USE OF CLUSTER AND PRINCIPAL COMPONENT ANALYSES TO PROFILE AREAS IN CALIFORNIA WHERE GROUND-WATER HAS BEEN CONTAMINATED BY PESTICIDES

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the leve l of vulnerability between land areas and that did not assume any part icular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where p esticide residues had been found in well water samples and the detecti on was attributed to legal agricultural applications. These sections w ere designated as known contaminated (KC) sections. Climate and soil d ata were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster gr oups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analys is (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was develo ped to compare the similarity of soil profiles derived for each KC sec tion cluster to individual candidate sections. Since the profiling sch eme was based only on data from KC sections, candidate sections that d id not match any KC cluster profile could only be considered dissimila r to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate upd ated well sampling information.