Modeling a two‐layer flow system at the subarctic, subalpine tree line during snowmelt
Bibliographic record
Abstract
In the subarctic it is common to encounter a two‐layer flow system consisting of a porous organic cover overlying frozen or unfrozen mineral soils with much lower hydraulic conductivities. The “simple lumped reservoir parametric,” or “semidistributed land‐use‐based runoff processes” (SLURP), model was adapted to simulate runoff generated by such a flow system from an upland shrub land to an open woodland downslope. A subalpine site in Wolf Creek, Yukon, Canada, was subdivided into two aggregated simulation areas (ASA), each being a unit characterized by a set of parameters. The model computes the vertical water balance and flow generation from several storages, and then routes the water out of the ASA. When applied to the 1999 snowmelt season, the model simulated the very low lateral flow and a large increase in storage in the mineral soil, as was observed in the field. The model was used to assess the sensitivity of the two‐layer flow system under a range of temperature, snow cover, and frost conditions. Results show that within the range of possible climatic conditions, the hydrologic system is unlikely to yield significant runoff across the subalpine tree line, but if ground ice is abundant in the soil pores, percolation will be limited and fast flow from the surface layer is enhanced.
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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 | 0.001 | 0.000 |
| 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".