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Alvin Jansen

Publications and source records attributed to Alvin Jansen.

2 recordsLinked to original sources

Dam removal cost databases and drivers

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.

Final Report

Patterns, drivers, and a predictive model of dam removal cost in the United States

Given the burgeoning dam removal movement and the large number of dams approaching obsolescence in the United States, cost estimating data and tools are needed for dam removal prioritization, planning, and execution. We used the list of removed dams compiled by American Rivers to search for publicly available reported costs for dam removal projects. Total cost information could include component costs related to project planning, dam deconstruction, monitoring, and several categories of mitigation activities. We compiled reported costs from 455 unique sources for 668 dams removed in the United States from 1965 to 2020. The dam removals occurred within 571 unique projects involving 1–18 dams. When adjusted for inflation into 2020 USD, cost of these projects totaled \$1.522 billion, with per-dam costs ranging from $1 thousand (k) to \$268.8 million (M). The median cost for dam removals was \$157k, \$823k, and \$6.2M for dams that were< 5 m, between 5–10 m, and > 10 m in height, respectively. Geographic differences in total costs showed that northern states in general, and the Pacific Northwest in particular, spent the most on dam removal. The Midwest and the Northeast spent proportionally more on removal of dams less than 5 m in height, whereas the Northwest and Southwest spent the most on larger dam removals > 10 m tall. We used stochastic gradient boosting with quantile regression to model dam removal cost against potential predictor variables including dam characteristics (dam height and material), hydrography (average annual discharge and drainage area), project complexity (inferred from construction and sediment management, mitigation, and post-removal cost drivers), and geographic region. Dam height, annual average discharge at the dam site, and project complexity were the predominant drivers of removal cost. The final model had an R 2 of 57% and when applied to a test dataset model predictions had a root mean squared error of $5.09M and a mean absolute error of \$1.45M, indicating its potential utility to predict estimated costs of dam removal. We developed a R shiny application for estimating dam removal costs using customized model inputs for exploratory analyses and potential dam removal planning.

Frontiers in Ecology and Evolution