Sensitivity analysis of the STICS-MACRO model to identify cropping practices reducing pesticides losses

Lammoglia Sabine Karen Djidemi, Makowski David, Moeys Julien, Justes Eric, Barriuso Enrique, Mamy Laure. 2017. Sensitivity analysis of the STICS-MACRO model to identify cropping practices reducing pesticides losses. Science of the Total Environment, 580 : 117-129.

Quartile : Q1, Sujet : ENVIRONMENTAL SCIENCES

Résumé : STICS-MACRO is a process-based model simulating the fate of pesticides in the soil-plant system as a function of agricultural practices and pedoclimatic conditions. The objective of this work was to evaluate the influence of crop management practices on water and pesticide flows in contrasted environmental conditions. We used the Morris screening sensitivity analysis method to identify the most influential cropping practices. Crop residues management and tillage practices were shown to have strong effects on water percolation and pesticide leaching. In particular, the amount of organic residues added to soil was found to be the most influential input. The presence of a mulch could increase soil water content so water percolation and pesticide leaching. Conventional tillage was also found to decrease pesticide leaching, compared to no-till, which is consistent with many field observations. The effects of the soil, crop and climate conditions tested in this work were less important than those of cropping practices. STICS-MACRO allows an ex ante evaluation of cropping systems and agricultural practices, and of the related pesticides environmental impacts.

Mots-clés Agrovoc : système de culture, pesticide, lutte biologique

Classification Agris : F08 - Systèmes et modes de culture
H01 - Protection des végétaux - Considérations générales

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

• Lammoglia Sabine Karen Djidemi, INRA (FRA) ORCID: 0000-0002-8807-2791
• Makowski David, AgroParisTech (FRA)
• Moeys Julien, Swedish University of Agricultural Sciences (SWE)
• Justes Eric, CIRAD-PERSYST-UMR SYSTEM (FRA) ORCID: 0000-0001-7390-7058
• Barriuso Enrique, INRA (FRA)
• Mamy Laure, INRA (FRA) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/589372/)

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