Assessing Erosion Hazards due to Floods on Fans: Physical Modeling and Application to Engineering Challenges
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Bibliographic record
Abstract
Experiments using a 1∶30 scale physical model show that channel degradation on alluvial fans is dominated by lateral channel migration rather than vertical incision. The results are used to estimate the exposure probability during single flood events with peak flows up to twice the formative flow, considering both the burial depth beneath the channel bed and the setback from the channel banks. For the largest flows modeled, the exposure probability fell below the detection limits for this analysis when the burial depth was greater than approximtely 3.6 times the mean flow depth, and the lateral setback distance was greater than approxinately 0.9 times the mean flow width for the formative flow. The minimum depth-of-cover criterion accounts for the worst-case occurrence of net bed degradation during a single flood event, but does not consider the vertical degradation that could occur in channels because of knickpoint development and migration, or in channels with engineered banks that prevent channel width adjustments; they also do not consider the potential effects of debris flows. These hazards are driven by different processes and require different analyses to evaluate the potential exposure risk. Because the experiments evaluated the effects of single flood events, the results do not account for shifting channel position over time, and they are intended to guide monitoring of channel behavior for existing infrastructure. The results also can be used to guide infrastructure design, but in this case the design will need to consider the cumulative effect of channel migration and avulsion over the design life span of the infrastructure.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it