Numerical modeling of liquid water movement through layered snow based on new measurements of the water retention curve

Hirashima, Hiroyuki; Yamaguchi, Satoru; Sato, Atsushi; Lehning, Michael

doi:10.1016/j.coldregions.2010.09.003

Cited by 89 publications

(98 citation statements)

References 20 publications

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“…Furthermore, our wet-snow avalanches occurred in spring on steep terrain, so that terrain conditions would have to be considered (e.g. Hock, 2003). Whereas temperature-index models provide reasonable results for melt rates when integrated over long time periods, the accuracy decreases with increasing temporal resolution, which is a major disadvantage for wet-snow avalanche forecasting.…”

Section: Discussionmentioning

confidence: 99%

“…Snow stratigraphy at the beginning of the melt season might be quite responsive to the addition of water, while more "mature" or ripe snowpack will not respond to the addition of water. As soon as the snowpack is ripe, an efficient drainage system will be established and water will no longer affect stability (Kattelmann, 1985). In situ measurements capturing the above described thermal and mechanical evolution are difficult to perform since changes tend to occur fast, and only represent point observations.…”

Section: Discussionmentioning

confidence: 99%

“…There are two possibilities to calculate the liquid water content for every layer within the modelled snow cover (Hirashima et al, 2010). Since water transport, especially on slopes is a very complex phenomenon, the water transport codes that are presently implemented within SNOWPACK cannot depict the full complexity of flowing water within the snowpack which is responsible for wet-snow avalanche formation.…”

Section: Calculation Of Energy Balance and Liquid Watermentioning

confidence: 99%

“…Romig et al, 2005). However, there are many examples which show that air temperature is in many cases not a good predictor and causes a high number of false alarms (Kattelmann, 1985). Nevertheless, it appears to be a variable clearly related to wet-snow instability (Baggi and Schweizer, 2009;Peitzsch et al, 2012).…”

mentioning

confidence: 99%

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Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

Mitterer¹,

Schweizer²

2013

The Cryosphere

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Abstract. Wet-snow avalanches are notoriously difficult to predict; their formation mechanism is poorly understood since in situ measurements representing the thermal and mechanical evolution are difficult to perform. Instead, air temperature is commonly used as a predictor variable for days with high wet-snow avalanche danger -often with limited success. As melt water is a major driver of wet-snow instability and snow melt depends on the energy input into the snow cover, we computed the energy balance for predicting periods with high wet-snow avalanche activity. The energy balance was partly measured and partly modelled for virtual slopes at different elevations for the aspects south and north using the 1-D snow cover model SNOWPACK. We used measured meteorological variables and computed energy balance and its components to compare wet-snow avalanche days to non-avalanche days for four consecutive winter seasons in the surroundings of Davos, Switzerland. Air temperature, the net shortwave radiation and the energy input integrated over 3 or 5 days showed best results in discriminating event from non-event days. Multivariate statistics, however, revealed that for better predicting avalanche days, information on the cold content of the snowpack is necessary. Wet-snow avalanche activity was closely related to periods when large parts of the snowpack reached an isothermal state (0 • C) and energy input exceeded a maximum value of 200 kJ m −2 in one day, or the 3-day sum of positive energy input was larger than 1.2 MJ m −2 . Prediction accuracy with measured meteorological variables was as good as with computed energy balance parameters, but simulated energy balance variables accounted better for different aspects, slopes and elevations than meteorological data.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Calculation Of Energy Balance and Liquid Watermentioning

confidence: 99%

mentioning

confidence: 99%

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Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

Mitterer¹,

Schweizer²

2013

The Cryosphere

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“…During dye tracer experiments in a nonripe snowpack with temperatures below the freezing point, matrix flow was observed in the uppermost layers of the snowpack whereas preferential flow was observed in deeper layers only (Techel et al, 2008;Würzer et al, 2017). Various approaches of water flow transport in snowpack were further investigated which included rainfall simulation (Conway and Benedict, 1994;Eiriksson et al, 2013;Juras et al, 2013;Singh et al, 1997), artificial wetting (Avanzi et al, 2015;Katsushima et al, 2013; and numerical modelling (Hirashima et al, 2010(Hirashima et al, , 2014Wever et al, 2014aWever et al, , 2015. Rainwater can refreeze when percolating through cold snow (Pfeffer and Humprey, 1998).…”

