How do debris flood events affect alluvial fans and the distribution of geohazards? An experimental study
Bibliographic record
Abstract
Climate change has increased the frequency and intensity of wildfires in British Columbia, causing debris floods (i.e. floods with relatively high sediment concentrations) in environments that do not typically experience them. A physical model was used to explore the impacts of debris floods on the morphology and geohazard distribution of an alluvial fan built by floods with lower sediment concentrations. The model was not scaled to a specific real-world prototype but represents a generic class of streams that have a gravel/cobble fan with a gradient of about 6%. Fan topography was surveyed every 30 min using digital photogrammetry, and surface changes were documented via time-lapse video. High sediment concentration debris floods initially infilled the pre-existing channel and aggraded the upper fan, increasing the average fan slope, particularly at the apex. A return to floods with low sediment concentrations following the debris floods caused the channel to incise in the upper fan, disconnecting the channel from the fan surface at the apex, and returning the channel to its pre-debris flood gradient. Repeated sequences of debris floods and floods produced cycles of aggradation and incision that increasingly confined the stream at the fan apex. The result of this increased confinement was to restrict bank erosion and channel migration to the middle part of the fan, leaving the flanks relatively inactive. The experiments demonstrate how the dynamics of sediment deposition and erosion at the fan apex during one debris flood can constrain subsequent channel activity and change the proportion of the fan that is impacted by a subsequent debris flood.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".