Reach‐scale contributions of road‐surface sediment to the Honna River, Haida Gwaii, BC
Bibliographic record
Abstract
Abstract Gravel road surfaces can be a major source of fine sediment to streams, yet their contribution to channel reach sediment balances remains poorly documented. To quantify the input of road surface material and to compare this input with natural sediment sources at the reach scale, suspended sediment dynamics was examined and a 16‐month sediment balance was developed for a ~35 channel‐width (approx. 425 m) reach of the Honna River, a medium‐size, road‐affected stream located in coastal British Columbia. Of the 105 ± 33 t of suspended material passing through the reach, 18 ± 6% was attributed to the road surface. The high availability of sediment on the road surface appears to limit hysteresis in road run‐off. During rainstorms that increase streamflow, road surface material composed 0.5–15% of sediment inputs during relatively dry conditions from April to the end of September and 5–70% through wetter conditions from October to the end of March, but our data do not show evidence of major sediment accumulation on the riverbed in the reach. A comparison of modelled sediment production on the road surface with observed yields from drainage channels suggests that (1) during low intensity rainfall, ditches and drainage channels may trap sediment from road run‐off, which is subsequently released during events of greater intensity, and/or (2) production models do not effectively describe processes, such as deposition or erosion of sediment in ditches, which control sediment transport and delivery. Our findings further emphasize the risk of unpaved roads in polluting river systems and highlight the continued need for careful road design and location away from sensitive aquatic environments. Copyright © 2016 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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; both teacher heads agree on what is shown here.
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".