Tracking the sediment plume from the 7th February 2021 Chamoli (Uttarakhand, India) hazard cascade
Bibliographic record
Abstract
The 7th February Chamoli hazard cascade originated from a 25 million m³ rock/ice avalanche slope failure that transformed into a destructive, far travelled debris flow / debris flood. There has a been necessarily a significant science focus on the proximal and immediate part of the hazard cascade. Here we report on the larger spatial and temporal scale: the sediment plume that progressed over the following days and weeks along the Ganga (Ganges) River. At the time of submission this was still recognisable over 900 km from the landslide site and had passed through hydro and nuclear power schemes. Beyond the initial plume, which has implications for rapid sedimentation in hydropower schemes and water / aquatic habitat quality, the subsequent (or not) mobilisation of event sediments over future years is a possible medium term chronic-threat to some hydropower projects. We show spectral ‘recipes’ and semi-automated methods for tracking the mass movement sediment plume and quantifying celerity using Sentinel 2 imagery, infilled using high-temporal repeat optical imagery from Planet Labs. data. The plume averaged ~60 km/day and, as expected has begun to slow as the river gradient decreases, as well as becoming less distinctive as some sediment is deposited, and as other sediment-rich water joins the Ganga. The tracking of sediment plumes from these hazard cascades can be extended over inventories of similar events using both Sentinel 2 and Landsat archives. Such approaches allow us to provide insight into the possibilities of automated detection of hazard cascade sediment plumes to identify previously unknown events from remote source regions, as plumes have a far larger spatial-temporal footprint than the initial event.
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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 | 0.000 | 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) | 0.001 | 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".