Elevated healthcare strain during the COVID-19 pandemic increased patient mortality rates and prompted costly non-pharmaceutical interventions. This work examines how the size of a hospital's service population, which can be expanded by linking hospitals through patient transfer networks, influences healthcare strain through two diversification mechanisms: (i) volatility dampening, which reduces the volatility of demand for healthcare resources by aggregating uncorrelated individual patient needs, and (ii) epidemic phase averaging, which flattens demand peaks by aggregating patients from asynchronous local epidemics. Using facility-level intensive care unit (ICU) data across three COVID waves, we analyze how service population size affects the size of peaks in ICU occupancy, evaluate the two proposed mechanisms, and explore the health impacts of pooling through scenario simulations grounded in observed occupancy levels. We find that volatility dampening effects reduce variability in ICU occupancy at a rate proportional to the square root of population size, whereas the effectiveness of epidemic phase averaging is dependent on the transmission dynamics of the pathogen. Increasing service population size also reduces the frequency and magnitude of demand spikes, lowering the likelihood of costly short-term interventions and increasing demand predictability. In the winter 2020 wave, our simulations find that randomly constructed local pools (2-6 hospitals) reduce COVID ICU mortality by a median of 2%-7%, with reductions exceeding 6%-18% in the top decile of outcomes. These findings suggest that coordinated patient transfer strategies could meaningfully reduce mortality and costs during future pandemics.

Variable hydrometeorological conditions can impact electric utilities’ financial stability. Extreme temperatures often increase electricity demand, raising utility costs, while drought reduces hydropower generation and often reduces revenues, with financial impacts potentially exacerbated by spikes in fuel prices, particularly natural gas. In this study, a model of the US. West Coast power system is combined with a financial risk model of a large California electric utility as it responds to variable hydrometeorology and market conditions, and is used to test the performance of a novel financial tool for managing risk. An insurance contract based on a composite index of measures related to streamflow, temperature, and natural gas prices is developed and its cost-effectiveness is compared against a portfolio of three currently available index contracts each based on a single index. The new composite index contract achieves an equivalent reduction in the utility’s net revenue variance as a portfolio of the three existing contract types for roughly half the cost with the cost reduction largely attributable to lower basis risk associated with the composite index contract. The utility’s financial risk and the effectiveness of the new contract are also explored under an alternative regulatory scenario involving a pollution tax intended to reduce air pollution damages and emissions. Overall, this case study represents a new approach to managing financial risk arising from hydrometeorological and market variability for vertically integrated utilities, the most common utility structure.

Droughts and heatwaves create significant financial risk for hydropower suppliers, as drought reduces generation and revenues, while heatwaves increase demand and often costs. While many suppliers manage their risk independently, some are government-supported. This leads to an important question: How do the costs of a government-supported risk management strategy compare with a self-supported strategy? This research provides a framework to address this question, applying it to a hydropower supplier in the United States with access to a government-supported line of credit, the Bonneville Power Administration (BPA). The analysis includes models to stochastically simulate weather, electricity prices, and the BPA's operations. Results suggest that government support effectively mitigates the BPA's hydrometeorological financial risk but at costs to taxpayers that can exceed $1 billion over 20 years. Replacing the line of credit with index insurance comparably manages financial risk at lower costs limited to the BPA and its customers. This framework for comparing government- and self-supported approaches may prove useful to hydropower suppliers and governments, as they decide how to manage hydrometeorological financial risk, especially in lower-income countries with limited public funds.

In 2022, 2023 and 2024, flash droughts in the U.S. Midwest caused the lower Mississippi River to drop to record low levels during corn and soybean harvest season. Grain barges that move the crops downriver to New Orleans for export were forced to reduce their loads to avoid grounding. The load reductions and by extension the low river levels have been attributed as the causes for significant spikes in barge spot prices during the droughts, which for the transit from St. Louis, MO to New Orleans, LA climbed from an average pre‐drought maximum of $27/ton to as high as >$105/ton in 2022. A dynamic regression model was developed to test whether the barge rate highs might also be the result of high fuel costs over the same period. Results produced by the model not only support this hypothesis but indicate that the increases in fuel costs were the dominant reason barge rates spiked. The influence of the flash droughts on the other hand was estimated to account for ≤16% of the peak rates. These results are supported by the fact that the rates did not surge during past events when barge loads had to be reduced and shipping was delayed, including during flash droughts in 2012 and 2013.

