Hydrogeochemical Assessment and Irrigation Suitability of Groundwater in Banaskantha’s Vegetation Zone, India
Why this work is in the frame
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Bibliographic record
Abstract
Groundwater serves as the principal supply of water for home and agricultural purposes in the semi-arid Banaskantha district of Gujarat, India. This study provides a thorough hydrogeochemical analysis of 207 groundwater samples that were taken during the post-monsoon season in 2021 from the vegetation zone. pH, EC, TDS, TH, Ca2+, Mg2+, Na+, K+, Cl-, SO₄²⁻, HCO₃⁻, CO₃²⁻, NO₃⁻, and F⁻ were among the physicochemical parameters that were examined and contrasted with BIS and WHO standards. The majority of the samples have high salinity, excessive hardness, and high levels of carbonate and chloride, according to the results, making the water mostly unfit for human consumption. Rock-water interactions, evaporation, and human inputs have modified the hydrochemical facies characterised by Piper and Durov diagrams, which show the dominance of Ca–Mg–Cl–SO₄ and Na–Cl types. In addition to the Irrigation Water Quality Index (IWQI), indices like SAR, MAR, KR, PI, PS, and RSC were used to assess irrigation suitability. Irrigation use is restricted by high magnesium hazard and heightened potential salinity, even if SAR readings indicate low sodicity hazard. Evaluation of irrigation water quality using IWQi values shows that only 1.45% of samples fall under the ‘no restriction’ category, while 18.84% have ‘low restriction.’ About 35.27% of samples are classified as ‘moderate restriction,’ and 39.61% as ‘high restriction,’ raising concerns about long-term soil and crop health. A further 4.83% fall into the ‘severe restriction’ class, indicating unsuitability for irrigation." Critical salinity and alkalinity danger zones are highlighted by spatial distribution mapping using GIS. To ensure stable agricultural output, the results underscore the crucial need for sustainable groundwater management and soil-water conservation techniques. These findings underscore the urgent need for sustainable groundwater management, soil–water conservation strategies, and policy interventions focused on regulating groundwater extraction, promoting efficient irrigation practices, and ensuring long-term water security in the region.
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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) | 0.000 | 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 it