Assessing Water Quality Index in Kani-Qirzhala Area, Erbil City, Kurdistan Region of Iraq
Bibliographic record
Abstract
Groundwater is an essential water source in many areas in the Kurdistan Region of Iraq (KRI). The groundwater can be used for many purposes such as municipal, agricultural, and domestic. The objective of this study is to assess the quality of groundwater in the Kani-Qirzhala area. The study area covers 60 km2, and includes twenty-seven water wells, which have been selected and used to study the water quality parameters in such area. Canadian Council of Ministers for the Environment Water Quality Index method was used to evaluate Water Quality Index and SPSS software version 25 even to study the correlation between Water Quality Index and water quality parameters. The results indicated that the quality of water in most of the wells is fair, except the quality of water in wells 19, 24, and 27 is found to be poor. Well19 is located close to the Erbil landfill site (Kani-Qirzhala) and this poor quality is due to the effect of Landfill site leachate. The Well 24 is in the Erbil store area where the leachate of landfill is discharged to this surrounding area. The quality of water in well 27, on the other hand, was marginal and existed on the eastern side of the study area. The significant correlation revealed a good correlation between WQI and water quality parameters such as (pH, EC, TDS, Ca2+ Na1+, Mg2+, NO3-1, K1+, SO42-, Cl1-, Hardness, Alkalinity, Iron, and Copper).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".