Factor analysis/Principal Component Analysis (FA/PCA) were applied to the data set on water quality in upper Acaraú River basin (Brazil) to study the effects caused by human activities on water. Variables were measured at six key sampling sites (villages and agricultural areas) in four campaigns from February/2003 to March/2004. The samples were analyzed for pH, temperature, color, electrical conductivity, turbidity, nitrate, ammonia, sodium, chloride, potassium, sulfate, total hardness, calcium, magnesium, total alkalinity, alkalinity bicarbonate, total suspended solids, dissolved oxygen (DO), 5-days biochemical oxygen demand (BOD5), total phosphate, orthophosphate, chlorophyll-a, and feacal coliform. Multivariate statistical techniques, (FA/PCA), allowed the identification of variables that explain the major percent of total variance. Three components were identified as responsible for the data structure, explaining 88% of the total variance of the data set. Model showed that the first factor (39.81% of variance) assigned as mineralization factor. The second one (29.22% of variance) represented as nutrients group. The third factor (19.16% variance) assigned as a combination of agricultural area runoff and weathering. Varimax rotation showed that the mainly water quality parameters were related to mineralization (natural process) and non-point pollution (anthropogenic activities).
multivariate analysis; water monitoring; water pollution
