Glaciers are vital to water resources in the arid land of central Asia. Long-term runoff records in the glacierized area are particularly valuable in terms of evaluating glacier recession and water resource change on both a regional and global scale. The runoff records of streams draining basins with 46% current glacier cover, located at the Urumqi Glacier No. 1 in the source area of the Urumqi River in eastern Tianshan, central Asia, were examined for the purpose of assessing climatic and glacial influences on temporal patterns of streamflow for the period 1959–2018. Results suggest that runoff from the catchment correlates well with temperature and associated precipitation data. During the period 1993–2018, it increased by 114.39 × 10⁴ m³, which was 1.7 times the average runoff during the period 1959–1992. A simple water balance model is introduced to calculate the different components of the runoff, including precipitation runoff from glacier surface and from nonglacial areas, glacier mass balance and glacial runoff. Thus, the long-term change of each component and its response to climate change are revealed. We found that the period 1997–2018 is likely to be the “peak water” (tipping point) of the glacial runoff resulting from shrinkage of glacier area.

In this study, energy and mass balance is quantified using an energy balance model to represent the glacier melt of Urumqi Glacier No. 1, Chinese Tian Shan. Based on data from an Automatic Weather Station (4025 m a.s.l) and the mass balance field survey data nearby on the East Branch of the glacier, the “COupled Snowpack and Ice surface energy and Mass balance model” (COSIMA) was used to derive energy and mass balance simulations during the ablation season of 2018. Results show that the modeled cumulative mass balance (−0.67 ± 0.03 m w.e.) agrees well with the in-situ measurements (−0.64 ± 0.16 m w.e.) (r² = 0.96) with the relative difference within 5% during the study period. The correlation coefficient between modeled and observed surface temperatures is 0.88 for daily means. The main source of melt energy at the glacier surface is net shortwave radiation (84%) and sensible heat flux (16%). The energy expenditures are from net longwave radiation (55%), heat flux for snow/ice melting (32%), latent heat flux of sublimation and evaporation (7%), and subsurface heat flux (6%). The sensitivity testing of mass balance shows that mass balance is more sensitive to temperature increase and precipitation decrease than temperature decrease and precipitation increase.

Precipitation is a key process in the hydrologic cycle. However, accurate precipitation data are scarce in high mountainous areas, mainly restricted by complex topography, solid precipitation and sparse recording stations. In order to evaluate the quality of precipitation measurement, this study conducted a comparison campaign of precipitation measurements with the PWS100 laser sensor and the Geonor T-200B rain gauge for an entire year from 30 April 2018 to 1 May 2019 at an elevation of 3835 m in a nival glacial zone in eastern Tianshan, Central Asia. The results show that the daily precipitation values recorded by Geonor T-200B and PWS100 are well correlated and the annual precipitation amounts recorded by the two instruments differ by 7%, indicating good capabilities of both instruments in solid precipitation measurement. However, the amount of precipitation measured by Geonor T-200B was 36 mm lower in June to August and 120 mm higher in the remaining months compared with the values measured by PWS100. Our study indicated that Geonor T-200B is more efficient than PWS100 in terms of catching solid precipitation measurements. According to the PWS100 data, the experiment site was dominated by solid precipitation particles, accounting for 60% of total precipitation particles. Based on the precipitation particle and in-situ air temperature measurements, a set of temperature thresholds were established to discriminate rain, sleet and snow. The threshold temperature of rainfall and snowfall is −1.5 and 8 °C, respectively. When air temperature ranges from −1.5 to 8 °C, sleet occurs, meanwhile the ratio of rain to snow depends on air temperature.

