Influence of melt‐freeze‐cycles on the radionuclide transport in homogeneous laboratory snowpack

Radionuclides released to the environment and deposited with or onto snow can be stored over long time periods if ambient temperature stays low, particularly in glaciated areas or high alpine sites. The radionuclides will be accumulated in the snowpack during the winter unless meltwater runoff at the snow base occurs. They will be released to surface waters within short time during snowmelt in spring. In two experiments under controlled melting conditions of snow in the laboratory, radionuclide migration and runoff during melt‐freeze‐cycles were examined. The distribution of Cs‐134 and Sr‐85 tracers in homogeneous snow columns and their fractionation and potential preferential elution in the first meltwater portions were determined. Transport was associated with the percolation of meltwater at ambient temperatures above 0 °C after the snowpack became ripe. Mean migration velocities in the pack were examined for both nuclides to about 0.5 cm hr^?1 after one diurnal melt‐freeze‐cycle at ambient temperatures of ?2 to 4 °C. Meltwater fluxes were calculated with a median of 1.68 cm hr^?1. Highly contaminated portions of meltwater with concentration factors between 5 and 10 against initial bulk concentrations in the snowpack were released as ionic pulse with the first meltwater. Neither for caesium nor strontium preferential elution was observed. After recurrent simulated day‐night‐cycles (?2 to 4 °C), 80% of both radionuclides was released with the first 20% of snowmelt within 4 days. 50% of Cs‐134 and Sr‐85 were already set free after 24 hr. Snowmelt contained highest specific activities when the melt rate was lowest during the freeze‐cycles due to concentration processes in remaining liquids, enhanced by the melt‐freeze‐cycling. This implies for natural snowpack after significant radionuclide releases, that long‐time accumulation of radionuclides in the snow during frost periods, followed by an onset of steady meltwater runoff at low melt rates, will cause the most pronounced removal of the contaminants from the snow cover. This scenario represents the worst case of impact on water quality and radiation exposure in aquatic environments.     

Routing of canopy drip in the snowpack below a spruce crown

Snow that is retained by a forest canopy may either sublimate or evaporate directly from the crown or drop as snow clumps or meltwater to the ground. Redistributed snow and meltwater affect the snow structure and prevent the formation of mechanically weak layers, which is the prerequisite for avalanche formation in forests. In this paper we describe the results of dye tracer experiments conducted in a subalpine forest near Davos, Switzerland. Before a snowfall event we stained snow‐free branches of a spruce with a dye tracer solution. After snowfall the coloured meltwater dripping from the branches down on to the snowpack stained the percolation pathways of the meltwater in the snowpack. Photographs of the snow profiles indicate that the meltwater seeped almost vertically through the isothermal snowpack to the soil surface not exceeding the projected crown edge. Meltwater of different events moves along different preferential flow channels in the snow suggesting that old channels are not non‐conducting and additional meltwater fronts create new channels. Copyright © 1999 John Wiley & Sons, Ltd.     

Tracer release in melting snow: Diurnal and seasonal patterns

Time sequences of tracer release from an alpine snowpack were investigated at Mammoth Mountain, California in 1989. Lysimeter discharge and conductivity were recorded at 30 minute intervals. Three separate applications of chemical tracers were added to the snow surface to provide an ionic signal with known origins in the snowpack. Grab samples of meltwater and snow from snow pits were analysed for chemical composition. There were three distinct discharge periods, each characterized by diurnal fluctuations in discharge and conductivity. An inverse relation between discharge and conductivity was interpreted as the combination of a concentrated signal from regions in the pack less subject to leaching and a relatively dilute signal from near the snow surface where the snow was actively melting Conductivity peaks were highest and diurnal changes greatest immediately following periods of freezing. Grab samples showed little correlation with either 30 minute or daily average conductivity. Relative concentrations of individual ions in meltwater were similar between samples. Non-systematic grab sampling of snowpack meltwater is shown to be potentially misleading because of multiple ionic pulses over the ablation season and strong diurnal fluctuations in chemical concentrations. Continuous measurements of discharge conductivity are a good indicator of diurnal and seasonal changes in the rate of ion release from the snowpack, and should be used to guide sampling. Composite, or time-integrated samples rather than grab samples may be required to estimate daily and weekly rates of ion release in melting snow.     

