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Wildfire area has been increasing in most ecoregions across the western United States, including snow-dominated regions. These fires modify snow accumulation, ablation, and duration, but the sign and magnitude of these impacts can vary substantially between regions. This study compares spatiotemporal patterns of western United States wildfires between ecoregions and snow zones. Results demonstrate significant increases in wildfire area from 1984 to 2020 throughout the West, including the Sierra Nevada, Cascades, Basin and Range, and Northern to Southern Rockies. In the late snow zone, where mean annual snow-free date is in May or later, 70% of ecoregions experienced significant increases in wildfire area since 1984. The distribution of burned area shifted from earlier melt zones to later-melt snow zones in several ecoregions, including the Southern Rockies, where the area burned in the late snow zone during 2020 exceeded the total burned area over the previous 36 y combined. Snow measurements at a large Southern Rockies fire revealed that burning caused lower magnitude and earlier peak snow-water equivalent as well as an 18–24 d estimated advance in snow-free dates. Latitude, a proxy for solar radiation, is a dominant driver of snow-free date, and fire advances snow-free timing through a more-positive net shortwave radiation balance. This loss of snow can reduce both ecosystem water availability and streamflow generation in a region that relies heavily on mountain snowpack for water supply.

Increasing wildfire frequency and severity in high‐elevation seasonal snow zones presents a considerable water resource management challenge across the western United States (U.S.). Wildfires can affect snowpack accumulation and melt patterns, altering the quantity and timing of runoff. While prior research has shown that wildfire generally increases snow melt rates and advances snow disappearance dates, uncertainties remain regarding variations across complex terrain and the energy balance between burned and unburned areas. Utilizing paired in situ data sources within the 2020 Cameron Peak burn area on the Front Range of Colorado, U.S., during the 2021–2022 winter, we found no significant difference in peak snow water equivalent (SWE) magnitude between burned and unburned areas. However, the burned south aspect reached peak SWE 22 days earlier than burned north. During the ablation period, burned south melt rates were 71% faster than unburned south melt rates, whereas burned north melt rates were 94% faster than unburned north aspects. Snow disappeared 7–11 days earlier in burned areas than unburned areas. Net energy differences at the burned and unburned weather station sites were seasonally variable, the burned area snowpack lost more net energy during the winter, but gained more net energy during the spring. Increased incoming shortwave radiation at the burned site was 6x more impactful in altering the net shortwave radiation balance than the decline in surface albedo. These findings emphasize the need for post‐wildfire water resource planning that accounts for aspect‐dependent differences in energy and mass balance to accurately predict snowpack storage and runoff timing. Plain Language Summary Wildfires are burning more frequently at high‐elevations, where they modify the snowpack. This complicates efforts to predict when snowmelt runoff will occur and the amount of water that will melt from the snowpack. Wildfire generally causes snow to melt earlier in the year and at a faster rate. However, in complex, mountainous terrain, it is not well understood how the magnitude of these changes may differ between neighboring slopes. During the 2021–22 winter in the Cameron Peak burn area (2020) in Colorado, we found that in a high‐elevation snowpack there was no difference in the amount of water accumulated in the snowpack between areas that were burned by the fire and areas that were not. But in areas that burned, the amount of water in the snowpack reached its largest amount 22 days earlier than the areas that did not burn. The snowpack melted faster on both south and north facing slopes in the burned area than comparable unburned areas, causing the burned areas to be snow free 7–11 days earlier. These results highlight the need to account for complex terrain in water resource planning. Key Points The burned south site reached peak snow water equivalent 22 days earlier than all other sites, which peaked simultaneously Burned site melt rates were similar across aspects but exceeded unburned sites by ∼9 mm d−1, causing snow disappearance ∼9 days earlier Burned site net energy balance was dominated by longwave radiation losses in winter and shortwave radiation gains in spring

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of ‘perennial’ and ‘non-perennial’ are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future.

Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.

The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36∘ S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29∘ S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36∘ S experienced a significant loss of snow cover (2–5 fewer days of snow year−1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30∘ S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31∘ S, whereas the SAM better predicted SP south of 31∘ S.