Section: R Juras Et Al: Rainwater Propagation Through Snowpackmentioning

confidence: 99%

Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions

Juras

Würzer²,

Pavlásek

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. The mechanisms of rainwater propagation and runoff generation during rain-on-snow (ROS) events are still insufficiently known. Understanding storage and transport of liquid water in natural snowpacks is crucial, especially for forecasting of natural hazards such as floods and wet snow avalanches. In this study, propagation of rainwater through snow was investigated by sprinkling experiments with deuterium-enriched water and applying an alternative hydrograph separation technique on samples collected from the snowpack runoff. This allowed us to quantify the contribution of rainwater, snowmelt and initial liquid water released from the snowpack. Four field experiments were carried out during winter 2015 in the vicinity of Davos, Switzerland. Blocks of natural snow were isolated from the surrounding snowpack to inhibit lateral exchange of water and were exposed to artificial rainfall using deuterium-enriched water. The experiments were composed of four 30 min periods of sprinkling, separated by three 30 min breaks. The snowpack runoff was continuously gauged and sampled periodically for the deuterium signature. At the onset of each experiment antecedent liquid water was first pushed out by the sprinkling water. Hydrographs showed four pronounced peaks corresponding to the four sprinkling bursts. The contribution of rainwater to snowpack runoff consistently increased over the course of the experiment but never exceeded 86 %. An experiment conducted on a non-ripe snowpack suggested the development of preferential flow paths that allowed rainwater to efficiently propagate through the snowpack limiting the time for mass exchange processes to take effect. In contrast, experiments conducted on ripe isothermal snowpack showed a slower response behaviour and resulted in a total runoff volume which consisted of less than 50 % of the rain input.

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Measurements of the pore‐scale water flow through snow using Fluorescent Particle Tracking Velocimetry

Benjamín¹,

Horender²,

Gromke

et al. 2013

Water Resources Research

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[1] Fluorescent Particle Tracking Velocimetry (FPTV) measurements of the pore-scale water flow through the pore space of a wet-snow sample are presented to demonstrate the applicability of this measurement technique for snow. For the experiments, ice-cooled water seeded with micron sized fluorescent tracer particles is either sprinkled on top of a snow sample to investigate saturated and unsaturated gravity-driven flow or supplied from a reservoir below the snow sample to generate upward flow driven by capillary forces. The snow sample is illuminated with a laser light sheet and the fluorescent light of the particles transported with the water in the pore space is recorded with a high-speed camera equipped with an optical filter. Tracking algorithms are applied to the images to obtain flow paths and flow velocities. A flow loop found in a pore space for the case of saturated gravity flow together with the tortuosity of the particle trajectories indicate the three-dimensionality of the water flow in wet snow. The average vertical flow velocities in the pore spaces were 11.2 mm s À1 for the downward saturated gravity flow and 9.6 mm s À1 for the upward flow that is driven by capillary forces for the limited cases presented as examples of the measurement technique. In the case of unsaturated gravity-driven flow, the average and the maximum flow velocities were found to be 30 times smaller than for the saturated gravity flow. Velocity histograms show that the fraction of the total water flowing against the main flow direction was about 3-5%, and that the horizontal velocities average to zero for both the saturated gravity-driven and the capillary flow.Citation: Walter, B., S. Horender, C. Gromke, and M. Lehning (2013), Measurements of the pore-scale water flow through snow using Fluorescent Particle Tracking Velocimetry, Water Resour. Res., 49,[7448][7449][7450][7451][7452][7453][7454][7455][7456]

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Numerical modeling of liquid water movement through layered snow based on new measurements of the water retention curve

Cited by 89 publications

References 20 publications

Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions

Measurements of the pore‐scale water flow through snow using Fluorescent Particle Tracking Velocimetry

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