Suspended sediment dynamics at high and low storm flows in two small watersheds
Bibliographic record
Abstract
Abstract A record spanning almost 20 years of suspended sediment and discharge measurements on two reaches of an agricultural watershed is used to assess the influence of in‐channel sediment supplies and bed composition on suspended sediment concentrations (SSC). We analyse discharge‐SSC relationships from two small streams of similar hydrology, climate and land use but widely different bed compositions (one dominated by sand, the other by gravel). Given that sand‐dominated systems have more fine sediment available for transport, we use bed composition and the relative proportion of surface sand and gravel to be representative of in‐channel sediment supply. Both high flow events and lower flows associated with onset and late recessional storm flow (‘low flows’) are analysed in order to distinguish external from in‐channel sources of sediment and to assess the relationship between low flows and sediment supply. We find that SSC during low flows is affected by changes to sediment supply, not just discharge capacity, indicated by the variation in the discharge‐SSC relationship both within and between low flows. Results also demonstrate that suspended sediment and discharge dynamics differ between reaches; high bed sand fractions provide a steady supply of sediment that is quickly replenished, resulting in more frequent sediment‐mobilizing low flow and relatively constant SSC between floods. In contrast, SSC of a gravel‐dominated reach vary widely between events, with high SSC generally associated with only one or two high‐flow events. Results lend support to the idea that fine sediment is both more available and more easily transported from sand‐dominated streambeds, especially during low flows, providing evidence that bed composition and in‐channel sediment supplies may play important roles in the mobilization and transport of fine sediment. In addition, the analysis of low‐flow conditions, an approach unique to this study, provides insight into alternative and potentially significant factors that control fine sediment dynamics. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.001 | 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".