Modeling Reactive Solute Transport in Permafrost‐Affected Groundwater Systems
Bibliographic record
Abstract
Abstract Understanding the interactions between ground freeze‐thaw, groundwater flow, and solute transport is imperative for evaluating the fate of contaminants in permafrost regions. However, predicting solute migration in permafrost‐affected groundwater systems is challenging due to the inherent interactions and coupling between subsurface mass and energy transport processes. To this end, we developed a numerical model that considers coupled groundwater flow, subsurface heat transfer, and solute transport, including water‐ice phase change, solute‐dependent porewater freezing, and temperature‐dependent solute reaction rates. As an illustrative example, we present simulations to investigate the potential for contamination from a municipal wastewater lagoon in the Canadian sub‐arctic. Two‐dimensional groundwater models assuming varying permafrost conditions were developed to evaluate possible contaminant migration scenarios associated with groundwater flow from the lagoon to a river, including the transport of conservative, degradable, and sorbing solutes. Model results reveal important transport mechanisms controlling the behavior of aqueous contaminants in permafrost landscapes as well as the hydrogeologic factors affecting reactive transport in cold regions. Seasonal freeze‐thaw episodically restricts connectivity of transport pathways, which attenuates both transport and reaction rates. However, elevated solute concentrations can depress the freezing temperature of porewater and produce thaw‐induced solute transport. Both thermally driven and solute‐enhanced thaw can decrease ice content in permafrost, which can have significant implications for solute migration. Therefore, thermo‐hydrogeologic process controlling reactive transport in cold‐region groundwater systems must be considered when quantitatively assessing the impact of changing environmental conditions on contaminant hydrogeology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".