Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Sensitivity analyses for four pesticide leaching models.

Igor G Dubus1, Colin D Brown, Sabine Beulke

  • 1Cranfield Centre for EcoChemistry, Cranfield University, Silsoe, Beds MK45 4DT, UK. i.dubus@brgm.fr

Pest Management Science
|September 17, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The prevalence and acceptability of mesocosm studies submitted for macrophytes in pesticide risk assessment.

Integrated environmental assessment and management·2025
Same author

A User-Friendly Kinetic Model Incorporating Regression Models for Estimating Pesticide Accumulation in Diverse Earthworm Species Across Varied Soils.

Environmental science & technology·2024
Same author

Evaluation of models to estimate the bioaccumulation of organic chemicals in earthworms.

Ecotoxicology and environmental safety·2024
Same author

Earthworm lipid content and size help account for differences in pesticide bioconcentration between species.

Journal of hazardous materials·2024
Same author

Effects of soil redistribution by tillage on subsequent transport of pesticide to subsurface drains.

Pest management science·2022
Same author

A knowledge-based approach to designing control strategies for agricultural pests.

Agricultural systems·2020

Pesticide leaching models show high sensitivity to input parameters, particularly those affecting chemical sorption and degradation. Addressing uncertainty in these factors is crucial for accurate crop protection risk assessment.

Area of Science:

  • Environmental Science
  • Soil Science
  • Agricultural Chemistry

Background:

  • Pesticide registration in Europe relies on leaching models like PELMO, PRZM, PESTLA, and MACRO.
  • Understanding model sensitivity to input parameters is vital for accurate environmental risk assessment.

Purpose of the Study:

  • To conduct sensitivity analyses on widely used European pesticide leaching models.
  • To investigate the influence of parameter uncertainty on model predictions for pesticide leaching and water balance.

Main Methods:

  • One-at-a-time sensitivity analyses were performed on four leaching models (PELMO, PRZM, PESTLA, MACRO).
  • Simulations involved two theoretical pesticides across sandy loam and clay loam soils under four scenarios.
  • Input parameters were varied within uncertainty bounds to assess impact on percolation and leachate loading.

Related Experiment Videos

Main Results:

  • Model predictions for base-case scenarios varied, with MACRO showing transient high losses in clay loam.
  • Percolation predictions were minimally sensitive to a few parameters, driven mainly by meteorology.
  • Pesticide loss predictions exhibited high sensitivity to numerous parameters, especially sorption (Kf, nf) and degradation (DT50, QTEN).
  • Soil properties also influenced predictions, and sensitivity was greater with limited leaching.

Conclusions:

  • Pesticide loss predictions are highly sensitive to chemical sorption and degradation parameters.
  • Model uncertainty, particularly in these parameters, must be addressed in crop protection risk assessments.
  • Meteorological variables are key drivers for water balance predictions in these models.