Measuring the Unsaturated Hydraulic Conductivity of Growing Media with a Tension Disc
Bibliographic record
Abstract
In greenhouse and nursery production, there is an increasing interest in water conservation and environmental quality. The use of closed and semi‐closed subirrigation systems to grow plants potted in organic growing media is an important step in this direction. However, the design of efficient subirrigation systems requires a detailed characterization of the unsaturated hydraulic conductivity of the organic substrates on rewetting. In many cases, organic substrates have extremely high‐saturated hydraulic conductivities and also exhibit a dual porosity. Given the lack of a suitable technique for measuring the unsaturated hydraulic conductivity of these substrates near saturation, as well as at saturation in pots (the equivalent of “field conditions” in nursery and greenhouse production), a new in situ procedure has been developed. It is based on an analytical solution to steady state upward flow and assumes a single (SEA) or piecewise exponential (PEA) relationship between the unsaturated hydraulic conductivity and the soil water potential. The proposed method was tested for a sand and an organic growing medium. The results indicate that the unsaturated hydraulic conductivity curve may be obtained from water flux measurements using a specifically designed tension disc placed on top of the substrate, and that the estimates on rewetting are much more accurate, particularly at water contents close to saturation, than those obtained using the instantaneous profile method. Moreover, the proposed procedure is easy to carry out, requires only an inexpensive tension disc and is based on a sound physical representation of the rewetting process. Results indicated that the PEA is appropriate for most substrates and that the SEA can be considered as a special case of the PEA if only one exponential “piece” is required for the entire range (e.g., the sand).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".