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International audience; The pesticide registration process, as well as the chemical status of surface water bodies survey for the WFD reporting, involve interpreting data from public surface water monitoring networks. Identifying the main causes of the observed contamination is then useful to allow programming sound actions and/or verify mitigation measures efficiency. Two complementary methods were developed at France scale by Irstea and could help to perform those evaluations. This study, led with the support of the French Agency for Food, Environmental and Occupational Health & Safety, aims at testing and comparing those methods, for a range of eight pesticides which formulations are under re-registration process. The first method compensates the poor temporal representativeness of monitoring data at the sampling station scale by aggregating the observations by fortnights and at the hydro-ecoregions scale (homogeneous spatial units in terms of geology, relief, climate and land use -31 at the French scale-). The 90th centile concentration is calculated to obtain an envelope curve of the contamination. The results highlight that this method is relevant for discriminating spatial and temporal tendencies (inter and intra annual) of the surface water contamination. The second method, named ARPEGES, assesses the potential routes of surface water bodies’ contamination by single pesticides, the elementary spatial entity being the water body catchment (according to the WFD definition). It takes into account both pesticide characteristics (degradation and mobility), pesticide use and environmental vulnerability. The crossing rules, based on expert judgment and Bayesian network, allows identifying possible causes of contamination. The results showed that both methods were consistent. An on-going work consists in consolidating the comparison between the two methods considering a wider range of active substances and years, and a more accurate spatialized data for pesticide use, especially in view of the 2019 WFD reporting.

International audience; The pesticide registration process, as well as the chemical status of surface water bodies survey for the WFD reporting, involve interpreting data from public surface water monitoring networks. Identifying the main causes of the observed contamination is then useful to allow programming sound actions and/or verify mitigation measures efficiency. Two complementary methods were developed at France scale by Irstea and could help to perform those evaluations. This study, led with the support of the French Agency for Food, Environmental and Occupational Health & Safety, aims at testing and comparing those methods, for a range of eight pesticides which formulations are under re-registration process. The first method compensates the poor temporal representativeness of monitoring data at the sampling station scale by aggregating the observations by fortnights and at the hydro-ecoregions scale (homogeneous spatial units in terms of geology, relief, climate and land use -31 at the French scale-). The 90th centile concentration is calculated to obtain an envelope curve of the contamination. The results highlight that this method is relevant for discriminating spatial and temporal tendencies (inter and intra annual) of the surface water contamination. The second method, named ARPEGES, assesses the potential routes of surface water bodies’ contamination by single pesticides, the elementary spatial entity being the water body catchment (according to the WFD definition). It takes into account both pesticide characteristics (degradation and mobility), pesticide use and environmental vulnerability. The crossing rules, based on expert judgment and Bayesian network, allows identifying possible causes of contamination. The results showed that both methods were consistent. An on-going work consists in consolidating the comparison between the two methods considering a wider range of active substances and years, and a more accurate spatialized data for pesticide use, especially in view of the 2019 WFD reporting.