Tillage Effects on Water and Salt Distribution in a Vertisol during Effluent Irrigation and Rainfall
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Bibliographic record
Abstract
Most previous investigations of the effects of irrigation with a moving sprinkler irrigation system (MSIS) on surface runoff have studied in loess soils. However, Vertisols have different properties than loess soils and therefore could behave differently during sprinkler irrigation. The objectives were to determine the runoff, soil loss, and water and salt distribution in a Vertisol field under secondary effluent irrigation with an MSIS while subjected to various tillage practices and rainfall conditions. The experimental site was a cotton ( Gossypium hirsutum L.) field located in the Yizre'el Valley, Israel. Two tillage treatments were studied: local practice (control) and microbasins. Water content and salt concentration in the soil and seed cotton yield and plant height were measured at various positions along the slope during the irrigation season, and the water and salt content were measured at one position during the rainy season. The average runoff and soil loss (from a 5.5‐m −2 plot) per irrigation event for the entire irrigation season were 12.5 mm and 64.6 g m −2 , respectively, in the control and 3.3 mm and 13 g m −2 , respectively, in the microbasin treatment. The water, salt, and cotton yield distributions along the slope were quite uniform in the two treatments. The high infiltration of the runoff through cracks limited the effects of the runoff downhill flow on the water and salt distribution along the slope. At the end of the irrigation season, the average electrical conductivity (EC) down to 1.5‐m depth was ≈2.3 dS m −1 in both treatments. After the rainy season, the average EC in the control was 0.6 dS m −1 in the 0‐ to 0.6‐m depth range and 3.4 dS m −1 in the 0.6‐ to 1.5‐m depth range. Conversely, in the microbasins, the salt was leached to below 1.5‐m depth by rainfall. However, further study is needed to determine the salt distribution in the areas between the microbasins.
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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