Evaluation of Water Quality and Sustainability of Treated Wastewater for Irrigation and the Municipal Uses in Karbala Province
Bibliographic record
Abstract
This study was conducted to assess the quality of treated wastewater from the wastewater treatment project in Karbala. and its reuse for irrigation and municipal by Canadian Water Quality Index (CWQI). Samples were collected periodically with three replications from (Dec. 2021 –Jul.2022). The results showed that the water was characterized by high salinity, TDS, TSS, total hardness, EC, and turbidity, which were recorded at 2039 -3739 mg/l; 1030-2640; 30-48 mg.L-1. 3740 -2040 µs/cm and 3.17 -8.5 NTU respectively, major cations and anions (Cl-, PO4-3, NO3-, S2O4-2 and K+) exceed significantly to (57-380; 0.003-4.99; 8.63-44.25; 453-1340; 4.537) mg. L-1, sodicity index (SAR, Na+ and Sodium percentage ratio) and magnesium hazard, were detected 0.59 – 4.89; 138-447.5 12.98-43.76), Water can be classed depending on that as a permit to good. However, it’s categorized as marginal-fair according to the CCME Water quality index, especially in the far station from the plant water. Principal Component Analysis (PCA) showed depending on its effect on the value of the index, where the first group PCA1 recorded the largest proportion (35.26%) and includes dissolved solids, EC, salinity, Na, SAR, Na%, alkalinity, SO4, pH, DO, BOD5 Mg risk of magnesium. The second group, PCA2, with the lowest percentage (18.78%), was represented by temperature, Ca+2, total hardness, K, Cl, PO4, NO3, TSS, and turbidity. This water is a wealth that can be exploited in the cultivation of the desert adjacent to Karbala governorate, and by adopting different methods to reduce the effect of salinity.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".