This article presents analysis and synthesis of findings concerning the problem of cost-effective placement of best management practices (BMPs) emerging from NIFA CEAP and the USDA NRCS jointly-funded competitive grant projects, and future research needs. The synthesis focuses on two fundamental aspects of the cost-effectiveness problem: (1) how to assess the location- and farmer-specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed so that a given water quality goal is achieved with the lowest possible policy outlay or a given conservation policy budget results in the best possible water quality improvement. We find that data availability remains a significant limiting factor for capturing within-watershed variability in the costs. Evolutionary algorithms have shown to provide workable ways to identify cost-effective BMP placement even for large, diverse watersheds and large numbers of potential BMPs. Future research needs include furthering the investigation, both conceptually and empirically, of the impact of the uncertainty in the BMP costs and water quality improvement benefits within the cost-effectiveness problem, and the development of the models that could consistently integrate the estimates of BMP cost components developed using alternative modeling approaches and/or attained under alternative economic conditions and for alternative geographic regions.