Viscosity dependent dual‐permeability modeling of liquid manure movement in layered, macroporous, tile drained soil
Bibliographic record
Abstract
A scarcity of information exists on how physical processes govern the movement of liquid manure, or other viscous fluids, through layered macroporous soils. To elucidate these complex flow and transport phenomena, a viscosity dependent, two‐dimensional dual‐permeability model that considers macropore anisotropy is employed to simulate field experiments where liquid swine manure (LSM) was applied to silt loam with both a soil crust and plowpan layer present. Using data from the field experiment as a benchmark, the model was used to predict nutrient (NH 4 ‐N and total P) breakthrough to tile drains; and to assess the influence of reduced permeability crust and plowpan layers, and fluid viscosity, on solute movement within 48 h of LSM application. Results demonstrate the importance of viscosity on flow and transport in macroporous soils. By increasing LSM viscosity, nutrient breakthrough to tile drains can be greatly reduced, and near surface nutrient retention can increase. The presence of a nonmacroporous soil crust layer can also lead to reduced nutrient concentrations in tile discharge by reducing pressure heads in the underlying A‐horizon soil matrix, resulting in reduced macropore flow; whereas a low permeability plowpan layer at the base of the A horizon can increase pressure heads in the A‐horizon soil matrix and lead to increased macropore flow. Multiple target point parameter sensitivity analysis revealed that relative parameter sensitivity can be a transient characteristic, and that hydraulic properties of the A and B horizon tend to exhibit their greatest influence over the respective early and late time solute breakthrough characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".