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 and first-step uncertainty analyses for the preferential flow model MACRO.

Igor G Dubus1, Colin D Brown

  • 1Cranfield Centre for EcoChemistry, Cranfield University, Silsoe, Bedfordshire,UK. i.dubus@cranfield.ac.uk

Journal of Environmental Quality
|February 12, 2002
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

Sensitivity analyses of the MACRO model show pesticide losses are highly sensitive to sorption and degradation parameters, unlike water percolation which is mainly influenced by soil pore structure. Uncertainty in pesticide loss predictions is significant.

Area of Science:

  • Environmental Science
  • Soil Science
  • Hydrology

Background:

  • Preferential flow models like MACRO are crucial for assessing pesticide leaching.
  • Understanding model sensitivity and uncertainty is vital for accurate environmental risk assessment.

Purpose of the Study:

  • To perform sensitivity analyses on the MACRO model using one-at-a-time and Monte Carlo approaches.
  • To assess the sensitivity of pesticide leaching predictions to various input parameters in different soil types.

Main Methods:

  • Simulated leaching of two hypothetical pesticides in sandy loam and clay loam soils.
  • Assessed model sensitivity using predictions of accumulated water percolation and pesticide losses at 1-m depth.
  • Varied input parameters within uncertainty ranges for a first-step uncertainty assessment.

Related Experiment Videos

Main Results:

  • Water percolation predictions showed minimal sensitivity to input parameters, primarily influenced by micropore-macropore water content.
  • Pesticide loss predictions were highly sensitive to sorption and degradation parameters, varying with simulation scenarios.
  • Hydrological properties significantly impacted pesticide losses under specific conditions, highlighting substantial prediction uncertainty.

Conclusions:

  • Pesticide loss predictions from the MACRO model exhibit significant uncertainty, influenced by parameter variability.
  • A probabilistic framework is recommended for integrating uncertainty into pesticide exposure estimations for regulatory purposes.
  • Model sensitivity differs between water flow and solute transport, emphasizing the need for careful parameterization.