Design and Installation of Zero-Tension Lysimeters in an Inclined Cover
Bibliographic record
Abstract
The infiltration component of the water budget in a soil cover layer is difficult to measure under field conditions. Often, zero-tension (or pan) lysimeters are used for that purpose. Although they are relatively cheap and easy to build, as well as easy to install, their design may be more complex than one thinks. Indeed, the design depends on the unsaturated properties of the soil in which it is installed, in particular the hydraulic conductivity function. The latter is often derived from the water retention curve and the limitations inherent in this process may lead to errors, resulting in the lysimeter being dysfunctional. The walls of a zero-tension lysimeter must be high enough to permit the development of a pressure greater than atmospheric at the base of the container, from where the infiltrated water drains. Using theoretical and numerical approaches, and considering construction constraints (in terms of layer thicknesses), this paper presents a procedure to determine the height of zero-tension lysimeters that were installed in a 300 m2 experimental cover (a double capillary barrier constituted of a layer of deinking by-products, sand and gravel) placed above a municipal solid waste facility. Numerical simulations were used to evaluate lysimeter performance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".