AbstractA dredging backlog in American harbors has produced inefficiencies, delays, and lost revenues for waterway-based logistics and trade. Policymakers have called for increased spending to address maintenance concerns that underscores the need to improve the allocation of public funds or innovate on alternative financing mechanisms. The cost of dredging in the United States has increased more than 250% since 1990 which calls into question the sustainability of current practices. Given that the objective of dredging is to facilitate waterways transport, this study investigated the tradeoffs between transportation cost savings and maintenance spending in the Great Lakes. We use Monte Carlo simulations to calculate Maritime Transport Efficiencies (MTE) as mass per time for bulk iron ore vessels, the predominant vessels on the Great Lakes waterway. Transportation costs, assessed over a range of uncertain demand and fuel pricing, are predicted from natural variations in water surface elevation. Estimates of MTE applied to predict transportation costs are useful in determining annual demand levels for dredging when considered in aggregate, suggesting an opportunity for market-driven funding models for harbor maintenance. Cost savings are evident under conditions such as high-water levels or reduced demand. Increased transportation costs, predicted using MTE, are compared to dredging expenditure. Considering dredging and operating costs together reveals total cost savings. This study produces a quantitative understanding of demand-driven harbor needs which may lead to market-based funding decisions.

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