Measuring flooding through time is crucial for understanding exposure and vulnerability — key components to estimating flood risks and impacts. Yet, historical records of flood inundation are sparse. In this study, we reconstruct flood extents for 78 damaging events in eastern North Carolina between 1996 and 2020 using high‐resolution geospatial data and address‐level National Flood Insurance Program (NFIP) records. We train random forest models on NFIP‐based labeled flood presence and absence data and a suite of geospatial predictors. Then, we predict the probability of flood damage at every 30 m grid cell within our model domain. Our models achieve an average Area Under the Curve of 0.76 and outperform flood extent estimates from process‐based and remote sensing models when evaluated against NFIP data for six events. We find that approximately 90,000 (2.3%) buildings in our study area flooded at least once, of which over 20,000 (0.53%) flooded more than once. Our estimate is more than double the number of buildings that filed NFIP claims between 1996 and 2020. Furthermore, 43% of flooded buildings are located outside the Federal Emergency Management Agency (FEMA) Special Flood Hazard Area. Our results illustrate that flood exposure, especially repetitive exposure, is much more widespread than previously recognized. By generating a comprehensive record of past flood extents using address‐level observations of damage, we create a first‐of‐its‐kind geospatial database that can be used to identify locations of repetitive flooding. This represents a crucial first step in examining the dynamic relationships between flood exposure, vulnerability, and risk.

Many water markets in the Western United States (U.S.) have the ability to reallocate water temporarily during drought, often as short-term water rights leases from lower value irrigated activities to higher value urban uses. Regulatory approval of water transfers, however, typically takes time and involves high transaction costs that arise from technical and legal analyses, discouraging short-term leasing. This leads municipalities to protect against drought-related shortfalls by purchasing large volumes of infrequently used permanent water rights. High transaction costs also result in municipal water rights rarely being leased back to irrigators in wet or normal years, reducing agricultural productivity. This research explores the development of a multi-year two-way option (TWO) contract that facilitates leasing from agricultural-to-urban users during drought and leasing from urban-to agricultural users during wet periods. The modeling framework developed to assess performance of the TWO contracts includes consideration of the hydrologic, engineered, and institutional systems governing the South Platte River Basin in Colorado where there is growing competition for water between municipalities (e.g., the city of Boulder) and irrigators. The modeling framework is built around StateMod, a network-based water allocation model used by state regulators to evaluate water rights allocations and potential rights transfers. Results suggest that the TWO contracts could allow municipalities to maintain supply reliability with significantly reduced rights holdings at lower cost, while increasing agricultural productivity in wet and normal years. Additionally, the TWO contracts provide irrigators with additional revenues via net payments of option fees from municipalities.

Abstract The ability to reallocate water to higher‐value uses during drought is an increasingly important “soft‐path” tool for managing water resources in an uncertain future. In most of the Western United States, state‐level water market institutions that enable reallocation also impose substantial transaction costs on market participants related to regulatory approval and litigation. These transaction costs can be prohibitive for many participants in terms of both costs and lengthy approval periods, limiting transfers and reducing allocation efficiency, particularly during drought crises periods. This manuscript describes a mechanism to reduce transaction costs by adapting an existing form of informal leases to facilitate quicker and less expensive transfers among market participants. Instead of navigating the formal approval process to lease a water right, informal leases are financial contracts for conservation that enable more junior holders of existing rights to divert water during drought, thereby allowing the formal transfer approval process to be bypassed. The informal leasing approach is tested in the Upper Colorado River Basin, where drought and institutional barriers to transfers lead to frequent shortages for urban rights holders along Colorado's Front Range. Informal leases are facilitated via option contracts that include adaptive triggers and that define volumes of additional, compensatory, releases designed to mitigate impacts to instream flows and third parties. Results suggest that more rapid reallocation of water via informal leases could have resulted in up to $222 million in additional benefits for urban rights holders during the historical period 1950–2013.

