Seasonal dynamics of a coupled hillslope — river system in the Arctic revealed by semi-automated satellite image analysis
Bibliographic record
Abstract
Proliferation of retrogressive thaw slumps has the potential to dominate the sediment yield in arctic watersheds through an influx of hillslope-derived sediment to rivers. We develop a suite of algorithms to semi-automate measurements of thaw slump growth and river suspended sediment concentrations from satellite imagery with the intent of linking the production of sediments on a hillslope to the presence of sediment in an adjacent stream at the seasonal scale. We apply our semi-automated methods to quantify seasonal changes in scar zone area, headwall retreat, and suspended sediment concentration at a thaw slump in the Canadian Northwest Territories, which has doubled in size during the observation period. The semi-automated approaches record up to 30 cm/day of headwall retreat, strongly correlated with warm season temperature, and an approximate doubling in suspended sediment concentration downstream of the thaw slump relative to an upstream control reach. The semi-automated results of the slump growth compare well with previous observations of retrogressive thaw slumps and with manual measurements from satellite imagery. Seasonal patterns in the suspended sediment concentration and thaw slump erosion identify the signal of thaw slump sediments in the river as most prominent during the late summer, when sediment stored in the scar zone can be mobilized by precipitation. The ability of the semi-automated methods to capture the seasonal dynamics of the reach demonstrates the possibility of extending their use to other thaw slumps across the Arctic.
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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 | 0.000 | 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 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".