Water and salt transport characteristics in a soil column in the presence of a low-permeable body
Bibliographic record
Abstract
Soil water infiltration is an important factor affecting surface runoff, soil erosion, and soil solute transmission. Increasing soil infiltration reduces runoff and erosion. The presence of low-permeable body in soil can enhance soil infiltration capacity. However, different depths of low-permeable body have unknown effects on water infiltration and salt transfer. In this work, we evaluated the effects of low-permeable body with varied depths (control (CK), 0, 0.5, 1, and 1.5 cm) on silty loam soil water and salt movement using 15 soil columns (23 cm internal diameter, 50 cm length). Experimental results showed that low-permeable body increased infiltration rate and wetting front migration rate. Infiltration rate and wetting front propulsion rate decreased with the increase of the burial depth. Compared with the CK, when the depth of wetting front reached 20 cm, the infiltration time of 0, 0.5, 1, and 1.5 cm burial depth treatment was shortened by 72.24%, 56.29%, 44.61%, and 31.01%, respectively. Simultaneously, the existence of low-permeable body led to the increase of soil water content and salt content in the same soil layer, which indicated that the low-permeable body enhanced the soil holding capacity and reduced the salt leakage to the deep soil. Furthermore, the Philip’s model and the algebraic model were used to describe the infiltration process. Fitting results showed that the sorptivity in the Philip’s model increased with burial depth, while the comprehensive shape coefficient in the algebraic model decreased. Therefore, this study provides a reference for the application of low-permeable body in the improving soil infiltration capacity and controlling salt transport.
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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".