The last decade has seen dramatic growth in solar power. In some regions, the most favorable land for solar panels is farmland, which is often flat and exposed to high levels of irradiance. At the same time, the agricultural sector is faced with growing challenges, notably changing water availability and increasingly frequent extreme weather events. The combination of these trends presents an opportunity for a synergistic relationship between the agriculture and solar sectors: agrivoltaic systems (AVS). In AVS, solar panels are placed above and between crops, such that the same land produces both food and energy. This system has beneficial microclimate impacts, such as reduced evapotranspiration. Yet, despite these benefits there has been limited uptake of AVS. One reason may be hesitation on the part of farmers, whose perceptions of AVS have been explored little. This analysis seeks to address part of this gap by exploring the relationship between farmer perceptions and interest in AVS. A Likert scale survey was designed and distributed to farmers across two large, agriculturally productive states, North Carolina and California. Responses from the 41 participants who fully completed the survey suggest that farmers who perceive AVS as diversifying their income or whose goals include reducing water use are the most interested in installing AVS. Respondents also identified financial viability as a major concern, agreeing that upfront cost is a major barrier to AVS, and markets as the most influential driver of crop decisions. These findings provide insights for policymakers interested in expanding AVS, particularly in response to environmental stressors, such as water scarcity and extreme weather events. They also suggest the aspects of AVS that may be most important to farmers, and most effective in encouraging AVS uptake. This information can support efforts to promote AVS, contributing to sustainable agriculture.

As regions around the world invest billions in new infrastructure to overcome increasing water scarcity, better guidance is needed to facilitate cooperative planning and investment in institutionally complex and interconnected water supply systems. This work combines detailed water resource system ensemble modeling with multiobjective intelligent search to explore infrastructure investment partnership design in the context of ongoing canal rehabilitation and groundwater banking in California. Here we demonstrate that severe tradeoffs can emerge between conflicting goals related to water supply deliveries, partnership size, and the underlying financial risks associated with cooperative infrastructure investments. We show how hydroclimatic variability and institutional complexity can create significant uncertainty in realized water supply benefits and heterogeneity in partners' financial risks that threaten infrastructure investment partnership viability. We demonstrate how multiobjective intelligent search can design partnerships with substantially higher water supply benefits and a fraction of the financial risk compared to status quo planning processes. This work has important implications globally for efforts to use cooperative infrastructure investments to enhance the climate resilience and financial stability of water supply systems. Hamilton and colleagues demonstrate critical water supply risks and financial tradeoffs for California utilities investing in cooperative infrastructure projects and develops computational methods for designing more resilient partnerships under uncertainty.

Key Takeaways Cooperation among water utilities expands opportunities to provide an affordable, reliable water supply, both now and in the long term. Computational modeling of utility partnerships can explore the potential benefits (and pitfalls) of cooperative infrastructure development. Analysis of agreements for shared treatment plant development in North Carolina provides a framework for design and evaluation of cooperation in other utility contexts.

Regionalization approaches—where utilities in close geographic proximity cooperate to manage drought risks and co‐invest in new infrastructure—are increasingly necessary strategies for leveraging economies of scale to meet growing demands and navigate financial risks. However, regionalization also brings new challenges to water supply planning. Successful regionalization policies must equitably balance the interests of multiple partners while navigating power relationships between regional actors. In long‐term infrastructure planning contexts, this challenge is heightened by the evolving system‐state dynamics, which may be fundamentally reshaped by infrastructure investment. This work introduces Equitable, Robust, Adaptive, and Stable Deeply Uncertain Pathways (DU Pathways ERAS ), an exploratory modeling framework for developing regional water supply management and infrastructure investment pathways. DU Pathways ERAS provides an integrated framework for stakeholders to evaluate the equity of policy outcomes across cooperating partners and explore regional power relationships within cooperative infrastructure policies. To capture the time‐evolving dynamics of infrastructure pathways, DU Pathways ERAS features new tools to measure the adaptive capacity of pathway policies and evaluate time‐evolving vulnerability. We demonstrate our framework on a six‐utility water supply partnership seeking to develop cooperative infrastructure investment pathways in the Research Triangle, North Carolina. Our results indicate that commonly employed framings of robustness can have large and unintended adverse consequences for regional partnerships. Results further illustrate that regional and individual vulnerabilities are highly interdependent and emphasize the need to limit counterparty risks through carefully designed cooperative agreements. Beyond the Research Triangle, these results are broadly applicable to cooperative water supply infrastructure investment and management globally.

