Assessment of Irrigation Water Quality Using the Canadian Water Quality Index (CWQI) in the Hilla Main Canal, Iraq
Bibliographic record
Abstract
Water quality was assessed for the main Hilla canal and three distributary channels (HC 19 at 49+243 km, HC 20 at 52+123 km, and HC 2L at 44+056 km), located in the alraarinjia of Babil, for the Hilla-Kifil Irrigation Project.The Canadian Water Quality Index (CWQI) is used to assess the irrigation water quality of the Hilla Main Canal and three distributary channels.Water samples were collected monthly from February to May 2021 and analyzed for electrical conductivity, pH, sodium adsorption ratio, total hardness, magnesium, sodium, and calcium, and compare with specifications.Based on the current outcomes, it was found that all the elements fall within the specifications until some tests where they were outside the specification, as in (TH).Besides, the value of CWQI (94.73%) was between good and excellent, and this indicates that the water is appropriate for irrigation purposes in that area.The findings of the current studies, in comparison with previous studies on the one hand and the standard specifications on the other, proved the effectiveness of the indicator and the accuracy of its results.This means, The Hilla Main Canal and distributary channels generally have good irrigation water quality according to the CWQI, But the slight increase in total hardness requires monitoring and treatment.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".