Water retention curve of snow with different grain sizes

Yamaguchi, Satoru; Katsushima, Takafumi; Sato, Atsushi; Kumakura, Toshiro

doi:10.1016/j.coldregions.2010.05.008

Cited by 80 publications

(93 citation statements)

References 18 publications

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“…According to the results by Stormont and Anderson (1999) in soils, water will enter the underlying coarser layer when ψ at the interface decreases to ψ WE ; at this suction, the coarser soil layer firstly becomes conductive (Stormont and Morris, 1998;Khire et al, 2000). A decrease in ψ during ponding is caused by the fact that θ and ψ are related by a hysteretic relation called the water retention curve (WRC) (Daanen and Nieber, 2009;Yamaguchi et al, 2010;Adachi et al, 2012;Yamaguchi et al, 2012). In soils, Hillel and Baker (1988) and Baker and Hillel (1990) note also that, after reaching ψ WE , subsequent flow in the coarser layer will be marked by fingers if, in steady conditions, the hydraulic conductivity of the lower layer at ψ WE is greater than the flux through the top layer q (due to mass conservation).…”

Section: F Avanzi Et Al: Capillary Barriers In Snowmentioning

confidence: 99%

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

et al. 2016

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Abstract. Data of liquid water flow around a capillary barrier in snow are still limited. To gain insight into this process, we carried out observations of dyed water infiltration in layered snow at 0 • C during cold laboratory experiments. We considered three different finer-over-coarser textures and three different water input rates. By means of visual inspection, horizontal sectioning, and measurements of liquid water content (LWC), capillary barriers and associated preferential flow were characterized. The flow dynamics of each sample were also simulated solving the Richards equation within the 1-D multi-layer physically based snow cover model SNOW-PACK. Results revealed that capillary barriers and preferential flow are relevant processes ruling the speed of water infiltration in stratified snow. Both are marked by a high degree of spatial variability at centimeter scale and complex 3-D patterns. During unsteady percolation of water, observed peaks in bulk volumetric LWC at the interface reached ∼ 33-36 vol % when the upper layer was composed by fine snow (grain size smaller than 0.5 mm). However, LWC might locally be greater due to the observed heterogeneity in the process. Spatial variability in water transmission increases with grain size, whereas we did not observe a systematic dependency on water input rate for samples containing fine snow. The comparison between observed and simulated LWC profiles revealed that the implementation of the Richards equation reproduces the existence of a capillary barrier for all observed cases and yields a good agreement with observed peaks in LWC at the interface between layers.

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Section: F Avanzi Et Al: Capillary Barriers In Snowmentioning

confidence: 99%

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

et al. 2016

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“…Water movement in the snowpack is now governed by the Richards equation (Richards, 1931), which takes into consideration Darcy's law; hydraulic diffusivity and hydraulic conductivity are calculated by the van Genuchten model (van Genuchten, 1980) adapted to snow (Shimizu, 1970;Hirashima et al, 2010;Yamaguchi et al, 2010Yamaguchi et al, , 2012.…”

Section: Smap Model Overviewmentioning

confidence: 99%

Numerical simulation of extreme snowmelt observed at the SIGMA-A site, northwest Greenland, during summer 2012

et al. 2015

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Abstract. The surface energy balance (SEB) from 30 June to 14 July 2012 at site SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)-A, (78 • 03 N, 67 • 38 W; 1490 m a.s.l.) on the northwest Greenland Ice Sheet (GrIS) was investigated by using in situ atmospheric and snow measurements as well as numerical modeling with a one-dimensional multi-layered physical snowpack model called SMAP (Snow Metamorphism and Albedo Process). At SIGMA-A, remarkable near-surface snowmelt and continuous heavy rainfall (accumulated precipitation between 10 and 14 July was estimated to be 100 mm) were observed after 10 July 2012. Application of the SMAP model to the GrIS snowpack was evaluated based on the snow temperature profile, snow surface temperature, surface snow grain size, and shortwave albedo, all of which the model simulated reasonably well. Above all, the fact that the SMAP model successfully reproduced frequently observed rapid increases in snow albedo under cloudy conditions highlights the advantage of the physically based snow albedo model (PBSAM) incorporated in the SMAP model. Using such data and model, we estimated the SEB at SIGMA-A from 30 June to 14 July 2012. Radiation-related fluxes were obtained from in situ measurements, whereas other fluxes were calculated with the SMAP model. By examining the components of the SEB, we determined that low-level clouds accompanied by a significant temperature increase played an important role in the melt event observed at SIGMA-A. These conditions induced a remarkable surface heating via cloud radiative forcing in the polar region.

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“…Old and wet snow on the other hand has coarse, rounded grains accompanied by lower capillary suction. In the water retention curve proposed by Yamaguchi et al (2010), dendricity is not explicitly taken into account. However, SNOW-PACK initialises new snow layers with small grains and these layers thereby exhibit also higher suction than melt forms or old snow in the simulations.…”

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Model simulations of the modulating effect of the snow cover in a rain-on-snow event

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Jonas²,

Fierz³

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. In October 2011, the Swiss Alps underwent a marked rain-on-snow (ROS) event when a large snowfall on 8 and 9 October was followed by intense rain on 10 October. This resulted in severe flooding in some parts of Switzerland. Model simulations were carried out for 14 meteorological stations in two affected regions of the Swiss Alps using the detailed physics-based snowpack model SNOW-PACK. We also conducted an ensemble sensitivity study, in which repeated simulations for a specific station were done with meteorological forcing and rainfall from other stations. This allowed the quantification of the contribution of rainfall, snow melt and liquid water storage on generating snowpack runoff. In the simulations, the snowpack produced runoff about 4-6 h after rainfall started, and total snowpack runoff became higher than total rainfall after about 11-13 h. These values appeared to be strongly dependent on snow depth, rainfall and melt rates. Deeper snow covers had more storage potential and could absorb all rain and meltwater in the first hours, whereas the snowpack runoff from shallow snow covers reacts much more quickly. However, the simulated snowpack runoff rates exceeded the rainfall intensities in both snow depth classes. In addition to snow melt, the water released due to the reduction of liquid water storage contributed to excess snowpack runoff. This effect appears to be stronger for deeper snow covers and likely results from structural changes to the snowpack due to settling and wet snow metamorphism. These results are specifically valid for the point scale simulations performed in this study and for ROS events on relatively fresh snow.

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Water retention curve of snow with different grain sizes

Cited by 80 publications

References 18 publications

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

Numerical simulation of extreme snowmelt observed at the SIGMA-A site, northwest Greenland, during summer 2012

Model simulations of the modulating effect of the snow cover in a rain-on-snow event

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