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Evaluation of water quality and risk assessment by coupled geospatial and statistical approach along lower Damodar river.
- Source :
- International Journal of Environmental Science & Technology (IJEST); Oct2022, Vol. 19 Issue 10, p9549-9570, 22p
- Publication Year :
- 2022
-
Abstract
- Groundwater quality is regulated by hydrological, physical, geochemical and biological factors. The current study assessed groundwater quality with the help of a water quality index by integrating the analysis of physicochemical parameters and heavy metals at 40 rural locations in Hooghly and Howrah districts along the lower Damodar river. The water quality index showed that 51.89 km<superscript>2</superscript> out of the 601.17 km<superscript>2</superscript> study area exceeded acceptable limits (water quality index > 100) of potable water. Arsenic was the most sensitive parameter followed by iron, manganese and fluoride. Bairakurchi area was severely contaminated due to high concentration of arsenic and iron, and Haraditiya was severely contaminated due to high concentration of iron. A risk assessment was performed for adults and children on exposure to heavy metals, using deterministic and probabilistic approaches. Monte Carlo simulation was applied for the probabilistic analysis and sensitivity analysis to determine the parameters most influencing risk hazard. The hazard index demonstrated that children were at higher risk than adults. The sensitivity analysis showed that concentration of heavy metals greatly influenced risk value. Principal component analysis and correlation matrix were applied to ascertain the relationship among the parameters. Five principal components were extracted with 76.29% cumulative variance. A strong correlation was found between heavy metals and physicochemical parameters, i.e. arsenic and iron (0.928), arsenic and manganese (0.809), iron and turbidity (0.867) and calcium and hardness (0.957). [ABSTRACT FROM AUTHOR]
- Subjects :
- WATER quality
GROUNDWATER quality
RISK assessment
HEAVY metals
MONTE Carlo method
Subjects
Details
- Language :
- English
- ISSN :
- 17351472
- Volume :
- 19
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- International Journal of Environmental Science & Technology (IJEST)
- Publication Type :
- Academic Journal
- Accession number :
- 159141360
- Full Text :
- https://doi.org/10.1007/s13762-021-03644-0