HydroSource has undertaken efforts to better understand opportunities for new hydropower generation in the United States that can be achieved in an efficient and environmentally friendly manner. 

The New Stream-Reach Development Resource Assessment provides users with data detailing the potential for new hydropower development in stream segments that currently have no hydroelectric facilities. A methodology was designed to identify and characterize stream-reaches with high energy density and, most importantly, spatially joins the energy potential of stream-reaches with information related to natural ecological systems; sensitive species; areas of social and cultural importance; and policy, management, and legal constraints. The primary goals of the Tool are to provide information and data that are applicable to multiple types of assessments, scenarios, and assumptions, and to improve decision making and strategic planning by various organizations and individuals. 

The Non-Powered Dam Resource Assessment evaluates the additional hydropower potential from non-powered dams. The United States has more than 80,000 dams that do not produce electricity. The abundance, relatively lower cost to add power at non-powered dams, and the environmental favorability given that the dams are already in place of Non-Powered Dams (NPDs), combined with the reliability and predictability of hydropower, make these dams an attractive source for expanding the nation's renewable energy supply. The Resource Assessment provides interested stakeholders with in-depth information about regional hydropower potential. 

The Stream Network for Standard Model Hydropower (SMH) Explorer is a geovisual analytics platform that empowers user-guided energy-water-environment module data analysis and inquiries in support of the Standard Modular Hydropower (SMH) Technology Acceleration research project. A stream network dataset was developed specifically to meet the needs of SMH Explorer users and was also used as the input to the SMH site classification clustering analysis. This stream network includes many environmental, energy, and social geographic attributes compiled from numerous other data sources and thought to be relevant to SMH stakeholders.