Citation
Scott T. DeNeale, Antonia Chu, Mustafa Altinakar, Jason Hedien and Vladimir Koritarov. 2026. Cost Model for Pumped Storage Hydropower Geomembrane Lining Systems. HydroSource. Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.
Overview
The Cost Model for Pumped Storage Hydropower Geomembrane Lining Systems offers an approximation of geomembrane lining system costs for pumped storage hydropower (PSH) reservoirs. Geomembrane lining systems have been used around the world for over 60 years for the construction of dams and reservoirs. Although geomembrane lining systems have found widespread use in the construction of canals and waste containment systems, they have not been utilized in the construction of new PSH facilities in the United States since the Mount Elbert PSH powerplant in Colorado. For this reason, PSH developers in the United States expressed the need for a tool that would allow them to estimate the costs of geomembrane lining systems for their PSH projects. To meet this need, the Cost Model for Pumped Storage Hydropower Geomembrane Lining Systems was developed by Oak Ridge National Laboratory with support from Argonne National Laboratory and Stantec, Inc. This Cost Model will enable PSH developers to develop a preliminary estimate of the cost of geomembrane lining systems and to better understand different reservoir lining options and their cost and performance characteristics, thus enabling them to make informed decisions related to preferred reservoir lining systems for their PSH projects.
The Cost Model relies on geometric calculations and engineering cost estimation approaches. While the model can rely entirely on custom user inputs, some default unit cost estimates were collected based on outreach to vendors supplying equipment. Conditions: The Cost Model is not intended to replace professional engineering design and calculation. The Model makes a number of assumptions, and data related to unit
cost rates are based on very limited information and are presented in 2024$. The user is responsible for all inputs used in the model. Additional insights into more detailed engineering considerations are provided in the User Guide and Report available here: SAME PLACEHOLDER FOR URL.
Related Records
2024 National Hydropower Map
In this map poster, we use Oak Ridge National Laboratory’s 2022 Existing Hydropower Assets Plant Dataset to visualize the geospatial distribution and characteristics of U.S. operational hydropower plants.
View Map