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Non-point source pollution (NPP) is caused by the movement of water over and through the ground, generally after each rainfall. The runoff picks up and carries away natural and manmade pollutants, eventually depositing them in water bodies like lakes, rivers and coastal waters. Thus the pollutants left on the surface from various sources accumulate in receiving water bodies. For example, crop cultivation requires more use of chemicals and nutrients than natural vegetative cover like forest and grasslands. Tillage operations affect the soil structure and the level of chemicals in the soil. Such activities make the nutrient rich topsoil fragile and cause it to lose more chemicals and soil particles during rainfall. Lands in residential and development uses, such as lawns and gardens are managed more intensively, which encourages the generation of even more pollutants. On the other hand, urban areas have higher percentages of impervious to porous surfaces that result in low percolation and higher runoff. During precipitation, the runoff carries more nutrients and sediments from agricultural and residential lands resulting in higher chemical level and turbidity in the water. Thus increasing urbanization coupled with increasing use of nutrients and chemicals in agricultural lands create significant challenges to maintain water quality. Recent water quality studies have focused on developing and successfully applying various biophysical simulation methods to model levels of NPP and to identify critical locations from which these pollutants originate (Bhuyan et al., 2001; Mankin et al. 1999; Marzen et al., 2000). These models collect and use various geospatial data, facilitating the spatial analysis of sources and effects of point and non-point pollutants with reference to their origin and geographical locations. The findings of such models help the environmental policy planners to understand both the short-term and long-term effects of changes from alternative land management scenarios and simulate how the pollution can be reduced effectively through the institutionalization of best management practices. This study uses the BASINS-SWAT modeling framework, one of the latest biophysical modeling tools to estimate the effects of land use change in the quality of water. Simulations are done to estimate the level of

Estimating the Impact on Water Quality under Alternate Land Use Scenarios: A Watershed Level BASINS-SWAT Modeling in West Georgia, United States