The state of Colorado’s West Slope Basins are critical headwaters of the Colorado River and play a vital role in supporting Colorado’s local economy and natural environment. However, balancing the multi-sectoral water demands in the West Slope Basins is an increasing challenge for water managers. Internal variability - irreducible uncertainty stemming from interactions across non-linear processes within the hydroclimate system - complicates future vulnerability assessments. Climate change may exacerbate drought vulnerability in the West Slope Basins, with significant streamflow declines possible by mid-century. In this work, we introduce a novel multi-site Hidden Markov Model (HMM)-based synthetic streamflow generator to create an ensemble of streamflows for all six West Slope Basins that better characterizes the region’s hydroclimate and drought extremes. We capture the effects of climate change by perturbing the HMM to generate a climate-adjusted ensemble of streamflows that reflects plausible changes in climate. We then route both ensembles of streamflows through StateMod, the state of Colorado’s water allocation model, to evaluate spatially compounding drought impacts across the West Slope basins. Our results illustrate how drought events emerging from the system’s stationary internal variability in the absence of climate change can have significant impacts that exceed extreme conditions in the historical record. Further, we find that even relatively modest levels of plausible climate changes can cause a regime shift where extreme drought impacts become routine. These results can inform future Colorado River planning efforts, and our methodology can be expanded to other snow-dominated regions that face persistent droughts.

Robustness analysis can support long-term planning, design and operation of large-scale water infrastructure projects confronting deeply uncertain futures. Diverse actors, contextual specificities, sectoral interests, and risk attitudes make it difficult to identify an acceptable and appropriate robustness metric to rank decision alternatives under deep uncertainty. Here, we contribute an exploratory framework to demonstrate how methodological choices affect robustness evaluation. The framework is applied to a multi-actor, multi-sector Inchampalli-Nagarjuna Sagar (INS) water transfer megaproject in Southern India. We evaluate a suite of dynamic adaptive water transfer strategies discovered using evolutionary multi-objective direct policy search (EMODPS), a status quo strategy of no water transfer, and a strategy proposed by regional authorities. We evaluate robustness across wide-ranging scenarios that capture key uncertainties in potential future changes in reservoir inflows and water demands in the basins. Results show that the priorities of different actors, sectoral perspectives, and risk attitude significantly affect robustness rankings of strategies. We found that compromise strategies obtained from EMODPS are better able to balance the diverse performance requirements across various actors and sectors when compared to the no-transfer and proposed transfer. We reveal a key robustness tradeoff between the donor basin’s ecological requirements and the recipient basin’s socio-economic requirements. While robustness analysis is central to water infrastructure planning, we show why exploratory robustness analyses that engage with conflicting stakeholder objectives is vital for long-term sustainability. Furthermore, the selection of compromise solutions should be guided by an explicit understanding of how assumed risk attitudes shape stakeholders’ understanding of consequential vulnerabilities.

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 (UCRB), 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.

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.

California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region’s natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate-change based scenarios to better understand how impacts propagate through California’s complex water system. A stochastic weather generator, conditioned on tree-ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550-1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food-Energy-Water System model (CALFEWS), a highly resolved, daily model of water storage and conveyance throughout California. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi-year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years emerge. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Scenarios have emerged as valuable tools in managing complex human-natural systems, but the traditional approach of limiting focus on a small number of predetermined scenarios can inadvertently miss consequential dynamics, extremes, and diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by exploring a wide range of possible futures and identifying those that yield consequential vulnerabilities. However, vulnerabilities are typically identified based on aggregate robustness measures that do not take full advantage of the richness of the underlying dynamics in the large ensembles of model simulations and can make it hard to identify key dynamics and/or narrative storylines that can guide planning or further analyses. This study introduces the FRamework for Narrative Scenarios and Impact Classification (FRNSIC; pronounced “forensic’): a scenario discovery framework that addresses these challenges by organizing and investigating consequential scenarios using hierarchical classification of diverse outcomes across actors, sectors, and scales, while also aiding in the selection of narrative storylines, based on system dynamics that drive consequential outcomes. We present an application of this framework to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin’s diverse users and its obligations to downstream states through Lake Powell. We show how FRNSIC can explore alternative sets of impact metrics and drought dynamics and use them to identify narrative drought storylines, that can be used to inform future adaptation planning.

