Assessment of snow drift impact in the northern steppe region of China

Zuo, Hongchao; Yan, Min; Wang, Haibing; Zhi, Dong; Li, Gangtie

doi:10.1016/j.catena.2019.02.023

Cited by 7 publications

(11 citation statements)

References 18 publications

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“…Cryospheric hazards, including snowstorms, snowdrifts, avalanches, GLOFs, and permafrost collapse, have direct impacts on both the inhabitants and infrastructure of the region. Such risks have been exacerbated by the recent expansion of human activities into dangerous regions that were previously avoided, such as tourist installations in alpine regions that are now becoming ice-free [8,9,[67][68][69]. Cryospheric hazards in the SAM include snowstorms, snowdrifts, flooding, and drought [70].…”

Section: Snow Drought and Snowmelt Floodmentioning

confidence: 99%

“…The direct or cascading effects of the cryosphere on the human system consist of both positive and negative feedback. On the one hand, the cryosphere has triggered and exacerbated a series of natural disasters [5,6], such as avalanches [7] and snow drifts [8], permafrost collapse [9], rain-on-snow (ROS) flooding [10] and glacier lake outburst floods (GLOFs) [11,12], and drought [13]. On the other hand, the cryosphere serves the human being by supplying fresh water and regulating the climate and runoff [1].…”

Section: Introductionmentioning

confidence: 99%

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Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China

et al. 2022

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Optimizing the functions and services provided by the mountain cryosphere will maximize its benefits and minimize the negative impacts experienced by the populations that live and work in the cryosphere-fed regions. The high sensitivity of the mountain cryosphere to climate change highlights the importance of evaluating cryospheric changes and any cascading effects if we are to achieve regional sustainable development goals (SDGs). The southern Altai Mountains (SAM), which are located in the arid to semi-arid region of central Asia, are vulnerable to ecological and environmental changes as well as to developing economic activities in northern Xinjiang, China. Furthermore, cryospheric melting in the SAM serves as a major water resource for northeastern Kazakhstan. Here, we systematically investigate historical cryospheric changes and possible trends in the SAM and also discover the opportunities and challenges on regional water resources management arising from these changes. The warming climate and increased solid precipitation have led to inconsistent trends in the mountain cryosphere. For example, mountain glaciers, seasonally frozen ground (SFG), and river ice have followed significant shrinkage trends as evidenced by the accelerated glacier melt, shallowed freezing depth of SFG, and thinned river ice with shorter durations, respectively. In contrast, snow accumulation has increased during the cold season, but the duration of snow cover has remained stable because of the earlier onset of spring melting. The consequently earlier melt has changed the timing of surface runoff and water availability. Greater interannual fluctuations in snow cover have led to more frequent transitions between snow cover hazards (snowstorm and snowmelt flooding) and snow droughts, which pose challenges to hydropower, agriculture, aquatic life, the tail-end lake environment, fisheries, and transboundary water resource management. Increasing the reservoir capacity to regulate interannual water availability and decrease the risk associated with hydrological hazards related to extreme snowmelt may be an important supplement to the regulation and supply of cryospheric functions in a warmer climate.

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Section: Snow Drought and Snowmelt Floodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China

et al. 2022

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“…Snow fences are installed on both sides of roads as an effective mitigation tool, reducing the impact of drifting snow on traffic by decreasing the wind speed and capturing more snow on the lee side of the barrier or fence [17]. Furthermore, this redistribution due to drifting snow may result in spatial heterogeneities in the meltwater resources across the steppe region, which will then exacerbate spatial heterogeneities in vegetation by altering the hydrothermal conditions of the soil [18]. Drifting snow sublimation may also represent serious moisture loss [19], with the simulated snow mass loss due to drifting snow sublimation being 69.8 mm in the Qilian Mountains in the northern Qinghai-Tibet Plateau, which accounts for ~23.99% of the total snowfall in the area [14].…”

Section: Introductionmentioning

confidence: 99%

“…However, field observations of drifting snow need to be acquired to calibrate and validate the numerical models. Field observation methods have gradually evolved from manual records of drifting snow events to automatic records of snowdrift flux to address this increasing need for observations [18,22,23]. The FlowCapt sensor is a relatively stable acoustic sensor [24][25][26] that is now widely used for monitoring drifting snow around the world, including East Antarctica [27,28], the Indian Himalayas [29], and the French Alps [30].…”

