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Article

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

by
Wei Zhang
1,*,
Yongping Shen
1,
An’an Chen
2 and
Xuejiao Wu
1
1
Koktokay Snow Station, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2
College of Urban and Environmental sciences, Northwest University, Xi’an 710127, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(3), 1406; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031406
Submission received: 17 November 2021 / Revised: 23 January 2022 / Accepted: 26 January 2022 / Published: 28 January 2022
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Abstract

:
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.

1. Introduction

The cryosphere encompasses the portion of the Earth’s surface where water is in solid form, including mountain glaciers, ice cover, ice sheets, snow cover, permafrost, seasonally frozen ground (SFG), solid precipitation, and sea, lake, and river ice [1,2]. There are strong interactions between the cryosphere, Earth system, and anthroposphere [2,3,4]. 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]. Approximately 1.9 billion people are essentially fed (at least in part) by meltwater from the cryosphere [13,14,15,16]. For example, the water security of 800 million people in both the Indus and Tarim river basins is controlled by glacial meltwater in High Mountain Asia [13]. The cryosphere also provides a potential new perspective from which to view regional and global sustainable development, and will directly affect the realization of sustainable development goals (SDGs), including those related to eliminating poverty and hunger; the provision of clean water, sanitation, affordable and clean energy; and aquatic and terrestrial life [17].
The cryosphere serves as an indicator of climate change, with significant cryospheric change being represented by rapid ice loss in response to ongoing global warming [18,19,20]. Furthermore, there are both positive and negative feedbacks of the cryospheric changes to the anthroposphere. Although the shrinking ice reserves in High Mountain Asia will initially produce increased glacial runoff volumes and protect large populations from drought stress before 2030, the continued shrinkage of these high-mountain glaciers will lead to runoff reductions later in the twenty-first century [13,21,22]. Therefore, a proper assessment of the opportunities and challenges on regional water resources that cryospheric changes pose to the well-being of the region and its population will need to become a critical aspect of regional and global strategic planning if we are to mitigate the negative effects of these ongoing changes.
One of the key challenges in determining the impact of cryospheric changes is their complexity, with significant spatiotemporal heterogeneity in the cryosphere being driven by the highly variable nature of local conditions. Although regional climatic conditions exert an important control on the state of the cryosphere, it is also heavily influenced by various external parameters. For example, frozen ground is shaped by snow cover, vegetation, peat, wildfires, and other phenomena [23,24,25]. Debris (negative or positive) [26] and light-absorbing impurities (positive) [27] are significant factors that influence the melting of mountain glaciers, and changes to snow cover are related to vegetation [28], topography [29], elevation [30], and other factors. Therefore, the cryosphere may not always be shrinking at the local scale. For example, the glaciers in the Karakoram Range are currently experiencing the so-called “Karakoram anomaly” [31], with increased snow cover observed across the high altitudes of northern Pakistan [32] and stable permafrost present in the northern Great Khingan Mountains, China [24]. Determining the nature and extent of cryospheric changes caused by global warming will facilitate cryospheric water resource utilization and risk management.
The Altai Mountains of Inner Asia remain a relatively pristine landscape. However, recent socio-ecological changes have introduced challenges regarding the management of natural resources, particularly water. The Altai Mountains form the ‘Water Tower’ of a wider region, with the populations in the highland to lowland regions of the surrounding four nations depending on the river, stream, and lake waters derived from melting snow and glaciers for their livelihood and economic activities [16,33]. Climate change has increased in mountainous regions at an ever-accelerating pace over the last century [34], with the Altai Mountains being no exception to these drastic changes. The southern Altai Mountains (SAM) experienced significant temperature and precipitation increases over the period 1966–2015 [35]. Our field investigations indicate that summer droughts, which have caused serious livestock losses in the SAM, are preceded by winters with limited snowfall. The SAM has been experiencing increasing water stress in recent years, highlighting the urgent need to assess the effect of cryospheric changes on water resources.
This study aims to: (a) discover the change characteristics of main cryospheric elements during the period 1961–2015, as well as any spatiotemporal trends that may exist, and (b) assess the opportunities and challenges that these cryospheric changes pose to the regional water resource management, including the hydrological processes, water resources, water management (hydropower, agriculture, tail-end lakes, fisheries, aquatic life, and water rights associated with transboundary rivers), and their correlation with SDGs. The findings of this assessment will be useful for sustainable development in the SAM.

