Hydraulic Conductivity Dynamics during Salt Leaching of a Sodic, Structured Subsoil
Bibliographic record
Abstract
Leaching of salts in the presence of elevated soil sodicity can result in reduced hydraulic conductivity due to clay swelling or dispersion. This study examines the dynamics and mechanisms of hydraulic conductivity decrease induced during salt leaching of a structured, smectite‐bearing subsoil. Intact soil cores were initially equilibrated with aqueous solutions of elevated salinity and sodicity. Results of leaching with a solution of fixed sodicity demonstrated that, in this structured soil, salinity levels were successfully leached before reaching a stable hydraulic conductivity. This disequilibrium between decreases in hydraulic conductivity and permeameter effluent salinity appear to be the result of diffusion‐controlled swelling. Diffusion of salts out of low permeability soil aggregates may be slowed by diffuse double layer swelling trapping salts within the smallest pores. A higher degree of sensitivity to saline–sodic swelling effects was observed for the structured soil in this study compared to repacked soils of higher swelling clay content from other studies. Higher sensitivity of structured subsoils to saline–sodic swelling effects may be attributed to aggregate breakdown and plugging of macropores, heterogeneity in swelling‐clay distribution resulting in a locally higher degree of swelling, and/or increased internal swelling due to physical restriction caused by overburden loading. Potential irreversibility of pore network damage caused by soil structure breakdown motivates mitigating saline–sodic disruption of field hydraulic conductivity before it occurs.
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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".