The influence of a rock glacier on the riverbed hydrological system
Bibliographic record
Abstract
Climate change is accelerating cryosphere degradation in mountain regions, and altering hydrological and geomorphological dynamics within deglaciating catchments. Rock glaciers, which degrade slower than glaciers, can exert a prolonged influence on water resources in alpine watersheds. This study investigates both the direct and indirect influences of a rock glacier on the Shár Shaw Tagà (Grizzly Creek) riverbed in the St. Elias Mountains (Yukon, Canada). We applied a unique multimethod approach combining hydro-physicochemical and isotopic characterization, drone-based thermal infrared (TIR) imagery, and visible time-lapse imagery. Results reveal that the rock glacier's geomorphic and thermal properties constrain the riverbed and its underlying alluvial aquifer, driving shallow groundwater resurgence. These indirect disruptions promote downstream cryo-hydrological processes by facilitating aufeis formation and modifying the physicochemical properties of surface water. In contrast, direct hydrological influence from the rock glacier's internal drainage system to downstream surface waters appears minimal. This configuration is transitional, as the constraint imposed by ground ice is expected to diminish with progressive permafrost degradation. Overall, this study identifies the critical yet transient role of rock glaciers in alpine hydrology. Beyond their internal hydrological behaviour, they shape catchment hydrology through geomorphic controls. Our findings highlight the need to account for indirect effects when evaluating hydrological dynamics in deglaciating catchments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".