Temporary Assessment of the Quality of Tigris River Water During the Wet Season in Central Iraq Using the CCME WQI and Irrigation Indices
Bibliographic record
Abstract
Iraq experienced varying climate changes from 2022-2023, with a rise in summer temperatures, moderate winter temperatures, and a decrease in rainfall compared to the previous years. Therefore, this study focused on assessing the water quality of the Tigris River in selected districts during the wet season for drinking and irrigation purposes. Monthly samples from the Tigris River were collected (December, January and February 2022-2023) and 13 physiochemical parameters were thoroughly examined. A few physiochemical parameters in the Tigris water exceeded the World Health Organization's (WHO) permissible levels in the samples, which were in December, 9.05 and 10.7mg/ L for turbidity (Tur) in Shirqat and Alam, and 349mg/ L for sodium (Na) in Alam. In January, the value of 252 and 256mg/L were recorded for total hardness (TH) in Hawija and Alam. In February, a value of was recorded 11.1 for Tur in Alam, while 136, 146, and 140 mg/L were recorded for total alkaline (Alk) in Shirqat, Hawija, and Alam. The Canadian Water Quality Index (CCME WQI) rated the Tigris River water as Good, indicating acceptable water quality for human use. Likewise, the study assessed the suitability of Tigris water for crop irrigation using various irrigation indices, revealing that it was suitable for soil and crops in the studied areas during the wet period.
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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 | 0.001 | 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 | 0.001 |
| 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".