Sediment Dynamics and Bed Stability in Step‐Pool Streams: Insights From 18 Years of Field Observations
Bibliographic record
Abstract
Abstract Step‐pools are a common morphology in gravel‐bed streams with gradients between 3% and 30%, where coarse sediment and wood are present. Recent experimental work has offered insight on the formation of step‐pools, flow resistance, and interactions between sediment transport and channel morphology. However, field observations are sparse and often limited by short observation periods. Using an extensive 18‐year data set, we examine controls on sediment mobility, step stability, and sediment storage in East Creek, a step‐pool reach in British Columbia. Event bedload yield correlated with peak flow and ranged over two orders of magnitude. For most events, bedload grain‐size was finer than the grain size distribution of the sediment found in pools. Fractional sediment mobility was independent of the flow magnitude and controlled by sediment supply. The large stones that comprise the steps were generally mobile during large events (>10‐year recurrence interval), although the largest ones were not. Despite the movement of large stones, the skeleton of the steps remained in place even during an event with a near 125‐year recurrence interval. Temporal trends in sediment storage in pools show that most events cause negligible changes in sediment storage. Our field observations indicate that the step‐pool morphology of East Creek is stable, as the morphology and shape of the steps persisted under a wide range of flows. The overall stability of the reach is confirmed by observed trends in bedload yield and particle mobility.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".