An integrated multivariate statistical approach for the evaluation of spatial variations in groundwater quality near an unlined landfill

Abstract

Groundwater is a major resource for water supply in Canada, and 43 of 68 Saskatchewan municipalities rely on groundwater or combined groundwater and surface water sources. The Regina landfill is built on top of the Condie aquifer, without an engineered liner. Missing data and inconsistent sampling make a traditional groundwater assessment difficult. An integrated statistical approach using principle component analysis, correlation analysis, ion plots, and multiple linear regression is used to study groundwater contamination at the Regina landfill. Geological locations of the water samples were explicitly considered. The abundance of cations in the groundwater was Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ > Mn²⁺; and for anions SO₄²⁻ > HCO₃⁻ > Cl⁻. Correlation analysis and ion plots pointed to gypsum and halite dissolution being the main factors affecting groundwater chemistry. Principal component analysis yielded three principal components, responsible for 80.7% of the total variance. For all monitoring well groups, the sodium absorption ratio was generally less than one. The variation in the ratio from monitoring well groups suggests possible groundwater contamination from landfill operation. Wilcox diagrams indicate groundwater near the landfill is unsuitable for irrigation. A two-step multiple linear regression was used to develop a model for total hardness prediction.

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