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Abstract Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long‐term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large‐ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy‐related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno‐economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large‐ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large‐ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

Abstract Shared community scenarios of societal and environmental system changes have underpinned a broad range of research and assessment studies over the past several decades. These scenarios have largely aimed to address specific questions within broad issue areas like climate change or biodiversity and generally provided information on the drivers of change. The consequences of those drivers, such as impacts on society and policy responses, have tended to be left to the research community to investigate, using scenarios of drivers as inputs to their studies, producing projections of a disparate set of relevant output metrics. While this approach has had many benefits, it has fallen short of producing a robust, comparable literature describing outcomes across studies in common metrics. We argue that new scenarios are needed that extend current approaches to be organized around common outcome metrics for the well‐being and resilience of society and ecosystems. We propose an approach that would focus on agreed upon outcomes for well‐being and resilience as well as critical drivers of change, cut across issues and scales in multiple sectors, and draw on new systematic methods of scenario generation and discovery to highlight scenarios that are most critical in understanding societal risks and responding to them. Research derived from this outcome‐based scenario development approach would facilitate improved assessment of risks of and responses to a range of stressors and the multi‐sector interactions they generate.

Abstract Understanding the long‐term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human‐Earth system, as the long‐term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long‐term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low‐carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food‐energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties.

We explore sustainable electricity system development pathways in South America’s MERCOSUR sub-region under a range of techno-economic, infrastructural, and policy forces. The MERCOSUR sub-region includes Argentina, Brazil, Chile, Uruguay, and Paraguay, which represent key electricity generation, consumption, and trade dynamics on the continent. We use a power system planning model to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results show that, under business-as-usual conditions, wind and solar contribute more than half of new generation capacity by 2050, though this requires substantial expansion of natural gas-based capacity. While new hydropower appears to be less cost-competitive, the existing high capacity of hydropower provides critically important flexibility to integrate the wind and solar and to avoid further reliance on more expensive or polluting resources (e.g., natural gas). Over 90% emission cut by 2050 could be facilitated mostly by enhanced integration (predominantly after 2040) of wind, solar, and battery storage with 11%–28% additional cost, whereas enhanced expansion of hydropower reduces the cost of low-carbon transition, suggesting trade-off opportunities between saving costs and environment in selecting the clean energy resources. Achieving high emission reduction goals will also require enhanced sub-regional electricity trade, which could be mostly facilitated by existing interconnection capacities.

There is significant uncertainty in how global water supply will evolve in the future, due to uncertain climate, socioeconomic, and land use change drivers and variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance for food and energy production. In this work, we introduce a framework that integrates stochastic hydrology and human-environmental systems to characterize uncertainty in future water supply and its multisector impacts. We develop a global stochastic watershed model and demonstrate that this model can generate a large ensemble of realizations of basin-scale runoff with global coverage that preserves the mean, variance, and spatial correlation of a historical benchmark. We couple this model with a well-known human-environmental systems model to explore the impacts of runoff variability on the water and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sectors and regions. Impacts are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future, such as the Indus River basin. For this basin, we find that the variability in future irrigation water withdrawals and irrigated cropland increase over time due to uncertainty in renewable water supply. We also use the Indus basin to show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across human and natural systems and spatial scales.

The impacts of water scarcity depend on physical basin characteristics and global economic dynamics. Here, the authors show scenario assumptions can yield either highly positive or negative economic impacts due to water scarcity, and the drivers of these impacts are basin-specific and cannot be determined a priori.

Abstract Future water scarcity is a global concern with impacts across the energy, water, and land (EWL) sectors. Countries in Latin America and the Caribbean (LAC) are significant producers of agricultural goods, so disruptions resulting from water scarcity in LAC have global importance. Understanding where water scarcity in LAC could occur and what could exacerbate it is critical for strategic resource management and planning, both regionally and globally. Assessing future water scarcity in LAC is challenging given the complex interactions among the EWL sectors and the multiple uncertainties acting across spatial scales. To illuminate these dynamics, we use scenario discovery on a large ensemble representing diverse futures simulated using an integrated human‐environmental systems model. We quantify future water scarcity and its economic impacts across several physical and economic metrics. We find that future levels of reservoir storage expansion could be a significant driver of physical and economic water scarcity, highlighting the importance of strategic water infrastructure development in maintaining future water availability. Changes in crop profit are driven by both water supply and demand, emphasizing the complexity of EWL multisector dynamics. While most of LAC is poised to have abundant land and water resources available for future development, basins in Mexico and along the Pacific coast of South America experience high exposure to severe outcomes and uncertainty across outcomes for at least one metric. We find that drivers of severe scarcity vary spatially and across metrics, highlighting the region's heterogeneity and the importance of considering multiple metrics to assess water scarcity.

Water, energy, and food are all essential components of human societies. Collectively, their respective resource systems are interconnected in what is called the “nexus”. There is growing consensus that a holistic understanding of the interdependencies and trade-offs between these sectors and other related systems is critical to solving many of the global challenges they present. While nexus research has grown exponentially since 2011, there is no unified, overarching approach, and the implementation of concepts remains hampered by the lack of clear case studies. Here, we present the results of a collaborative thought exercise involving 75 scientists and summarize them into 10 key recommendations covering: the most critical nexus issues of today, emerging themes, and where future efforts should be directed. We conclude that a nexus community of practice to promote open communication among researchers, to maintain and share standardized datasets, and to develop applied case studies will facilitate transparent comparisons of models and encourage the adoption of nexus approaches in practice.

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

Abstract This study seeks to understand how Argentina's energy, water, and land (EWL) systems will co‐evolve under a representative array of human and earth system influences, including socioeconomic change, climate change, and climate policy. To capture Argentina's sub‐national EWL dynamics in the context of global change, we couple the Global Change Analysis Model with a suite of consistent, gridded sectoral downscaling models to explore multiple stakeholder‐engaged scenarios. Across scenarios, Argentina has the economic opportunity to use its vast land resources to satisfy growing domestic and international demand for crops, such as oil (e.g., soy) and biomass. The human (rather than earth) system produces the most dominant changes in mid‐century EWL resource use. A Reference scenario characterized by modest socioeconomic growth projects a 40% increase in Argentina's agricultural production by 2050 (relative to 2020) by using 50,000 km2 of additional cropland and 40% more water. A Climate Policy scenario designed to achieve net‐zero carbon emissions globally shortly after mid‐century projects that Argentina could use 100,000 km2 of additional land (and 65% more water) to grow biomass and other crops. The burden of navigating these national opportunities and challenges could fall disproportionately on a subset of Argentina's river basins. The Colorado and Negro basins could experience moderate‐to‐severe water scarcity as they simultaneously navigate substantial irrigated crop demand growth and climate‐induced declines in natural water availability. Argentina serves as a generalizable testbed to demonstrate that multi‐scale EWL planning challenges can be identified and managed more effectively via integrated analysis of coupled human‐earth systems.