Empirical Modeling of Spatial Vulnerability Applied to a Norflurazon Retrospective Well Study in California

نویسندگان

  • F. Spurlock
  • J. Troiano
چکیده

One goal of mandated well monitoring in California, U.S.A, is to search for residues of active ingredients previously undetected in the state’s groundwater. The realization that pesticide residues move into groundwater via a number of different pathways has lead us to develop an empirical approach to delineate vulnerable areas; major climatic and edaphic features of areas where pesticides residues have been detected in well water have been identified on a geographic basis. The objective of this study was to evaluate the use of our empirical model in a retrospective well sampling study for norflurazon, a pre-emergence herbicide with physical-chemical properties that indicated potential to move offsite with water. In our modeling approach, sections of land, which are 2.59 km areas, were identified as having a greater potential for contamination based on soil and depth-to-groundwater data. Wells were sampled from a subset of these sections where use of norflurazon was historically the greatest. Norflurazon residue was detected in 8 of 43 wells sampled in Fresno County, CA., and in concentrations ranging from 0.07 to 0.69 μg L. This result was considered highly successful because residues had not been detected in 18 previous California groundwater studies for other active ingredients, some of which had been detected in other state and federal sampling programs. Location of sampling sites in these previous 18 California studies was based only on pesticide use data. The detections of norflurazon in this study indicated that, even though using an empirical modeling approach appeared to be unorthodox, it enabled us to effectively identify vulnerable areas. Abbreviations: CALVUL, California vulnerability modeling approach; DGW, Depth-togroundwater; DPR, California Department of Pesticide Regulation; DEA, deethylatrazine; ACET, deethylsimazine; KC, known contaminated; MDL, minimum detection limit. Published in J. Environ. Qual. 28:397-403 (1999).

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تاریخ انتشار 1999