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1.
Environ Monit Assess ; 195(2): 272, 2023 Jan 06.
Article in English | MEDLINE | ID: mdl-36607446

ABSTRACT

This paper demarcated the most vulnerable regions within the Poiney sub-basin (Tamil Nadu state in India) with respect to the groundwater quality. An index-based vulnerability assessment was carried out by measuring the physico-chemical variables such as pH, electrical conductivity, total dissolved solids, magnesium, sodium, chloride, sulphate, bicarbonate and fluoride in the pre-monsoon and post-monsoon samples. Water quality index varied across the sub-basin due to differences in the water quality induced by anthropogenic activities related to land use practices and presence of industries. The MT3D engine coupled with visual MODFLOW identified that sulphate released from tanneries and leather factories is the main effluent contaminating the groundwater. Model reveals that both the flow and contaminant transport is towards southeast with maximum and minimum calculated head of 201.82 mg/l and 265.92 mg/l and calculated sulphate concentration of 394.40 mg/l and 46.79 mg/l respectively.


Subject(s)
Groundwater , Water Pollutants, Chemical , Water Quality , Water Supply , India , Environmental Monitoring/methods , Water Pollutants, Chemical/analysis , Sulfates/analysis
2.
Environ Res ; 204(Pt B): 112069, 2022 03.
Article in English | MEDLINE | ID: mdl-34555406

ABSTRACT

Consideration of groundwater vulnerability as a planning parameter is imperative in the current context of depleting groundwater resources for the efficient land use planning. This study aims for groundwater vulnerability assessment by modifying SINTACS model and involve dynamics of land use change in a case study of Paravanar sub-basin in the Tamil Nadu state of south India. Thematic maps of land use generated from remote sensing data and associated field investigations were the input for the SINTACS model. These maps integrated in GIS helped to derive intrinsic vulnerability into very low, low, medium and high vulnerability categories. The strongest correlation (r = 0.74) between intrinsic vulnerability index and the water quality index, estimated from field observations, suggested better efficiency of this model compared to the conventional SINTACS index. Application of the modified SINTACS led to the conclusion that 12.2%, 28.7%, 45.9%, and 13.1% of the study area categorized very low vulnerability, low vulnerability, moderate vulnerability and high vulnerability, respectively and should be considered for efficient land use planning.


Subject(s)
Environmental Monitoring , Groundwater , India , Water Quality
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