Section: Introductionmentioning

confidence: 99%

Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia

Zhang

Chen

et al. 2022

Water

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Drifting snow is a significant factor in snow redistribution and cascading snow incidents. However, field observations of drifting snow are relatively difficult due to limitations in observation technology, and drifting snow observation data are scarce. The FlowCapt sensor is a relatively stable sensor that has been widely used in recent years to obtain drifting snow observations. This study presents the results from two FlowCapt sensors that were employed to obtain field observations of drifting snow during the 2017–2018 snow season in the southern Altai Mountains, Central Asia, where the snow cover is widely distributed. The results demonstrate that the FlowCapt sensor can successfully acquire stable field observations of drifting snow. Drifting snow occurs mainly within the height range of 80-cm zone above the snow surface, which accounts for 97.73% of the total snow mass transport. There were three typical snowdrift events during the 2017–2018 observation period, and the total snowdrift flux caused during these key events accounted for 87.5% of the total snow mass transport. Wind speed controls the occurrence of drifting snow, and the threshold wind speed (friction velocity) for drifting snow is approximately 3.0 m/s (0.15 m/s); the potential for drifting snow increases rapidly above 3.0 m/s, with drifting snow essentially being inevitable for wind speeds above 7.0 m/s. Similarly, the snowdrift flux is also controlled by wind speed. The observed maximum snowdrift flux reaches 192.00 g/(m2·s) and the total snow transport is 584.9 kg/m during the snow season. Although drifting snow will lead to a redistribution of the snow mass, any accumulation or loss of the snow mass is also affected synergistically by other factors, such as topography and snow properties. This study provides a paradigm for establishing a field observation network for drifting snow monitoring in the southern Altai Mountains and bridges the gaps toward elucidating the mechanisms of drifting snow in the Altai Mountains of Central Asia. A broader network of drifting snow observations will provide key data for the prevention and control of drifting snow incidents, such as the design height of windbreak fences installed on both sides of highways.

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“…Shenguan Qiang et al used wind tunnel simulation to study the characteristics of snow drift and the distribution of snow on the roof [5] ; Hejun Zuo et.al. studied the effect of snow drift impact in the northern steppe region of China [6] ; Xuanyi et al coupled the Snowmelt model and the snowdrift model to study coupling results of the distribution of snow on the roof [7] ; Chen Bailian et al analyzed characteristics of the freezing disaster and its weather cause with Guizhou as the representative area [8] . Not the disaster-causing mechanisms of different locations during the same freezing rain and snow disasters are different, but the disaster-causing mechanisms of freezing disasters at different times in the same location are also obviously different.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Coupling Laws of Disaster Inducing Factors of Frozen Rain and Snow Disasters in Southern China—Taking Changsha City as an Example

Wang¹,

Chen²,

Chang³

et al. 2021

dteees

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In order to study the causes and laws of freezing rain and snow disasters in southern China caused by coupling of multiple disaster inducing factors, the meteorological observation data of the severe rain and snow freezing disasters in Changsha in January 2008 was analyzed in this paper. The fluctuation characteristics of typical disaster inducing factors and disaster factors coupling law were studied, and the following conclusions were drawn: (1) Temperature-humidity coupling system will promote the occurrence of freezing disasters such as glaze, freezing fog, freezing rain and sleet; (2) Wind and precipitation are important causes for the occurrence of freezing disasters, and their coupling effect will lead to typical disasters such as snow drift and rain-wind phenomenon, which will aggravate freezing disasters; (3) Daily maximum temperature, daily minimum temperature and the average temperature are significantly negatively correlated with the degree of freezing disasters, and the effects of humidity and precipitation on freezing disasters are significantly positively correlated. The results showed that the coupling analysis of disaster inducing factors could provide a powerful tool for the freezing disasters prevention and emergency management.

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Assessment of snow drift impact in the northern steppe region of China

Cited by 7 publications

References 18 publications

Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China

Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China

Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia

Analysis of the Coupling Laws of Disaster Inducing Factors of Frozen Rain and Snow Disasters in Southern China—Taking Changsha City as an Example

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