Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China
Bibliographic record
Abstract
The objective of this study was to evaluate the performance of the FAO-AquaCrop model in winter wheat in the southern Loess Plateau of China. Multi-year field experimental data from 2004 and 2011 were used to calibrate and validate the model for simulating biomass, canopy cover (CC), soil water content, and grain yield under rainfed conditions. The model performance was evaluated using root mean square error (RMSE) and Willmott index of agreement (d) as criteria. The RMSE ranged from 0.16 to 0.38 t/ha for simulating aboveground biomass, 1.87 to 4.15% for CC, 0.50 to 1.44 t/ha for grain yield, and 5.70 to 22.56 mm for soil water content. The d ranged from 0.22 to 0.89, 0.25 to 0.43, 0.36 to 0.62 and 0.95 to 0.98 for aboveground biomass, CC, soil water content and grain yield, respectively. Generally, the model performed better for simulating CC and yield than biomass and soil water content. The results further indicated that AquaCrop is capable of simulating winter wheat yield under rainfed conditions. Further improvement may be needed to capture the variation of different management practices such as fertility and irrigation levels in this region.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".