2. Data and Methods

2.1. Study Area

The SAM is mainly located in the northern part of the Xinjiang Uygur Autonomous Region of China (Figure 1). The SAM ranges from 224 to 4265 m above sea level (a.s.l.) and has a continental temperate climate that is strongly affected by the Siberian cold air masses and the westerlies in winter [36]. There was an increasing trend observed in relative humidity from the 1900s to the 1990s that has since switched to a decreasing trend [37]. The high- to low-elevation vegetation zones across the SAM consist of alpine tundra with snow patches and bare rocks, alpine wetlands and meadows, needle-leaved forests and scrubs, subalpine meadows, montane steppes, and desert steppes [38]. The main rivers in this region include the Irtysh and Ulungur. The Irtysh originates in the SAM, flows northwest into Kazakhstan, and then joins the Ob River near the city of Khanty-Mansiysk, western Siberia, Russia, before draining into the Arctic Ocean [33,39]. The Ulungur is an inland river that originates in western Mongolia and flows south into Altay Prefecture of northern Xinjiang of China, where it then flows northwest and empties into Ulungur Lake [40].
Pastoral livestock husbandry is prevalent in the Altai Mountains, with annual increases in the number of livestock significantly exceeding the environmental capacity [41,42]. Grazing begins in late April and ends in early October following the timing of snow cover in the SAM. The annual economic report of Altay Prefecture in 2017 (http://www.xjalt.gov.cn/sjalt/dataalt.html, accessed on 17 November 2021) stated that the total cropland area was 3.84 million mu (0.63 million acres), with oil crops, food crops, and pasture being the main crop types. There was 3.16 million livestock in the region, with goats and sheep, cattle, and horses accounting for 74.0%, 19.6%, and 4.2% of the total, respectively. The regional population and croplands are concentrated mainly on the floodplains of the Irtysh and Ulungur rivers. The population increased by 4.2% between 2007 and 2016, with a 2014 urbanization rate of 56.9% in the Chinese Altay Prefecture. The average water availability (including surface water and groundwater) and consumption during the period 2007–2016 were 111.9 × 108 and 36.7 × 108 m3, respectively, but there were significant interannual fluctuations in water availability.

2.2. Data Resources and Methods

For this study, we used a combination of meteorological, hydrological, cryospheric, and socio-economic data. We used daily air temperature and precipitation measurements, collected between 1961 and 2015, from seven national meteorological stations located on the southern edge of the Altai Mountains that were operated by the China Meteorological Administration (CMA). In the data processing process, the monthly average or annual average temperatures are obtained by the arithmetic average, but the monthly and annual precipitation are obtained by summing daily precipitation. Monthly discharge measurements spanning the period 1957–2015 were obtained from two national hydrological stations, i.e., Kuwei station in the headwaters of the Irtysh River Basin and Kelatashi station in the western part of the SAM. The monthly water level of Ulungur Lake between 1992 and 2016 was obtained from the Hydrology Reconnaissance Bureau (HRB) of Altay Prefecture, China. The locations of the meteorological and hydrological stations used in this study are shown in Figure 1 and Table 1.
The cryospheric data included the observations of snow cover, SFG, river ice, and glaciers. The daily snow thickness and SFG depth during the cold season (October–April), snow cover and SFG durations, and soil temperature at 40-cm depth were monitored synchronously with the weather conditions by CMA. The timing of river ice formation and breakup was observed by HRB during the period 1981–2013, with the river ice thickness measured every 10 days. The glacier information was derived mainly from the First and Second Chinese Glacier Inventories, which were completed in the 1960s and 2000s, respectively.
The socio-economic datasets were obtained from the Yearbook of Social and Economic Statistics (YSEC) from Xinjiang Uygur Autonomous Region of China, Water Resources Bulletin (WRB) of Xinjiang Uygur Autonomous Region of China, and the Annual Economic Report (AER) of Chinese Altay Prefecture (http://www.xjalt.gov.cn/sjalt/dataalt.html, accessed on 17 November 2021). The population and demographic composition, and regional gross domestic product (GDP) between 2007 and 2016 were derived primarily from the YSECs, and the water resources availability and consumption date for the same period were obtained from the WRBs. The hydropower production and energy consumption, and agricultural planting structure between 2017 and 2019, were obtained from the AERs.
In the data processing process, the monthly average or annual average temperatures are obtained by the arithmetic average of daily average data, but the monthly and annual precipitation are obtained by summing daily precipitation.

