Estimating rill erosion and sediment transport processes along a saturated purple soil slope
Bibliographic record
Abstract
A plough pan with reduced permeability accumulates infiltrated water along slopes then saturates the cultivated layer under continuous rain. Topsoil saturation is a frequent phenomenon and an important process of the special soil slopes. A methodology and device system was used in this study to keep cultivated purple soil saturated. Strands of scouring tests were developed to quantify the rill erosion and sediment transport processes along a saturated purple soil slope at four experiment slopes (5°, 10°, 15°, and 20°) and three flow discharges (2, 4, and 8 L·min−1). The experimental results indicated that the sediment transport capacity on a saturated purple soil slope ranged from 0.03 to 1.56 kg·s−1·m−1 with the increasing trend along the slope gradient and flow discharge, and the increasing trend could be well matched by a nonlinear multivariable equation. The sediment concentration of the saturated purple soil slope exponentially increased with rill length and decreased with the increment rate, and the maximum sediment concentrations observed in this study in different hydraulic events ranged from 108.13 to 1174.20 kg·m−3. Saturated and non-saturated purple soil slopes erode differently with the maximum sediment concentration of saturated purple soil slope recorded at approximately 1.42–2.10 times the values for non-saturated purple soil slope. The findings of this research help illustrate the sediment transportation and erosion behaviors of a saturated purple soil slope and serve as the basis for determining the parameters in the erosion models of the purple soil slope.
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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".