Low water levels in the Great Lakes have recently had significant financial impacts on the region's commercial shipping, which transports hundreds of millions of dollars' worth of bulk goods each year. Cargo capacity is a function of a ship's draft, the distance between water level and the ship's bottom, and lower water levels force ships to reduce cargo loads to prevent running aground in shallow harbors and locks. Financial risk transfer instruments, such as index-based insurance contracts, may provide an adaptable method for managing these financial risks. In this work, a relationship between water levels and shipping revenues is developed and used in an actuarial analysis of the frequency and magnitude of revenue losses. This analysis is used to develop a standardized suite of binary financial contracts, which are indexed to water levels and priced according to predefined thresholds. These contracts are then combined to form hedging portfolios with different objectives for the shippers. Results suggest that binary contracts could substantially reduce the risk of financial losses during low lake level periods and at a relatively low cost of only one to three percent of total revenues, depending on coverage level.

Hydropower on the Great Lakes makes up a substantial fraction of regional electricity generation capacity. Hydropower producers on the Niagara River (flowing between lakes Erie and Ontario) operate as run‐of‐river, and changing lake levels alter interlake flows reducing both generation and revenues. Index‐based insurance contracts, wherein contract payouts are linked to lake levels, offer a tool for mitigating this risk. As a potentially useful tool, pricing of financial insurance is typically based on historical behavior of the index. However, uncertainty with respect to the impacts of climate change on lake level behavior and how this might translate to increased (or decreased) risk for those selling or buying the insurance remains unexplored. Portfolios of binary index‐insurance contracts are developed for hydropower producers on the Niagara River, and their performance is evaluated under a range of climate scenarios. Climate Informed Decision Analysis is used to inform the sensitivity of these portfolios to potential shifts in long‐term, climatological variations in water level behavior. Under historical conditions, hydropower producers can use portfolios costing 0.5% of mean revenues to increase their minimum revenue threshold by approximately 18%. However, a one standard deviation decrease in the 50 year mean water level potentially doubles the frequency with which these portfolios would underperform from the perspective of a potential insurer. Trade‐offs between portfolio cost and the frequency of underperformance are investigated over a range of climate futures.

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