Insights into the evolution of mass flow dynamics from the seismic analysis of the 18 March 2007 Mt. Ruapehu, New Zealand lake-breakout lahar
Bibliographic record
Abstract
At 23:18 UTC on 18 March 2007 Mt. Ruapehu produced the biggest lahar in New Zealand in over 100 years when a tephra dam holding crater lake water back collapsed causing 1.3x106 m3 of water to flow out and rush down the Whangaehu channel. The outburst of water transformed into a hyperconcentrated streamflow, which traveled more then 200 km from source finally flowing into the Tasman Sea on the West coast of New Zealand. Here, we describe the seismic signature of the lake-breakout lahar over the course of 83 km along the Whangaehu river system using three 3-component broadband seismometers installed <10 m from the channel at distances of 7.4, 28, and 83 km from the crater lake source. Examination of 3-component seismic amplitudes, peak spectral frequency, and directionality combined with video imagery and sediment concentration data depicts the evolution of an ever transforming lahar from a highly turbulent out-burst flood (high peak frequency throughout), to a fully bulked up multi-phase hyperconcentrated flow (varying frequency patterns depending on the lahar phase) to a slurry flow (bedload dominant). Estimated directionality ratios show the elongation of the lahar with distance from source and extraordinary promise for mass flow monitoring and detection systems where streamflow is already present. Ultimately, the 3-component broadband seismic data for the 18 March 2007 lahar at Mt. Ruapehu may lead to more accurate and advanced real-time waring systems for mass flows through the use of seismic frequency and directionality analysis worldwide.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".