Analysis of plant root–induced preferential flow and pore-water pressure variation by a dual-permeability model
Bibliographic record
Abstract
Vegetation can affect slope hydrology and stability via plant transpiration and induced matric suction. Previous work suggested that the presence of plant roots would induce preferential flow, and its effects may be more significant when the planting density is high. However, there is a lack of numerical studies on how planting density affects soil pore-water pressure and shear strength during heavy rainfall. This study aims to investigate the impact of plant root–induced preferential flow on hydromechanical processes of vegetated soils under different planting densities. Two modelling approaches, namely single- and dual-permeability models, were integrated with an infinite slope stability approach to simulate pore-water pressure dynamics and slope stability. Laboratory tests on soils with two different planting densities for a plant species, Schefflera heptaphylla, were conducted for numerical simulations. The single-permeability model overestimated the pore-water pressure in shallow soil and underestimated the infiltration depth. The dual-permeability model, which is able to model the effects of preferential flow, can better capture the observations of rapid increase of pore-water pressure and deeper pressure response in the vegetated soil. However, caution should be taken on the choice of pore-water pressure when using the dual-permeability model to assess the factor of safety. The dual-permeability model using the pore-water pressure in the preferential flow domain and that in the matrix domain would result in a lower and higher factor of safety, respectively.
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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 | 0.000 | 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 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".