Experimental and Numerical Study on the Coupled Processes of Salt Migration and Moisture Movement Under Evaporation in the Vadose Zone
Bibliographic record
Abstract
In arid and semi-arid regions, soil salinization has emerged as an escalating environmental challenge. Soil salinity not only alters the soil structure but also influences water movement and distribution. The coupled processes of water movement, heat transfer, and solute transport in the vadose zone interact dynamically, warranting an in-depth investigation into coupled processes of matter and energy. This study developed a numerical model of coupled water-vapor–heat–salt transport in the vadose zone, validated through evaporation experiments and compared with a conventional model excluding osmotic potential. It is found that salt presence reduces evaporation rates while enhancing soil moisture movement. Liquid water movement is primarily governed by matric and osmotic potential gradient, whereas water vapor movement is dominated by temperature gradients. Matric potential influences water vapor movement only at the soil surface, and the impact of salt on water vapor movement diminishes with increasing water content. Notably, matric potential significantly affects water vapor movement only when soil water vapor relative humidity is below unity. The proposed model effectively describes multi-field coupling transport and clarifies the role of osmotic potential in regulating liquid and vapor water dynamics.
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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) | 0.000 | 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) | 0.001 | 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".