Assessment of Pollution Risks in the Kufa River Using Water Quality Indices and Principal Component Analysis
Bibliographic record
Abstract
The Kufa River, located in Al-Najaf Province, plays a vital role in the local community by supplying water primarily for irrigation and drinking purposes.This study aims to evaluate the water quality of the Euphrates River, specifically along a 42 km stretch through Al-Najaf, using a Water Quality Index (WQI), multivariate statistical methods, and geospatial techniques.Seventeen water quality parameters and five heavy metals were measured to calculate both the Arithmetic Water Quality Index (WQI) and the Integrated Water Quality Index (IWQI).The concentration of cations followed the order Na+ ˂ K+ ˂ Ca²+ ˂ Mg²+, while anions were ranked NO₃⁻ ˂ Cl⁻ ˂ HCO₃⁻ ˂ SO₄²⁻.The results revealed significant spatial variation in IWQI values, ranging from poor to unsuitable, with water quality deteriorating from upstream to downstream locations.IWQI scores indicated that water quality ranged from poor to unsuitable at all seven sampling sites, with average values of 215.98 and 295.35 based on Iraqi (IQ) and World Health Organization (WHO) standards, respectively, thereby confirming the extent of water quality deterioration.In addition, heavy metal contamination was evaluated using the Heavy Metal Pollution Index (HPI) and the Heavy Metal Evaluation Index (HEI).For irrigation purposes, parameters including Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), and Soluble Sodium Percentage (SSP) were assessed.While most samples were categorized as permissible, two sites were classified as good based on their lower salinity levels.Statistical analysis, including Principal Component Analysis (PCA), revealed that four major factors influence water quality: organic pollution, dissolved oxygen (DO), magnesium levels, and alkalinity.The proximity of sampling sites to wastewater treatment plants and agricultural zones contributed to elevated pollutant concentrations, whereas upstream areas were primarily affected by domestic sewage.The study emphasizes the severe water quality degradation in the Kufa River.This study provides valuable insights for pollution control and sustainable water resource management in the Kufa River.By identifying heavily polluted sites such as S3 and S5 and highlighting key contaminants like cadmium and phosphate, the study offers a clear understanding of priority areas for intervention.The use of IWQI and PCA helped show spatial pollution patterns, guiding directed improvements such as real-time monitoring, enhanced wastewater treatment, and better regulation of pollution sources.These findings aim to support informed decisions and long-term strategies for water quality protection in the region.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".