A methodology to develop a GIS-based system for the surface water risk assessment of agricultural chemicals is described. It is based on the integration of relational and spatial databases, GIS incorporating raster and vector, mass balance models, and pesticide risks indicators. Surface water pollution was modeled by taking into account two main processes: the load due to drift and the load due to a rainfall−runoff event. The former is immediately consequent to pesticide application; the second occurs a short period afterward. Thus two distinct PEC (predicted environmental concentration) values were estimated, differing in time. A pilot approach was applied to the herbicide alachlor on corn in Lombardia region (northern Italy) and represents the first stage of a wider project. Although the resultant alachlor PEC and risk maps represent a static image of a worst-case simulation, the main objective was to provide information for the territory with respect to relative risks at the watershed level, which is important in managing risks to the aquatic environment. The driving forces and spatial variability of the above-mentioned processes were investigated to improve knowledge about the territory and to indicate the need for more detailed site-specific studies.

A methodology to develop a GIS-based system for the surface water risk assessment of agricultural chemicals is described. It is based on the integration of relational and spatial databases, GIS incorporating raster and vector, mass balance models, and pesticide risks indicators. Surface water pollution was modeled by taking into account two main processes:  the load due to drift and the load due to a rainfall−runoff event. The former is immediately consequent to pesticide application; the second occurs a short period afterward. Thus two distinct PEC (predicted environmental concentration) values were estimated, differing in time. A pilot approach was applied to the herbicide alachlor on corn in Lombardia region (northern Italy) and represents the first stage of a wider project. Although the resultant alachlor PEC and risk maps represent a static image of a worst-case simulation, the main objective was to provide information for the territory with respect to relative risks at the watershed level, which is important in managing risks to the aquatic environment. The driving forces and spatial variability of the above-mentioned processes were investigated to improve knowledge about the territory and to indicate the need for more detailed site-specific studies.

Verro, R., Calliera, M., Maffioli, G., Auteri, D., Sala, S., Finizio, A., et al. (2002). GIS-based system for surface water risk assessment of agricultural chemicals. 1. Methodological approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 36(7), 1532-1538 [10.1021/es010089o].

GIS-based system for surface water risk assessment of agricultural chemicals. 1. Methodological approach

SALA, SERENELLA;FINIZIO, ANTONIO;VIGHI, MARCO
2002

Abstract

A methodology to develop a GIS-based system for the surface water risk assessment of agricultural chemicals is described. It is based on the integration of relational and spatial databases, GIS incorporating raster and vector, mass balance models, and pesticide risks indicators. Surface water pollution was modeled by taking into account two main processes: the load due to drift and the load due to a rainfall−runoff event. The former is immediately consequent to pesticide application; the second occurs a short period afterward. Thus two distinct PEC (predicted environmental concentration) values were estimated, differing in time. A pilot approach was applied to the herbicide alachlor on corn in Lombardia region (northern Italy) and represents the first stage of a wider project. Although the resultant alachlor PEC and risk maps represent a static image of a worst-case simulation, the main objective was to provide information for the territory with respect to relative risks at the watershed level, which is important in managing risks to the aquatic environment. The driving forces and spatial variability of the above-mentioned processes were investigated to improve knowledge about the territory and to indicate the need for more detailed site-specific studies.
Articolo in rivista - Articolo scientifico
A methodology to develop a GIS-based system for the surface water risk assessment of agricultural chemicals is described. It is based on the integration of relational and spatial databases, GIS incorporating raster and vector, mass balance models, and pesticide risks indicators. Surface water pollution was modeled by taking into account two main processes:  the load due to drift and the load due to a rainfall−runoff event. The former is immediately consequent to pesticide application; the second occurs a short period afterward. Thus two distinct PEC (predicted environmental concentration) values were estimated, differing in time. A pilot approach was applied to the herbicide alachlor on corn in Lombardia region (northern Italy) and represents the first stage of a wider project. Although the resultant alachlor PEC and risk maps represent a static image of a worst-case simulation, the main objective was to provide information for the territory with respect to relative risks at the watershed level, which is important in managing risks to the aquatic environment. The driving forces and spatial variability of the above-mentioned processes were investigated to improve knowledge about the territory and to indicate the need for more detailed site-specific studies.
pesticides; GIS; models; surface water; ecotoxicological risk
pesticide; risk assessment; GIS; surface water
English
1532
1538
7
Verro, R., Calliera, M., Maffioli, G., Auteri, D., Sala, S., Finizio, A., et al. (2002). GIS-based system for surface water risk assessment of agricultural chemicals. 1. Methodological approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 36(7), 1532-1538 [10.1021/es010089o].
Verro, R; Calliera, M; Maffioli, G; Auteri, D; Sala, S; Finizio, A; Vighi, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/61136
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