Groundwater quality assessment using the water quality index: case study in the north-western part of Drini i Bardhë River basin, Kosovo
Bibliographic record
Abstract
Drinking water sources are susceptible to pollutants depending on geological conditions and agricultural, industrial and other human activities. Water quality assessment has always been a major part of environmental management plans. The water quality index (WQI) method plays an important role and is a powerful tool for analysing the overall water quality. The purpose of this study was to analyse and present the results for the quality of groundwater in the north-western part of the Drini i Bardhë River basin, Kosovo, based on data that were collected from 50 sampling points, 48 different wells (dug and drilled) and two springs in November 2018–January 2019. Through this work, it has been possible to provide authentic information on this study area to the public, who use these waters for water supply, irrigation and other purposes. Processing, analysis and interpretation of the results are based on statistical methods, water quality standards and the WQI method. The completion of the study followed a scientific research work methodology based on field and laboratory studies. For calculating the WQI, groundwater samples were analysed in terms of 13 physico-chemical parameters – namely, T, pH, electrical conductivity, total dissolved solids, total hardness, sodium (Na + ) ions, calcium (Ca 2+ ) ions, magnesium (Mg 2+ ) ions, potassium (K + ) ions, bicarbonates (HCO 3 − ), chlorides (Cl − ), sulfates (SO 4 2− ) and nitrates (NO 3 − ). Based on the results obtained and a comparison with World Health Organization standards, it was shown that the parameters of the groundwater are within the allowed limit values for drinking water. The values obtained for the WQIs of the groundwater samples from the north-western part of the Drini i Bardhë River basin, Kosovo, range from 11 to 116, indicating that these waters are mainly in good and excellent condition, and only sample SP40 had water unfit for consumption.
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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 | 0.004 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".