Water scarcity is a growing problem around the world, and regions such as California are working to develop diversified, interconnected, and flexible water supply portfolios. To meet their resilient water portfolio goals, water utilities and irrigation districts will need to cooperate across scales to finance, build, and operate shared water supply infrastructure. However, planning studies to date have generally focused on partnership-level outcomes (i.e., highly aggregated mean cost-benefit analyses), while ignoring the heterogeneity of benefits, costs, and risks across the individual investing partners. This study contributes an exploratory modeling analysis that tests thousands of alternative water supply investment partnerships in the Central Valley of California, using a high-resolution simulation model to evaluate the effects of new infrastructure on individual water providers. The viability of conveyance and groundwater banking investments are as strongly shaped by partnership design choices (i.e., which water providers are participating, and how do they distribute the project’s debt obligation?) as by extreme hydrologic conditions (i.e., floods and droughts). Importantly, most of the analyzed partnership structures yield highly unequal distributions of water supply and financial risks across the partners, limiting the viability of cooperative partnerships. Partnership viability is especially rare in the absence of groundwater banking facilities, or under dry hydrologic conditions, even under explicitly optimistic assumptions regarding climate change. These results emphasize the importance of high-resolution simulation models and careful partnership structure design when developing resilient water supply portfolios for institutionally complex regions confronting scarcity.

Hydrologic variability can present severe financial challenges for organizations that rely on water for the provision of services, such as water utilities and hydropower producers. While recent decades have seen rapid growth in decision-support innovations aimed at helping utilities manage hydrologic uncertainty for multiple objectives, support for managing the related financial risks remains limited. However, the mathematical similarities between multi-objective reservoir control and financial risk management suggest that the two problems can be approached in a similar manner. This paper demonstrates the utility of Evolutionary Multi-Objective Direct Policy Search (EMODPS) for developing adaptive policies for managing the drought-related financial risk faced by a hydropower producer. These policies dynamically balance a portfolio, consisting of snowpack-based financial hedging contracts, cash reserves, and debt, based on evolving system conditions. Performance is quantified based on four conflicting objectives, representing the classic tradeoff between “risk” and “return” in addition to decision-makers’ unique preferences towards different risk management instruments. The dynamic policies identified here significantly outperform static management formulations that are more typically employed for financial risk applications in the water resources literature. Additionally, this paper combines visual analytics and information theoretic sensitivity analysis to help decision-makers better understand how different candidate policies achieve their comparative advantages through differences in how they adapt to real-time information. The methodology developed in this paper should be applicable to any organization subject to financial risk stemming from hydrology or other environmental variables (e.g., wind speed, insolation), including electric utilities, water utilities, agricultural producers, and renewable energy developers.

Hydrologic variability poses an important source of financial risk for hydropower-reliant electric utilities, particularly in snow-dominated regions. Drought-related reductions in hydropower production can lead to decreased electricity sales or increased procurement costs to meet firm contractual obligations. This research contributes a methodology for characterizing the tradeoffs between cash flows and debt burden for alternative financial risk management portfolios, and applies it to a hydropower producer in the Sierra Nevada mountains (San Francisco Public Utilities Commission). A newly designed financial contract, based on a snow water equivalent depth (SWE) index, provides payouts to hydropower producers in dry years in return for the producers making payments in wet years. This contract, called a capped contract for differences (CFD), is found to significantly reduce cash flow volatility and is considered within a broader risk management portfolio that also includes reserve funds and debt issuance. Our results show that solutions relying primarily on a reserve fund can manage risk at low cost, but may require a utility to take on significant debt during severe droughts. More risk-averse utilities with less access to debt should combine a reserve fund with the proposed CFD instrument in order to better manage the financial losses associated with extreme droughts. Our results show that the optimal risk management strategies and resulting outcomes are strongly influenced by the utility’s fixed cost burden and by CFD pricing, while interest rates are found to be less important. These results are broadly transferable to hydropower systems in snow-dominated regions facing significant revenue volatility.