Debris-Flow Channel Headwater Dynamics: Examining Channel Recharge Cycles With Terrestrial Laser Scanning
Bibliographic record
Abstract
Debris-flows present a natural hazard to the safe operation of linear infrastructure in mountainous environments. The most significant contributor to debris-flow occurrence is a supply of readily erodible material, often created by rockfalls and other shallow landslides. The spatial distribution and total volume of storage are also critical factors, controlling the initiation location, predominant flow type, and termination location of debris-flow surges. Therefore, there is a need to be able to systematically incorporate debris recharge processes and timeframes into the monitoring and characterization of debris-flow hazards. In this work, the authors present the results of 7 years of terrestrial laser scanning (TLS) captured at the White Canyon. The White Canyon represents an analog to large scale, steep catchments to investigate the role of sediment supply on debris-flow processes. The TLS dataset was collected at monthly to quarterly intervals, providing a basis for analysis of debris transfer processes occurring on the study slope. A rockfall database of over 72,000 events was generated from 52 change detection analyses and is linked to catchment recharge and transfer processes. The results indicate that the 17 channels analyzed in the White Canyon do not directly match the conceptual models proposed from the supply theory. The channels display a variety of behaviors when exposed to the same climate signature. The temporal data acquisition rate was found to have a significant influence on the dynamics of movement that can be interpreted from TLS change detection analysis. The work highlights the need for higher frequency monitoring and the integration of climate data into the analysis, in order to better understand these dynamic processes.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".