Compound-specific stable isotope analysis of pesticides: a combined monitoring and modeling approach to assess pesticide fate and degradation at catchment scale

Thursday, 18 December 2014: 11:05 AM
Boris Maurijn van Breukelen1, Stefanie Lutz1, Ype Van der Velde2, O. F. Elsayed3, Marie LeFrancq3, Sylvain Payraudeau3 and Gwenaël Imfeld3, (1)Free University of Amsterdam, Amsterdam, Netherlands, (2)Wageningen University, Wageningen, Netherlands, (3)University of Strasbourg, Strasbourg Cedex, France
Compound-specific stable isotope analysis (CSIA) has proven useful in asessing the fate of groundwater contamination. However, although evidence of diffuse pesticide degradation is crucial, and CSIA methods have been developed for several pesticides, there is a clear lack of field CSIA data of pesticides. This study now presents the first analysis of field CSIA data from a 47-ha agricultural headwater catchment (Alteckendorf, Alsace, France) in the period March to August 2012. Measured stream concentrations of the two investigated chloroacetanilide herbicides (S-metolachlor and acetochlor) were highest (65 μg/L) following an intense rainfall event in the first month after herbicide application. Carbon isotope ratios increased with more than 2 ‰ in 3 months, which indicates the occurrence of herbicide degradation during transport to the stream. Previously, field CSIA data have also been simulated with reactive transport models to evaluate degradation of groundwater contaminants. This study now presents such a model-assisted interpretation of CSIA data for the first time at catchment scale, which aims at exploring the added value of CSIA in monitoring and modelling of pesticide pollution. The conceptual mathematical model succeeded in reproducing the general trend in concentrations and carbon isotope ratios of metolachlor. It also allowed for the quantification of metolachlor degradation (above 70 % during the study period), and yielded a mass export of 1.8 % of the applied pesticide, which is in agreement with the measured pesticide export. The field concentration and CSIA data informed the model building by indicating the importance of overland flow, and slow pesticide degradation in groundwater compared to the upper soil zone. Moreover, incorporation of the field CSIA data into model calibration slightly reduced model uncertainty in the quantification of pesticide degradation. We suggest that a finer temporal CSIA resolution than possible in this study, especially during base flow conditions, would result in a more significant reduction of model uncertainty. Nonetheless, these results demonstrate how a combined monitoring and modelling approach of concentration and CSIA data can result in an improved understanding of pesticide transport and degradation at catchment scale.