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Advancing Energy-Water Resilience in Alaska, Hawaii, and U.S. Territories
Challenges facing Alaska, Hawaii, and U.S. Territories for both "energy for water" and "water for energy" are distinctive from the contiguous U.S. In this whitepaper, we discuss opportunities for new hydropower development and non-traditional water-energy linkages in these regions...
Hansen, C., Acharya, M., Ashraf, F., Atkinson, T., Chu, A., and Calderon, J.
Hydrotwin: an AI-based physics and optimization framework for improved water resource resilience in systems experiencing adverse events
This white paper focuses on water for energy.
As we move ahead into an uncertain future for water resource demand and supply, a massive challenge exists to optimize water systems to be resilient to a range of press/pulse extreme event states and conditions. Optimal decision-makin...
Bennett, K., Schwenk, J., and Garcia, M.
Hardening Forested Watersheds to Wildfire to Enhance Downstream Water Quality for Critical Energy Infrastructure
This white paper focuses on water-for-energy stability, emphasizing the risks to energy infrastructure from water quality impacts due to severely burned forested watersheds. The primary challenge is that energy production in the U.S. is vulnerable to surface water quality, with hi...
Crockett, J., and Krofcheck, D.
Water-Energy-Economics: Leveraging Market Instruments for Building Resilience
Energy and water systems exist in an economic context that shapes their supply and use, which in turn shapes the macroeconomics of the country. A holistic energy-water-economics view is needed that links physical resource constraints, sectoral interdependencies, policy and managem...
Wilson, K., and Wild, T.
Sensor Enabled Cured-in-Place (CIPP) Liners: Cutting Leaks Today, Powering Digital Twins and Real-Time Detection for Tomorrow's Resilient Intelligent Water Distribution Systems
Municipal water accounts for roughly 12% of total consumption in the United States (EPA and AWWA averages), yet an estimated 14% of this treated supply is lost through distribution line leaks (AWWA national average). Because municipal water carries significant embedded energy and ...
Robinson, G., Luo, L., Earni, S., and DeJong, M.
Aligning Energy, Water, and Agriculture: Near-Term Strategies for Resilience in Water-Stressed Regions
This white paper explores the intersection of energy, water, and agriculture, emphasizing the growing competition for water between irrigation and energy systems. It identifies near-term opportunities to enhance agricultural water management and electrification, while evaluating t...
Pacheco, C., and Mekonnen, M.
Forecast and Intelligence Enabled Reservoir Operations for Energy-Water Resilience
This white paper discusses the energy-water nexus and emphasizes the need for co-optimization of hydropower, reservoir management, and water supply operations to enhance resilience and reliability. It focuses on integrating water management intelligence with power system forecasti...
Sun, M., and Hansen, C.
Forecast-Informed, Market-Responsive Conjunctive Operations for Multi-Reservoir Water-Energy Systems
The white paper, "Forecast-Informed, Market-Responsive Conjunctive Operations for Multi-Reservoir Water-Energy Systems" , addresses the water-for-energy and energy-for-water nexus by proposing a framework for co-optimizing hydropower and cascading reservoir operations alongside fl...
Pavicevic, M., Mork, E., Yu, A., Herman, J., Emmons, J., and Ploussard, Q.
Increasing Robustness and Resilience of Water Delivery Infrastructure
This white paper outlines the need for a national testing capability for water treatment and delivery infrastructure to enhance energy-water resilience (EWR) and address existing knowledge and technology gaps. The vulnerability of water systems to contamination, physical compromis...
Reese, S., Gagnon, O., and Otto, M.
Agentic Optimization for Resilience in Hydropower Reservoir Systems
The growing electricity demand in the U.S. requires a resilient energy strategy. Hydropower is a major component of that strategy but is subject to environmental and human stressors that impact its dependability. AI-driven reinforcement learning, called "Agentic" learning, presen...
Schwenk, J., Garcia-Cardona, C., Bennett, K., Singh, S., and Brelsford, C.