Project team is internal to Sandia National Laboratories.


Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Proposed power plants must often target waterways and aquifers prone to overdraft or home to environmentally sensitive species to meet their ferrous demand for water. Acquisition of water rights, permits and public support are thus a formidable hurdle for the licensing of new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy will require a 30% increase in power generation capacity by 2025? Maintaining an affordable supply of energy and water poses a credible threat to national security. While water and energy are inextricably linked, the planning and management of these fundamental resources are currently approached in isolation. In fact, the need for coordinated planning and management is one of the leading findings of the Regional Needs Assessment Workshops conducted as part of the Energy–Water Research Roadmap Development exercise.


The primary goal of this research is to develop a decision support framework for integrated energy-water planning and management. The model will target the needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. Specifically the model will help answer such questions as:

  • What are possible energy and water shortfall scenarios for a particular region?
  • What are tradeoffs between alternative energy futures to meet projected shortfalls?
  • What are tradeoffs between alternative water allocation schemes?
  • What are the economic and policy consequences of these alternative futures?
  • What are tradeoffs between local energy production versus out of basin production (i.e., tradeoff in energy reliability versus reduced pollution and water use)?

The decision support framework will be designed to link a variety of computational platforms (i.e., system dynamics to detailed energy/water management models) with geospatial databases and visualization tools. Further, this framework will integrate analysis and optimization capabilities to aid in identifying trade-offs, and “best” alternatives among an overwhelming number of options and objectives. This decision support framework will be able to address policy and trade-offs for models at multiple scales.