Pesticides groundwater modelling relies on input data characterised by a high intrinsic variability: Is the resulting risk for groundwater credible?

Abstract

In the framework of Regulation (EC) 1107/2009, concerning the placing of plant protection products (PPP) on the market, FOCUS models are used to predict active substances concentration in groundwater. The predicted environmental concentration in groundwater (PEC_GW) are influenced by active substance specific parameters, namely DT₅₀, K_OM and Freundlich coefficient (1/n), whose minimal variation in certain combinations of intervals significantly affects PEC_GW output. Considering that minimal variation are intrinsic in all laboratory studies, this approach may lead to not acceptable variations in the results for regulatory purposes. In the present article, PEC_GW were calculated for all maize crop scenarios, using 808 dummy active substances with different combinations of DT₅₀, K_OM and 1/n values, in order to quantify the influence of each single parameter on the final result of PEARL and PELMO models. The results obtained were used to create a classification system for the input parameters K_OM and DT₅₀ in order to minimise the input uncertainty effects. Even if this approach is scientifically viable yet, due to its conservative nature, it cannot be considered suitable in the regulatory framework, where acceptability of an active substance is strictly related to the limit value of 0.1 μg/L. Nevertheless, this classification system could represent an important screening or preliminary assessment to plan pesticide monitoring programmes. Based on the results of this analysis, it is believed that the assessment of pesticide leaching into groundwater should be revised to take into account this variability. Considering that both PEARL and PELMO FOCUS models deal with interaction between a chemical and a complex system like soil and weather, the selection of input data cannot pretend to rely on single specific number. Considering that intrinsic uncertainty cannot be eliminated from experimental work, a revision of the criteria used to identify the proper input data and a thorough revision of the actual groundwater modelling is recommended.

Keywords: Drinking water; Groundwater; PEARL; PELMO; Pesticides modelling; Regulation.