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Abstract In the western United States, water supplies largely originate as snowmelt from forested land. Forests impact the water balance of these headwater streams, yet most predictive runoff models do not explicitly account for changing snow‐vegetation dynamics. Here, we present a case study showing how warmer temperatures and changing forests in the Henrys Fork of the Snake River, a seasonally snow‐covered headwater basin in the Greater Yellowstone Ecosystem, have altered the relationship between April 1st snow water equivalent (SWE) and summer streamflow. Since the onset and recovery of severe drought in the early 2000s, predictive models based on pre‐drought relationships over‐predict summer runoff in all three headwater tributaries of the Henrys Fork, despite minimal changes in precipitation or snow accumulation. Compared with the pre‐drought period, late springs and summers (May–September) are warmer and vegetation is greener with denser forests due to recovery from multiple historical disturbances. Shifts in the alignment of snowmelt and energy availability due to warmer temperatures may reduce runoff efficiency by changing the amount of precipitation that goes to evapotranspiration versus runoff and recharge. To quantify the alignment between snowmelt and energy on a timeframe needed for predictive models, we propose a new metric, the Vegetation‐Water Alignment Index (VWA), to characterize the synchrony of vegetation greenness and snowmelt and rain inputs. New predictive models show that in addition to April 1st SWE, the previous year's VWA and summer reference evapotranspiration are the most significant predictors of runoff in each watershed and provide more predictive power than traditionally used metrics. These results suggest that the timing of snowmelt relative to the start of the growing season affects not only annual partitioning of streamflow, but can also determine the groundwater storage state that dictates runoff efficiency the following spring. 

Abstract Massive ground ice in Arctic regions underlain using continuous permafrost influences hydrologic processes, leading to ground subsidence and the release of carbon dioxide and methane into the atmosphere. The relation of massive ground ice such as ice wedges to water tracks and seasonally saturated hydrologic pathways remains uncertain. Here, we examine the location of ice wedges along a water track on the North Slope of Alaska using Ground‐Penetrating Radar (GPR) surveys, in situ measurements, soil cores, and forward modeling. Of nine unique GPR surveys collected in the summers of 2022 and 2023, seven exhibit distinctive “X”‐shaped reflections above columnar reflectors that are spatially correlated with water track margins. Forward modeling of plausible geometries suggests that ice wedges produce reflection patterns most similar to the reflections observed in our GPR profiles. Additionally, a large magnitude (∼71 mm) rain event on 8 July 2023 led to a ground collapse that exposed four ice wedges on the margin of the studied water track, ∼100 m downstream of our GPR surveys. Together, this suggests that GPR is a viable method for identifying the location of ice wedges as air temperatures in the Arctic continue to increase, we expect that ice wedges may thaw, destabilizing water tracks and causing ground collapse and expansion of thermo‐erosional gullies. This ground collapse will increase greenhouse gas emissions and threaten the Arctic infrastructure. Future geophysical analysis of upland Arctic hillslopes should include additional water tracks to better characterize potential heterogeneity in permafrost vulnerability across the warming Arctic. 

Abstract Non‐perennial streams are receiving increased attention from researchers, however, suitable methods for measuring their hydrologic connectivity remain scarce. To address this deficiency, we developed Bayesian statistical approaches for measuring both average active stream length, and a new metric called average communication distance. Average communication distance is a theoretical increasedeffective distancethat stream‐borne materials must travel, given non‐continuous streamflow. Because it is the product of the inverse probability of surface water presence and stream length, the average communication distance of a non‐perennial stream segment will be greater than its actual physical length. As an application we considered Murphy Creek, a simple non‐perennial stream network in southwestern Idaho, USA. We used surface water presence/absence data obtained in 2019, and priors for the probability of surface water, based on predictions from an existing regional United States Geological Survey model. Average communication distance posterior distributions revealed locations where effective stream lengths increased dramatically due to flow rarity. We also found strong seasonal (spring, summer, fall) differences in network‐level posterior distributions of both average stream length and average communication distance. Our work demonstrates the unique perspectives concerning network drying provided by communication distance, and demonstrates the general usefulness of Bayesian approaches in the analysis of non‐perennial streams. 

Abstract Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no‐flow fraction, date of first no flow, and duration of the dry‐down period, with further divergence between natural and human‐altered watersheds. Aridity was a primary driver of no‐flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry‐down duration showed stronger associations with nonclimate drivers compared to no‐flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.