potential.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".