Winter runoff events pose an unquantified continental-scale risk of high wintertime nutrient export

Winters in snow-covered regions have warmed, likely shifting the timing and magnitude of nutrient export, leading to unquantified changes in water quality. Intermittent, seasonal, and permanent snow covers more than half of the global land surface. Warming has reduced the cold conditions that limit winter runoff and nutrient transport, while cold season snowmelt, the amount of winter precipitation falling as rain, and rain-on-snow have increased. We used existing geospatial datasets (rain-on-snow frequency overlain on nitrogen and phosphorous inventories) to identify areas of the contiguous United States (US) where water quality could be threatened by this change. Next, to illustrate the potential export impacts of these events, we examined flow and turbidity data from a large regional rain-on-snow event in the United States' largest river basin, the Mississippi River Basin. We show that rain-on-snow, a major flood-generating mechanism for large areas of the globe (Berghuijs et al 2019 Water Resour. Res. 55 4582&ndash;93; Berghuijs et al 2016 Geophys. Res. Lett. 43 4382&ndash;90), affects 53% of the contiguous US and puts 50% of US nitrogen and phosphorus pools (43% of the contiguous US) at risk of export to groundwater and surface water. Further, the 2019 rain-on-snow event in the Mississippi River Basin demonstrates that these events could have large, cascading impacts on winter nutrient transport. We suggest that the assumption of low wintertime discharge and nutrient transport in historically snow-covered regions no longer holds. Critically, however, we lack sufficient data to accurately measure and predict these episodic and potentially large wintertime nutrient export events at regional to continental scales. &nbsp;</p

The Post-Wildfire Impact of Burn Severity and Age on Black Carbon Snow Deposition and Implications for Snow Water Resources, Cascade Range, Washington

Wildfires in the snow zone affect ablation by removing forest canopy, which enhances surface solar irradiance, and depositing light absorbing particles [LAPs, such as black carbon (BC)] on the snowpack, reducing snow albedo. How variations in BC deposition affects post-wildfire snowmelt timing is poorly known and highly relevant to water resources. We present a field-based analysis of BC variability across five sites of varying burn age and burn severity in the Cascade Range, Washington State, United States. Single particle soot photometer (SP2) analyses of BC snow concentrations were used to assess the impact of BC on snow albedo, and radiative transfer modeling was used to estimate the radiative effect of BC on snowmelt. Results were compared to Snowpack Telemetry (SNOTEL) data from one site that burned in 2012 and another in a proximal unburned forest. We show that post-wildfire forests provide a significant source of BC to the snowpack, and this effect increases by an order of magnitude in regions of high versus low burn severity, and decreased by two orders of magnitude over a decade. There is a shift in the timing of snowmelt, with snow disappearance occurring on average 19 ± 9 days earlier post-wildfire (2013–19) relative to pre-wildfire (1983–2012). This study improves understanding of the connection between wildfire activity and snowmelt, which is of high relevance as climate change models project further decreases in snowpack and increases in wildfire activity in the Washington Cascades

Quantifying the effects of forest vegetation on snow accumulation, ablation, and potential meltwater inputs, Valles Caldera National Preserve, NM, USA

I quantified the competing effects of forest vegetation on snow accumulation and ablation in a lower mid-latitude montane environment where solar radiation dominates winter snow-atmosphere energy fluxes and limited work has been focused. Detailed snowpit analyses and ultrasonic snow depth sensors indicated forest vegetation affected snowcover in three ways; canopy interception and sloughing, enhanced snowpack metamorphism and ablation, and shading of direct solar radiation. Competing accumulation and melt processes determine the snow cover duration, SWE yield, and potential meltwater inputs. On average, canopy interception resulted in 44% less SWE accumulating beneath the canopy. I observed an inverse correlation between snowpack density and grain size with distance from the tree bole at maximum accumulation. Larger grains and lower densities near the bole indicated enhanced metamorphism of the near tree snowpack. Snow surveys around 15 trees at max accumulation indicated that the north sides of trees had 24.6% (p=0.01) more SWE than south tree sides. Micro- to tree scale observations support our stand and catchment-scale finding that a shaded snowpack experiences increased SWE accumulation, decreased ablation and melt rates, and prolonged seasonal snow cover. Specifically, we found that vegetative shading may delay the basin average maximum SWE accumulation by up to three weeks and greatly increase snow cover duration by minimizing snowmelt rates. Data point to compelling differences in forest ablation and melt processes in this lower mid-latitude where enhanced insolation augments the physical processes observed elsewhere. A binary regression tree model indicated strong correlation (R 2 = 0.54) between micro-scale (i.e. 10-cm resolution) canopy structure indices and snow depth, suggesting that future remotely sensed vegetation data may improve snow distribution models. A better understanding of the effects of forest cover on a basin's snowpack will prepare us to more accurately predict the potentially wide-ranging hydrologic impacts of climate, land cover, and land use change in these seasonally snow covered forested environments.Digitized from paper copies provided by the Department of Hydrology & Atmospheric Sciences

