A Comparative Analysis of the Weighted Arithmetic and Canadian Council of Ministers of the Environment Water Quality Indices for Water Sources in Ohaozara, Ebonyi State, Nigeria
Bibliographic record
Abstract
This study compared the Weighted Arithmetic and Canadian Council of Ministers of the Environment water quality indices on water sources in Ohaozara, Ebonyi State, Nigeria. Water samples were collected from two communities of Uburu and Okposi in Ohaozara Local Government Area. Borehole sample was collected from Uburu while hand dug well sample was collected from Okposi. These samples were collected in the months of May and June 2021, presenting a total of four samples. The Weighted Arithmetic Water Quality Index (WAWQI) and the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) analytical methods were used in the determination of the water quality index (WQI). The results revealed that the WAWQI value for hand dug well in the month of May and June were 10.379 and 9.445 respectively, representing a water quality status of excellent for each month. However, the WAWQI value for the borehole sample in the month of May and June indicated 89.371 and 100.19 respectively, representing a water quality status of very poor and unfit for drinking in that order. The high WQI values of the borehole sample revealed the presence of toxic heavy metal contaminants of lead and arsenic in the water source as observed in the physicochemical analysis. The CCME-WQI value for the hand dug well sample indicated 53.513 while the CCME-WQI value for the borehole sample showed 49.668 with both water sources having a water quality ranking of marginal. This meant both water sources were frequently threatened and their conditions far from desired levels. The study revealed that while both indices provided a single number to describe water quality status and are widely utilised globally, the WAWQI is more sensitive to toxic heavy metal contaminants due to the use of unit weight calculation in the WQI determination. It showed that the WAWQI is better suited to be applied in the study area to alert consumers due to the abundance of solid mineral deposits in the study area and the potential for water pollution. Comparatively, the study also revealed that CCME-WQI is more moderate to all contaminants due to the use of scope (F1), Frequency (F2) and Amplitude (F3) calculation in the determination of the WQI which resulted to the marginal water quality ranking obtained for both the borehole and the hand dug well water samples.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 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".