EVALUATION OF SELECTED DRINKING WATER QUALITY PARAMETERS USING CCME-WQI IN NAKURU MUNICIPALITY, KENYA
Bibliographic record
Abstract
Purpose: Reliable baseline information on overall quality status of drinking water at spatial and temporal scales is important in drinking water management systems, ensuring access to clean and safe drinking water. The study aimed at determining the suitability of natural and treated water for drinking in Nakuru Municipality, Kenya. An attempt was also made to explore the applicability of CCME-WQI (Canadian Council of Ministers of the Environment Water Quality Index) in evaluation of groundwater quality data for drinking uses. Methodology: The study adopted a stratified random sampling technique that was employed systematically in conjunction with point and line techniques to create stratas/sampling components while ensuring each water cluster was represented through the sampling process. Analytical values of electrical conductivity, pH, selenium, cadmium, chloride and fluoride were used to determine quality status of water sourced from river and boreholes and as input parameters in calculation of index values. The evaluation and characterization of natural borehole water quality for drinking purposes was made using the water quality index (WQI) of the Canadian Council of Ministries of the Environment (CCME). Results: The quality of natural and treated drinking water was found to be fresh in pH, chloride and electrical conductivity but contaminated in selenium, cadmium and fluoride in line with respective regulatory standards for drinking water. Based on the CCME-WQI, index values for all sampled sites representing natural borehole water were calculated in a range of 29.83 to 37.71 with an average value of 31.05 and ranked as poor. Unique contribution to theory, practice and policy: Considering the limitations associated with the conventional methods in water quality monitoring, there is need to utilize other scientific based methods that can fill in the gaps to improve the current state of governance and practice of drinking water management systems. The CCME-WQI method as applied in this study can be utilized in evaluation of water quality monitoring data to facilitate water resources operational management and their allocation for different uses.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".