3. Results

3.1. Climate Change in the SAM

Air temperature and precipitation dominate cryospheric changes, highlighting the necessity to conduct climate change research in the SAM [20]. The mean annual air temperature and precipitation were 3.83 °C and 175.7 mm, respectively, during the period 1961–2015 in the SAM. The coldest and warmest monthly air temperatures were −17.42 °C in January and 21.74 °C in July, respectively. The maximum and minimum monthly precipitation were 24.5 mm in August and 6.8 mm in February, respectively, and the average solid precipitation (November–March) was 56.7 mm. Precipitation increased significantly at the higher elevations, with the rates varying between 25 and 30 mm hm−1 in the SAM based on datasets that spanned 1980–2015 from the Fuyun meteorological station (806 m a.s.l.), and the Koktokay (1200 m a.s.l.) and Kuwei (1374 m a.s.l.) national hydrological stations. The temperature lapse rate in the SAM was −0.38 °C hm−1 [33]. Increased solid precipitation resulted in more snowfall in the high mountains, with snowfall events even occurring from September to June on areas where the altitude exceeded 2500 m.
The monthly air temperature (°C) and precipitation (%) anomalies observed by CMA also illustrated increasing air temperature and precipitation trends during the period 1961–2015 in the SAM (Figure 2). Abrupt air temperature changes occurred mainly in the late 1980s and early 1990s, with the largest variations occurring in March and April (Figure 2a), and these variations had a major impact on the spring precipitation pattern and snowmelt processes. The precipitation anomaly (Figure 2b) indicated that there was a significant increase in winter precipitation as well as an increase in the frequency of extreme precipitation events. For example, 118 mm of snowfall accumulated in the SAM between November 2009 and January 2010 due to a rare snowstorm in the SAM (Figure 3a).

3.2. Observed Cryospheric Changes

Snow cover, frozen ground (SFG and permafrost), river ice, and mountain glaciers are the typical cryospheric elements in the SAM. Snow cover is the most important cryospheric element, and the most typical landform from November to March in the plain areas, and from October to May in the high-mountain areas [33,43]. Frozen ground develops poleward and from low to high elevation, transitioning from the SFG regions along the mountainous edge to the high-mountain (>2000 m a.s.l.) permafrost regions. River ice is particularly important in the SAM because all of the rivers have seasonal ice cover. The SAM glaciers are primarily located in the Tavan Bogd, which spans northwestern China, eastern Kazakhstan, western Mongolia, and Russia (Figure 1). The cryosphere has been experiencing ongoing rapid changes in the SAM caused by global warming. The snow cover and SFG variations between 1961 and 2015, and river ice variations between 1981 and 2013 are shown in Figure 3.

3.2.1. Increasing Snow Cover

Increases in snow thickness and duration from low to high elevation have occurred after periods of increased precipitation and colder meteorological conditions in the SAM [43]. For example, snow cover has remained until late June and the snow duration has exceeded 250 days in the headwaters of the Irtysh Basin [33]. The average maximum snow thickness and duration observed by CMA were 27.3 cm and 116 days, respectively, on the edge of the SAM. Long-term observations (1961–2015) exhibited positive snow thickness and duration trends in the SAM, with a positive correlation between snow duration and maximum snow thickness (Figure 3a). There was a slight decline in the annual maximum snow thickness before the 1980s, with sharp increases since the late 1980s. The maximum snow depth peaked near 75 cm in 2010. The maximum snow thickness interannual anomaly is currently exhibiting ongoing growth.
Snow cover accumulates solid precipitation that is influenced by both precipitation and temperature [20]. The observed changes in snow thickness and duration have been caused mainly by shifts in accumulation and ablation that are related to snowfall and melt, respectively. Higher winter and spring air temperatures will result in a shift from solid to liquid precipitation as well as more frequent and intense melting [18]. However, in the SAM, the temperature increase caused by global warming has not been sufficient to produce either a solid to liquid shift in the precipitation pattern or increased snowmelt in winter due to the extreme cold, with an average air temperature of −15.5 °C and an air temperature still below 0 °C despite the ongoing warming in the SAM. The increase in winter precipitation dominated the 1961–2015 changes in the snow cover regime in the SAM.

