Biases in the spatial estimation of pesticide loss to groundwater

Yves Coquet , Dalila Hadjar , Jean-Marc Gilliot , Marie-Paule Charnay , Julien Moeys , Alexandre Dufour , Nicolas Beaudoin (1)

1 INRA - Institut National de la Recherche Agronomique

Prediction of pesticide fate in soils is highly sensitive to parameters describing sorption and degradation processes, namely the Koc partioning coefficient between the soil solution and organic carbon fraction and the half-life DT50 for degradation. This paper explores the impact of getting Koc and DT50 values either from databases or from site-specific measurements on the predicted fate of atrazine, isoproturon and metamitron on the catchment scale. Pesticide fate on the scale of the Bruyères-et-Montbérault catchment, France, was predicted using the SEAMS software that couples a one-dimensional local-scale model of pesticide fate to a geographic information system. The results show that the use of database average values for Koc and DT50 underestimates the average risk of pesticide leaching calculated from site-specific Koc and DT50 values, whereas maximised risk scenarios based on extreme Koc and DT50 values may be overestimated when using database values. Whenever available, site-specific data should be preferred to limit bias in pesticide leaching risk assessments on the catchment scale.

Mots clés: herbicide; pesticide fate; spatial variability; soil; environmental risk assessment

Domaines: Sciences agricoles; Ecologie, Environnement

Yves Coquet, Dalila Hadjar, Jean-Marc Gilliot, Marie-Paule Charnay, Julien Moeys, et al.. Biases in the spatial estimation of pesticide loss to groundwater. Agronomy for Sustainable Development, 2005, 25 (4), pp.465-472. ⟨hal-00886307⟩