Distributed parameter hydrologic models offer many advantages over lumped parameter models in tracking and controlling nonpoint source pollutants, but they are constrained by the excessive data input and processing they require. However, rapidly emerging technology in the form of geographic information systems (GIS) and the increasing availability of digital spatial databases are greatly reducing these constraints and expanding the range of applications of these models. This study describes the coupling of a distributed parameter agricultural nonpoint source pollution model (AGNPS) with a GIS (ERDAS) to evaluate the impact of nonpoint source pollution on water quality in a mid- sized (334 km2) agricultural watershed in southeastern Michigan. ERDAS is used to integrate spatial data sets from multiple sources into a single GIS database from which parameters needed to run the AGNPS model can be generated. The AGNPS model estimates the amounts, origin and distribution of sediments and nutrients across the watershed in response to a storm of a specified magnitude. By integrating the GIS and by using existing statewide and national spatial databases, the AGNPS model is easily employed to run iterative simulations of hypothetical landscape scenarios. These simulations indicate that the agriculturalization of land and the loss of forested cover significantly alter sediment and nutrient budgets across the watershed. The expansion of urban land cover appeared to have the greatest overall impact on runoff and nutrient fluxes, while agricultural expansion generated the largest increases in sediment concentrations and sediment yields. Forest expansion dramatically reduced the generation and delivery of all forms of nonpoint source pollution modeled. This integration of GIS with distributed parameter landscape modeling has considerable potential to aid in land use planning and in identifying locations most vulnerable to storm-driven runoff and erosion.