Water managers must constantly balance investment in infrastructure upgrades to ensure reliable water supply with the affordability of water rates for consumers. As a result, trade-offs between water supply and financial objectives have become central to the long-term sustainability of utility operations. Few studies, however, have directly quantified decision-relevant financial benchmarks of water supply system adaptation. Benchmarks include debt covenants, guidelines required by creditors seeking assurance that debt will be repaid. Violation of covenant thresholds risks a downgrade of a utility's credit rating, higher interest rates on future debt, and higher costs for new infrastructure. This work introduces an exploratory modeling framework that carefully couples adaptive water supply planning with financial modeling to better track how utility budgetary decision making can adapt to infrastructure expansion and future water demand growth. Demonstrated through an evaluation of infrastructure planning for Tampa Bay Water (TBW), results showcase TBW budgetary adaptation in response to water demand growth and supply expansion, quantifying the financial implications of infrastructure planning decisions and demand growth on water rates as well as the bond covenants. This study underscores the importance of integrating dynamic and adaptive financial modeling in providing realistic decision support that addresses both supply reliability and financial stability.

Direct damage from flooding at residential properties has typically been categorized as insured, with liabilities accruing to insurers, or uninsured, with costs accruing to property owners. However, residential flooding can also expose lenders and local governments to financial risk, though the distribution of this risk is not well understood. Flood losses are not limited to direct damages, but also include indirect effects such as decreases in property values, which can be substantial, though are rarely well quantified. The combination of direct damage and property value decrease influences rates of mortgage default and property abandonment in the wake of a flood, creating financial risk. In this research, property-level data on sales, mortgages, and insurance claims are used in combination with machine learning techniques and geostatistical methods to provide estimates of flood losses that are then utilized to evaluate the risk of default and abandonment in eastern North Carolina following Hurricane Florence (2018). Within the study area, Hurricane Florence generated $366M in observed insured damages and an estimated $1.77B in combined uninsured damages and property value decreases. Property owners, lenders, and local governments were exposed to an additional $562M in potential losses due to increased rates of default and abandonment. Areas with lower pre-flood property values were exposed to greater risk than areas with higher valued properties. Results suggest more highly resolved estimates of a flooding event's systemic financial risk may be useful in developing improved flood resilience strategies.

Hydrologic variability presents significant challenges to water providers in terms of managing supply risk, but resilient systems must also manage the corresponding financial risk. During drought water providers pump less water, make fewer water deliveries, and earn less revenue. Meanwhile, their costs are mostly fixed, with a large fraction linked to debt service resulting from the capital-intensive development of water supply infrastructure. The consequent budget shortfalls can be very disruptive and must be managed effectively if this critical infrastructure is to remain resilient in a future that involves increasingly frequent and severe droughts. For this research, an object-oriented model was developed that integrates hydrologic and financial systems to provide new insights into ways in which large water providers can better quantify and manage their financial risk and establish strategies for promoting greater financial resiliency in the face of climate change. This work involves a case study of the Central Arizona Project (CAP), one of the largest water providers in the Western U.S. that serves nearly 6 million people (e.g., Phoenix, Tucson), as well as large tracts of irrigated land and the demands of several Native American tribes. Current reductions in CAP's access to Colorado River water will reduce its water deliveries by 40% this year, resulting in substantially lower revenues. In response, CAP will raise its wholesale water prices significantly so that it can meet its costs. As an alternative to increasing wholesale prices, CAP could consider reducing the financial risks of hydrologic uncertainty by utilizing some portion of its reserve funds or leveraging its ad valorem tax. Results suggest that CAP's use of reserves could limit annual price increases to 10% or 15% per year through 2028, but to limit annual price increases to 5% under drier conditions would nearly deplete existing reserves in a few years.

