Water Track Formation and Development on Hillslopes in the Canadian High Arctic
Bibliographic record
Abstract
Hillslopes in the Canadian High Arctic can express curious quasi-linear features commonly referred to as water tracks. Though they physically resemble rills, they are not typically characterized by sustained surface flows following rainfall or snowmelt; hence, no obvious evidence of active particle transport is observed. This motivates several questions which at present are little explored. First, how does hillslope geomorphology (e.g. slope, soil moisture properties, etc.) affect the cross- and down-slope topographic patterns that we see? Second, what mechanism(s) causes water track patterns to develop, and what are the roles of freeze-thaw, granular, and fluid-flow-driven processes? Answers to these questions have broad implications for periglacial geomorphology because water tracks (and water-track-like features) are thought to play an important role in the development of channel networks and are particularly important in water-limited polar desert environments. Furthermore, these features are believed to exist as a transition between the hillslope and channel regimes, but deepening of the active layer in response to climate change will increase the potential for further incision and expansion of water tracks.Our goal is to begin to address these knowledge gaps through a multi-disciplinary approach combining field and modelling techniques. We use field data acquired from a hillslope located on Devon Island, Nunavut with water-track-like features to assess the connections between hillslope geomorphology and water track shape. We created a digital elevation model (DEM) of the field site from topographic LiDAR data that we collected using both drone surveying and the Akhka-R4DW backpack LiDAR methods. Spectral analysis indicates that there is no dominant feature wavelength, but rather a finite range of wavelengths between 1 and 2 meters characterizes the highest spectral powers, on average. We find no correlation between hillslope gradient (proxy for hillslope location) and feature wavelength distribution. Last, using the hillslope DEM, we map the water track network to determine the dominant length scales, and we then explore whether these length scales correlate to topographic metrics of the hillslope.The diversity of water track wavelength and length scales, along with the relationships and lack of relationships identified between the features and the hillslope suggests the study site is in an early stage of response to the ongoing rapid change of High Arctic climate. Therefore, we anticipate continued development into the foreseeable future, with implications for expansion of the existing local drainage network as the warming climate deepens the active layer through which hydrologic processes occur.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".