VARIABILITY OF MELTWATER AND SOLUTE FLUXES FROM HOMOGENEOUS MELTING SNOW AT THE LABORATORY SCALE

Four experiments were performed to examine the relationship between the meltwater flow field and ion release from melting snow. A 0.4 m³ volume of snow was placed in a Plexiglass box and melted from above using a heating plate. The meltwater and solute fluxes issuing from the bottom of the snow were monitored. In experiments with NaCl tracer added to the snow, the solute concentrations were generally lower in the flow fingers than in the background wetting front. Dye tracer experiments revealed contemporaneous areas of concentrated dye and dilute meltwater in flow fingers. This suggests that the meltwater in flow fingers is diluted by low concentration water from the top of the snowpack. Flow fingers contribute more meltwater flux primarily because the flow is maintained for a longer period of time than in the non-finger areas; however, the relative contribution of flow fingers to solute flux was apparently not as great as that of the background wetting front because of dilution of solute in the flow finger areas.     

A modelling framework to simulate field‐scale nitrate response and transport during snowmelt: The WINTRA model

Modelling nutrient transport during snowmelt in cold regions remains a major scientific challenge. A key limitation of existing nutrient models for application in cold regions is the inadequate representation of snowmelt, including hydrological and biogeochemical processes. This brief period can account for more than 80% of the total annual surface runoff in the Canadian Prairies and Northern Canada and processes such as atmospheric deposition, overwinter redistribution of snow, ion exclusion from snow crystals, frozen soils, and snow‐covered area depletion during melt influence the distribution and release of snow and soil nutrients, thus affecting the timing and magnitude of snowmelt runoff nutrient concentrations. Research in cold regions suggests that nitrate (NO₃) runoff at the field‐scale can be divided into 5 phases during snowmelt. In the first phase, water and ions originating from ion‐rich snow layers travel and diffuse through the snowpack. This process causes ion concentrations in runoff to gradually increase. The second phase occurs when this snow ion meltwater front has reached the bottom of the snowpack and forms runoff to the edge‐of‐the‐field. During the third and fourth phases, the main source of NO₃ transitions from the snowpack to the soil. Finally, the fifth and last phase occurs when the snow has completely melted, and the thawing soil becomes the main source of NO₃ to the stream. In this research, a process‐based model was developed to simulate hourly export based on this 5‐phase approach. Results from an application in the Red River Basin of southern Manitoba, Canada, shows that the model can adequately capture the dynamics and rapid changes of NO₃ concentrations during this period at relevant temporal resolutions. This is a significant achievement to advance the current nutrient modelling paradigm in cold climates, which is generally limited to satisfactory results at monthly or annual resolutions. The approach can inform catchment‐scale nutrient models to improve simulation of this critical snowmelt period.     

Modification and testing of a one‐dimensional energy and mass balance model for supraglacial snowpacks

A one‐dimensional energy and mass balance snow model (SNTHERM) has been modified for use with supraglacial snowpacks and applied to a point on Haut Glacier d'Arolla, Switzerland. It has been adapted to incorporate the underlying glacier ice and a site‐specific, empirically derived albedo routine. Model performance was tested against continuous measurements of snow depth and meltwater outflow from the base of the snowpack, and intermittent measurements of surface albedo and snowpack density profiles collected during the 1993 and 2000 melt seasons. Snow and ice ablation was simulated accurately. The timing of the daily pattern of meltwater outflow was well reproduced, although magnitudes were generally underestimated, possibly indicating preferential flow into the snowpack lysimeter. The model was used to assess the quantity of meltwater stored temporally within the unsaturated snowpack and meltwater percolation rates, which were found to be in agreement with dye tracer experiments undertaken on this glacier. As with other energy balance studies on alpine valley glaciers, the energy available for melt was dominated by net radiation (64%), with a sizable contribution from sensible heat flux (36%) and with a negligible latent heat flux overall, although there was more complex temporal variation on diurnal timescales. A basic sensitivity analysis indicated that melt rates were most sensitive to radiation, air temperature and snowpack density, indicating the need to accurately extrapolate/interpolate these variables when developing a spatially distributed framework for this model. Copyright © 2008 John Wiley & Sons, Ltd.     

