Using the borehole permeameter to estimate saturated hydraulic conductivity for glacially over-consolidated soils
Bibliographic record
Abstract
Abstract The borehole permeameter (BP) method was developed in the 1950s by the United States Bureau of Reclamation to estimate saturated soil hydraulic conductivity (KS) in shallow boreholes completed above the water table. The approach has been improved over the years, and now accounts for flow due to pressure, gravity and soil capillarity. However, the BP method is calibrated only for normally consolidated soils and ponding depth (H) versus borehole radius (r) ratios (H/r) ≤ 22. The primary objective of this study was to recalibrate the BP method for use in glacially over-consolidated soils with H/r ranging from 0.05 to 200. Recalibration consisted of using numerically simulated steady BP flow for five representative glacially over-consolidated soils to update the BP shape function fitting parameters (Z1, Z2, Z3) for nine specified KS values and 15 test pit and borehole configurations. Four sets of fitting parameters were determined, which apply for H/r ≤ 20, H/r ≥ 20, soil with <12% silt content, and soil with >12% silt content. Relative to specified KS, the updated shape function parameters yielded BP estimates of KS with a maximum error of 13% and an average error of 3%, whereas the original shape function parameters (developed for normally consolidated soils and H/r ≤ 22) produced a maximum KS error of 94% and an average error of 23%. The numerical simulations were also used to develop criteria for estimating time required to achieve steady BP flow, and for correcting BP estimates of KS where steady flow was not achieved.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".