Estimating the monetary costs of aging dam removals in the United States
Introduces a cost-estimation model for predicting order-of-magnitude dam removal costs across the United States. Using dam age, condition, and hazard data, the study forecasts future removal investments and examines state-specific cost patterns, highlighting economic challenges of managing aging dam infrastructure under current policies.
Subject Tags
- Policy, Finance, and Markets
Abstract
As the pace of dam removals increases worldwide, tools to estimate their monetary costs remain scarce. We extend recent cost-estimation methods to include readily available covariates, which allows for predicting order-of-magnitude dam removal costs across the United States. We apply this model to forecast the monetary investments required to remove aging dams in the United States based on scenarios related to dam age, condition, and hazard to provide a range of plausible and relevant scenarios for planners and policymakers. Decommissioning just 20% of National Inventory of Dams structures over 75 years in age is projected to incur a mean cost of $6.4B by 2025 (n=3,935) and $22.4B by 2075 (n=15,165). Projected mean removal costs for dams in poor condition (n=7,475), and in poor condition and posing a high hazard (n=3,621) are $10.6B and $6.5B respectively. We also assess standardized cost estimates across states to examine state-specific cost trends. We conclude with a discussion of the economic challenges of managing aging dam infrastructure considering recent policies and funding allocations.
Citation
Jumani, S., McKay, S. K., Moberg, T., Hoenke, K., & Wenger, S. J. (2026). Estimating the Monetary Costs of Aging Dam Removals in the United States. Environmental Challenges, 101472.
TNC Authors
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Suman Jumani
Freshwater Protection Spatial Analyst • Protect Oceans, Lands and Waters
The Nature Conservancy
Email: suman.jumani@tnc.org -
Tara Moberg
Durable Freshwater Protection Advisor • Protect Oceans, Lands and Waters
The Nature Conservancy
Email: tmoberg@tnc.org