Measurement of Steady‐State Soil Water Flux across a Soil Horizon Interface
Bibliographic record
Abstract
Soil horizon interfaces have been shown to be focal points for localized, three‐dimensional redistribution of water and solutes in field soils. Therefore, understanding of the physics of water flow and transport in layered soils requires experimental observations of the magnitude and variability of local soil water flux under a variety of well‐defined boundary conditions. We developed a time domain reflectometry (TDR) method to measure the spatial pattern of steady‐state, local soil water flux density above and below a soil horizon interface under quasi‐steady surface water application and implemented it in laboratory and field experiments. Time series of TDR‐measured bulk soil electrical conductivity and TDR‐measured soil volumetric water content at each location are used to quantify the solute travel time under steady‐state flow conditions, which is then used to quantify steady‐state, local soil water flux density. Results from laboratory and field experiments showed that the proposed methodology yielded local soil water flux density estimates that were, on average, 104% of the applied surface water flux density (i.e., mass recovery = 104%), which is consistent with transient, local soil water flux density estimates from a previous study. For the field experiments, steady‐state, local soil water flux density estimates above and below an A/B horizon interface (measured across the length of a 6.75‐m transect) were negatively correlated to each other. The strength of the negative correlation, however, decreased with increasing surface water application rate, suggesting that the hydrologic response of the soil horizon interface is flux‐dependent. This flux‐dependent correlation between A and B horizon steady‐state soil water flux density is probably attributable to the spatial covariance between A and B horizon soil hydraulic properties.
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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 | 0.000 | 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".