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.

The precipitation δ¹⁸O-elevation gradients are important for paleoclimate, hydrology, and paleoelevation studies. The field setting for this research was the upper reaches of the Heihe River Basin within the Qilian Mountains in the Northern Tibetan Plateau. Three study sites were established along the Heihe main river. These sites were the Yingluoxia and Qilian hydrological stations and the Yeniugou meteorological station. The Yingluoxia hydrological station was the dividing point between the upper and middle reaches of the Heihe River Basin. The altitudes of these sites range from 1600 m to 3300 m. Summer precipitation is predominant with regard to the annual precipitation amount. By analysis of variance (ANOVA), the precipitation δ¹⁸O data collected from the three sites were analyzed, spanning a year of precipitation data from 2007.10 to 2008.9. The results showed that the δ¹⁸O-elevation gradient was not significant (α = 0.05) at a seasonal or annual scale in this region and the precipitation-weighted annual mean δ¹⁸O was −7.1‰. Mechanisms that have been proposed to explain this result consider the role of two processes, including (1) mixing of moisture sources, a process common in an arid and semiarid region, and (2) the absence of a mechanism for water vapor to climb along slopes in the precipitation system. Atmospheric water vapor mainly travels along the trend of the Qilian Mountains range rather than climbing it because this region is dominated by the westerlies and the trend of the Qilian mountains is geographically aligned to the NWW (north-west-west) direction. We demonstrated that, aside from the water vapor source, the spatial relationship between the water vapor transport pathway and the trend of the mountain range are the main driving factors associated with the stable isotope trends in precipitation. As a result, it is important to re-recognize the timing and location of groundwater recharge in the Heihe River Basin.