Estimation of evapotranspiration from a bioretention facility using a lysimeter and six predictive equations
Bibliographic record
Abstract
Low impact development practices such as bioretention are being used more frequently in stormwater management. The commonly considered aspects of bioretention are its ability for filtration and infiltration, but evapotranspiration is not frequently considered despite its potential to be a significant component of the water balance. A lysimeter study was conducted in Guelph, Ontario to estimate the ET rate from bioretention facilities. The lysimeter was designed to mimic standard bioretention design parameters. The average annual ET rate was 1.30 mm/d, with monthly averages ranging from -0.009-2.90 mm/d. The lysimeter-derived ET was then compared to ET predicted by the Hamon, Hargreaves-Samani, Jensen-Haise, Penman-Monteith, Priestley-Taylor, and Thorthwaite equations to determine their applicability to use in urban bioretention systems. The Jensen-Haise equation was found to perform the best once a coefficient of 0.5 was applied to consider the protected environment of the lysimeter.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".