Soil texture and layering effects on water and salt dynamics in the presence of a water table: a review
Bibliographic record
Abstract
Soil texture and its vertical spatial heterogeneity may greatly influence soil hydraulic properties and the distribution of water and solutes in the soil profile; therefore, they are of great importance for agricultural, environmental, and geo-engineering applications such as land reclamation and landfill construction. This paper reviews the following aspects on water and salt dynamics in the presence of a water table: (i) the effect of soil texture on the extent of upward movement of groundwater in homogenous soils and (ii) the impact of soil textural layering on water and salt dynamics. For a homogenous soil, the maximum height of capillary rise (h max ) or the evaporation characteristic length (ECL) is closely related to the soil texture. When the water table is deeper than h max , water will evaporate at some depth below surface and salts will be retained below the evaporation front, causing the separation of water and salt. For layered soils, flow barriers (capillary and hydraulic barriers) can make the soil hold more water than a nonlayered one. A capillary barrier may work when a fine-textured layer overlies a coarse-textured layer during infiltration or a coarse-textured layer overlies a fine-textured layer during evaporation, and a hydraulic barrier may occur when a poorly permeable layer exists in the soil profile. The extra water held by flow barriers may improve water availability to plants and may at the same time increase salinization and other environmental risks. Under special conditions, such as in seasonally frozen soils with a shallow water table, there is an additional soil salinization incentive caused by freeze–thaw cycles. Above all, further research is needed to understand the complex effects of soil texture and layering on water and salt dynamics, especially in artificial soils such as reclaimed soils with contrasting 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".