Pesticide vulnerability assessment considers both pesticides properties and the environmental conditions. As mentioned earlier, pesticide properties govern its persistence and mobility in the environment and consequently the pesticide vulnerability of the environment. Therefore, pesticide vulnerability assessment should consider both aspects.

The predictive power of these pesticide risk indicators may vary greatly depending on their structure. For instance, Pierlot et al. (2017) evaluated the predictive quality of 26 pesticide risk indicators. They compared results among the indicators and with measured data from three sites in France as well. They reported that the more complicated risk indicators were, the better predictive their quality was. For instance, MACRO, which is a process-based model of 1-D flow of water and pesticides, showed the best predictive power. While the indicators that only based on the pesticides dose (e. g. TFI) showed the lowest predictive quality.

A pesticide vulnerability map at the European level is available (Tiktak et al., 2006).


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