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Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase

Snowmelt from mountain headwater basins supplies approximately 80% of the runoff to reservoirs in the western United States (WUS), and is therefore a key component of western hydropower. Yet predicting runoff from hydrometeorological data in complex terrain (and its sensitivity to...

Rudisill, W., and Feldman, D.

Reinforcement Learning for Water-Energy Infrastructure Resilience and Evolution

This white paper outlines a foundational AI-based framework for improving resilience across the energy-water nexus, with a focus on electric grid and water system interdependencies under hydrologic and weather extremes. The focal area spans both "water for energy" and "energy for ...

Jackson, N., and Rao, N.

Employing AI-Enabled Prognostics for Energy-Water Resilience

This white paper focuses on strengthening the resilience and efficiency of hydropower systems at the energy-water nexus through AI-enabled prognostics and hardware-in-the-loop (HIL) simulation. It emphasizes integrating digital intelligence with physical infrastructure to optimize...

Zhao, S., Qiu, F., and Agalgaonkar, Y.

Energy-Efficient Water Management Using Geo-AI for Evapotranspiration and Crop Risk Analysis

This white paper outlines a strategy for enhancing energy-efficient water management in agriculture through the application of Geospatial Artificial Intelligence (GeoAI). The focus is on developing a Dynamic Irrigation Window Scheduling (DIWS) system that optimizes irrigation base...

Cafferty, K., and Pacheco, C.

Enabling Energy-Water Resilience in U.S. Data Centers: Water-Aware Grid Planning and Operations with Infrastructure-Compatible Cooling

Rapid, concentrated expansion of AI data centers is reshaping electricity demand profiles, local infrastructure requirements, and regional resource constraints. These facilities are often sized from tens to hundreds of megawatts with multi-gigawatt campus clusters. They are relati...

Zhou, Z., Wu, M., Qiu, F., Muehleisen, R., Zhao, D., Yan, E., and Worek, W.

AI-Enhanced Hydropower Systems: Smart Dams for a Resilient Future

This paper focuses on water-energy, using AI for smart, holistic hydropower operations to enhance water for energy resilience. The existing challenges include (a) increasing demand for water and electricity, requiring a shift to flexible, real-time hydropower operations due to ch...

Varadharajan, C., Ajami, N., Brodie, E., Ciulla, F., Falco, N., Feldman, D., Newcomer, M., Dwivedi, D., Li, Y., Nakata, R., Nakata, N., Nico, P., Williams, K., Mahoney, M., Ramakrishnan, L., and Cholia, S.

Water Energy Planning Strategies to meet Emerging Load from Data Centers

This white paper discusses the urgent need for innovative management of energy and water resources in the context of rapidly growing data centers, particularly as U.S. electricity demand is projected to increase by 35 to 40% by 2040 due to the rise of artificial intelligence (AI)....

Bhowmik, P., Cafferty, K., Klise, K., and Jackson, N.

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.

Maximizing American Energy Dominance with Forecasts of Energy Infrastructure Flood Exposure and AI Predictions of Consequences

This white paper focuses on water for energy. High frequency, reliable, and spatially explicit flood forecasts are necessary to forecast impacts to the energy system from hydrological hazards. While these tools are nearing operation at scale, they have not yet been systematicall...

Brelsford, C., Garcia, M., Robbins, Z., Schwenk, J., and Liu, Y.

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.

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