Assessing irrigation network performance based on different climate change and water supply scenarios: a case study in Northern Iran
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this paper was to investigate the performance of irrigation networks under climate change, through a case study of a sprinkler irrigation network in Bilesavar, Northern Iran. In this study, the performance of the irrigation network was evaluated using WaterGems in terms of the equity and the adequacy of pressure, and minimum and maximum velocity at the outlets based on different scenarios. The results showed that ETo may be around 6% higher than the baseline (1971-2000) by 2010-39, and 12% higher by 2050-79, consequently, irrigation requirements may be higher in the future. Owing to climate change, it was seen that the irrigation network may experience challenges in terms of pressure and discharge supply. With increasing demand on the network, equity and adequacy indices of pressure distribution were seen to decline. In order to adjust to these changes, adaption strategies such as changes in the area of cultivation showed the greatest impact in reducing the volume and demand of water in the network. In general, the results showed that the various potential climate change scenarios may have a significant impact on irrigation network performance.
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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 | 0.001 | 0.001 |
| 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 it