Measurement of Transient Soil Water Flux Across a Soil Horizon Interface
Bibliographic record
Abstract
Understanding the physics of water flow and transport in layered soils requires experimental observations of the magnitude and variability of these processes as they occur in the field. In this study, a time domain reflectometry (TDR) method to measure the spatial pattern of transient, local soil water flux above and below a soil horizon interface under quasi‐steady surface water application was developed and implemented in laboratory and field experiments. The method uses vertical TDR probes spanning two or more soil horizons or layers. Time series of soil water storage measured by the TDR probes are used to quantify transient, local soil water flux during infiltration under quasi‐steady surface water application. Results from the laboratory and field experiments showed that transient soil water flux estimates with the presented methodology were, on average, 106% of the applied water flux (i.e., mass recovery = 106%). Furthermore, in field experiments, excellent agreement between two independent measurements of local soil water flux through the A horizon showed that this methodology is robust and sensitive to spatial variations in soil water flux within soil horizons and changes in local soil water flux as the wetting front crosses the interface between two horizons. In the field experiments, transient local soil water flux through the A and B horizons (measured along a 6.75‐m‐long transect) were positively correlated to each other, but the strength of the correlation decreased with increasing surface water application rates. The flux‐dependent covariance between the measured patterns of transient A and B horizon soil water flux indicates that the soil horizon interface is a hydrologically significant component of the soil profile. In‐depth spatial analysis of the measured soil water flux patterns is the subject of a future study.
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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".