Sediment residence time in alluvial storage of black marl badlands
Bibliographic record
Abstract
The aim of this study is to estimate the sediment residence time in the stream network of two small headwater catchments (Laval and Moulin) characterized by a badlands landscape entrenched into Jurassic black marls of the Southern French Prealps. The method is based on an intensive field survey of the alluvial storage along the main stream reaches from which a scaling law between the average thickness of alluvial deposits and their width was established in order to predict the volume of alluvial deposits in the entire stream network. To complete this approach, bedload sediment yield monitored over the last 30 years with topographic surveying of sediment retention basins are used. The assessment of sediment residence time is performed according to a steady-state assumption, validated by the long-term dynamic equilibrium of bedload sediment yields. The results highlighted very close values of residence time between the catchments, around 3 years, despite a one order of magnitude difference in drainage area. It is shown that the rate of increase of alluvial storage with drainage area is the same as for sediment yield. This is likely attributed to the high degree of confinement of the stream network, which prevent the formation of a floodplain or large internal alluvial fans. Implications of these results for the prediction of the effects of bioengineering works in controlling erosion are discussed.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".