Pesticide Contamination of Surface and Groundwater in an Ethiopian Highlands’ Watershed
Bibliographic record
Abstract
Agricultural intensification in sub-Saharan African countries has significantly increased pesticide applications. Information on pesticide residues and their transport in groundwater and streams is needed to properly manage and reduce any harm to the ecosystem and environment. This information is lacking in the volcanic soils of Ethiopian highlands. Therefore, this study was conducted to assess pesticide concentrations in ground and surface water and their risk to humans and aquatic life. The 9 km2 rural watershed Robit Bata in the Lake Tana Basin was selected. Crops were grown under rainfed and irrigated conditions. Pesticide use was assessed, and groundwater samples were collected from eight wells and surface water samples at the outlet twice in the rain phase and once in the dry phase. Samples were analyzed for chlorpyrifos, dimethoate, (α and β) endosulfan, profenofos, NO3−, and pH. Chlorpyrifos and endosulfan, which are strongly adsorbed and slowly degrading pesticides, were found in nearly all surface and groundwater samples, with maximum concentrations in surface water of 8 µg L−1 for chlorpyrifos and 3 µg L−1 endosulfan. Maximum groundwater concentrations were only slightly lower. The weakly adsorbed and fast degrading pesticides, dimethoate, and profenofos were detected only in the rain phase after spraying in the groundwater, indicating preferential transport to groundwater at depths of up to 9 m. The average concentration was 0.38 μg L−1 for dimethoate in surface waters and 1.24 μg L−1 in groundwater. Profenofos was not detected in surface water. In the groundwater, the average concentration was 0.05 μg L−1. Surface water concentrations of chlorpyrifos and endosulfan were highly toxic to fish. The World Health Organization banned these pesticides worldwide. It should be phased out for use in Ethiopia to safeguard the ecological health of Lake Tana, which is rich in biodiversity and endemic fish species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".