Application of Harmonic Analysis of Water Levels to Determine Vertical Hydraulic Conductivities in Clay‐Rich Aquitards
Bibliographic record
Abstract
A harmonic analysis method was used to determine vertical hydraulic conductivities (Kv) in geologic media between vertically separated piezometers using water level measurements. In this method, each water level time series was filtered and then decomposed using harmonic analysis into a sum of trigonometric components. The phase and amplitude of each harmonic function were calculated. These data were used to estimate Kv values between vertically separated data sets assuming one-dimensional transient flow. The method was applied to water level data collected from nested piezometers at two thick clay-rich till aquitards in Saskatchewan, Canada. At one site, routine water levels were measured in 12 piezometers (installed between 1 and 29 m below ground surface) since installation (1995). At the other site, water levels were measured in seven piezometers (installed between 4 and 53 m below ground surface) since installation (1998-1999). The Kv calculated using harmonic analysis decreased with depth below the water table at both sites, approaching matrix estimates of hydraulic conductivity between 10 and 11 m and between 21 and 43 m below ground surface. These depths reflected the depth of extensive vertical fracturing at the sites and showed that the depth of fracturing may be site specific.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".