PAPERS
Relationship between Shear Strength and Snow Properties at the Base of Snowpack
2025 Volume 66 Issue 4 Pages 269-274
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2025 Volume 66 Issue 4 Pages 269-274
This study investigates how snow properties affect the shear strength at the base of snowpack. Field measurements of the shear strengths showed values ranging from 0.3 to 3.8 kN/m2, with an average value of 1.5 kN/m2. Despite the variation, it was confirmed that shear strength was positively correlated with dry snow density and snow hardness, and negatively correlated with liquid water content. Additionally, to understand the shear strength of snowpack under rainfall or rapid snowmelt, we measured the shear strength of an area of snowpack sprayed with water.
Snow avalanches can occur on slopes along railway lines. Therefore, railway companies operating in areas with heavy snowfall face the risk of serious operational disruptions such as derailments caused by avalanches. To prevent such disruptions, railway companies send out patrols when certain indicators are reached for each line section, such as specified temperatures and precipitation levels. However, these criteria are based on empirical based on observation and experience rather than on deduction from theoretical principles. In some cases, patrols are conducted even during periods or in areas where the risk of avalanches is low, using up significant labor resources. Therefore, establishing a method for evaluating avalanche risk based on theoretical principles would enable more accurate assessment of periods and locations where there is increased risk of avalanches, and ensure more effective and efficient deployment of patrols.
Avalanches can be classified into surface avalanches and full-depth avalanches. In surface avalanches the sliding surface is within the snow layer (Fig. 1, left). In full-depth avalanches, the sliding surface is at the base of the snowpack (Fig. 1, right, and Fig. 2) [1]. Both occur when the driving force exceeds the resisting force, so that the snow becomes unstable. It should be noted that driving force is the force that causes the avalanche to slide, and the resisting force opposes the slide. The stability of surface avalanches can be evaluated examining the relationship between the driving force and resisting force within the snow layer.
On the other hand, the stability of full-depth avalanches can be evaluated by examining the relationship between the snowpack base and the ground surface. An increase in driving force is caused by an increase in overburden load due to the addition of water to the snowpack during snowfall or rainfall associated with sudden temperature increases in the winter. On the other hand, a decrease in supporting force is caused by a reduction in shear strength due to the infiltration of rainwater or meltwater into the snowpack or the snowpack base. This results in the presence of water in the sliding surface.
Previous study [2] have reported relationships between shear strength and snow properties, such as snow density and water content within the snowpack, in surface avalanches. On the other hand, the shear strength of the snowpack base is difficult to evaluate because it is affected by soil properties, microtopography, and vegetation, all of which are important factors in full-depth avalanches. Therefore, this study focuses on full-depth avalanches.
Similar to the shear strength in the snowpack, the shear strength of the snowpack base is also thought to be influenced by snow properties such as snow density and water content. Previous studies [3, 4] have reported that the shear strength of the snowpack base tends to decrease as the water content increases in indoor tests. However, since there are no field observation results, the relationship between other snow properties such as density, hardness, and shear strength remains unclear. Therefore, the authors carried out field observations to investigate the relationship between the shear strength of the snowpack base and the snow properties. Additionally, to simulate sudden rainfall or meltwater arriving at the snowpack base, the changes in the shear strength were examined when natural snow was watered.
In the flat ground and the embankment (southeast slope and northwest slope, slope angle 35°) the Shiozawa Snow Testing Station (Minamiuonuma City, Niigata Prefecture: Fig 3), a total of 47 snow profile observations were conducted during the winter seasons of 2014, 2016, 2020, and 2021. The snow profile observations revealed the characteristics of the snow at the snowpack base (2 cm above ground level), such as density, water content, and hardness.
The shear strength (kN) at the boundary between the snowpack and the ground was measured using a shear frame and a digital load cell. As shown in Fig. 4, approximately 10 cm of snow on the ground surface was left after digging it out, and a shear frame was inserted from above. After removing the surrounding snow, the digital load cell was pulled to break the boundary between the ground surface and the snow. Then, the shear strength was measured. The pulling time was approximately 1 second. The average value obtained from 1 to 3 measurements per observation was divided by the effective cross-sectional area of the shear frame (0.025 m2) to obtain the shear strength per unit area (kN/m2). Note that the vegetation on the failure surface was either bare ground or grassland, and the type of vegetation on most of the failure surface after measurement was recorded (Fig. 5).
Assuming that sudden rainfall or snowmelt water reaches the base of the snowpack, we conducted tests focusing on changes in shear strength over time after sprinkling (Fig. 6).
The test procedure is described below.