3.2.2. Shrinking SFG

The currently available observations from frozen ground sites are located mainly in the SFG regions, and there are no permafrost observation sites in the SAM. Therefore, only the SFG change was investigated based on the CMA-derived dataset. Across the SAM, the SFG has followed a declining trend due to the continuous temperature rise. The mean SFG duration was 151 days, with a declining trend observed during the period 1961–2015 (Figure 3b). There was a 33-day decrease from 169 to 136 days during the study period that we attribute mainly to the ground thawing earlier. The initial ground freezing occurred slightly later, by about 5 days, whereas ground thawing occurred about 28 days sooner. This result was different from that found on Qinghai–Tibet Plateau during the period 1967–1997, where the lag in the initial ground freezing induced mainly a reduction in the freezing duration [44]. Obvious declines in the maximum freezing depth were also observed. However, the maximum freezing depth was stable before the 1980s, declined significantly from the late 1980s to the 1990s, and then increased in the 2000s and 2010s (Figure 3b). The mean maximum SFG freezing depth was 119 cm, varying from 82 cm in 1998, to 161 cm in 1984, and the mean shrinking rate was 5.8 cm/10 yr.
The warming trends in the monthly soil temperature are shown in Figure 4. There was an increase in soil temperature in all months, but the increase was most dramatic in March and April. The universal abrupt rise of soil temperature mainly occurred in the late 1990s except for in winter, whereas the maximum freezing depth began to increase. Another study indicated that snow cover was the dominant factor governing the SFG regime, whereas air temperature and snow cover were the primary and secondary factors controlling SFG degradation during the 1961–2015 study period on the edge of the Altai Mountains [25].

3.2.3. Thinning River Ice

River ice can have major effects on hydropower generation, winter transportation, flooding, ecology, channel morphology, and the design and construction of infrastructure along a given river [45]. Our field investigations and observations in the SAM indicated that river ice generally began to appear in mid-to-late November, with the rivers being fully covered by mid-December. The maximum river ice thickness was attained in mid-January, remained stable until mid-March, and then began to melt (and even collapse in some instances). River ice disappeared completely by mid-to-late April. These river ice changes affected mainly hydropower generation, spring snowmelt flooding, and bridge safety.
The observed river ice changes, which are recorded in the maximum freezing thickness and duration at Kuwei hydrological station over the period 1980–2013, are shown in Figure 3c. The average maximum freezing thickness and average river ice duration were 93.0 cm and 134.0 days, respectively, with the river ice exhibiting a significant negative trend. Compared with the 1980s, the average river ice duration and maximum freezing thickness declined by 16.5 days and 30.0 cm for the 2000s. This period coincided with a 1.3 °C increase in the average air temperature from 3.0 to 4.3 °C. We obtained a mean decrease in river ice duration of 12.7 days for every rise in air temperature of 1 °C, which was twice the global mean of 6.10 ± 0.08 days per 1 °C rise in air temperature [46]. The SAM region is located on the southern edge of the stable river ice region, such that the river ice is more sensitive to climate change. It is therefore likely that the river ice may become unstable in the future due to ongoing global warming.

3.2.4. Ongoing Shrinkage and Disappearance of Mountain Glaciers

The mountain glaciers in the SAM have undergone rapid mass loss over recent decades, and this continues today. The number of mountain glaciers in the SAM decreased from 403 to 271 between the First and Second Chinese Glacier Inventories in the 1960s and 2000s, respectively, with 32.75% of the SAM mountain glaciers disappearing. The regional glacier area also decreased from 289.29 to 185.77 km2, which equates to a loss in the glacial area of 35.78%. The simulation results from a mass-balance model that was forced by the outputs of a regional climate model indicated that the mean specific mass balance for the entire Altai Mountain Range was about −0.69 m water equivalent (w.e.) yr−1 during the period 1990–2011, with about 81.3% of these glaciers experiencing a negative net mass balance [47]. The mass balance rates in the SAM, which were based on topographic maps (1959), the SRTM DEM (2000), and ASTER stereo images (2008), were −0.43 ± 0.02 and −0.54 ± 0.13 m w.e. yr−1 during the periods 1959–1999 and 1999–2008, respectively, which indicated that the mountain glaciers experienced continued and accelerating shrinkage over this 50-year timeframe, with 7.06 ± 0.03 km3 of total ice loss [48]. Increased mass accumulation due to additional snowfall has not slowed this rapid glacial loss, with the rise in air temperature being the dominant factor controlling glacial retreat in the SAM.
The cryosphere in the SAM has generally been shrinking, and this trend is expected to continue. The Representative Concentration Pathway (RCP) 4.5 climate scenario suggests that the glacial area in the Altai Mountains region will shrink by 26 ± 10% by 2100, whereas the RCP 8.5 scenario suggests that it will shrink by 60 ± 15% [49]. The globally averaged river ice duration for the period 2080–2100 declines by 16.7 days relative to the period 2009–2029 under the RCP 8.5 scenario, whereas it declines by 7.3 days under the RCP 4.5 scenario; the river ice duration in the SAM is predicted to shorten by more than 50 days [46]. An assessment of the COP21 climate change targets indicated that the global permafrost area would eventually experience a >40% reduction if the climate stabilized at 2 °C above pre-industrial levels, whereas stabilizing the climate at 1.5 °C would save approximately 2 million km2 of permafrost relative to the 2 °C threshold [50]. The permafrost in the SAM is already on the verge of disappearance. Global snow cover (depth or mass) is projected to decline by another 25% (10% to 40%) in the near future (2031–2050), regardless of which RCP climate scenario is applied [51]. Reductions of up to 80% (50% to 90%) are expected under RCP 8.5, 50% (30% to 70%) under RCP 4.5, and 30% (10% to 40%) under RCP 2.6 by the end of the century (2081–2100). Snow cover will also shrink across the SAM for different increases in the global mean temperature in the future. All of the climate scenarios point to a reduction of the cryosphere in the Altai Mountains in the future.

