Assessment of Contamination Potential of Groundwater Adjacent to the Waste Disposal Site at Khulna: Contamination Indices, Multivariate Statistics and Geostatistical Approach

  • Rafizul I
  • Partha D
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Abstract

This study aimed to evaluate the contamination potential of groundwater using various contamination indices available in the literature. To these attempts, fifteen groundwater samples were collected during rainy and dry seasons from the selected tubewells located nearby waste disposal site at Rajbandh, Khulna, Bangladesh. In the laboratory, the concentration of metal elements such as Fe, Mn, Cr, Cu, Pb, Zn, Ni, Cd, Na, K, Ca, As and Mg in groundwater were measured through stanadard methods. The contamination indices such as groundwater quality index (GWQI), degree of contamination (Cd), heavy metal evaluation index (HEI) and heavy metal contamination index (HPI) were used to quantify the level of contamination of groundwater. The values of GWQI, Cd, HEI and HPI of groundwater were found less in rainy season than that of dry season due to dilution of groundwater. GWQI reveals that 26.67% of tubewells yield very poor, while, 73.33% of poor water condition. The result of principal component analysis (PCA) indicates that As contamination in groundwater caused from anthropogenic activities, while, Na, Ca and Mg from natural sources. Pearson’s correlations indicates that most of the metal elements were in highly positive correlations with each other. The spatial distribution of various indices reveals that contamination of groundwater was found comparatively higher in the nearest tubewells and decreases in relation to the increasing of water sampling distances. The outcome of this study will further be helpful for other researchers to quantify the level of contamination of groundwater from tubewells. Journal of Engineering Science 12(1), 2021, 9-20

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APA

Rafizul, I. M., & Partha, D. B. (2021). Assessment of Contamination Potential of Groundwater Adjacent to the Waste Disposal Site at Khulna: Contamination Indices, Multivariate Statistics and Geostatistical Approach. Journal of Engineering Science, 12(1), 9–20. https://doi.org/10.3329/jes.v12i1.53096

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