Abstract
Research investigated the robustness of Monte Carlo techniques when applied to pesticide fate models. Work focused on predictions for leaching of a hypothetical pesticide to groundwater using the PELMO model. The robustness of the Monte Carlo approach was estimated by i) repeating the probabilistic modelling 10 times using different seed numbers (the seed number is used to initiate the generation of random sequences) for various number of model runs; and ii) assessing the dependence of Monte Carlo results on small variations in the procedures for parameterising statistical distributions for Koc and DT50. Monte Carlo results were found to be inherently variable (CV 5 to 211% for 10 replicates) even when a relatively large number of model runs (5000) were undertaken. Results were also found to be affected by slight changes in the parameterisation of probability density functions and in the assignment of correlation between parameters. The levels of variability reported have the potential to affect regulatory decisions. The findings suggest that extreme care should be exercised when undertaking Monte Carlo modelling or assessing the results of probabilistic modelling.
| Original language | English |
|---|---|
| Title of host publication | PESTICIDE IN AIR, PLANT, SOIL & WATER SYSTEM |
| Editors | AAM DelRe, E Capri, L Padovani, M Trevisan |
| Place of Publication | 27100 PAVIA |
| Publisher | LA GOLIARDICA PAVESE |
| Pages | 409-415 |
| Number of pages | 7 |
| ISBN (Print) | 88-7830-359-3 |
| Publication status | Published - 2003 |
Keywords
- uncertainty
- risk assessment
- probabilistic
- Monte Carlo
- reliability
- DATA SET
- UNCERTAINTY
- SENSITIVITY