A Short Review of the Methods for Determining Saturated Hydraulic Conductivity and a Comparison of Large and Small-Scale In-Situ Methods
Bibliographic record
Abstract
Saturated hydraulic conductivity (KS) can be determined with correlation or hydraulic methods. Hydraulic methods can be classified as laboratory and large-scale or small-scale in-situ methods. Auger-hole, inversed auger-hole and Guelph Permeameter are the most common small-scale in-situ methods. The KS determined by small-scale methods has high spatial variability, has different values in the horizontal and vertical directions, and varies in different depths. Large scale methods enter an extensive soil body into the measurement process to eliminate variation. This paper aimed to evaluate the conventional field methods of measuring KS using the drain outflow as the reference method and investigate the effect of initial soil moisture on KS’s measuring accuracy by the inversed auger-hole method. Experiments were conducted in two 10-hectare research fields in south Khuzestan. KS was measured by the inversed auger-hole method in barren, dry soil before constructing the irrigation and drainage network. After the construction, the KS was measured by drainage water outflow as a large-scale method, as well as by auger-hole and inversed auger-hole methods in moist soil after several irrigations. The KS measured by conventional small-scale in-situ methods in Fields One and Two were respectively 42.5% and 62.9% lower than the drainage water outflow method. Considering the drain outflow as the reference method, there is no significant advantage between the auger-hole and inverse auger-hole methods. As in Field One, the values obtained from the auger-hole method were closer to the reference method, and in Field Two, the values obtained from the inversed auger-hole method were closer.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".