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Record W4408435664 · doi:10.5194/egusphere-egu25-7345

The role of water tracks in permafrost hillslope hydrology

2025· preprint· en· W4408435664 on OpenAlexaffabout
Sarah G. Evans, Sarah E. Godsey, Joanmarie Del Vecchio, Rachel J. Harris, Rebecca J. Frei, Brandon Yokeley, Aaron A. Mohammed, Clara Chew, Kaden Cusack, Emma S. Ferm, Key Hatch, Gabrielle Matejowsky, Raven Polk, Cansu Culha

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPermafrostHydrology (agriculture)Environmental scienceGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Hillslope hydrology in upland permafrost regions (e.g., Alaska, High Canadian Arctic, Russia, Antarctica) is often dominated by water tracks, zones of enhanced soil moisture in unchannelized depressions that concentrate water flow downslope. Continued warming of permafrost regions may alter hydrologic cycling, leading to increased frequency of extreme hydrologic events like drought and flooding and modification to biogeochemical cycles. It is therefore imperative to parametrize the role of water tracks in the hydrology of the permafrost environments. In this study, we synthesize uniting and distinguishing hydrologic characteristics of water tracks across permafrost regions and then examine water track seasonality, occurrence, and contribution to the permafrost hydrologic cycle using field observation, remote sensing, and numerical modeling for permafrost hillslopes on the North Slope of Alaska, USA. Results suggest that water tracks occur across climate and hydrologically disparate permafrost landscapes but have ubiquitous surface wetness, vegetation, and snow duration patterns that can be identified remotely using 3-m resolution PlanetScope imagery. Detailed field investigation from 2022-2024 of three study sites with ~20 water tracks and ~15 gullies suggests that water tracks are hydrologically distinct from larger, variably channelized hillslope features and require more precipitation and time to initiate discharge following rainfall events. Across these study sites, concentration-discharge relationships reveal that water tracks can exhibit drastically different dynamics of particulate and dissolved organic carbon export based on landscape attributes. Young water fraction analysis found that in 2023, 24–78% of runoff from the study sites was young water less than 35 days old during the observed summer thaw season, and model-estimated young water fraction increased by two-fold when factoring in the fall shoulder season. Geophysical investigations indicate the presence of buried ice wedges on the margins of studied water tracks, supporting the idea that water tracks may form from the coalesced drainage of patterned ground. Over time, these drainage patterns likely evolve and widen into present-day water tracks that act as flow conduits and discharge liquid water into the fall shoulder season after the adjacent hillslope has frozen. Our ongoing analysis explores how water track flow seasonality may influence observed ground collapse and mediate or enhance the permafrost-carbon feedback.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.234
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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