Evaluating water quality of Awash River using water quality index
Bibliographic record
Abstract
Awash river has been impaired by various types of pollution owing to waste released from different socio-economic activities in its basin.This research was aimed at evaluating its quality status with respect to drinking and irrigation water uses.Based on accessibility and land use severity, 17 sample sites were chosen along the river and sampling was done twice in each of the dry and wet seasons.Thereafter, both onsite and offsite water quality analyses were undertaken following standard procedures.Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) was applied to compute the water quality indices.Accordingly, the drinking and irrigation water quality indices of the upper basin were found to be 34.79 and 46.39 respectively, which were in the poor and marginal categories of the Canadian water quality ranking.Meanwhile, the respective indices for the middle/lower basin, which were 32.25 and 62.78, lie in the poor and fair ranges of the ranking.Although the difference in the dataset used for the two cases and natural purification in the course of the river might contribute to the difference in WQI, it is generally conceivable that the water quality of the river is below the good rank.Establishment of wastewater treatment plants and storm water quality management at hotspot areas are recommended to improve the quality.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".