(1) Approximately 10 cm of snow is left at the base of an area measuring approximately 1.5 m × 1.7 m. The site is prepared to allow a shear frame to be set up.
(2) Measure the shear strength, density, moisture content, and hardness of the soil before watering.
(3) Using a watering can, approximately 8 L of tap water (approximately 3°C) is sprinkled over the excavated area for approximately 3 minutes. The amount of sprinkled water per converted unit area is 3.1 mm, equivalent to a rainfall intensity of 62.6 mm/h.
(4) Shear strength, density, moisture content, and hardness are measured 30 minutes, 1 hour, 3 hours, and 5 hours, after sprinkling the water. 2 to 4 shear strength measurements were taken at each time interval, and the average value was calculated.
Figure 7 shows the snow conditions (the daily average temperature and the snow depth) and the dates on which the shear strength was measured over the course of four winters (2014, 2016, 2020, and 2021). Figure 7 shows that the 2016 winter had slightly shorter snow periods and slightly shallower maximum snow depths than other winters. However, snow conditions were generally normal for all four winters.
Shear strength measurements were conducted at intervals of approximately 10 to 30 days from the coldest winter period through to snowmelt. The quality of snow at the base of the snowpack for all measurements was granular.
Figure 8 shows the results of shear strength measurements for each winter season. The results indicate that shear strength varies over time at each location and that there is no clear temporal trend.
When comparing the shear strength measurement results on flat areas with those on slopes, the values on flat areas tend to remain around 2.0 kN/m2. On the other hand, the values on the southeast slope tend to remain around 1.0 kN/m2, which is lower than the value on flat areas. The shear strength values on the northwest slope were intermediate between those on the flat area and the southeast slope (1.5 kN/m2). Therefore, when the shear strength of snow on the flat area and slopes during the same period are compared, it shows that the values on the flat area tended to have greater values. The total of 47 measured shear strength values ranged from 0.3 to 3.8 kN/m2, with an average value of 1.5 kN/m2 (Fig. 9). When the measured values were classified into 0.5 kN/m2 intervals, the most frequent occurrences were in the 0.5−1.0 kN/m2 and 1.5−2.0 kN/m2 ranges, followed by 1.0−1.5 kN/m2 range. Therefore, most of the measurements in this study fell within the range of 0.5−2.0 kN/m2, which was comparable to the values obtained in indoor tests by Kamiishi et al. and Takahashi et al. Furthermore, this paper presents the measured shear strength at the sliding surface within the snow layer during surface avalanches (0.1−10 kN/m2, with an average of 1.0 kN/m2) [5]. Additionally, the results were similar in magnitude to those obtained from shear strength measurements within the snow layer during surface avalanches (ranging from 0.1 kN/m2 to 10 kN/m2, with an average of 1.0 kN/m2).
Next, Fig. 10 shows the relationship between shear strength, dry density, moisture content, and hardness.
Examining the relationship between shear strength and dry density, as shown in the top of Fig. 10, reveals a positive correlation regardless of the measurement location (flat area: 0.43, southeast slope: 0.60, northwest slope: 0.50). Comparing the correlation coefficients, it is clear that the correlation is stronger on slopes than on flat areas. Additionally, the dry density is particularly low on the southeast and northwest slopes when the shear strength is 1 kN/m2 or lower.
Next, examination of the relationship between shear strength and water content, as shown in the middle row of Fig. 10, reveals that although the correlation coefficients are small, it has a negative correlation on flat areas and on southeast slopes (flat areas: −0.38, southeast slopes: −0.41). This indicates that as shear strength decreases, moisture content tends to increase. There was little correlation among the measured values overall on northwest slopes. However, a trend of larger shear strength associated with lower moisture content was observed when focusing on shear strength of 3.0 kN/m2 or less. Nevertheless, even when the moisture content was high, at around 10%, the shear strength was large, reaching 3.0 kN/m2 or more in some cases. Similar values were observed on the southeast slope, but these values were based on only one data point, and the variation in shear strength of 2.0 kN/m2 or less is relatively small. Therefore, the impact on the entire data set is considered to be small. In cases where the value is greater than 3.0 kN/m2, the number of data points is small, so it is necessary to continue accumulating measurement data and quantitatively evaluate the influence of moisture content on shear strength. In summary, although there is some variation, shear strength increases with higher dry density and hardness and decreases with higher water content.
