User subjectivity in Monte Carlo modeling of pesticide exposure

• Published in: Environmental toxicology and chemistry 2006-08, Vol.25 (8), p.2227-2236
• Main Authors: Beulke, Sabine, Brown, Colin D., Dubus, Igor G., Galicia, Hector, Jarvis, Nicholas, Schaefer, Dieter, Trevisan, Marco
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Degradation; Earth Sciences; Ecotoxicology, biological effects of pollution; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Techniques; Leachates; Leaching; Methods and techniques (sampling, tagging, trapping, modelling...); Moisture content; Monte Carlo; Monte Carlo Method; Monte Carlo simulation; Pesticide exposure modeling; Pesticides; Pesticides - toxicity; Probability; River basins; Samples; Sciences of the Universe; Soil Pollutants - toxicity; Soils; Sorption; Surface water; User subjectivity
• ISSN: 0730-7268; 1552-8618
• DOI: 10.1897/05-332R.1

Monte Carlo techniques are increasingly used in pesticide exposure modeling to evaluate the uncertainty in predictions arising from uncertainty in input parameters and to estimate the confidence that should be assigned to the modeling results. The approach typically involves running a deterministic model repeatedly for a large number of input values sampled from statistical distributions. In the present study, six modelers made choices regarding the type and parameterization of distributions assigned to degradation and sorption data for an example pesticide, the correlation between the parameters, the tool and method used for sampling, and the number of samples generated. A leaching assessment was carried out using a single model and scenario and all data for sorption and degradation generated by the six modelers. The distributions of sampled parameters differed between the modelers, and the agreement with the measured data was variable. Large differences were found between the upper percentiles of simulated concentrations in leachate. The probability of exceeding 0.1 μg/L ranged from 0 to 35.7%. The present study demonstrated that subjective choices made in Monte Carlo modeling introduce variability into probabilistic modeling and that the results need to be interpreted with care.