Hydro-sedimentological drivers of fine sediment ingress in a gravel-bed river
Bibliographic record
Abstract
• In-situ investigations of fine sediment ingress in gravel-bed rivers remain limited. • Ingress rates and directional mechanisms of accumulation were investigated across a range of flow conditions. • Three designs of sediment traps (>250 traps in total) were used. • Linear mixed effects models showed that the ingress of cohesive particles were well explained by mean hydro-sedimentological parameters. • Observed results have important implications on the legacy effects that can originate from ingressed particles. Most studies investigating fine sediment ingress in gravel-bed rivers have been conducted at the laboratory scale, and even fewer have explored the ingress processes of flocculated particles. Here, an extensive in-situ sampling programme was undertaken to investigate hydro-sedimentological drivers of interstitial fine sediment accumulation and to evaluate fine sediment ingress directional mechanisms in a gravel-bed river located on the eastern slopes of the Rocky Mountains in southern Alberta. Three sediment trap designs were installed across seven deployment cycles at four sites along the river. Instantaneous discharge, suspended solids concentration, and particle size distributions (of suspended and ingressed particles) were measured, while relevant hydraulic parameters were modelled with a flow model (MOBED). Distinct patterns of ingress dynamics between non-cohesive and cohesive fractions of fine sediment were observed. While the assessed hydro-sedimentological parameters did not statistically explain the ingress rates of non-cohesive 0.5 – 2 mm particles, the opposite was observed for < 0.5 mm particles, which were mostly transported in flocculated form. For flocculated sediment, horizontal ingress accounted for ∼ 60 % of interstitial accumulation. Directional ingress mechanisms, however, were dependent on flow conditions for both particle size fractions, with vertical and horizontal accumulations becoming more important during higher and lower energy flows, respectively. Our observations demonstrate the importance of ingress for the interstitial accumulation of fine sediment, even during events with flow above the critical threshold conditions for fine sediment gravitational deposition. Despite the comparable ingress rates to other studies, no interstitial clogging was observed in this study, demonstrating the channel potential storage capacity, which has implications for legacy impacts from landscape disturbances in the Crowsnest River catchment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".