Sensitivity analysis of the Pesticide in Water Calculator model for applications in the Pampa region of Argentina
; Létourneau, Guillaume ; Rousseau, Alain ; Brodeur, Celine Marie Julie 
Otros responsables
Fecha
01/2020
Editorial
Elsevier Science
Revista
Science of the Total Environment
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Institución organizadora
ISSN
0048-9697
eISSN
1879-1026
ISBN
Idioma
Inglés
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Clasificación temática
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Resumen
Despite the widespread use of pesticides in the Pampa region of Argentina, mathematical models are rarely employed to predict pesticide fate due to the lack of regionally tested models and the absence of readily available databases to run such models. The objective of the current study was to perform a sensitivity analysis of the Pesticide in Water Calculator (PWC) model for the Pampa Region of Argentina. The sensitivity analysis was performed while simulating applications of 2,4-D (mobile, low Kd) and glyphosate (soil-binding, high Kd) in five localities of the Pampa region: Anguil, Paraná, Marcos Juárez, Pergamino and Tres Arroyos. The sensitivity of the various parameters involved in PWC modelling was evaluated though a two-steps sensitivity analysis which included a first screening of less sensitive parameters with Morris method, followed by a fully global sensitivity analysis of the remaining parameters using Sobol method. When ran under soil and climate conditions typical of the Pampa region of Argentina, PWC was most sensitive to 25% of the parameters evaluated. The sensitive parameters identified depended mainly on the nature of the pesticide molecule being modelled; the location and endpoint considered having much less influence on the sensitivity results. Sensitive parameters belonged to two main grand categories: (i) degradation rates of the pesticide in soil and water, and (ii) parameters descriptive of soil binding, runoff and erosion. The sensitivity analysis of the model PWC performed in the current study represents a crucial first step towards the development and expansion of probabilistic pesticide risk assessment in Argentina, and provides important parameterization criteria that will help obtaining more certain modelling results from PWC in Argentina and elsewhere.
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