Seasonal transition of hydrological processes in a slow‐moving landslide in a snowy region

A comprehensive understanding of seasonal hydrological dynamics is required to describe the influence of pore‐water pressure on the stability of landslides in snowy regions. This study reports on the results of continuous meteorological and hydrological observations over 2 years on a landslide body comprising Neogene sedimentary rocks in northern Japan, where a thick (3–5 m) seasonal snowpack covers the land surface. Monitoring of the volumetric water content in shallow unsaturated zones (<0.8 m depth) and pore‐water pressure in saturated bedrock at depths of 2.0 and 5.2 m revealed clear seasonality in hydrological responses to rainfall and meltwater supply. During snow‐free periods, both the shallow soil moisture and deep pore‐water pressure responded rapidly to intense rainwater infiltration. In contrast, during snowmelt, the deep pore pressure fluctuated in accordance with the daily cycle of meltwater input, without notable changes in shallow moisture conditions. During occasional foehn events that cause intense snow melting in midwinter, meltwater flows preferentially through the layered snowpack, converging to produce a localized water supply at the ground surface. This episodically triggers a significant rise in pore‐water pressure. The seasonal differences in hydrological responses were characterized by a set of newly proposed indices for the magnitude and quickness of increases in the pressure head near the sliding surface. Under snow‐covered conditions, the magnitude of the pressure increase tends to be suppressed, probably owing to a reduction in infiltration caused by a seasonal decrease in the permeability of surface soils, and effective pore‐water drainage through the highly conductive colluvial layer. Deep groundwater flow within bedrock remained in a steady upwelling state, enhanced by increasing moisture in shallow soils under snow cover, reflecting the convergence of subsurface water from surrounding hillslopes.     

Temporal observations of a seasonal snowpack using upward‐looking GPR

An increase of the spatial and temporal resolution of snowpack measurements in Alpine or Arctic regions will improve the predictability of flood and avalanche hazards and increase the spatial validity of snowpack simulation models. In the winter season 2009, we installed a ground‐penetrating radar (GPR) system beneath the snowpack to measure snowpack conditions above the antennas. In comparison with modulated frequency systems, GPR systems consist of a much simpler technology, are commercially available and therefore are cheaper. The radar observed the temporal alternation of the snow height over more than 2·5 months. The presented data showed that with moved antennas, it is possible to record the snow height with an uncertainty of less than 8% in comparison with the probed snow depth. Three persistent melt crusts, which formed at the snow surface and were buried by further new snow events, were used as reflecting tracers to follow the snow cover evolution and to determine the strain rates of underlaying layers between adjacent measurements. The height in two‐way travel time of each layer changed over time, which is a cumulative effect of settlement and variation of wave speed in response to densification and liquid water content. The infiltration of liquid water with depth during melt processes was clearly observed during one event. All recorded reflections appeared in concordance with the physical principles (e.g. in phase structure), and one can assume that distinct density steps above a certain threshold result in reflections in the radargram. The accuracy of the used impulse radar system in determining the snow water equivalent is in good agreement with previous studies, which used continuous wave radar systems. The results of this pilot study encourage further investigations with radar measurements using the described test arrangement on a daily basis for continuous destruction‐free monitoring of the snow cover. Copyright © 2010 John Wiley & Sons, Ltd.     

EFFECT OF SNOW AND FIRN HYDROLOGY ON THE PHYSICAL AND CHEMICAL CHARACTERISTICS OF GLACIAL RUNOFF

Near-surface processes on glaciers, including water flow over bare ice and through seasonal snow and firn, have a significant effect on the speed, volume and chemistry of water flow through the glacier. The transient nature of the seasonal snow profoundly affects the water discharge and chemistry. Water flow through snow is fairly slow compared with flow over bare ice and a thinning snowpack on a glacier decreases the delay between peak meltwater input and peak stream discharge. Furthermore, early spring melt flushes the snowpack of solutes and by mid-summer the melt water flowing into the glacier is fairly clean by comparison. The firn, a relatively constant feature of glaciers, attenuates variations in water drainage into the glacier by temporarily storing water in saturated layer. Bare ice exerts opposite influences by accentuating variations in runoff by water flowing over the ice surface. The melt of firn and ice contributes relatively clean (solute-free) water to the glacier water system.     

