A Simplified Falling‐Head Technique for Rapid Determination of Field‐Saturated Hydraulic Conductivity
Bibliographic record
Abstract
Simplified measurements of the field‐saturated hydraulic conductivity, K fs , require short duration experiments, small water volumes, and easily transportable equipment. A simplified falling‐head (SFH) technique for the rapid determination of K fs has been developed and tested. The technique consists in applying a small volume of water on a soil surface, confined by a ring inserted a short distance into the soil, and then measuring the time from the application of water to the instant at which the surface area is no longer covered by water. A measurement of the initial and field‐saturated soil water contents, and an estimate of the α* parameter of the Gardner's exponential model are then used to calculate K fs using a simple solution that includes gravity. The K fs of both repacked and undisturbed soil cores was determined in the laboratory by the SFH and the early time constant‐head (ECH) techniques. The SFH and (constant‐head) pressure infiltrometer (PI) techniques were then compared in the field. The maximum discrepancy between the mean K fs results obtained within an experiment was of a factor of approximately two. This difference is negligible in most practical applications and it was concluded that the SFH technique compared favorably with the ECH technique in the laboratory and to the PI technique in the field. The SFH technique appears promising for determining K fs in a relatively short period of time without the need for extensive instrumentation or analytical methodology, and therefore it appears suitable for detailed field measurements over large areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".