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The effectiveness of conservation practices depends on their placement on the fields within the watershed. Cost effective placement of these practices for maximum water quality benefits on each field requires comparing a very large number of possible land use scenarios. To address this problem, we combine the tools of evolutionary algorithm with the Soil and Water Assessment Tool (SWAT) model and cost data to develop a tradeoff frontier of least cost of achieving nutrient reductions and the corresponding locations of conservation practices. This approach was applied to the Raccoon River Watershed, which drains about 9,400 km2 of an intensive agriculture region in west-central Iowa. Calibration and validation of the SWAT model was performed and evaluated using R2 and Nash-Sutcliffe (E). Strong correlation was found for streamflow as indicated by both values being more than 0.75 for annual as well as monthly calibration (1996-2004) and validation (1986-1995) periods. Nitrate comparisons yielded similar correlation with both values more than 0.7 for annual and monthly calibration, but weak correlation (around 0.5) was observed during the validation period. Model verification on limited phosphorus data (2001-04) yielded strong correlation with values more than 0.8. Applying genetic algorithm to the calibrated watershed produced multitudes of optimal solutions of achieving nutrient reductions in relation to the total cost of placing these practices. For example, a 30% reduction in nitrate (and a corresponding 53% reduction in phosphorus) at the watershed outlet can be achieved with a cost of 80 M$/year. This solution frontier allows policymakers and stakeholders to explicitly see the tradeoffs between cost and nutrient reductions.