From 1970 to 1980, Summit County, Colorado, was the fastest growing county in the United States. Many of its residents use onsite wastewater systems (OWS) and private wells. In the Dillon Reservoir Watershed, located in southern Summit County, watershed water-quality management issues related to OWS effluent are more prominent because of population growth, thin soils, and consequent nutrient and pathogen transport. The objective of this study is to quantify the effects of OWS wastewater pollutants on the ground water and surface water using a GIS-linked watershed-scale water-quality model. Soil and Water Assessment Tool (SWAT), which is incorporated into the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) modeling package available from the U.S. EPA, was used for the study. SWAT utilizes physically based data, simulates land use and management scenarios, and takes into account process interactions through a GIS environment. Comprehensive and accurate watershed-scale modeling is an arduous task, and SWAT helps to simplify this with several methods. First, in a GIS environment, SWAT subdivides a large watershed into smaller, spatially-linked subwatersheds either with grid-based information (DEM, NEXRAD, or LULC) or by surface topography. Then, GIS coverages of land use, management practices, and soil type are used to further divide each subwatershed into Hydrologic Response Units (HRUs). The HRUs simplify model simulations by lumping together similar land uses and soil types so loadings from each HRU may be calculated efficiently and then summed for each subwatershed. Pollutant loadings from each subwatershed are then routed downstream through each subwatershed’s outlet. Water-quality data from groundwater and surface-water samples, as well as stream-gaging and groundwater hydraulic-head data have been collected in the watershed. The modeling concentrates on three focus areas (subdivisions) in the watershed that represent different types of pollutant loadings. Data collected upstream and downstream of the sites show a change in the signature of nitrate, phosphorus, and other chemical parameters. These data are used to calibrate the SWAT model. The performance of the model is gauged by its ability to reproduce observed data, and upon the reasonableness of model predictions.