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Record W4415077006 · doi:10.9734/ijecc/2025/v15i105066

Hydrogeochemical Assessment and Irrigation Suitability of Groundwater in Banaskantha’s Vegetation Zone, India

2025· article· en· W4415077006 on OpenAlex
Mukesh P. Chaudhari, Gh Ali, Ravi Patadiya, Pratik Chavda, Pranav S Shrivsatav

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Environment and Climate Change · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater and Watershed Analysis
Canadian institutionsLambton College
Fundersnot available
KeywordsIrrigationGroundwaterHydrology (agriculture)AlkalinityVegetation (pathology)Dominance (genetics)Water qualityIrrigation statistics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.263
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it