Empirical modeling of spatial vulnerability applied to a norflurazon retrospective well study in California

One goal of mandated well monitoring in California is to search tor residue s of active ingredients previously undetected in the state's groundwater. T he realization that pesticide residues move into groundwater via several di fferent pathways has led us to develop an empirical approach to delineate v ulnerable areas; major climatic and edaphic features of areas where pestici des residues have been detected in well water have been identified on a geo graphic basis. The objective of this study was to evaluate the use of our e mpirical model in a retrospective well-sampling study for norflurazon, a pr eemergence herbicide with physical-chemical properties that indicated poten tial to move offsite with water. In our modeling approach, sections of land , which are 2.59 km(2) areas, were identified as having a greater potential for contamination based on soil and depth-to-groundwater (DGW) 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 well s sampled in Fresno County, California, and in concentrations ranging from 0.07 to 0.69 mu g L-1. This result was considered highly successful because residues had not been detected in 18 previous California groundwater studi es for other attire ingredients, some of which had been detected in other s tate and federal sampling programs. Location of sampling sites in these pre vious 18 California studies was based only on pesticide use data. The detec tions of norflurazon in this study indicated that, even though using an emp irical modeling approach appeared to he unorthodox, it enabled us to effect ively identify vulnerable areas.