Water quality index along the Euphrates between the cities of Al-Qaim and Falluja: A comparative study
Bibliographic record
Abstract
Abstract Water Quality Index (WQI) is a useful and unique method of measuring water quality. It is often used to determine the status of water quality in simple terms (e.g. good or bad, usable or unusable) to assess water quality and evaluate its suitability for different purposes. The research objectives are to assess the spatial variability of the water quality index (WQI) and make comparisons among monitors sites on the Euphrates River in Anbar Governorate. The monitoring and assessment were carried out on eleven sampling sites along the Euphrates River between the cities of Al-Qaim and Fallujah, spatially and temporally, over a period of 4 years from 2010 to 2013. To calculate the WQI, several Physico-chemical parameters, namely, pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (T.H), turbidity (TUR), dissolved oxygen (DO), alkalinity (Alk.), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), chloride ion (Cl-), sulphate ion (SO42-) and nitrate ion (NO3-) were analysed in line with the Canadian Council of Ministers of the Environment Water Quality Index methodology (CCME WQI). The water quality index values in these stations on the Euphrates River in the study area ranged from fair to a marginal category in the study period. The current results concluded that the alterations existed in the concentration of the Physico-chemical parameters in most months, except January and September, along the Euphrates between the cities of Al-Qaim and Fallujah, as a result of harmful practices. The present study revealed that the Euphrates River water is polluted due to human activities, agricultural run-off, the release of inadequately treated wastewater, making it unsuitable for human consumption unless treated properly.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".