Analysis of mulched drip irrigation with brackish water in cotton fields using the HYDRUS-3D numerical model
Bibliographic record
Abstract
This study combined continuous monitoring in the field using computer modeling to understand soil water movement and salt transport so as to design a suitable irrigation system for cotton using mulched drip irrigation with brackish water. A reasonable irrigation regime was determined and verified using thresholds of water and salinity stress in the various stages of cotton growth. In addition, some key factors, such as emitter discharge rate, emitter spacing, and initial water content, were screened for simulation, and irrigation uniformity and desalination rate were selected as the indicators for evaluation. The results showed that: ( i) The HYDRUS-3D model was a useful tool for designing suitable irrigation regimes, and the determined suitable irrigation quota was 5160 m 3 hm −2 under mulched drip irrigation with brackish water during the growth period of cotton in 2019. ( ii) The irrigation uniformity and leaching rate decreased with an increase in the emitter discharge, and the linear relationship between uniformity, leaching rate, and emitter discharge could be identified. ( iii) The irrigation uniformity and leaching rate decreased with an increase in emitter spacing, and power functions might be used to calculate uniformity, leaching rate, and emitter spacing. ( iv) The irrigation uniformity and leaching rate increased with an increase in initial water content, and the relationship between the two indexes and initial water content was defined by a linear function and a power function, respectively. These results provided a valuable reference for the rational use of drip irrigation with brackish water.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".