A Parametric Model For Estimating Costs For Remediating Contaminated Sediment Sites Using A Dredging Method - A Budgetary & Planning Tool For Decision-Makers

Contaminated sediments, whether in freshwater or marine systems, pose a significant environmental challenge both within the United States and across the globe. When it comes to cost estimating for sediment-related cleanup projects, headline after headline seems to read something like “Cost Estimates Increased for XYZ Project” or “Cost Estimate Rises to $(fill in your own astronomical number way above original estimates).” Why do these calculations remain such a persistent challenge to financial professionals and planners charged with estimating such cleanup efforts? One predominant reason is that estimating the true costs of such projects is tremendously difficult and riddled with high degrees of uncertainty. Simply put, what professionals need is a “better mousetrap.” To develop a better “mousetrap”, we assessed the current practices employed in developing such estimates. According to the U.S. Department of Defense and U.S. Department of the Army, there are three basic types of cost estimation techniques that are used either individually or in combination - Analogy, Build Up, and Parametric Modeling. Each approach has been used throughout industry with varying degrees of success. However, according to the DoD/DoA, there are currently no real-world examples of parametric models for estimation of sediment treatment project costs. We’ve created a viable Parametric Model for assisting managers and decision-makers in developing appropriate cost estimates for the processing and disposal of dredged materials which can be used for planning and budgetary purposes, communicating with appropriate stakeholders, and providing guidance to senior management. This multi-variable financial model enables cost estimates for either a single site or a portfolio of sites [while still allowing for individual site specifications] by providing cumulative costs over the overall remediation time horizon. It allows for “what if” scenarios and provides both numerical and graphical depictions of these aforementioned cost estimates.