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Dam removal cost databases and drivers

October 31, 2023

The United States (U.S.) has over 90,000 dams listed in the National Inventory of Dams that provide vital infrastructure to support water management for municipal and industrial uses including irrigation, hydropower, flood control, navigation, recreation, and habitat, among other uses (NID 2023). The Bureau of Reclamation (Reclamation) and U.S. Army Corps of Engineers (USACE) operate and maintain approximately 489 and 740 dams, respectively, as well as associated structures which provide flood risk management, navigation, water supply, hydropower, environmental stewardship, fish and wildlife conservation, and recreation benefits. As dams age, structural and operational maintenance investments increase until a time when decisions on whether to rehabilitate, replace, or decommission the dam need to be made. While most dams continue to provide important value even with maintenance requirements, at least 2,000 dams have been removed in the U.S. during the past 110 years, with an upward trend in the last few decades (American Rivers 2023). Decommissioning a dam may be considered when the purpose of the dam is no longer needed or other factors such as dam safety, fish passage, recreation safety, or river restoration goals take higher priority and are more economically feasible for the dam owner long-term.

Dam safety programs, river restoration programs, and asset class management programs need cost estimating methods to consider dam decommissioning when appropriate. Traditional cost estimating approaches in planning stages focus mainly on dam removal construction and may leave out or have uncertainty on important complexities that can have substantial effects on total costs and be critical for project success. As the numbers of dam removal case studies increase, a growing set of cost data has become available (Duda et al. 2023a; Tullos and Bountry 2023; American Rivers 2022). However, total costs vary over five orders of magnitude for similar size dams, and it was unclear why. We evaluated three sets of cost data that had varying level of details regarding elements contributing to dam removal costs reported by project managers working on the dam removal studies and construction means and methods.

We created planning-level cost estimating tools to assist with projects needing to consider the dam removal alternative: (1) new databases of case studies (Duda et al. 2023a; Tullos and Bountry 2023); (2) scoping questions to help determine if complexity cost drivers will be present; (3) machine learning based regression trees to estimate a potential cost range; and (4) a Computation Guide for Cost Estimating that can be used to inform discussions on potential dam removal cost items, quantities, and unit costs (appendix A). The collected data showed that dam height is important but is not a reliable predictor of the removal cost without considering other elements. However, knowing some basic characteristics about the average annual flow and geographic location of the dam site, in addition to dam size, can improve the ability to use past case studies for planning-level cost estimating. By additionally incorporating scoping questions related to sediment removal, mitigation, or other infrastructure, the likelihood of complexity cost drivers and the initial uncertainty of a cost estimate can be further reduced especially for small dams. Applying the Computation Guide for Cost Estimating requires more robust information but helps users reduce cost uncertainty. This step further refines the dam removal objective, removal approach (partial or full; phased or instantaneous), engineering design, construction means and methods, quantities, and unit costs, and results in a quantitative cost estimate.

Publication Year 2024
Title Dam removal cost databases and drivers
Authors Jennifer A. Bountry, Timothy J. Randle, Alvin Jansen, Jeffrey J. Duda, Suman Jumani, Desiree D. Tullos, Kyle McKay, Susan Bailey
Publication Type Report
Publication Subtype Federal Government Series
Series Title Final Report
Series Number ST-2023-21084 and ENV-2023-002
Index ID 70252622
Record Source USGS Publications Warehouse
USGS Organization Western Fisheries Research Center