Impact of the spaciotemporal variability of the snowpack conditions on internal liquid water fluxes

Author(s):  
Eole Valence ◽  
Michel Baraër

<p>In cold regions, the seasonal snowpack plays an important hydrological role. By storing and releasing solid precipitation, the snowpack gives shape to the yearly hygrogram. In addition, by modulating liquid water pathway and residence time, snowpack internal conditions have a strong implication on the partitioning of meltwater among streamflow, groundwater recharge and soil moisture storage. During rain on snow (ROS) events, snowpack conditions influence timing and amount of liquid water inflow to the surface drainage system, with winter floods and ice jams as potential consequences.</p><p>Recent observations and projections show an increase in ROS frequency in many cold regions of the world. This trend raises concern about a possible increase in winter floods and ice jams events with climate change. In order to better anticipate the hydrological consequences of the increasing ROS phenomenon, a good understanding of the processes and conditions influencing liquid water release from the snowpack is required. </p><p>The present study articulates around a multimethod approach to characterize liquid water storage and movement in a snowpack in a non-mountainous environment. By combining drone-based high frequency GPR, NIR photogrammetry, time domain reflectometry, stable isotopes of water and other manual measurements throughout a winter season, we aim monitoring the spatiotemporal evolution of the snowpack liquid water content as well as the water fluxes at the snowpack margins.</p><p>Preliminary results show that, combining the selected methods allows tracking liquid water storage and movements in the snowpack throughout an entire season.</p>

Author(s):  
Anne D. W. Nuijten ◽  
Inge Hoff ◽  
Knut V. Høyland

Heated pavements are used as an alternative to removing snow and ice mechanically and chemically. Usually a heated pavement system is automatically switched on when snowfall starts or when there is a risk of ice formation. Ideally, these systems run based on accurate predictions of surface conditions a couple of hours ahead of time, for which both weather forecasts and reliable surface temperature predictions are needed. The effective thermal conductivity of the snow layer is often described as a function of its density. However the thermal conductivity of a snow layer can vary considerably, not only for snow samples with a different density, but also for snow samples with the same density, but with a variation in the liquid water content. In this paper a physical temperature and surface condition model is described for snow-covered roads. The model is validated for an entire winter season on a heated pavement in Norway. Two different models to describe the thermal conductivity through the snow layer were compared. Results show that the thermal conductivity of the snow layer can be best described as a function of the density for snow with a low liquid water content. For snow with a high water content, the thermal conductivity can be best described as a function of the volume fractions and thermal conductivity of ice, water, and air, in which air and ice are modeled as a series system and water and air/ice in parallel.


2000 ◽  
Vol 30 (4) ◽  
pp. 624-630 ◽  
Author(s):  
Jed P Sparks ◽  
Gaylon S Campbell ◽  
R Alan Black

Time domain reflectometry (TDR) offers an opportunity to measure the liquid water content of otherwise frozen plant material. We applied TDR technology to the examination of freezing in three types of wood represented by Robinia pseudoacacia L. (ring porous), Populus trichocarpa Torr. & A. Gray (diffuse porous), and Pinus contorta Dougl. ex Loud. and Larix occidentalis Nutt. (conifer wood). Gravimetric analysis revealed similar water contents of all wood types during the summer. In contrast, winter data showed that R. pseudoacacia wood exhibited a lower total (liquid and ice) water content (0.250 m3·m-3) than that of Populus trichocarpa (0.600 m3·m-3) or of the two conifer species' wood (0.510 m3·m-3). Additionally,R. pseudoacacia wood contained more air by volume during the winter than all other wood types (air-filled porosity 0.34 m3·m-3 compared with 0.12-0.22 for all other species). At all temperatures below 0°C, R. pseudoacacia wood contained less liquid water than the other wood types, as revealed by TDR measures. The TDR analysis further demonstrated that more than 25% of the water in wood of all species was liquid even at temperatures of -15°C. This liquid water is likely found within the cell wall and is potentially transportable at temperatures well below 0°C.


Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 647 ◽  
Author(s):  
Carlos Pérez Díaz ◽  
Jonathan Muñoz ◽  
Tarendra Lakhankar ◽  
Reza Khanbilvardi ◽  
Peter Romanov

1981 ◽  
Vol 27 (95) ◽  
pp. 175-178 ◽  
Author(s):  
E. M. Morris

Abstract Field trials show that the liquid-water content of snow can be determined simply and cheaply by a version of Bader’s solution method.


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