Sources of uncertainty in pesticide fate modelling

I G Dubus, C D Brown, S Beulke

Research output: Contribution to journalLiterature reviewpeer-review

Abstract

There is worldwide interest in the application of probabilistic approaches to pesticide fate models to account for uncertainty in exposure assessments. The first steps in conducting a probabilistic analysis of any system are: 0) to identify where the uncertainties come from; and (ii) to pinpoint those uncertainties that are likely to affect most of the predictions made. This article aims at addressing those two points within the context of exposure assessment for pesticides through a review of the different sources of uncertainty in pesticide fate modelling. The extensive listing of sources of uncertainty clearly demonstrates that pesticide fate modelling is laced with uncertainty. More importantly, the review suggests that the probabilistic approaches, which are typically being deployed to account for uncertainty in the pesticide fate modelling, such as Monte Carlo modelling, ignore a number of key sources of uncertainty, which are likely to have a significant effect on the prediction of environmental concentrations for pesticides (e.g. model error, modeller subjectivity). Future research should concentrate on quantifying the impact these uncertainties have on exposure assessments and on developing procedures that enable their integration within probabilistic assessments. (C) 2003 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)53-72
Number of pages20
JournalScience of the Total Environment
Volume317
Issue number1-3
DOIs
Publication statusPublished - 30 Dec 2003

Keywords

  • uncertainty
  • sensitivity
  • Monte Carlo
  • probabilistic
  • pesticide
  • model
  • leaching
  • PROBABILISTIC RISK ASSESSMENT
  • MONTE-CARLO TECHNIQUES
  • ROOT-ZONE MODEL-3.12
  • SPATIAL VARIABILITY
  • LEACHING MODELS
  • REGIONAL-SCALE
  • SENSITIVITY-ANALYSIS
  • FIELD-SCALE
  • GROUNDWATER VULNERABILITY
  • STOCHASTIC SIMULATION

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