The effects of existing water-eroded channels on water erosion and tillage erosion, and the integration of these effects into models of total soil erosion
Bibliographic record
Abstract
Water-eroded channels are focal points for water, wind, and tillage erosion processes as they can function as pathways for sediment transport, sources or traps of sediments and topography features that alter the nature of soil redistribution by tillage. The linkages and interactions of different erosion processes around the channel area are complex and dynamic, not only during the period when the channel is created but also after it is created. The effects of channels on subsequent water and tillage erosion and their contribution to total soil erosion have not been examined. To fill this knowledge gap, we carried out three studies, focusing on the role of channels in water and tillage erosion processes and the assessment of total soil erosion. In the first study, we examined the effects of a channel on tillage translocation. For downslope tillage, channels reduced total translocation, whereas, for upslope tillage, channels increased total translocation. For contour tillage, channels increased total translocation as well. The patterns of tillage translocation can be well explained by the balance of the trapping effect versus the energy-intensity-increase effect. Soil movement decreases when the trapping effect dominates and increases when other effect dominates. Additionally, a plot experiment examined the effects of an existing channel and tillage on water erosion. With an existing channel, runoff discharge and sediment export increased, whereas, with tillage, runoff discharge and sediment export decreased. When an existing channel was tilled, the effects of tillage dominated, while the existing channel only demonstrated some minor impacts. In the third study, a modeling procedure was developed to integrate the Raster-RUSLE2, Ephemeral Gully Erosion Estimator and Modified Directional Tillage Erosion Model for simulating water and tillage erosion. This integrated approach incorporated insights gained from previous studies on interaction effects. The individual models provided reasonable estimations for specific erosion processes, while the integrated model accurately estimated total soil erosion across most field areas. However, higher errors and uncertainties were observed in gully areas, potentially due to their dynamic erosion processes or limitations in input data resolution and accuracy, indicating that the gully area is a weak point for soil erosion modeling.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".