Impact of Soil Amendments on the Hydraulic Conductivity of Boreal Agricultural Podzols
Bibliographic record
Abstract
Hydraulic properties of soil are the basis for understanding the flow and transport through the vadose zone. It has been demonstrated that different soil amendments can alter the soil properties affecting soil hydrology. The aim of this study was to determine the effect of soil amendments on hydraulic conductivity (K) of a loamy sand podzolic soil under both unsaturated (Kunsat) and near-saturated (near Ksat) conditions in an agricultural setting. A field experiment was conducted with two common soil amendments: Dairy manure (DM) in 2016 and 2017 and biochar (BC) once only in 2016. DM and BC were incorporated up to a depth of 0.15–0.20 m at a rate of 30,000 L ha−1 and 20 Mg ha−1, respectively. A randomized complete block experimental design was used and the plots planted with silage corn (Zea mays L.) without irrigation. The treatments were: Control without amendment (0N), inorganic N fertilizer (IN), two types of DM (IN+DM1 and IN+DM2), and two treatments with BC (IN+BC and IN+DM1+BC). Infiltration data were collected using a mini disk infiltrometer under three tension levels in which −0.04 and −0.02 m was ascribed as unsaturated (at the wet end) and −0.001 m as near-saturated condition. Based on the measured infiltration rates, Kunsat and near Ksat hydraulic conductivities were calculated. There were no significant effects of DM and BC on bulk density and near Ksat. Treatments IN+DM1, IN+DM2, and IN+DM1+BC significantly reduced the Kunsat compared to the control. Since these soil amendments can influence soil hydrology such as reduced infiltration and increased surface runoff, carefully monitored application of soil amendments is recommended.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".