Impact of Changes in Land Use and Land Cover in the Contribution Basin of Doutor João Penido Water Supply Reservoir of Juiz de Fora, MG, Brazil
Bibliographic record
Abstract
Changes in the land use and land cover in areas adjacent to water reservoirs directly affect the quality of this water. This research presents a study on the water quality in the basin of one of the most important public water supply reservoirs in the city of Juiz de Fora, Minas Gerais. The main objective of this study was to analyze the behavior of limnological parameters and the correlation with land use and land cover in the contribution basin of the Doutor João Penido reservoir (CBJPR). The methodology was based on the analysis of water quality parameters, related to water samples collected from 2012 to 2015. Six sampling points were chosen from different locations: spring, medium course, main tributaries of the reservoir and the reservoir catchment. The parameters analyzed were turbidity, total solids (TS), oxygen consumed (OC), dissolved oxygen (DO), electrical conductivity, total nitrogen (TN), total phosphorus (TP), E. Coli, temperature, pH and total dissolved solids (TDS). The Kendall’s tau test was used to analyze the correlations between the parameters of water quality, land use and land cover in the CBJPR. In general, measured parameters showed better results in spring and in reservoir catchment, showing a worse quality of the water along the tributaries and the dilution power of the reservoir. The correlations pointed to the need for protection and preservation of forests in strategic locations to ensure good water 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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".