Probabilistic risk assessment of cotton pyrethroids: III. A spatial analysis of the Mississippi, USA, cotton landscape

Citation
P. Hendley et al., Probabilistic risk assessment of cotton pyrethroids: III. A spatial analysis of the Mississippi, USA, cotton landscape, ENV TOX CH, 20(3), 2001, pp. 669-678
Citations number
7
Categorie Soggetti
Environment/Ecology
Journal title
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
ISSN journal
07307268 → ACNP
Volume
20
Issue
3
Year of publication
2001
Pages
669 - 678
Database
ISI
SICI code
0730-7268(200103)20:3<669:PRAOCP>2.0.ZU;2-V
Abstract
Estimates of potential aquatic exposure concentrations arising from the use of pyrethroid insecticides on cotton produced using conventional procedure s outlined by the U.S. Environmental Protection Agency's Office of Pesticid e Programs Environmental Fate and Effects Division seem unrealistically hig h. Accordingly, the assumptions inherent in the pesticide exposure assessme nt modeling scenarios were examined using remote sensing of a significant M ississippi, USA, cotton-producing county. Image processing techniques and a geographic information system were used to investigate the number and size of the water bodies in the county and their proximity to cotton. Variables critical to aquatic exposure modeling were measured for approximately 600 static water bodies in the study area. Quantitative information on the rela tive spatial orientation of cotton and water, regional soil texture and slo pe, and the detailed nature of the composition of physical buffers between agricultural fields and water bodies was also obtained. Results showed that remote sensing and geographic information systems can be used cost effecti vely to characterize the agricultural landscape and provide verifiable data to refine conservative model assumptions. For example, 68% of all ponds in the region have no cotton within 360 m and 92% of the ponds have no cotton within 60 m. Only 2% of ponds have cotton present in all directions around the ponds and within 120 m. These are significant modifications to convent ional pesticide risk assessment exposure modeling assumptions and exemplify the importance of using landscape-level risk assessments to better describ e the Mississippi cotton agricultural landscape. Incorporating spatially ch aracterized landscape information into pesticide aquatic exposure scenarios is likely to have greater impact on the model output than many other refin ements.