Multivariate statistical techniques, cluster analysis (CA) and factor analysis/principal component analysis (FA/PCA), were applied to analyze the similarities or dissimilarities among the sampling sites to identify spatial and temporal variations in water quality and sources of contamination (natural and anthropogenic). The aquifer under study is supplied by the Trussu River, which has a general direction from west to east, within Iguatu County, Ceará, Brazil. Groundwater samples were collected in four shallow wells, located at the Trussu River alluvial, from October 2002 to February 2004. The samples were analyzed for 13 parameters: pH, electrical conductivity (EC), Na, Ca, Mg, K, Cl, HCO(3), PO(4), NH(4)-N, NO(3)-N, SO(4), and sodium adsorption ratio (SAR). Two zones were very well differentiated based on cluster analysis results, and implied a relation to geographic position and time variation. One zone called UL-upland region-corresponds to upland of studied area, used mainly for irrigation and livestock activities. The other zone called DL-downland region-corresponds to the region downstream and is occupied by human settlements. These results may be used to reduce the number of samples analyzed both in space and time, without too much loss of information. Three major independent factors that define water quality in the UL region and four in DL region were identified in the PCA. At both regions, rotated component (RC) loadings identified that the variables responsible for water quality composition are mainly related to soluble salts variables (natural process) and nutrients (high loads of NO(3)-N, NH(4)-N), expressing anthropogenic activities. RC also revealed that hydrochemical processes were the major factors responsible for water quality.