Comparing the hydrology of grassed and cultivated catchments in the semi‐arid Canadian prairies
Bibliographic record
Abstract
Abstract At the St Denis National Wildlife Area in the prairie region of southern Saskatchewan, Canada, water levels in wetlands have been monitored since 1968. In 1980 and 1983 a total of about one‐third of the 4 km2 area was converted from cultivation to an undisturbed cover of brome grass. A few years after this conversion all the wetlands within the area of grass dried out; they have remained dry since, whereas wetlands in adjacent cultivated lands have held water as before. Field measurements show that introduction of undisturbed grass reduces water input to the wetlands mainly through a combination of efficient snow trapping and enhanced infiltration into frozen soil. In winter, the tall brome grass traps most of the snowfall, whereas in the cultivated fields more wind transport of snow occurs, especially for short stubble and fallow fields. Single‐ring infiltration tests were conducted during snowmelt, while the soil was still frozen, and again in summer. The infiltrability of the frozen soil in the grassland is high enough to absorb most or all of the snowmelt, whereas in the cultivated fields the infiltration into the frozen soil is limited and significant runoff occurs. In summer, the infiltrability increases for the cultivated fields, but the grassland retains a much higher infiltrability than the cultivated land. The development of enhanced infiltrability takes several years after the conversion from cultivation to grass, and is likely due to the gradual development of macropores, such as root holes, desiccation cracks, and animal burrows. Copyright ©2002 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".