Spatial and Temporal Influences on Hydraulic Properties in Macroporous Tile-Drained Soil
Bibliographic record
Abstract
This study investigated post-harvest temporal changes in macroporosity and hydraulic properties, relative to subsurface drain position, at three different locations within a single field. Tension and double-ring infiltrometer tests were conducted on the field surface at distances between 0 and 4 m from drains to determine hydraulic conductivity and a soil structural parameter as a function of pressure head [K(ψ) and α′(ψ), respectively], and field-saturated hydraulic conductivity (Kfs). At two of the locations, duplicate sets of infiltration tests were conducted on significantly drier soils about 1 mo after the initial tests. Macroporosity values at each location were determined visually and with capillary theory (i.e., hydraulically effective macroporosity, ), and results from the two methods were compared. At the two field locations with relatively low B horizon permeability, surface soil Kfs was greatest above the drains; however, at the location with the greatest B horizon permeability, surface soil Kfs increased away from the drain. The Kfs was also significantly (P < 0.1) greater under drier soil conditions. Although α′(ψ) and K(ψ) relationships were not influenced by drain position, they did exhibit temporal variability. For ψ < −2 cm, both α′(ψ) and K(ψ) were less in dry soil, whereas for ψ > −1 cm, both α′(ψ) and K(ψ) tended to be greater in dry soil. The was not influenced by drain position but tended to be greater in wetter soil, although attributable to pores with equivalent diameter >0.3 cm tended to be greater in dry soil. The was approximately 100 times less than visible macroporosity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".