Snowmelt response to simulated warming across a large elevation gradient, southern Sierra Nevada, California

Abstract. In a warmer climate, the fraction of annual meltwater produced at high melt rates is projected to decline due to a contraction of the melt season to an earlier period of lower energy. How snowmelt rates, including extreme events relevant to flood risk, may respond to a range of warming over a mountain front remains poorly known. We present a model sensitivity study of snowmelt response to warming across a 3600 m elevation gradient in the southern Sierra Nevada, USA. A snow model was run for three distinct years and verified against extensive ground observations. To simulate the impact of climate warming on meltwater production, measured meteorological conditions were modified by +1 °C to +6 °C. The total annual snow water volume exhibited linear reductions (−10 % °C−1) consistent with previous studies. However, the sensitivity of snowmelt rates to successive degrees of warming varied nonlinearly with elevation. Middle elevations and years with more snowfall were prone to the largest reductions in snowmelt rates, with lesser changes simulated at higher elevations. Importantly, simulated warming causes extreme daily snowmelt (99th percentiles) to increase in spatial extent and intensity and shift from spring to winter. The results offer critical insight into the sensitivity of mountain snow water resources and how the rate and timing of water availability may change in a warmer climate. The identification of future climate conditions that may increase extreme melt events is needed to address the climate resilience of regional flood control systems. </jats:p

Snowpack-climate manipulation using infrared heaters in subalpine forests of the Southern Rocky Mountains, USA

Effects of infrared heaters on snow accumulation, snowmelt, and snow–atmosphere energy exchange were examined at Niwot Ridge, Colorado (CO) and compared to a naturally warmer, but otherwise similar subalpine site in the Valles Caldera National Preserve, New Mexico (NM). Observed snow accumulation was 30% lower on average and snow melted out 16 days earlier in the heated plots compared to the controls. Soil temperature during snowmelt was 3°C greater on average and soil moisture was 4% lower on average in heated plots compared to controls. In NM, snow accumulation was 23% lower, snow melted 23 days earlier, soil temperature was 0.6°C greater, and soil moisture was 13% lower on average relative to CO controls. In order to estimate differences in energy and mass balance fluxes at the snow–atmosphere interface in control versus warmer plots, the 1-D, physically based snowmelt model, SNOWPACK, was used. Model results indicated that heaters alter radiative, turbulent and mass fluxes by amounts comparable to the differences between CO and NM fluxes. The proportion of the energy flux associated with latent heat exchange during snowmelt was 9–27% of the total energy flux in heated models and 19–22% of NM models compared to 3–7% in control models. Thus, sublimation loss to the atmosphere was greater in both experimentally and naturally warmer cases relative to the control case. We conclude that IR heaters can provide alterations to the timing and magnitude of snow accumulation and snowmelt consistent with conditions observed at a warmer analog site and with climate and hydrology model projections. Impacts of IR heating on energy partitioning and sublimation should be considered when designing manipulations of the snowpack, as reductions in snowmelt water may alter biological or ecological processes

Pervasive alterations to snow-dominated ecosystem functions under climate change

© 2022 National Academy of Sciences. All rights reserved.Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.11Nsciescopu

Increasing Alaskan river discharge during the cold season is driven by recent warming

Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic

Interannual and seasonal variability of snow depth scaling behavior in a subalpine catchment

Understanding and characterizing the spatial distribution of snow are critical to represent the energy balance and runoff production in mountain environments. In this study, we investigate the interannual and seasonal variability in snow depth scaling behavior at the Izas experimental catchment of the Spanish Pyrenees (2,000 to 2,300 m above sea level). We conduct variogram analyses of 24 snow depth maps derived from terrestrial light detection and ranging scans, acquired during six consecutive snow seasons (2011-2017) that span a range of hydroclimatic conditions. We complement our analyses with bare ground topography data and wind speed and direction measurements. Our results show temporal consistency in the spatial variability of snow depth, with short-range fractal behavior and scale break lengths that are similar to the optimal search distance (25 m) previously reported for the topographic position index, a terrain-based predictor of snow depth. Beyond the 25-m scale break, there is little to no fractal structure. We report a long-range scale break of the order of 185-300 m for most dates-aligned with the dominant wind direction-and patterns between anisotropies in scale break lengths of shallow snow cover and directional terrain scaling behavior. The temporal consistency of snow depth scaling patterns suggests that, in addition to guiding the spatial configuration of physically based models, fractal analysis could be used to inform the design of independent variables for statistical models used to predict snow depth and its variability.Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) CONICYT FONDECYT 3170079 CONICYT/PIA Project AFB18000