Secondary Geomorphic Processes and their Influence on Alluvial Fan Morphology, Channel Behaviour and Flood Hazards
Bibliographic record
Abstract
Alluvial fans form through primary and secondary geomorphic processes. Primary processes act to transport sediment from the watershed to the fan while secondary processes re-mobilize and rework the fan surface. While primary processes on alluvial fans are well studied, secondary processes and their relationship to fan flood hazards have received little attention. The experiments described herein isolate the role of secondary processes in determining alluvial fan behaviour and morphology. We conducted four experiments, in which alluvial fans were allowed to evolve under alternating primary and secondary process periods, with different durations of secondary processes. While the secondary process duration changed, the total primary process duration remained constant keeping the total volume of sediment constant for each experimental fan. Experiments with longer durations of secondary processes generated fans with larger areas and gentler gradients. In addition, longer secondary process durations led to increased flow channelization and centralization between flood periods. These morphologic changes resulted in fewer avulsions, that occurred later during primary process periods. These results indicate that changes to the relative duration of primary and secondary process periods caused by climate change can affect fan morphology and flow behaviour.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".