II. Snow hydrology processes and remote sensing

In the last 20 years remote sensing research has led to significant progress in monitoring and measuring certain snow hydrology processes. Snow distribution in a drainage basin can be adequately assessed by visible sensors. Although there are still some interpretation problems, the NOAA-AVHRR sensor can provide frequent views of the areal snow cover in a basin, and snow cover maps are produced operationally by the National Weather Service on about 3000 drainage basins in North America. Measurement of snow accumulation or snow water equivalent with microwave remote sensing has great potential because of the capabilities for depth penetration, all-weather observation and night-time viewing. Several critical areas of research remain, namely, the acquisition of snow grain size information for input to microwave models and improvement in passive microwave resolution from space. Methods that combine both airborne gamma ray and visible satellite remote sensing of the snowpack with field measurements also hold promise for determining areal snow water equivalent. Some remote sensing techniques can also be used to detect different stages of snow metamorphism. Various aspects of snowpack ripening can be detected using microwave and thermal infra-red capabilities. The capabilities for measurement of snow albedo and surface temperature have direct application in both snow metamorphism and snowpack energy balance studies. The potentially most profitable research area here is the study of the bidirectional reflectance distribution function to improve snow albedo measurements. Most of the remote sensing capabilities in snow hydrology have been developed for improving snowmelt-run-off forecasting. Most applications have used the input of snow cover extent to deterministic models, both of the degree day and energy balance types. Snowmelt-run-off forecasts using satellite derived snow cover depletion curves and the models have been successfully made. As the extraction of additional snow cover characteristics becomes possible, remote sensing will have an even greater impact on snow hydrology. Important remote sensing capabilities will become available in the next 20 years through space platform observing systems that will improve our capability to observe the snowpack on an operational basis.     

Incorporating topographic variability into a simple regional snowmelt model

General circulation models (GCMs), or stand‐alone models that are forced by the output from GCMs, are increasingly being used to simulate the interactions between snow cover, snowmelt, climate and water resources. The variation in snowpack extent, and hence albedo, through time in a cell is likely to be substantial, especially in mid‐latitude mountainous regions. As a consequence, the energy budget simulation by a GCM relies on a realistic representation of snowpack extent. Similarly, from a water resource perspective, the spatial extent of the pack is key in predicting meltwater discharges into rivers. In this paper a simple computationally efficient regional snow model has been developed, which is based on a degree‐day approach and simulates the fraction of the model domain covered by snow, the spatially averaged melt rate and the mean snowpack depth. Computational efficiency is achieved through a novel spatial averaging procedure, which relies on the assumptions that precipitation and temperature scale linearly with elevation and that the distribution of elevations in the domain can be modelled by a continuous function. The resulting spatially averaged model is compared with both observations of the duration of snow cover throughout Austria and with results from a distributed model based on the same underlying assumptions but applied at a fine spatial resolution. The new spatially averaged model successfully simulated the seasonal snow duration observations and reproduced the daily dynamics of snow cover extent, the spatially averaged melt rate and mean pack depth simulated by the distributed model. It, therefore, offers a computationally efficient and easily applied alternative to the current crop of regional snow models. Copyright © 2004 John Wiley & Sons, Ltd.     

Isotope variations in a Sierra Nevada snowpack and their relation to meltwater

Isotopic variations in melting snow are poorly understood. We made weekly measurements at the Central Sierra Snow Laboratory, California, of snow temperature, density, water equivalent and liquid water volume to examine how physical changes within the snowpack govern meltwater δ¹⁸O. Snowpack samples were extracted at 0.1 m intervals from ground level to the top of the snowpack profile between December 1991 and April 1992. Approximately 800 mm of precipitation fell during the study period with δ¹⁸O values between −21.35 and −4.25‰. Corresponding snowpack δ¹⁸O ranged from −22.25 to −6.25‰. The coefficient of variation of δ¹⁸O in snowpack levels decreased from −0.37 to −0.07 from winter to spring, indicating isotopic snowpack homogenization. Meltwater δ¹⁸O ranged from −15.30 to −8.05‰, with variations of up to 2.95‰ observed within a single snowmelt episode, highlighting the need for frequent sampling. Early snowmelt originated in the lower snowpack with higher δ¹⁸O through ground heat flux and rainfall. After the snowpack became isothermal, infiltrating snowmelt displaced the higher δ¹⁸O liquid in the lower snowpack through a piston flow process. Fractionation analysis using a two-component mixing model on the isothermal snowpack indicated that δ¹⁸O in the initial and final half of major snowmelt was 1.30‰ lower and 1.45‰ higher, respectively, than the value from simple mixing. Mean snowpack δ¹⁸O on individual profiling days showed a steady increase from −15.15 to −12.05‰ due to removal of lower δ¹⁸O snowmelt and addition of higher δ¹⁸O rainfall. Results suggest that direct sampling of snowmelt and snow cores should be undertaken to quantify tracer input compositions adequately. The snowmelt sequence also suggests that regimes of early lower δ¹⁸O and later higher δ¹⁸O melt may be modeled and used in catchment tracing studies.     

