Groundwater flow and storage within an alpine meadow-talus complex
Bibliographic record
Abstract
Abstract. The different types of geological deposits and rock formations found in alpine watersheds play key roles in regulating the rate and timing of runoff to mountain rivers. Talus and alpine meadows are dominant features in these areas, but scant data exist for their capacity to store and transmit groundwater. To gain further understanding of these processes, we have undertaken a combined geophysical and hydrological study of a small (2100 m2) alpine meadow and surrounding talus within the Lake O'Hara watershed in the Canadian Rockies. Several intersecting ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) profiles and a seismic refraction profile were acquired to map the thickness of the talus and to image the topography of the bedrock basin that underlies the meadow. From analysis of the GPR and seismic profiles, we estimate that the talus deposits are relatively thin (<6 m). Combined interpretations from the GPR and ERT data show that the fine-grained sediment comprising the meadow basin has a total volume of ca. 3300 m3 and has a maximum thickness of ca. 4 m. Annual snow surveys and stream gauging reveal that the total input volume of snowmelt and rainfall to the meadow basin is several times larger than its groundwater storage capacity, giving rise to low total-dissolved species concentrations (14–21 mg/L) within the meadow groundwater. Observations from four piezometers established on the meadow show that the water table fluctuates rapidly in response to spring snowmelt and precipitation events but otherwise maintains a relatively stable depth of 0.3–0.4 m below the meadow surface during summer months. A slug test performed on one of the piezometers indicated that the saturated hydraulic conductivity of the shallow meadow sediments is 2.5×10−7 m/s. We suggest that a bedrock saddle imaged underneath the southern end of the meadow forms a natural constriction to subsurface flow out of the basin and helps to maintain the stable water-table depth.
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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".