Estimation of Future Crop Water Requirements for 2020 and 2050, Using CROPWAT
Bibliographic record
Abstract
The objective of this study was to determine the impacts of potential climate change on daily and total crop water requirements (CWR) of peaches in Southern Ontario using CROPWAT in conjunction with the climate scenarios derived from SDSM. Baseline climate is based on the 30 year-period, 1971-2000 of the mean monthly normals, and two time periods in the future centered on the decades of 2020s (2010-2039) and 2050s (2040-2069). The climate parameters of temperature, precipitation, relative humidity, sunshine duration and wind speed were downscaled using the SDSM (version 3.1) method. To determine the future crop water requirements (CWR), the CROPWAT model (FAO, 1992) was used to simulate the daily and the season total CWR and irrigation requirements for the present and the future decades. Results compared to the base climate show an increase in crop water requirements of 6.0 % (39 mm) per season using the SDSM-CGCM1 model for 2020s and 3.0% (20 mm) per season using both the SDSM-HADCM3 A2 & B2 models for 2020s. About 8 % (56 mm) increase in using the SDSM-CGCM1 and HADMC3 A2 models for 2050s, and 7.0 % (43 mm) per season. However, the irrigation requirements decreased, compared to the current situation, by 6.0 % (18 mm) (assuming 90% irrigation efficiency) using the SDSM-CGCM1 for 2020s and by 27% (81 mm) for both SDSM-HADCM3 A2 & B2 models for 2020s. While in 2050s, a decrease of 2.71% (8 mm), 21% (64 mm) and 6% (59 mm) using the SDSM-CGCM1, SDSM-HADCM3 A2 and SDSM-HADCM3 B2, respectively for 2050s.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".