This study aims to combine GIS and statistical methods such as Multiple Factor Analysis (MFA) and Multiple Linear Regression to characterize the spatio-temporal variation of groundwater quality and the factors affecting nitrate levels in groundwater of Bolinao. A hundred and twelve (112) wells in total were sampled for water quality including parameters such as pH, DO, ORP, salinity, conductivity, chlorophyll a and nitrate. About half of the nitrate levels in the study area exceeded the Maximum Concentrate Level (MCL) recommended by USEPA of 44.66 mg/L ranging from undetectable to 196 mg/L. Results showed that water quality was poor mostly at the vicinity of the foreshore area and high density built-up area, indicating human activity released significant amounts of pollutants to the groundwater. MFA revealed that septic tank density, TDS, Three-Dimensional Inverse Distance Weight (3D IDW), well depth, and distance to the shoreline had intercorrelation with nitrate in dry and early of rainy season. However, during the mid-rainy season, nitrate had no relationship with any variable that may be due to the effect of run off and rain water dilution on groundwater. Results from multiple regression analysis showed that the variables providing significant information to  the  variability of nitrate keep  changing spatially and temporally, suggesting assumption of using the same explanatory variables to describe nitrate in the entire study area and every season is ineffective.