Determination of Hydraulic Properties in Sloping Landscapes from Tension and Double-Ring Infiltrometers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The majority of landscapes, natural or cultivated, are nonlevel. However, specifically designed instruments are not available for estimation of soil hydraulic properties in sloping landscapes. The objective of this study is to examine if tension and double-ring infiltrometers are suitable for determination of soil hydraulic properties on sloping soil surfaces. A field experiment was conducted in a silt loam soil (Typic Haplustolls) in Saskatchewan, Canada to explore the usefulness of tension and double-ring infiltrometers for the determination of soil hydraulic properties in sloping landscapes. Soil surfaces were created to represent four treatments, 0 (level), 7, 15, and 20% slopes. For each treatment, water infiltration rates were measured using a double-ring infiltrometer and a tension infiltrometer at −3, −6, −10, −13, −17, and −22 cm water pressure heads. In addition, three-dimensional computer simulation studies were performed for a tension infiltrometer with various disc diameters and water pressure heads for different surface slopes. Steady-state infiltration rate, field-saturated hydraulic conductivity, unsaturated hydraulic conductivity as a function of water pressure head, macroscopic capillary length parameter, and water-conducting macro- and mesoporosity were compared for different surface slopes. These parameters were not significantly different (p < 0.05) between level and sloping lands. Experimental and numerical results of this study suggest that both tension and double-ring infiltrometers are suitable for characterization of surface soil hydraulic properties in landscapes with slopes up to 20%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it