Multivariate Analysis of the Dynamics in Water Quality and Trophic Status of the Crocodile River and Hartbeespoort Dam
Bibliographic record
Abstract
Economic expansion coupled with population growth and associated anthropogenic activities are a threat to water resources globally. This study assessed the dynamics in water quality and trophic status of one of South Africa's hyper-eutrophic reservoirs, the Hartbeespoort Dam. Spatio-temporal variability in water quality parameters was determined on historical data spanning a period of forty years (1980-2020), with the aim of determining decadal changes in the Water Quality Index (WQI), the Water Pollution Index (WPI), the Canadian Council of Ministers of the Environment-Water Quality Index (CCME-WQI) as well as the Nutrient Pollution Index (NPI) and TN:TP ratios in the Hartbeespoort Dam as well as the Crocodile River. The calculated indices provide a single aggregated standardized score of water quality. The efficiency of a bioremediation programme (2007-2012) implemented as a mitigation measure to combat eutrophication in the dam was assessed. The study also investigated the impact of rainfall on the variability of the concentration and level of selected physico-chemical parameters. The results of the study revealed that apart from turbidity, rainfall has no significant impact on the variability of other water quality parameters studied. Furthermore, the WQI, CCME-WQI, WPI, as well as the NPI classified the general water quality of the dam as extremely poor and highly polluted. Moreover, TN:TP showed an increase in TP over time, further exacerbating hypereutrophic conditions in the catchment. The study also showed that the bioremediation programme was effective in reducing external P loading, however, bioturbation resulted in the resuspension of historical internal P loads, thus maintaining high phosphate concentrations at the site downstream from the Hartbeespoort Dam.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".