Water and Sediment Supply Requirements for Post-Wildfire Debris Flows in the Western United States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This work explores two hypotheses related to runoff-related post-wildfire debris flows: 1) their initiation is limited by rainstorm intensity rather than cumulative rainfall depths and 2) they are not sediment supply limited. The first hypothesis suggests that it is common to generate more than enough rainfall to account for the volume of water in the debris flow, but to actually produce a debris flow, the water must be delivered with sufficient intensity. This is demonstrated by data from 44 debris flows from eight burned areas in California, Colorado, and Utah. Assuming a debris flow comprises 30 percent water and 70 percent solids, these events were generated during rainstorms that produced an average of 17 times as much water as necessary to develop a debris flow. Even accounting for infiltration, the rainstorms still generated an overabundance of water. Intensity dependence is also shown by numerous cases in which the exact timing of debris flows can be pinpointed and is contemporaneous with high-intensity bursts of rainfall. The hypothesis is also supported by rainfall intensity-duration thresholds where high-volume storms without high-intensity bursts do not generate debris flows. The second hypothesis of sediment-supply independence for the initiation of debris flows is supported by a significant increase in flow volume occurring directly after wildfire, compared to flows in unburned terrain. Also, repeated flows within short time intervals are only possible with an abundance of channel sediment, dry ravel, and bank failure material that can be mobilized. Field observations confirm these sediment sources, even directly after a debris-flow.
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.
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 | 0.000 |
| 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