Near‐saturated surface soil hydraulic properties under different land uses in the St Denis National Wildlife Area, Saskatchewan, Canada
Bibliographic record
Abstract
Abstract Surface soil hydraulic properties are key factors controlling the partition of rainfall and snowmelt into runoff and soil water storage, and their knowledge is needed for sound land management. The objective of this study was to evaluate the effects of three land uses (native grass, brome grass and cultivated) on surface soil hydraulic properties under near‐saturated conditions at the St Denis National Wildlife Area, Saskatchewan, Canada. For each land use, water infiltration rates were measured using double‐ring and tension infiltrometers at −0·3, −0·7, −1·5 and −2·2 kPa pressure heads. Macroporosity and unsaturated hydraulic properties of the surface soil were estimated. Mean field‐saturated hydraulic conductivity ( K fs ), unsaturated hydraulic conductivity at −0·3 kPa pressure head, inverse capillary length scale (α) and water‐conducting macroporosity were compared for different land uses. These parameters of the native grass and brome grass sites were significantly ( p < 0·1) higher than that of the cultivated sites. At the −0·3 kPa pressure head, hydraulic conductivity of grasslands was two to three times greater than that of cultivated lands. Values of α were about two times and values of K fs about four times greater in grasslands than in cultivated fields. Water‐conducting macroporosity of grasslands and cultivated fields were 0·04% and 0·01% of the total soil volume, respectively. Over 90% of the total water flux at −0·06 kPa pressure head was transmitted through pores > 1·36 × 10 −4 m in diameter in the three land uses. Land use modified near‐saturated hydraulic properties of surface soil and consequently may alter the water balance of the area by changing the amount of surface runoff and soil water storage. Copyright © 2004 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 | 0.000 |
| 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 | 0.001 | 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".