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Sequential use of the STICS crop model and of the MACRO pesticide fate model to simulate pesticides leaching in cropping systems

  • Fate and impact of pesticides: new directions to explore
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Abstract

The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

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Acknowledgments

The authors are grateful to Pascal Farcy (INRA, UE Domaine d’Epoisses, Bretenière), Simon Giuliano, Gaël Rametti and François Perdrieux (INP-EI Purpan – UMR 1248 AGIR, Lamothe), and Arnaud Coffin and Frédéric Lombard (Université Bourgogne Franche-Comté, AgroSup Dijon, UMR 1347 Agroécologie) for providing field experimental data. They also thank Nick Jarvis for his help in developing the unofficial release of MACRO. This project was supported by the research program “For the Ecophyto plan (PSPE1)” funded by the French Ministry in charge of Agriculture (Perform project), by the research program “Assessing and reducing environmental risks from plant protection products” funded by the French Ministries in charge of Ecology and Agriculture (Ecopest project), and by the French Ministry in charge of Agriculture and by ONEMA (System-Eco-Puissance4 project). The field experiments are part of the DEPHY network. Sabine-Karen Lammoglia was supported by INRA (National Institute for Agricultural Research) (SMASH metaprogramme) and by the Perform project.

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Authors and Affiliations

  1. UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay, 78850, Thiverval-Grignon, France

    Sabine-Karen Lammoglia, Enrique Barriuso, Jesús-María Marín-Benito & Laure Mamy

  2. Department of Soil and Environment, Swedish University of Agricultural Sciences, 750 07, Uppsala, Sweden

    Julien Moeys & Mats Larsbo

  3. IRNASA-CSIC, 40-52 Cordel de Merinas, 37008, Salamanca, Spain

    Jesús-María Marín-Benito

  4. UMR AGIR, INRA, Auzeville, 31326, Castanet-Tolosan, France

    Eric Justes

  5. Université de Toulouse, INP-Ecole d’ingénieurs de Purpan, UMR AGIR, 75 voie du TOEC, 31076, Toulouse, France

    Lionel Alletto

  6. Université Bourgogne Franche-Comté, AgroSup Dijon, UMR Agroécologie, 26 bd Dr Petitjean, 21079, Dijon, France

    Marjorie Ubertosi & Bernard Nicolardot

  7. UMR Agroécologie, INRA, 17 rue Sully, 21065, Dijon, France

    Nicolas Munier-Jolain

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  1. Sabine-Karen Lammoglia
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  2. Julien Moeys
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  3. Enrique Barriuso
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  11. Laure Mamy
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Correspondence to Laure Mamy.

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Lammoglia, SK., Moeys, J., Barriuso, E. et al. Sequential use of the STICS crop model and of the MACRO pesticide fate model to simulate pesticides leaching in cropping systems. Environ Sci Pollut Res 24, 6895–6909 (2017). https://doi.org/10.1007/s11356-016-6842-7

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