Measuring Soil Hydraulic Properties Using a Cased Borehole Permeameter: Steady Flow Analyses
Bibliographic record
Abstract
New, constant‐head permeameter analyses for steady flow in cased boreholes were developed for in situ measurement of field‐saturated hydraulic conductivity ( K fs ) and matric flux potential (ϕ m ) in the vadose zone. The K fs and ϕ m parameters can be determined using calculations based on multiple ponded heads, dual heads, or a single head. The accuracy of the analyses was assessed using HYDRUS‐2D simulations of steady borehole discharge ( Q t ) vs. ponded head ( H ) for specified K fs , ϕ m , soil capillarity (α* = K fs /ϕ m ), and length ( L ) and radius ( a ) of the borehole screen. The multiple‐head and dual‐head calculations provided accurate K fs determinations (≤26% error) for the full range of tested capillarity (0.1 ≤ α* ≤ 14.45 m −1 ), screen radius ( a = 3–7.5 cm), screen length ( L = 0–45 cm), and head ( H = 3–200 cm). The multiple‐head and dual‐head calculations of ϕ m were similarly accurate (≤25% error) for high‐capillarity soils (α* ≤ 1 m −1 ), and for L / a ≤ 1 in moderate‐ to negligible‐capillarity soils (α* ≥ 9 m −1 ). The ϕ m calculations were not accurate, however, in moderate‐ to negligible‐capillarity soils with L / a > 1. The single‐head calculation with α* estimated using soil texture and structure categories was accurate only for K fs determination (≤23% error) in soils with moderate to negligible capillarity. For ϕ m determination, and for K fs determination in high‐capillarity soils, the single‐head calculation requires accurately known α* values. The analyses appear promising for K fs and ϕ m determination in the vadose zone, and further development and testing are ongoing.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".