Evaluation of Groundwater Quality Using Water Quality Index and GIS, The Case of Debre Tabor Town, Ethiopia
Bibliographic record
Abstract
Abstract Assessing the quality of groundwater for better management of the water sources is essential. This study is aimed at evaluating the groundwater quality of Debre Tabor town. Twelve groundwater samples were collected at hand dung wells during the wet season (Mid July-Mid August 2020) and dry season (1st February –Mid-March 2021). Various Physico-chemical parameters (pH, electrical conductivity (EC), Total dissolved solids (TDS), Temperature, Turbidity, Calcium (Ca 2+ ), Magnesium (Mg 2+ ), Chloride (Cl − ), Nitrate (No 3 − ), and microbiological parameters (Total coliform and Feacal coliform)) were analyzed and compared with the standard guidelines recommended by WHO. GIS was used to show the distribution of groundwater quality throughout the study area. WQI created by Canadian Council of Minster of the Environment (CCME) was applied to evaluate the suitability of the groundwater for drinking purposes. Also, the result shows that total coliform and faecal coliform at all groundwater wells were not suitable for drinking purpose. The result shows that Electrical conductivity, Temperature, Nitrate, Chloride and Magnesium at all groundwater wells were suitable for drinking purpose for both dry and wet season whereas Turbidity, pH, Calcium and Total Dissolved Solids are suitable for drinking purpose at some groundwater wells but not suitable at some wells. The water quality analysis result shows that spatial and seasonal variations of the parameters are significant throughout the study area(p < 0.05). According to CCMEWQI result seven groundwater samples show poor water quality status of 40.53-44 while, five groundwater samples show marginal water quality status of 44.19–55.82. Based on the information provided by the study, it is recommended to identify the source of contamination, provide properly designed sanitation systems and to monitor water quality at least once per year for effective and proper management of the groundwater 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 | 0.031 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".