Evaluation of Water Quality of Coastal and Groundwater of the Eastern Black Sea Basin, Turkey, Using Multivariate Statistical Analysis and Water Quality Index
Bibliographic record
Abstract
The eastern Black Sea Basin, which receives the most rainfall in Turkey and is rich in water resources, is covered with a dense forest cover. The basin is the most mountainous and elevated part of the Black Sea Region, stretching from the Terme Stream in the east of Samsun to the Georgian border. The basin, with a total area of 24,077 km2, provides 8% of Turkey’s potential with an average of 14.90 km3 surface water potential per year. Due to the height of the slope and the impermeable or semi-permeable layer of the subsurface, a significant part of the falling rain passes into the surface runoff. In the basin, where many small streams, large and small, emptied into the Black Sea independently of each other, the sub-basin boundaries were determined as water collection basins limited to the water section lines of these rivers. The data used in this study were measured results of well and spring water samples taken from 150 points by the State Hydraulic Works (DSI). Study data were obtained from the Eastern Black Sea Basin Hydrogeological Study Final Report. Measurements were made seasonally in 2020 and 2021. Measured parameters were electrical conductivity, dissolved oxygen, pH, temperature, salinity, NO3-N, NO3, NO2, NO2-N NH4, NH4-N, total phosphorus, total organic carbon, chloride, sulfate, bicarbonate, carbonate, fluoride, bromide, Ca, Mg, Na, K, cyanide, Cd, Pb, Hg, As, Cu, Zn, Ni, Se, Fe, Mo, Co, Ag, Mn, Sn, Cr. In order to evaluate the results, factor analysis and cluster analysis methods, which are multivariate statistical analysis methods, were used. At the same time, the evaluation was made using the water quality index method. In order to determine groundwater quality, sampling was carried out at 151 water points (92 wells, 59 springs) for four periods; anion-cation, heavy metals, aldehydes, phthalates, polyaromatic hydrocarbons, nitrogen compounds, pesticides, ketones, and phenols were analyzed. According to the chemical analysis results, the dominant cation in all sub-basins is Ca, and the dominant anion is HCO3. In terms of irrigation water, groundwater is generally in the “low salt, low sodium” water class. As a result of the analysis, the main parameters affecting the basin were determined. The most important parameters and factors affecting the basin were determined by factor analysis. Factors were grouped by cluster analysis. The Canadian Water Quality Index method was used for the calculation of the water quality index. The reason why it is preferred to use this index is that it can be applied to the regulations of the countries. By using the water quality index, the pollution level of water can be evaluated as poor, medium, bad, and very poor quality water. Indices are preferred in the evaluation of water pollution because they are understandable, especially for decision makers in the water field.
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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 | 0.002 |
| 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 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".