Evaluation of Beerkan Infiltration Method in Estimation of Saturated Hydraulic Conductivity of Soil
Bibliographic record
Abstract
Determination of the field-saturated hydraulic conductivity can result in very high variability. So, analysis and simulation of hydrological processes such as runoff from rain requires a lot of data of field-saturated hydraulic conductivity even on a small scale. To identify this variability as well as its source, eight widely used measurement methods were compared:(Double-ring, Single-ring, Guelph permeameter, Tension infiltrometer, BESTslope, BESTintercept, Wu1 and Wu2) to evaluate the BEST method. In the single-ring method was used a metal cylinder with a radius of 10 cm. It was found that the maximum and minimum estimates of hydraulic conductivity are in Wu1 method (0.104 cm/min) and tension infiltrometer (0.0063 cm/min), respectively. The methods of double-ring, single-ring and Tension infiltrometer were not statistically significant differences at 5%. BEST methods were not statistically significant differences but BESTintercept method 28% more than BESTslope method. According to the experiment data, Kfs was estimated using the BESTintercept method is closer to reality than BESTslope method. In generally, the BEST methods can be a good alternative to estimate field-saturated hydraulic conductivity and prevent from a lot of field measurements.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".