Low-income, rural frontline communities of California's Central Valley experience environmental and socioeconomic injustice, water insecurity, extremely poor air quality, and lack of fundamental infrastructure (sewage, green areas, health services), which makes them less resilient. Many communities depend financially on agriculture, while water scarcity and associated policy may trigger farmland retirement further hindering socioeconomic opportunities. Here we propose a multi-benefit framework to repurpose cropland in buffers inside and around (400-m and 1600-m buffers) 154 rural disadvantaged communities of the Central Valley to promote socioeconomic opportunities, environmental benefits, and business diversification. We estimate the potential for (1) reductions in water and pesticide use, nitrogen leaching, and nitrogen gas emissions, (2) managed aquifer recharge, and (3) economic and employment impacts associated with clean industries and solar energy. Retiring cropland within 1600-m buffers can result in reductions in water use of 2.18 km3/year, nitrate leaching into local aquifers of 105,500 t/year, greenhouse gas emissions of 2,232,000 t CO2-equivalent/year, and 5388 t pesticides/year, with accompanying losses in agricultural revenue of US$4213 million/year and employment of 25,682 positions. Buffer repurposing investments of US$27 million/year per community for ten years show potential to generate US$101 million/year per community (total US$15,578 million/year) for 30 years and 407 new jobs/year (total 62,697 jobs/year) paying 67 % more than prior farmworker jobs. In the San Joaquin Valley (southern Central Valley), where groundwater overdraft averages 2.3 km3/year, potential water use reduction is 1.8 km3/year. We have identified 99 communities with surficial soils adequate for aquifer recharge and canals/rivers within 1600 m. This demonstrates the potential of managed aquifer recharge in buffered zones to substantially reduce overdraft. The buffers framework shows that well-planned land repurposing near disadvantaged communities can create multiple benefits for farmers and industry stakeholders, while improving quality of life in disadvantaged communities and producing positive externalities for society.

Cooperative management of natural resources is a key component of a transition to a sustainable society and urban water supply planning is a prime example. Regional cooperation among urban water utilities is a powerful mechanism for improving supply reliability and financial stability in urban water supply systems. Through coordinated drought mitigation and joint infrastructure investment, water utilities can efficiently exploit existing water supplies and reduce or delay the need for new supply infrastructure. However, cooperative water management brings new challenges for planning and implementation. The benefits of cooperation may not be uniformly distributed across cooperating partners, resulting in the "instability" of cooperative compromises. Further, cooperation may add new vulnerabilities for each partner by imbuing their cooperating partners with the power to impact their performance through policy actions. Power imbalances stemming from these vulnerabilities can lead to conflict between cooperating partners that destabilize otherwise robust planning alternatives. This work contributes a new exploratory modeling centered framework for assessing cooperative stability and mapping power relationships in cooperative infrastructure investment and water supply management policies. Our framework uses multi-objective optimization as an exploratory tool to discover how cooperating partners may be incentivized to defect from robust regional water supply partnerships and identifies how the actions of each regional partner shape the vulnerability of its cooperating partners. Our methodology is demonstrated on the Sedento Valley, a highly challenging hypothetical regional urban water supply benchmarking problem. Our results reveal complex regional power relationships between the region's cooperating partners and suggest ways to improve cooperative stability.

Hydrologic variability can cause large swings in hydropower generation, inducing significant volatility in power sales. Dry years often result in low revenues that can threaten a hydropower supplier's ability to meet its fixed costs, leading to budget shortfalls, lower credit ratings, higher interest rates, and, ultimately, higher rates. This is particularly true for suppliers in hydropower-dominated regions, such as the Bonneville power administration (BPA). The BPA strategy for managing its hydrologic financial risk is multilayered, involving cash reserves, a line of credit, and tariff adjustments. Yet, compared to its long-term energy contracts and debt service, BPA's risk assessment is conducted on a short-term basis, thereby neglecting medium- and long-term temporal dynamics impacting their financial risk. This paper focuses on (1) evaluating BPA's hydrologic financial risk; and (2) testing the effectiveness of BPA's existing risk management strategy. Results suggest that BPA's financial risk will grow substantially over the next 20 years as its risk management tools become increasingly inadequate, providing cautionary lessons for organizations in similarly hydrodominated systems despite the current use of common risk management tools. (C) 2022 American Society of Civil Engineers.

