Improving the estimation of soil water evaporation based on days after wetting
Bibliographic record
Abstract
Abstract Soil evaporation constitutes a major pathway of water loss in agriculture. Understanding its dynamics in the face of drying and soil cover is fundamental to improve both simulation models and the sustainability of production systems. Thus, the objective of this study was to estimate soil evaporation as a function of drying and percentage of soil cover. Three experiments were carried out in three different periods. In each of the periods, in parallel and in an adjacent area, an experiment was carried out to evaluate the influence of weighing micro‐lysimeter (ML) height on the estimation of direct soil evaporation. The experiments were installed with a completely randomized design. For the experiments that measured evaporation as a function of cover, the treatments consisted of six different percentages of cover of the internal area of the ML (0%, 10%, 25%, 50%, 75% and 100%), with four replicates, using artificial plants to cover the soil. The experiments that estimated evaporation as a function of ML height were conducted with eight repetitions and three different ML heights (100, 200 and 300 mm). It was observed that the accumulated evaporation up to 25 days after wetting was 52% and 53% lower in micro‐lysimeters with 100 mm height, compared to those with 200 and 300 mm height, respectively, for all experiments. The new model developed to calculate soil evaporation as a function of the days after wetting and percentage of soil cover showed excellent performance (NSE > 0.95).
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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 | 0.000 |
| 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 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".