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Dynamic Population Mapping to Advance Energy-Water Resilience
Dynamic population mapping, combined with household-level energy and water demand profiling, enables precise, actionable forecasting and resilience planning for U.S. energy-water systems under variable population and climate conditions.
Energy and water systems face growing stres...
Zimmer, A., Tuccillo, J., Jeong, B., and Urban, M.
Reliable Water Resources for Resilient Next-Generation Geothermal Energy
This white paper focuses on expanding reclaimed wastewater for geothermal water management.
Challenges include rapid growth to 5 GW, rising demand for water in water-scarce regions. High volumes for drilling, stimulation, cooling, and reclaimed water infrastructure limits. High ...
Wu, M.
Integrated Water-Energy-Economics Framework for Public Water System Resilience
This paper highlights key energy-for-water challenges in U.S. public water systems (PWS): aging infrastructure, cost recovery gaps, hydrologic vulnerabilities, and high-demand users like data centers--which concentrate near population centers and existing PWS. It underscores the n...
Siddik, M., Ahmad, N., Guaita, S., and Chinthavali, S.
Improved quantification of river nutrient loading for better water quality and more efficient energy use
The focus of this paper is multi-sector dynamics involving agriculture practices, water quality and energy. Currently there lacks high-resolution spatiotemporal data regarding water quality and usage, forcing the planning for water treatment to adopt the conservative, worst-case a...
Tang, J., and Zhu, Q.
Aligning Bytes with Basins to Promote Data Center Growth in the U.S.
This white paper examines the water-energy tradeoffs of U.S. data-center expansion, highlighting how cooling choices, power sourcing, and siting decisions shape local water security, grid resilience, and watershed sustainability. The study focuses on integrating direct (on-site po...
Siddik, M., Turner, S., and Chinthavali, S.
Quantifying Energy Use across U.S. Water Sectors: A Scalable AI/ML-Driven Framework for Data Integration and Resilience Planning
This white paper explores opportunities to quantify and characterize energy use across major U.S. water sectors, including irrigation, water supply, and water treatment, with a focus on energy for water dimension. A scalable AI/ML-driven framework will be developed to harmonize fr...
Ghimire, G., Bhanja, S., and Martinez, R.
Standardized Siting and Risk Analysis Decision Support Mechanisms for Water-Intensive Industries
This paper focuses on water for cooling industrial energy generation loads and energy and water for cooling large process loads. A challenge is that siting any large facility with substantial water demands without understanding baseline conditions and assessing potential multi-sec...
Fuchs, H., Karki, U., Stokes-Draut, J., Rao, P., Varadharajan, C., Hodson, A., Ajami, N., and Shehabi, A.
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.
A Coupled Energy-Water Storage Architecture for Resilient Urban Power and Water Distribution
This white paper proposes a coupled energy-water storage architecture to enhance the resilience of urban power and water distribution networks. The concept leverages GLIDES concept (Ground-Level Integrated Diverse Energy Storage), which is a pneumo-hydraulic storage technology dev...
Chen, Y., and Sun, J.
Water Reuse Energy Demands and Water Quality Metrics
This white paper discusses strategies for enhancing water resilience in energy production by advancing water reuse and reclamation technologies, particularly for thermoelectric power plants and data centers. The focus is on efficiently closing the water loop by processing discharg...
Shurtliff, M., and Reese, S.