Urban water utilities, facing rising demands and limited supply expansion options, increasingly partner with neighboring utilities to develop and operate shared infrastructure. Inter‐utility agreements can reduce costs via economies of scale and help limit environmental impacts, as substitutes for independent investments in large capital projects. However, unexpected shifts in demand growth or water availability, deviating from projections underpinning cooperative agreements, can introduce both supply and financial risk to utility partners. Risks may also be compounded by asymmetric growth in demand across partners or inflexibility of the agreement structure itself to adapt to changing conditions of supply and demand. This work explores the viability of both fixed and adjustable capacity inter‐utility cooperative agreements to mitigate regional water supply and financial risk for utilities that vary in size, growth expectations, and independent infrastructure expansion options. Agreements formalized for a shared regional water treatment plant are found to significantly improve regional supply reliability and financial outcomes, despite highly correlated weather and climate across neighboring supply systems (e.g., concurrent drought events). Regional improvements in performance, however, mask tradeoffs among individual agreement partners. Adjustable treatment capacity allocations add flexibility to inter‐utility agreements but can compound financial risk to each utility as a function of the decision‐making of the other partners. Often the sensitivity to partners' decision‐making under an adjustable agreement degrades financial performance, relative to agreements with fixed capacities allocated to each partner. Our results demonstrate the significant benefits cooperative agreements offer, providing a template to aid decision‐makers in the development of water supply partnerships.

Electric power utilities face a wide range of risks that cause financial uncertainty, with potential impacts on prices for customers. Among these, weather variability and retail load defection are perhaps two of the most studied. Whereas weather extremes expose utilities to unpredictable swings in electricity supply and demand, retail load defection, in which customers adopt distributed energy resources or switch to alternative providers, can alter utility business models fundamentally. We showed for the first time that these two phenomena can interact dynamically, with potential negative consequences for electricity ratepayers. We found that retail load defection could alter utilities' financial exposure to weather risk in a matter of years. Using open-source power system simulation software coupled with a utility financial model, we simulated outcomes for a major hydropower-producing California electric utility under stationary hydrometeorological uncertainty, and under three different load defection scenarios ranging from 0% to 90%. We found that as load defection increases, the utility's three main businesses (wholesale generation, transmission, and retail distribution) shift in relative importance. As a consequence, the impacts of interannual variability in hydropower production and demand in the utility's system (a function of streamflow and air temperatures, respectively) become significantly altered. Air temperatures (a proxy for demand) become more predictive of utility financial performance, whereas the utility's exposure to hydrology is poised to shift in complex ways. Drought will remain a major risk, but extremely wet years (which historically are beneficial to the utility's significant hydropower holdings) may become damaging due to their association with low market prices. Our results also suggest that load defection could put much more pressure on utilities to make major annual rate adjustments or quickly adapt current strategies for managing weather risk. (C) 2021 American Society of Civil Engineers.

Water scarcity is a growing problem around the world, and regions such as California are working to develop diversified, interconnected, flexible, and resilient water supply portfolios. To meet these goals, water utilities, irrigation districts, and other organizations 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 cost‐benefit analyses), while ignoring the heterogeneity of benefits, costs, and risks across the individual partners. This study contributes an exploratory modeling analysis that tests thousands of alternative infrastructure partnerships in the Central Valley of California, using a daily scale simulation model (CALFEWS) 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 is the project's debt distributed?) as by extreme hydrologic conditions (i.e., floods and droughts). Importantly, most of the analyzed partnerships yield highly unequal distributions of water supply and financial risks across the partners, so that only 8% of the partnerships explored are capable of providing water to each partner for under $200/ML. Partnership viability is especially rare in the absence of groundwater banking facilities (1%), or under dry hydrologic conditions (1%), even under explicitly optimistic assumptions regarding climate change. Given these results, we outline several major policy implications for institutionally complex regions such as California, which are currently investing heavily in cooperative approaches to resilient water portfolio design.