Streamflow duration is important for aquatic ecosystems and assigning stream protection status. This study predicts streamflow duration, represented as the fraction of time with flow each year, using a combination of sensor data and crowd‐sourced visual observations for a study area in northern Colorado, USA. We used 11 stream stage sensors and 177 visual monitoring points to examine how frequently streams should be sampled to compute flow fractions accurately. This showed that the number of visual observations needed to compute accurate flow fractions increases with decreasing flow duration. We then developed random forest models to predict mean annual flow fractions using climate, topographic, and land cover predictors and found that snow persistence, summer precipitation, and drainage area were important predictors. Model performance was best when using sites with ≥10 visual observations. Our model predicts that almost all (98%) of streams in the study region are non‐perennial, about 10% more than the amount of non‐perennial streams in the National Hydrography Dataset. Stream type maps are sensitive to the time period of data collection and to thresholds used to represent perennial versus non‐perennial flow. To improve maps of non‐perennial streams, we recommend moving beyond categorical classification of streams to a continuous variable like flow fraction. These efforts can be best supported with frequent observations in time that span streams with a wide range of flow fractions and drainage area attributes. Plain Language Summary Most small streams in the world are not monitored, so we know little about when they are flowing or dry. Yet, the amount of time streams flow can determine whether they are protected by water quality legislation and streamside management plans. In this study we used visual observations of stream flow/no flow and stream sensors to develop a model that predicts the fraction of time that streams flow. At a study area in northern Colorado, volunteer observers documented stream flow/no flow at 177 stream segments, and we placed sensors in 11 headwater streams at different elevations. We found that streams needed to be visited approximately weekly to determine how long they flow each year. Streams that rarely flow needed to be visited more often than those that flow most of the time. Our model shows that most (98%) of the streams in the study area do not flow continuously. The amount of time that streams flow is sensitive to changing climate and water demands. Ongoing monitoring of these streams will help us track and predict the range of flow conditions that are possible throughout the vast networks of small streams that feed larger rivers and lakes. Key Points Predicted April–September fraction of time with flow using sensors, crowd‐sourced observations, and statistical models in Colorado streams Snow persistence, summer precipitation, and drainage area are dominant predictors of flow fractions in the Northern Colorado study area Developing a reliable model of flow fraction requires sampling diverse streams that span the full spectrum of flow fractions (0–1)

Rivers that cease to flow are globally prevalent. Although many epithets have been used for these rivers, a consensus on terminology has not yet been reached. Doing so would facilitate a marked increase in interdisciplinary interest as well as critical need for clear regulations. Here we reviewed literature from Web of Science database searches of 12 epithets to learn (Objective 1—O1) if epithet topics are consistent across Web of Science categories using latent Dirichlet allocation topic modeling. We also analyzed publication rates and topics over time to (O2) assess changes in epithet use. We compiled literature definitions to (O3) identify how epithets have been delineated and, lastly, suggest universal terms and definitions. We found a lack of consensus in epithet use between and among various fields. We also found that epithet usage has changed over time, as research focus has shifted from description to modeling. We conclude that multiple epithets are redundant. We offer specific definitions for three epithets (non-perennial, intermittent, and ephemeral) to guide consensus on epithet use. Limiting the number of epithets used in non-perennial river research can facilitate more effective communication among research fields and provide clear guidelines for writing regulatory documents.

Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt‐derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100‐m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo‐global‐warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation‐dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow‐dominated regions. Plain Language Summary Snowpack water storage has historically functioned as a reliable extension of manmade reservoir storage. Loss of this storage has consequences for water resource management, ecological communities, and natural hazards including wildfire. We modeled snow accumulation and melt at high spatial resolution in the Upper Colorado River Basin to assess patterns in the timing and magnitude of snow storage and snowmelt for historical and future scenarios. We analyze these patterns in relation to existing snow monitoring station coverage, and ask how this coverage may need to change in future decades to better represent water availability. Our results indicate widespread future snow storage losses at lower elevations, but limited change at higher elevations that will likely remain conducive to seasonal snow accumulation and melt for decades to come. Peak snow storage and peak snowmelt occurred earlier for all elevations in future years, with increased peak surface water input noted at all elevations. A greater fraction of future snow storage will be in currently unmonitored high elevations. Projected elevation dependent changes from this study have implications for other dry, snow dominated regions, and additional work is needed to evaluate combined effects of widespread snow loss and earlier, flashier input on coordinated water management. Key Points Projections show lower peak snow water equivalent (SWE) below 3,000 m and earlier peak SWE, peak surface water input (SWI) at all elevations Greater future peak SWI and reduced annual snow‐derived SWI for all elevations, with a more even SWI distribution throughout the year A greater fraction of future SWE will be in high elevations that are currently unmonitored

Wildfires are increasingly impacting high‐elevation forests in the western United States that accumulate seasonal snowpacks, presenting a major disturbance to a critical water reservoir for the region. In the first winter following the 2020 Cameron Peak wildfire in Colorado, the peak snow water equivalent in a high burn severity forest was 17%–25% less than nearby unburned sites. The loss of the forest canopy and a lower surface albedo led to an increasingly positive net shortwave radiation balance in the burned area, resulting in melt rates that were 82%–144% greater than unburned sites and snow disappearance occurred 11–13 days earlier. Late‐season snow storms temporarily buried soot, thus increasing the albedo and delaying melt‐out by an estimated 4 days per storm in our study area. While these storms temporarily reduce the higher melt rates imposed by wildfire impacts, SNOTEL measurements show that they occur non‐uniformly across the western U.S. Plain Language Summary Wildfire activity has increased markedly in the western U.S., with megafires (>100,000 acres) and high‐elevation fires becoming increasingly common. These fires are increasingly occurring in forests that accumulate substantial snowpacks and thus provide a reliable water resource for downstream populations. Following a fire, the loss of canopy can change how much snow accumulates and the rate and timing of its melting. Working in the 2020 Cameron Peak wildfire scar in Colorado, we found that a burned site accumulated less snow than unburned portions of the study area. The largest snowpack changes occurred in the spring, when snow in the burned site melted up to 144% faster and melted out 11–13 days earlier than unburned areas. The loss of tree canopy greatly increases the amount of solar energy that reaches the snow surface. Soot and debris from burned trees make the snow surface darker, resulting in more of this energy being absorbed. Late‐season snow storms were able to temporarily counteract some of these effects by burying the darker snow surface. As more and more of the western United States is fire‐impacted, it is essential to better understand and account for these impacts on this critical water reservoir for this region. Key Points Peak snow water equivalent in the burned area was 17%–25% lower than paired unburned areas Snowmelt rates were 82%–144% greater at the burned site compared to unburned sites and snow disappearance occurred 11–13 days earlier Late‐season snow storms reset albedo and delayed melt‐out, thus regional variability in storm frequency can modulate melt rates in burned areas

Wildfires can dramatically alter water quality, resulting in severe implications for human and freshwater systems. However, regional-scale assessments of these impacts are often limited by data scarcity. Here, we unify observations from 1984–2021 in 245 burned watersheds across the western United States, comparing post-fire signals to baseline levels from 293 unburned basins. Organic carbon and phosphorus exhibit significantly elevated levels ( p  ≤ 0.05) in the first 1–5 years post-fire, while nitrogen and sediment show significant increases up to 8 years post-fire. During peak post-fire response years, average carbon, nitrogen, and phosphorus concentrations are 3–103 times pre-fire levels, and sediment 19–286 times pre-fire concentrations. Higher responses are linked with greater forested and developed areas, which respectively explain up to 31 and 33% of inter-basin response variability. Overall, this analysis provides strong evidence of multi-year water quality degradation following wildfires in the western United States and highlights the influence of basin and wildfire features. These insights may aid water managers in preparation efforts, increasing resilience of water systems to wildfire impacts. Water quality in the western United States is affected by wildfires, with sediment and turbidity levels increasing up to 8 years post-fire, according to an analysis of sediment, dissolved organic matter, and nutrients in 538 watersheds.