Hydrogeochemical assessment of Ramsar wetland sites in Gujarat, India using environmetric techniques
Bibliographic record
Abstract
Ramsar wetlands are essential ecosystems that play a vital role in supporting biodiversity and maintaining water balance, making them ecologically and hydrologically significant. The study was conducted at four such sites in Gujarat — Khijadia, Nal Sarovar, Thol, and Wadhvana — to determine the variability in water quality, the predominant geochemical processes, and their potential for irrigation and domestic use. Major ions and physicochemical parameters in 12 surface water samples (3 samples from each wetland) were analyzed. Findings demonstrate slightly alkaline waters throughout the locations, with very high EC and TDS in Khijadia and Nal Sarovar due to evaporation and the intrusion of saline waters. In contrast, Thol and Wadhvana demonstrated relatively higher quality, but with locally elevated fluoride levels (>1.5 mg/L). The Thol and Wadhvana were rated good, and Khijadia and Nal Sarovar were rated poor by the Canadian WQI. High salinity hazards in Nal Sarovar and overall suitability in Thol and Wadhvana were demonstrated using irrigation indices (SAR, RSC, MAR, and KR). Piper, Durov, and Gibbs diagrams revealed four facies: Khijadia (Mg-Cl), Nal Sarovar (Na-Cl), Thol (Na-Cl), and Wadhvana (Ca-Mg-Cl). PCA identified three components that accounted for more than 90 % of the total variance, with strong correlations among Na⁺–Cl⁻–Mg²⁺ that are associated with salinity and rock-water interactions, suggesting these are the most significant controls. Elevated Na⁺, Cl⁻, and F⁻ suggest potential health risks for drinking use. In general, Khijadia and Nal Sarovar represent saline systems, whereas Thol and Wadhvana are freshwater wetlands influenced by local hydrology and lithology. These lessons offer guidelines for monitoring and managing wetlands in semi-arid areas to sustain ecological and human health.
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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 | 0.000 | 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) | 0.001 | 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".