Warming in mountainous areas has obvious elevation dependence (warming rate increases with elevation), which deeply impacts runoff change in mountainous areas. This study analysed the influence of elevation-dependent warming on runoff in the headwater region of the Urumqi River Basin (URB) based on meteorological data, remote sensing images, and runoff data. Results indicated a significant warming rate in the URB from 1960 to 2019 (0.362 °C/decade; p < 0.01). The temperature increased with an obvious elevation-dependent warming in the URB, especially during winter. Glaciers sharply retreated in the headwater region of the URB under regional warming, and remote-based results showed that glacier areas decreased by 29.45 km² (−57.81%) from the 1960s to 2017. The response of glacier mass balance and meltwater runoff to temperature change has a lag of 3 years in the headwater region of the URB. The elevation-dependent warming of temperature changes significantly impacted glacial meltwater runoff in the URB (R² = 0.49). Rising temperatures altered the glacial meltwater runoff, and the maximum annual runoff of the Urumqi Glacier No. 1 meltwater runoff increased 78.6% in 1990–2017 compared to 1960–1990. During the period of 1960–1996, the total glacial meltwater runoff amounted to 26.9 × 10⁸ m³, accounting for 33.4% of the total runoff during this period, whereas the total glacial meltwater runoff accounted for 51.1% of the total runoff in 1996–2006. Therefore, these results provide a useful reference for exploring runoff changes in mountainous watersheds in the context of elevation-dependent warming.

Surface albedo exerts substantial control over the energy available for glacier melting. For Urumqi Glacier No.1 in the Tien Shan Mountains, China, represented as a “summer accumulation” glacier, the variations in albedo driven by surface processes are complex and still poorly understood. In this study, we examined the interannual trends in ablation-period albedo from 2000 to 2021 using MOD10A1 products, evaluated the variation in bare-ice albedo retrieved from 13 end-of-summer Landsat images obtained between 2002 and 2019, and investigated the seasonal variation and diurnal cycle of surface albedo collected near the equilibrium line of the glacier by an AWS from September 2018 to August 2021. During the period of 2000–2021, the average ablation-period albedo presented a slight but not statistically significant downward trend, with a total decrease of 1.87%. Specifically, the decrease in glacier albedo was quicker in July than that in August, and there was a slight increase in May and June. The blackening phenomenon was shown on the east branch glacier, but not on the west branch glacier. For seasonal variability, a bimodal pattern was demonstrated, different from the unimodal seasonal variation in other midlatitude glaciers. The albedo peaks occurred in December and April or May. Under clear sky conditions, the diurnal cycle presented three patterns: a symmetric pattern, an asymmetric pattern, and a progressive decreasing pattern. Air temperature and solid precipitation are the main drivers of variations in glacier albedo, but in different periods of the ablation season, two climate variables affect albedo to varying degrees. The effect of surface albedo reduction enhanced glacier melting by about 20% over the past 20 years. The short-term increase in albedo caused by summer snowfall can considerably reduce glacier melting by as much as 80% in June.

As a heavily glaciated region, the Eastern Pamir plays a crucial role in regional water supply. However, considerable ambiguity surrounds the distribution of glacier ice thickness and the details of ice volume. Accurate data at the local scale are largely insufficient. In this study, ground-penetrating radar (GPR) was applied to assess the ice thickness at Muztagh Glacier No.16 (MG16) in Muztagh Ata, Eastern Pamir, for the first time, detailing findings from four distinct profiles, bridging the gap in regional measurements. We utilized a total of five different methods based on basic shear stress, surface velocity, and mass conservation, aimed at accurately delineating the ice volume and distribution for MG16. Verification was conducted using measured data, and an aggregated model outcome provided a unified view of ice distribution. The different models showed good agreement with the measurements, but there were differences in the unmeasured areas. The composite findings indicated the maximum ice thickness of MG16 stands at 115.87 ± 4.55 m, with an ice volume calculated at 0.27 ± 0.04 km³. This result is relatively low compared to the findings of other studies, which lies in the fact that the GPR measurements somewhat constrain the model. However, the model parameters remain the primary source of uncertainty. The results from this study can be used to enhance water resource assessments for future glacier change models.