Freeze–Thaw and Water Tension Effects on Soil Detachment
Bibliographic record
Abstract
Many areas of the northern United States and southern Canada, and particularly the 4 million ha of unirrigated cropland of the Northwestern Wheat and Range Region in the United States, experience severe water erosion under thawing soil conditions. Modeling soil erosion in these areas is hampered by a lack of knowledge of the relation of soil properties and moisture conditions to hydraulic resistance of thawing soils. This study was conducted to determine hydraulic and erodibility parameters of frozen and thawed soil under controlled moisture tension. A tilting flume was designed and constructed to allow near‐natural freezing and thawing of a soil mass and to apply shear stress from flowing water. Flow tests were conducted for 90 min under soil moisture tensions of 50, 150, and 450 mm. A linear relationship was found between detachment and applied shear stress at a given time and moisture tension. Critical shear stress values showed little change with time. Rill erodibility decreased with increased soil moisture tension but changed more rapidly during tests at 50‐ and 150‐mm tension. At 50‐mm tension, the time‐average erodibility, 689 g N −1 min −1 , was about the same, and the critical shear value, 1.53 N m −2 , about 60% of that found in tests of a similar Palouse silt loam soil tested under 50‐mm tension without freezing. This study adds to the body of knowledge that indicates that the transient nature of rill erodibility during soil freezing and thawing should be considered to improve the accuracy of continuous simulation erosion models for winter conditions.
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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) | 0.001 | 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".