Quantifying groundwater exchanges in the water balance of small thermokarst ponds: implications for carbon cycling
Bibliographic record
Abstract
• Thermokarst ponds, formed by permafrost mound thaw, discharge groundwater. • Carbon transport is implicated by thermokarst pond-groundwater connections. • A new conceptual model clarifies groundwater’s role in lithalsa thermokarst ponds. Permafrost mounds, formed in discontinuous and sporadic permafrost regions, are subject to thawing due to climate warming. Thaw-induced ground subsidence creates depressions encircled by high ramparts, leading to the formation of thermokarst ponds. These water bodies, accumulating water from precipitation and thawed permafrost, play key roles in biogeochemical cycling and greenhouse gas (GHG) emissions. Traditionally viewed as hydrogeologically isolated due to permafrost impeding groundwater flow and the low hydraulic conductivity of soil underneath these ponds, these systems are expected to become more interconnected as thaw progresses. This study uses several methods to examine groundwater connections in the Tasiapik Valley, Nunavik, Québec, Canada, where differing stages of lithalsa permafrost mound degradation result in a series of varying pond conditions. Four thermokarst ponds were monitored using direct hydrological measurements, water balance, and stable water isotopic tracer approaches to quantify groundwater contributions. Findings reveal varying degrees of pond connectivity to the subsurface, with ponds in silt experiencing net groundwater loss and those in sandy substrates showing dynamic responses to groundwater fluctuations. These varied interactions will have implications for how surface and subsurface carbon cycling occurs. The results of this study underscore the complex interactions between thermokarst ponds and groundwater systems and the importance of these dynamics in understanding hydrological and carbon cycling in permafrost regions.
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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 | 0.001 | 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".