Modelling of Seasonal Evapotranspiration from an Agricultural Field Using the Canadian Land Surface Scheme (CLASS) with a Pedotransfer Rule and Multicriteria Optimization
Bibliographic record
Abstract
The performance of the Canadian Land Surface Scheme (CLASS 3.5) was assessed using turbulent fluxes derived from data recorded at two micrometeorological stations located in a potato field in Quebec, Canada. The minimum stomatal resistance, the maximum leaf area index, and the initial water content of the third soil layer were optimized using the Non-Dominated Sorting Genetic Algorithm-II and the mean square error of the latent heat flux. With respect to benchmark solutions, the optimization improved the sensible and latent heat fluxes by 31 and 23%, respectively. The use of a pedotransfer rule in adjustment of the water content of mineral soils having small percentages of organic matter provided better estimates of the evapotranspiration during the growing stage. However, like the original version of the model (without the pedotransfer rule), it underestimated evapotranspiration throughout the maturity stage. It is noteworthy that the original version produced a good estimate of cumulative evapotranspiration over the entire season as a result of over- and underestimates at the beginning and maturity stage of the growing season, respectively.
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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 | 0.000 | 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 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".