Urban water utilities are increasingly exploring cooperative regional water supply investment and management strategies due to climate change and growing demands. Theoretically, regional cooperative agreements promise improved resource efficiency by realizing economies of scale, adding flexibility for achieving improved supply reliability, and, ideally, limiting individual and collective financial risks. However, there has been little research exploring how implementation uncertainties in the partners’ cooperative actions shape infrastructure investment and management pathways’ robustness and drive counterparty risks. Counterparty risks potentially exacerbate collaborating partners’ vulnerability to the supply and financial challenges they initially sought to mitigate through cooperation. To address these concerns, we introduce the Safe Operating Spaces for Deeply Uncertain Water Supply Pathways (DUSOS Pathways) framework. The framework, demonstrated on the multi-city Sedento Valley benchmarking test case, facilitates the formal characterization of the effects of implementation uncertainty within cooperative regional water supply investment and management policy pathways. Results demonstrate the path-dependent effects of implementation uncertainties in short-term operational drought mitigation instruments and long-term infrastructure investments. Our analysis further reveals the potential for increased regional conflict due to asymmetries between partners’ vulnerabilities to the actions of cooperating partners that can be exacerbated by other deeply uncertain factors that reduce their robustness (e.g., demand growth rates). The study finally delineates safe operating spaces, beyond which utilities experience robustness degradation and increased vulnerabilities to future uncertainties to guide implementation of cooperative policy pathways. Overall, this framework is broadly applicable to regional systems seeking to navigate complex cooperative regional water supply investment and management policy pathways.

To aid California's water sector to better manage future climate extremes, we present a method for creating a regional ensemble of plausible daily future climate and streamflow scenarios that represent natural climate variability captured in a network of tree-ring chronologies, and then embed anthropogenic climate change trends within those scenarios. We use 600 years of paleo-reconstructed weather regimes to force a stochastic weather generator, which we develop for five subbasins in the San Joaquin River in the Central Valley region of California. To assess the compound effects of climate change, we create temperature series that reflect scenarios of warming and precipitation series that are scaled to reflect thermodynamically driven shifts in the daily precipitation distribution. We then use these weather scenarios to force hydrologic models for each of the San Joaquin subbasins. The paleo-forced streamflow scenarios highlight periods in the region's past that produce flood and drought extremes that surpass those in the modern record and exhibit large non-stationarity through the reconstruction. Variance decomposition is employed to characterize the contribution of natural variability and climate change to variability in decision-relevant metrics related to floods and drought. Our results show that a large portion of variability in individual subbasin and spatially compounding extreme events can be attributed to natural variability, but that anthropogenic climate changes become more influential at longer planning horizons. The joint importance of climate change and natural variability in shaping extreme floods and droughts is critical to resilient water systems planning and management in the Central Valley region.

Holistic approaches are needed to investigate the capacity of current water resource operations and infrastructure to sustain water supply and critical ecosystem health under projected drought conditions. Drought vulnerability is complex, dynamic, and challenging to assess, requiring simultaneous consideration of changing water demand, use and management, hydrologic system response, and water quality. We are bringing together a community of scientists from the U.S. Geological Survey, National Center for Atmospheric Research, Department of Energy, and Cornell University to create an integrated human-hydro-terrestrial modeling framework, linking pre-existing models, that can explore and synthesize system response and vulnerability to drought in the Delaware River Basin (DRB). The DRB provides drinking water to over 15 million people in New York, New Jersey, Pennsylvania, and Delaware. Critical water management decisions within the system are coordinated through the Delaware River Basin Commission and must meet requirements set by prior litigation. New York City has rights to divert water from the upper basin for water supply but must manage reservoir releases to meet downstream flow and temperature targets. The Office of the Delaware River Master administers provisions of the Flexible Flow Management Program designed to manage reservoir releases to meet water supply demands, habitat, and specified downstream minimum flows to repel upstream movement of saltwater in the estuary that threatens Philadelphia public water supply and other infrastructure. The DRB weathered a major drought in the 1960s, but water resource managers do not know if current operations and water demands can be sustained during a future drought of comparable magnitude. The integrated human-hydro-terrestrial modeling framework will be used to identify water supply and ecosystem vulnerabilities to drought and will characterize system function and evolution during and after periods of drought stress. Models will be forced with consistent input data sets representing scenarios of past, present, and future conditions. The approaches used to unify and harmonize diverse data sets and open-source models will provide a roadmap for the broader community to replicate and extend to other water resource issues and regions.

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.

Regionalization approaches wherein 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 deeply uncertain risks. Successful regional cooperative investment and management pathways, however, 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 PathwaysERAS), an exploratory modeling framework for developing regional water supply management and infrastructure investment pathways. Our framework explores equity and power relationships within cooperative pathways using multiple rival framings of robustness, each representing a competing hypothesis about how performance objectives should be prioritized. To capture the time-evolving dynamics of infrastructure pathways, DU PathwaysERAS 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 equity. Results further illustrate that regional and individual vulnerabilities are highly interdependent, emphasizing the need to craft agreements that limit counterparty risks from the actions of cooperating partners. Beyond the Research Triangle, these results are broadly applicable to cooperative water supply infrastructure investment and management globally.