INCORPORATING UNCERTAINTY IN A CHEMICAL LEACHING ASSESSMENT

Pesticide leaching models are being used to assist in the regulation a nd management of pesticides by indicating their potential for leaching to groundwater. Uncertainty in model input data is not, regrettably, included in most pesticide leaching assessments. In the work described here, we use logarithmic transformations of the attenuation factor (A F), a simple process-based index model, to represent uncertainty in a pesticide leaching assessment. Characterization of a wide range of pes ticides as 'leachers' or 'non-leachers' for a specific Hawaii hydrogeo logical setting is facilitated by comparing the log-transformed AF, de signated AFR, for each chemical with two reference chemicals for which leaching behavior in Hawaii is known. Defining a mean and uncertainty interval for the AFR index of each chemical being ranked provides a p ractical method of incorporating data uncertainty into a regulatory pr otocol. (C) 1998 Elsevier Science B.V.