Supraglacial debris is widely present on glaciers in alpine environments and its distribution greatly affects glacier melt. The present study aims to determine the effect of debris on glacier ice melt on Ponkar Glacier, Manang District, Nepal. We estimated ice melt under various debris thickness using Energy Balance (EB) model and conductive heat flux methods, which are compared with in-situ observations. Four stakes are installed on the glacier at different debris thickness of 11-40 cm. Meteorological data from March 2016 to May 2018 are obtained from the Automatic Weather Station (AWS) installed on the glacier surface at an elevation of 3,881 m a.s.l. for the energy balance calculation. Debris surface temperature and different debris depths are also measured on the glacier. The calculated ablation rates from the conductive heat flux method are 0.9, 1.62 and 0.41 cm/d on pre-monsoon, monsoon and post-monsoon, respectively, with mean debris thermal conductivity 1.04 W/(m?K). The net radiation shows little variation between the seasons, while turbulent heat flux varies in the season. Sensible heat flux was found to be highest in post-monsoon season due to a larger temperature gradient between surface and air.

Climate warming increases the variability in runoff of semiarid mountains where seasonally-frozen ground is widely distributed. However, what is not well understood are the processes of runoff, hydrological drivers, and freeze-thaw cycles in seasonally-frozen ground in semiarid mountains. To understand how freeze-thaw cycles affect runoff processes in seasonally-frozen ground, we monitored hydrological processes in a typical headwater catchment with seasonally-frozen ground in Qilian Mountain, China, from 2002 to 2017. We analyzed the responses of runoff to temperature, precipitation, and seasonally-frozen ground to quantify process characteristics and driving factors. The results show that annual runoff was 88.5 mm accounting for 25.6% of rainfall, mainly concentrated in May to October, with baseflow of 36.44 mm. Peak runoff occurred in June, August, and September, i.e., accounting for spring and summer floods. Runoff during the spring flood was produced by a mix of rainfall, melting snow, and melting seasonally-frozen ground, and had a significant correlation with air temperature. Runoff was mainly due to precipitation accumulation during the summer flood. Air temperature, average soil temperature at 0-50 cm depth, and frozen soil depth variable explained 59.60% of the variation of runoff in the thawing period, while precipitation variable explained 21.9%. Thawing-period runoff and soil temperature had a >0.6 correlation coefficient (P <0.05). In the rainfall-period, runoff was also affected by temperature, soil moisture, and precipitation, which explained 33.6%, 34.1% and 18.1%, respectively. Our results show that increasing temperature and precipitation will have an irreversible impact on the hydrological regime in mountainous basins where seasonally-frozen ground is widely distributed.

Based on salt-frost heave tests of sulfate saline soil under repeated freeze-thaw cycles, this paper discusses the mechanism of the salt-frost heave under long-term freeze-thaw cycles. The results show that the salt-frost heave can be restricted considerably by loads, and there is a critical load for the salt-frost heave cumulative effect. Under this load, peak values of salt-frost heave approach a constant, and the residual values become 0. There is no longer structure heave or cumulative effect of saline soil exposed to freeze-thaw cycles under the critical load. Taking cumulative effect into account in calculations of salt-frost heave, a salt-frost heave model under freeze-thaw cycles is developed.

Carex brunnescens (Pers.) Poir. is considered to be the only clonal herb found to date that can develop and form fixed dunes in Maqu alpine degraded grasslands of northwestern China. However, due to strong dormant characteristics of C. brunnescens seeds, the sand-fixing effect of the plant is severely limited. This study explores a technique that can rapidly promote the seed germination of C. brunnescens, and also investigates the adaptation and sand-fixing effect by cultivating C. brunnescens seedlings to establish living sand barriers in the sand ridges of moving sand dunes. Results show that the seed germination rate obtained a maximum of 63.7% or 65.1% when seeds were treated with 150 mg/L gibberellic acid (GA₃) for 24 h followed by soaking in sulfuric acid (98% H₂SO₄) for 2.5 min or sodium hydroxide (10% NaOH) for 3.5 h, and then germinated (25 °C in daytime and 5 °C at nighttime) in darkness for 10 d. After breaking seed dormancy of C. brunnescens, the living sand barrier of C. brunnescens (plant spacing 15-20 cm; sand barrier spacing 10-20 m) was established in the perpendicular direction to the main wind in the middle and lower parts of the sand ridges on both sides of the moving sand dunes. When the sand ridges were leveled by wind erosion, the living sand barrier (plant spacing 15-20 cm; sand barrier spacing 0.5-1.0 m) of C. brunnescens was reestablished on the wind-eroded flat ground. Finally, a stable sand-fixing surface can be formed after connecting the living sand barriers on both sides, thus achieving a good sand-fixing effect. These findings suggest that rapid seed germination technology combined with the sand-fixing method of C. brunnescens can shorten the seed germination period and make the seedling establishment become much easier which may be an effective strategy to restore and reconstruct Maqu degraded grasslands.

Water is the most important limiting factor in arid areas, and thus water resource management is critical for the health of dryland ecosystems. However, global climate change and anthropogenic activity make water resource management more difficult, and this situation may be particularly crucial for dryland restoration, because of variation in water uptake patterns associated with artificial revegetation of different ages and vegetation type. However, there is lacking long-term restorations that are suitable for studying this issue. In Shapotou area, Northwest China, artificial revegetation areas were planted several times beginning in 1956, and now form a chronosequence of sand-binding landscapes that are ideal for studying variability in water uptake source by plants over succession. The stable isotopes δ¹⁸O and δ²H were employed to investigate the water uptake patterns of the typical revegetation shrubs Artemisia ordosica and Caragana korshinskii,which were planted in different years. We compared the stable isotope ratios of shrub stem water to groundwater, precipitation, and soil water pools at five layers (5-10, 10-40, 40-80, 80-150, and 150-300 cm). The results indicate that Artemisia ordosica derived the majority of their water from the 20-150 cm soil layer, whereas Caragana korshinskii obtained water from the 40-150 cm soil layer. The main water sources of Artemisia ordosica and C. korshinskii plants changed over time, from deeper about 150 cm depth to shallow 20 cm soil layer. This study can provide insights into water uptake patterns of major desert vegetation and thus water management of artificial ecosystems, at least in Northwest China.

PM_2.5 and PM₁₀ were the main air pollutants during winter in Lanzhou New District, China. In this paper, WRF model output combined with hourly monitoring data of pollutant concentration was used to analyze characteristics of the concentration change and to study the relationship between meteorological elements and PM₁₀/PM_2.5 in Lanzhou New District in January, 2018. Meanwhile, the concentration changes of PM_2.5 and PM₁₀ were predicted by wavelet analysis combined with BP neural network. The results show that: (1) Due to the cold front process in winter, PM_2.5 was negatively correlated with the water vapor mixing rate. PM₁₀ was positively correlated with air temperature and negatively correlated with air pressure. (2) There was an inversion layer in the atmosphere near the high value day of PM_2.5 and PM₁₀, the surface was controlled by low pressure, low wind speed, and the situation of low value day of PM_2.5 was the opposite. On the day of high value of PM₁₀, the air temperature below 600 hPa was higher, and the wind speed near the surface was also higher. (3) Wavelet analysis combined with BP (Back Propagation) neural network had a good prediction effect on PM_2.5, which could basically reflect the hourly change of PM_2.5 concentration. However, the simulation effect of PM₁₀ was poor, and the input parameters of surrounding pollutants should be added to improve the prediction effect.