Devasena, M and Bivin Ebeneze, S (2023) Geostatistical modelling of groundwater quality for irrigation: a case study of Mayiladuthurai district, Tamil Nadu. Modeling Earth Systems and Environment, 9 (2). pp. 1811-1823. ISSN 2363-6203
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Abstract
The present work was carried out in the district of Mayiladuthurai, Tamil Nadu, India, which forms the delta part of the river Cauvery. Groundwater quality parameters of pre-monsoon and post-monsoon seasons of nine consecutive years were analysed to evaluate the status of groundwater quality for irrigation. Water quality data were initially subjected to cation–anion balance error analysis. Cluster analysis was then performed on data sets using SPSS software from which three clusters were identified based on the level of water contamination. Principal component analysis of water quality showed that factors such as seawater intrusion, anthropogenic activity and natural geology lead to deterioration of water quality in that region. Using Schoeller diagram, major ions in the water were found to be Na+, HCO3−, Cl−, Mg2+ and SO42−. From the Piper diagram, water type was predicted to be a mixed water type indicating that freshening of aquifer is essential. Weighted overlay analysis was performed using seven selective parameters that affected irrigation water quality using QGIS; it was found that groundwater quality falls under suitable zone in 53% of agricultural area and moderately suitable zone in 47% of agricultural area. Major factor contributing to decline in water quality was salinity, followed by magnesium hazard, as inferred from sensitivity analysis performed on the different water quality parameters
Item Type: | Article |
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Uncontrolled Keywords: | aquifer; cluster analysis; error analysis; geostatistics; GIS; groundwater; irrigation; magnesium; principal component analysis; qualitative analysis; salinity; software; water chemistry; water quality; water resource |
Subjects: | B Civil Engineering > Water Resource planning |
Divisions: | Civil Engineering |
Depositing User: | Users 5 not found. |
Date Deposited: | 19 Jul 2024 08:25 |
Last Modified: | 19 Aug 2024 03:29 |
URI: | https://ir.psgitech.ac.in/id/eprint/771 |