Modelling the spatial–temporal variability of spring snowmelt in an arctic catchment

Arctic spring landscapes are usually characterized by a mosaic of coexisting snow‐covered and bare ground patches. This phenomenon has major implications for hydrological processes, including meltwater production and runoff. Furthermore, as indicated by aircraft observations, it affects land‐surface–atmosphere exchanges, leading to a high degree of variability in surface energy terms during melt. The heterogeneity and related differences when certain parts of the landscape become snow free also affects the length of the growing season and the carbon cycle. Small‐scale variability in arctic snowmelt is addressed here by combining a spatially distributed end‐of‐winter snow cover with simulations of variable snowmelt energy balance factors for the small arctic catchment of Trail Valley Creek (63 km²). Throughout the winter, snow in arctic tundra basins is redistributed by frequent blowing snow events. Areas of above‐ or below‐average end‐of‐winter snow water equivalents were determined from land‐cover classifications, topography, land‐cover‐based snow surveys, and distributed surface wind‐field simulations. Topographic influences on major snowmelt energy balance factors (solar radiation and turbulent fluxes of sensible and latent heat) were modelled on a small‐scale (40 m) basis. A spatially variable complete snowmelt energy balance was subsequently computed and applied to the distributed snow cover, allowing the simulation of the progress of melt throughout the basin. The emerging patterns compared very well visually to snow cover observations from satellite images and aerial photographs. Results show the relative importance of variable end‐of‐winter snow cover, spatially distributed melt energy fluxes, and local advection processes for the development of a patchy snow cover. This illustrates that the consideration of these processes is crucial for an accurate determination of snow‐covered areas, as well as the location, timing, and amount of meltwater release from arctic catchments, and should, therefore, be included in hydrological models. Furthermore, the study shows the need for a subgrid parameterization of these factors in the land surface schemes of larger scale climate models. Copyright © 2005 John Wiley & Sons, Ltd.     

Prediction of temperature variation within a snowpack in open areas and under different canopy covers

Snow temperature is a major component of many physical processes in a snowpack. The temperature and the change in temperature across a layer have a dominant effect on physical properties of snow grains as well as its hardness, strength, and failure resistance. In this study, temperature and snow cover thickness were measured during the snow season of 2007–2008 in 11 elevation classes and in three different sampling locations, one in an open area and two under different forest canopy covers for each class along Kartalkaya road, Bolu. Each sampling site was visited 44 times to collect data including snow depth, snow surface temperature, ground temperature, and temperature within snowpack at 20‐cm intervals. Seven different models are developed to determine snowpack temperature variations under forest canopy covers and in an open area with different leaf area index values. All models were performed using a multilayer perceptron (MP) method for the Bolu–Kartalkaya area, Turkey. MP approach constitutes a standard form of neural network modeling and can modify two‐layer linear perceptron methods using three and more layers. The ability of MP is to handle complex nonlinear interactions, which ease the natural process of modeling. This method can overcome complex computations using neuron networks, and they can easily nonlinearly link input and output variables. The predictive errors are determined on the basis of mean absolute error and mean square error criteria. The Nash–Sutcliffe sufficiency score showing compliance between observed and predicted values is also calculated. According to the mean absolute error, the mean square error, and the Nash–Sutcliffe sufficiency score criteria, the predictive errors are within reasonable error intervals, justifying the use of the developed MP models for engineering applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Spatial controls on the distribution and dynamics of a marginal snowpack in the Australian Alps

