Surface Water Intrusion, Land Use Impacts, and Bacterial Community Composition in Shallow Groundwater Wells Supplying Potable Water in Sparsely Populated Areas of a Boreal Region

Abstract

Rural communities often rely on groundwater for potable water supply. In this study, untreated groundwater samples from 28 shallow groundwater wells in Finland (<10 m deep and mostly supplying untreated groundwater to <200 users in rural areas) were assessed for physicochemical water quality, stable water isotopes, microbial water quality indicators, host-specific microbial source tracking (MST) markers, and bacterial community composition, activity, and diversity (using amplicon sequencing of the 16S rRNA gene and 16S rRNA). Indications of surface water intrusion were identified in five wells, and these indications were found to be negatively correlated, overall, with bacterial alpha diversity (based on amplicon sequencing of the 16S rRNA gene). High levels of turbidity, heterotrophs, and iron compromised water quality in two wells, with values up to 2.98 nephelometric turbidity units (NTU), 16,000 CFU/ml, and 2,300 μg/liter, respectively. Coliform bacteria and general fecal indicator Bacteroidales bacteria (GenBac3) were detected in 14 and 10 wells, respectively (albeit mostly at low levels), and correlations were identified between microbial, physicochemical, and environmental parameters, which may indicate impacts from nearby land use (e.g., agriculture, surface water, road salt used for deicing). Our results show that although water quality was generally adequate in most of the studied wells, the continued safe use of these wells should not be taken for granted. IMPORTANCE Standard physicochemical water quality analyses and microbial indicator analyses leave much of the (largely uncultured) complexity of groundwater microbial communities unexplored. This study combined these standard methods with additional analyses of stable water isotopes, bacterial community data, and environmental data about the surrounding areas to investigate the associations between physicochemical and microbial properties of 28 shallow groundwater wells in Finland. We detected impaired groundwater quality in some wells, identified potential land use impacts, and revealed indications of surface water intrusion which were negatively correlated with bacterial alpha diversity. The potential influence of surface water intrusion on groundwater wells and their bacterial communities is of particular interest and warrants further investigation because surface water intrusion has previously been linked to groundwater contamination, which is the primary cause of waterborne outbreaks in the Nordic region and one of the major causes in the United States and Canada.

Keywords: 16S rRNA; bacteria; drinking water; groundwater; groundwater bacteria; isotopes; microbial diversity; potable water; rural; water quality; water supply; wells.

FIG 1

Boxplots showing physicochemical data for the 28 shallow groundwater wells. Some relatively extreme values were removed to improve plot readability. These values are indicated below the plots from which they were removed, with the corresponding well numbers given in respective order. Medians were not significantly affected by removal of these values. Boxplots were generated in R.

FIG 2

Stable water isotope results from the wells compared to surface water samples and to rainfall. Data for Oulanka local meteoric water line (LMWL) and Rokua and Posio local evaporation lines (LEL) were taken from previous studies (72, 73, 99). Wells with various d-excess values and/or alignment with LEL lines are marked with well numbers.

FIG 3

Boxplots showing differences between alpha diversity metrics in DNA- and cDNA-derived 16S amplicons. Boxplots were generated in R.

FIG 4

Heatmap showing differences in bacterial communities based on taxonomic classifications of DNA- and cDNA-derived 16S amplicons generated in QIIME 2 using the SSU SILVA 132 majority taxonomy. The heatmap was generated in R (using the pheatmap package) (113) from the log-transformed relative abundance values of bacterial classes which had a relative abundance of 5% or more in at least one library. Columns were clustered using average linkage hierarchical clustering based on the Bray–Curtis dissimilarity matrix of the data set (using the vegan package) (116).

FIG 5

Correlograms showing (A) correlations between physicochemical data, microbiological data, and environmental data and (B) correlations between physicochemical data and alpha diversity metrics. Both correlograms were constructed using a Spearman rank-based correlation coefficient matrix and associated P values. Only the statistically significant correlations (P < 0.05) are shown. Red colors are positive correlations. Blue colors are negative correlations. In each case, the intensity of the color indicates the strength of the correlation. Spearman rank-based correlation coefficients were calculated using the rcorr function from the Hmisc R package (114), and correlograms were produced using the corrplot function from the corrplot R package (115). ¹SFS 3016 method, ²ISO 9308-1 method.

FIG 6

Nonmetric multidimensional scaling (NMDS) based on sequence analysis of bacterial 16S rRNA on the DNA (blue) and cDNA (red) levels. Comparison of bacterial communities on the DNA and cDNA levels (A) and effect of environmental parameters on bacterial community composition on the DNA (B) and cDNA (C) levels. In panel A, dispersion ellipses indicate centroids of microbial communities on the DNA and cDNA levels. In panels B and C, selected environmental parameters (P ≤ 0.05) fitted to the ordinations are indicated by arrows. Well numbers are indicated inside the data points.

FIG 7

Map of the well locations and the sampling sites and regions for additional stable water isotope samples for rain (black point; Oulanka LMWL, reference 72) and surface water evaporation (lined areas; Rokua LEL, reference , and Posio LEL, reference 99). LMWL, local meteoric water line; LEL, local evaporation line.