Combining stable isotopes with contamination indicators: A method for improved investigation of nitrate sources and...

Excessive nitrate (NO₃^-) concentration in groundwater raises health and environmental issues that must be addressed by all European Union (EU) member states under the Nitrates Directive and the Water Framework Directive. The identification of NO₃^- sources is critical to efficiently control or reverse NO₃^- contamination that affects many aquifers. In that respect, the use of stable isotope ratios ¹⁵N/¹⁴N and ¹⁸O/¹⁶O in NO₃^- (expressed as δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-, respectively) has long shown its value. However, limitations exist in complex environments where multiple nitrogen (N) sources coexist. This two-year study explores a method for improved NO₃^- source investigation in a shallow unconfined aquifer with mixed N inputs and a long established NO₃^- problem. In this tillage-dominated area of free-draining soil and subsoil, suspected NO₃^- sources were diffuse applications of artificial fertiliser and organic point sources (septic tanks and farmyards). Bearing in mind that artificial diffuse sources were ubiquitous, groundwater samples were first classified according to a combination of two indicators relevant of point source contamination: presence/absence of organic point sources (i.e. septic tank and/or farmyard) near sampling wells and exceedance/non-exceedance of a contamination threshold value for sodium (Na⁺) in groundwater. This classification identified three contamination groups: agricultural diffuse source but no point source (D+P-), agricultural diffuse and point source (D+P+) and agricultural diffuse but point source occurrence ambiguous (D+P±). Thereafter δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- data were superimposed on the classification. As δ¹⁵N-NO₃^- was plotted against δ¹⁸O-NO₃^-, comparisons were made between the different contamination groups. Overall, both δ variables were significantly and positively correlated (p < 0.0001, r_s = 0.599, slope of 0.5), which was indicative of denitrification. An inspection of the contamination groups revealed that denitrification did not occur in the absence of point source contamination (group D+P-). In fact, strong significant denitrification lines occurred only in the D+P+ and D+P± groups (p < 0.0001, r_s > 0.6, 0.53 ≤ slope ≤ 0.76), i.e. where point source contamination was characterised or suspected. These lines originated from the 2-6‰ range for δ¹⁵N-NO₃^-, which suggests that i) NO₃^- contamination was dominated by an agricultural diffuse N source (most likely the large organic matter pool that has incorporated ¹⁵N-depleted nitrogen from artificial fertiliser in agricultural soils and whose nitrification is stimulated by ploughing and fertilisation) rather than point sources and ii) denitrification was possibly favoured by high dissolved organic content (DOC) from point sources. Combining contamination indicators and a large stable isotope dataset collected over a large study area could therefore improve our understanding of the NO₃^- contamination processes in groundwater for better land use management. We hypothesise that in future research, additional contamination indicators (e.g. pharmaceutical molecules) could also be combined to disentangle NO₃^- contamination from animal and human wastes.