J. Troiano et al., USE OF CLUSTER AND PRINCIPAL COMPONENT ANALYSES TO PROFILE AREAS IN CALIFORNIA WHERE GROUND-WATER HAS BEEN CONTAMINATED BY PESTICIDES, Environmental monitoring and assessment, 32(3), 1994, pp. 269-288
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.