Seasonal snowpacks in marginal snow environments are typically warm and nearly isothermal, exhibiting high inter‐ and intra‐annual variability. Measurements of snow depth and snow water equivalent were made across a small subalpine catchment in the Australian Alps over two snow seasons in order to investigate the extent and implications of snowpack spatial variability in this marginal setting. The distribution and dynamics of the snowpack were found to be influenced by upwind terrain, vegetation, solar radiation, and slope. The role of upwind vegetation was quantified using a novel parameter based on gridded vegetation height. The elevation range of the catchment was relatively modest (185 m), and elevation impacted distribution but not dynamics. Two characteristic features of marginal snowpack behaviour are presented. Firstly, the evolution of the snowpack is described in terms of a relatively unstable accumulation state and a highly stable ablation state, as revealed by temporal variations in the mean and standard deviation of snow water equivalent. Secondly, the validity of partitioning the snow season into distinct accumulation and ablation phases is shown to be compromised in such a setting. Snow at the most marginal locations may undergo complete melt several times during a season and, even where snow cover is more persistent, ablation processes begin to have an effect on the distribution of the snowpack early in the season. Our results are consistent with previous research showing that individual point measurements are unable to fully represent the variability in the snowpack across a catchment, and we show that recognising and addressing this variability are particularly important for studies in marginal snow environments.     

Estimating sublimation of intercepted and sub‐canopy snow using eddy covariance systems

Direct measurements of winter water loss due to sublimation were made in a sub‐alpine forest in the Rocky Mountains of Colorado. Above‐and below‐canopy eddy covariance systems indicated substantial losses of winter‐season snow accumulation in the form of snowpack (0·41 mm d^?1) and intercepted snow (0·71 mm d^?1) sublimation. The partitioning between these over and under story components of water loss was highly dependent on atmospheric conditions and near‐surface conditions at and below the snow/atmosphere interface. High above‐canopy sensible heat fluxes lead to strong temperature gradients between vegetation and the snow‐surface, driving substantial specific humidity gradients at the snow surface and high sublimation rates. Intercepted snowfall resulted in rapid response of above‐canopy latent heat fluxes, high within‐canopy sublimation rates (maximum = 3·7 mm d^?1), and diminished sub‐canopy snowpack sublimation. These results indicate that sublimation losses from the sub‐canopy snowpack are strongly dependent on the partitioning of sensible and latent heat fluxes in the canopy. This compels comprehensive studies of snow sublimation in forested regions that integrate sub‐canopy and over‐story processes. Copyright © 2007 John Wiley & Sons, Ltd.     

Water isotopes and hydrograph separation in different glacial catchments in the southeast margin of the Tibetan Plateau

Snow and glaciers are known to be important sources for freshwater; nevertheless, our understanding of the hydrological functioning of glacial catchments remains limited when compared with lower altitude catchments. In this study, a temperate glacial region located in the southeast margin of the Tibetan Plateau is selected to analyse the characteristics of δ¹⁸O and δD in different water sources and the contribution of glacier–snow meltwater to streamflow. The results indicate that the δ¹⁸O of river water ranges from ?16.2‰ to ?10.2‰ with a mean of ?14.1‰ and that the δD values range from ?117.0‰ to ?68.0‰ with a mean of ?103.1‰. These values are more negative than those of glacier–snow meltwater but less negative than those of precipitation. The d ‐excess values are found to decrease from meltwater to river to lake/reservoir water as a result of evaporation. On the basis of hydrograph separation, glacier–snow meltwater accounts for 51.5% of river water in the Baishui catchment in the melting season. In the Yanggong catchment, snow meltwater contributes 47.9% to river water in the premonsoon period, and glacier meltwater contributes only 6.8% in the monsoon period. The uncertainty in hydrograph separation is sensitive to the variation of tracer concentrations of streamflow components. The input of meltwater to a water system varies with local climate and glacier changes. The results confirm that hydrograph separation using water isotopes is valuable for evaluating the recharge sources of rivers, especially in ungauged glacial regions. This study provides insights into the hydrological processes of glacial catchments on the Tibetan Plateau, which is important for water resource management.