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Abstract Climate change‐induced shifts in snow storage and snowmelt patterns pose risks for adverse impacts to people, the environment, and irrigated agriculture. Existing research primarily focuses on evaluating these risks to irrigated agriculture at large scales, overlooking the role of local context in shaping risk dynamics. Consequently, many “at‐risk” areas lack insight into how adaptation strategies for managing risk through water supply augmentation or water conservation vary across contexts and over time. To address this gap, we develop a comprehensive index for evaluating irrigated agriculture's risk and adaptation potential to changes in snow at local scales and apply it throughout the western US. Results confirm trends toward escalating risk for changes in snow storage and snowmelt patterns over the century. However, substantial heterogeneity in the extent and drivers of risk exists due to variability in localized interactions between declines in water supply (approximately −9% ± 13% by 2100) and increased agricultural demand (approximately 7% ± 5% by 2100). Despite an existing focus on supply augmentation as a critical adaptation strategy to reduce risk, we show its effectiveness diminishes for many areas over time, declining to an average of −54% of historical augmentation potential by 2100. Conserving water through historical changes in crop acreage and type emerges as a more stable adaptation measure, reducing demand by 7%–8% regardless of time. While particularly relevant for higher elevation, less intensive agricultural settings in snowmelt‐dependent regions, findings underscore the need for strategies that support local‐scale, context‐appropriate adaptation to effectively manage escalating risk as snow changes.

Privately owned rangelands in the western US support many ecosystem services and are threatened by financial incentives favoring conversion to housing development and more intensive forms of agriculture. Recognizing this threat, the impact investment community has identified rangeland management as a potential investing strategy to produce financial returns while preserving or enhancing the ecosystem services provided by intact rangelands. This strategy is based primarily on the notion that a capital-intensive conversion from continuous to rotational grazing can financially sustain rangelands through a combination of increased productivity and potentially monetized ecosystem service flows. The potential for these gains is supported by compelling anecdotal evidence, yet a robust body of scientific literature based on rigorous field experiments has not supported those claims, nor produced transferrable estimates of the benefits provided by rotational grazing of livestock (particularly cattle in the western US). Therefore, to demonstrate investment viability and measure investment success, impact investors will likely need to address these well-documented disconnects through some combination of monitoring and process-based modeling. This study examines the extent to which existing modeling tools are up to this task, by assessing the ability of two process-based models to represent four specific rotational grazing benefits put forth by impact investors, using a ranch in northeastern Wyoming as a case study. Using the Soil Water Assessment Tool, we simulated high magnitude changes in the water balance from surface runoff to evapotranspiration, which may be a benefit or negative impact depending on context (Benefit 1). We simulated a decrease in soil water storage under rotational grazing, which directly contradicts the outcome assumed in investment literature (Benefit 2). Using the InVEST beta Rangeland Production Model (based on the Century ecosystem model), we simulated increased biomass productivity (Benefit 3) under rotational grazing, which enhanced animal performance under some management parameters but negatively impacted it in others (Benefit 4). We conclude that the impact investing community will likely find greater success through a shift to objective-oriented ranch management, rather than a specific focus on rotation, and will also need additional investment in science and monitoring to demonstrate benefits.

Climate change is altering the seasonal accumulation and ablation of snow across mid-latitude mountainous regions in the Northern Hemisphere with profound implications for the water resources available to downstream communities and environments. Despite decades of empirical and model-based research on snowmelt-driven streamflow, our ability to predict whether streamflow will increase or decrease in a changing climate remains limited by two factors. First, predictions are fundamentally hampered by high spatial and temporal variability in the processes that control net snow accumulation and ablation across mountainous environments. Second, we lack a consistent and testable framework to coordinate research to determine which dominant mechanisms influencing seasonal snow dynamics are most and least important for streamflow generation in different basins. Our data-driven review marks a step towards the development of such a framework. We first conduct a systematic literature review that synthesizes knowledge about seasonal snowmelt-driven streamflow and how it is altered by climate change, highlighting unsettled questions about how annual streamflow volume is shaped by changing snow dynamics. Drawing from literature, we then propose a framework comprised of three testable, inter-related mechanisms—snow season mass and energy exchanges, the intensity of snow season liquid water inputs, and the synchrony of energy and water availability. Using data for 537 catchments in the United States, we demonstrate the utility of each mechanism and suggest that streamflow prediction will be more challenging in regions with multiple interacting mechanisms. This framework is intended to inform the research community and improve management predictions as it is tested and refined.