To confirm the differences in shear strength based on ground vegetation conditions, the shear strength histograms in Fig. 8 were classified into two categories: bare ground and grassland categories as shown in Fig. 11. As a result, with the exception of one case, all shear strengths below 1.0 kN/m2 were measured in grassland. Shear strength tended to be lower in grassland, with lower strength classes occurring more frequently. In the case of tall, soft grasses, such as those measured in this study (Fig. 5), the grass does not get caught in the snow. Instead, it acts as an intermediate layer between the snow and the ground surface. In such cases, the grasses facilitate snow sliding, resulting in lower shear strength.
Figure 12 shows the time-dependent changes in shear strength after watering. Figure 13 shows the time-dependent changes in dry density, moisture content, and hardness of the snow after watering. The measured shear strength before watering was 2.8 kN/m2; dry density, 442 kg/m3; moisture content, 13.5%; and hardness, 94.4 kN/m2. The shear strength decreased by approximately 60% 30 minutes after watering and remained largely constant thereafter. Similar to shear strength, hardness decreased by approximately 30% after watering and subsequently fluctuated slightly remaining at a similar level. The dry density and moisture content varied slightly but remained nearly constant from immediately after watering.
According to Izumi [6], wetting snow causes changes to its structure, leading to a rapid decrease in snow hardness. It is thought that this is due to the infiltrated water weakening the bonds between ice particles. The decrease in hardness after watering is also thought to be due to this effect. Although there was some variability, results from shear strength measurements in field observations revealed a positive correlation between shear strength and hardness. Therefore, the decrease in hardness due to watering is considered to be one of the factors that contribute to the reduction in shear strength at the base of the snowpack. Additionally, although it is generally expected that watering snow increases its moisture content, rapid watering in this case caused the snow to exceed its water-holding capacity, leading to swift drainage within the snow layer. This is considered a factor that contributed to the small change in moisture content. As a result, the dry density remained nearly constant. However, water may have been present between the snow surface and the ground surface, which could have potentially contributed to the decrease in shear strength.
Based on the above results, it was found that rapid rainfall and snowmelt can significantly affect the shear strength of the snowpack base. The presence or absence of such water infiltration history may also influence the variability of measurement values in field observations. It is expected that further verification will be conducted in the future to determine if rainfall or snowmelt history can effectively evaluate shear strength. Additionally, collecting measurement data under different conditions, such as changes in surface permeability coefficients, is expected to improve our understanding of the phenomenon.
In this study, we investigated the relationship between shear strength at the base of snow cover and snow properties. These properties are important for assessing the risk of full-depth avalanches. Our findings are based on field observations of bare ground and grassland in flat areas and embankments and field sprinkling tests. The results revealed the following:
(1) The range of measured shear strength values at the base of the snowpack was between 0.3 and 3.8 kN/m2. The average values for flat terrain, southeastern slopes, and northwestern slopes were 2.0 kN/m2, 1.0 kN/m2, and 1.5 kN/m2, respectively.
(2) The temporal variation in shear strength was unclear, and it fluctuated throughout the winter season.
(3) During the same period, shear strength was generally lower on slopes than on flat ground.
(4) A positive correlation was confirmed between shear strength and dry density at all measurement points.
(5) A negative correlation was confirmed between shear strength and moisture content on flat ground and on the southeast slope. However, on the northwest slope, this relationship could not be confirmed due to the influence of cases with high shear strength despite high moisture content.
(6) No correlation was confirmed between shear strength and hardness on flat ground. However, a positive correlation was confirmed on slopes.
(7) When examining shear strength measurements by grassland and bare ground, all cases with shear strength values of 1.0 kN/m2 or less were from grassland, except for one case.
(8) The results of the watering test showed that hardness decreases immediately after heavy rainfall or snowmelt. This increase in hardness may reduce the shear strength at the base of the snowpack.
In this study, we examined the relationship between shear strength measurements and snow conditions during snow accumulation. However, changes in the applied load and particle size after snow accumulation may also influence shear strength. We also plan to conduct more detailed measurements and analyses to investigate the effects more precisely by factor, such as ground conditions (e.g., vegetation types), on shear strength.
This paper is based on the content of a presentation delivered at the 38th Cold Region Technology Symposium [7].
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Ryota SATO
Senior Researcher, Meteorological Disaster Prevention Laboratory, Disaster Prevention Technology Division Research Areas: Glaciology |
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Daisuke TAKAHASHI
Researcher, Meteorological Disaster Prevention Laboratory, Disaster Prevention Technology Division Research Areas: Glaciology |
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Katsuhisa KAWASHIMA, Ph.D. Professor, Research Institute for Natural Hazards and Disaster Recovery, Niigata University Research Areas: Glaciology |
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Takane MATSUMOTO, Ph.D. Project Associate Professor, Research Institute for Natural Hazards and Disaster Recovery, Niigata University Research Areas: Glaciology |