4. Discussion

Cryospheric functions and services, including water supply and hydrological regulation, will change dramatically under a warmer climate, with changes in meltwater availability having significant cascading effects on water management, such as hydropower generation, agriculture, livestock and fisheries, and the environment of tail-end lakes. Furthermore, cryospheric hazards, such as snow droughts and snowmelt flooding, will expose the population in the SAM to additional risk. In this part, we will assess the opportunities and challenges that these cryospheric changes pose to the regional water resource and human system in the SAM.

4.1. Hydrological Processes and Water Availability

Snowmelt is the dominant factor in SAM hydrological processes. Hydrograph separation via stable isotope technology in the headwaters of the Irtysh River Basin highlighted that the contribution of snowmelt to runoff reached 58.1% during the spring snowmelt period, whereas rainfall, snowmelt, and groundwater accounted for 49.1%, 36.9%, and 14.0%, respectively, of the annual runoff [33]. Global warming has made these seasonal runoff distributions highly sensitive to changes in snowpack accumulation and melting in snowmelt-fed river basins [52], and this increased sensitivity is also observed in the SAM (Figure 5). Two typical SAM basins were analyzed to investigate the hydrological effect of cryospheric change: the Kuwei national hydrological station is located in the eastern part of the SAM where there are no glaciers [33,43], whereas the Kelatashi station is located in the western part of the SAM with this river being fed by both snow and glacial meltwater [47].
The observed changes in the monthly runoff distributions between 1957 and 2015 at Kuwei and Kelatashi are shown in Figure 5. The maximum monthly streamflow occurred in June at both stations, with the long-term average May–July runoff accounting for 70.49% and 59.19% of the annual runoff at Kuwei and Kelatashi, respectively. The snow- and glacier-fed runoff distribution was more uniform than the runoff fed by only snowmelt because snowmelt only occurred in the spring and glacier recharge occurred mainly in the summer. The 1957–2015 cryospheric changes have led to a runoff redistribution that is represented by an increase in April and May discharge percentages, and June and July declines in the SAM (Figure 5). The earlier increase in the water supply will further aggravate the time difference between water supply and demand, which is not conducive to the sustainable and efficient utilization of water resources.
Basins that experience significant reductions in the proportion of precipitation falling as snow may also see a reduction in their annual streamflow [53]. However, despite increased snow cover and an acceleration in glacial melting, there was no significant increase in the annual runoff between 1957 and 2015 in SAM. Variations in the observed monthly streamflow anomalies during the period 1957–2015 at the Kuwei and Kelatashi stations are shown in Figure 6. There was a significant decline in July runoff across the eastern SAM, but a general increase in spring runoff (Figure 6a), although the interannual fluctuations were amplified here by the earlier onset of snowmelt and variable accumulations (Figure 3a). Across the western SAM, runoff in spring increased significantly but then declined slightly in summer and autumn due to the earlier melting of snow cover and accelerated melting of the mountain glaciers (Figure 6b). The contribution of snowmelt will continue to expand for both 2 °C and 4 °C of warming in the SAM [52]. Although water resources have remained relatively stable in the SAM, recent cryospheric changes have led to the redistribution of these water resources, such that continued changes will amplify the challenges currently facing downstream water management.

4.2. Water Management

The SAM is a typical arid to semi-arid region, with hydropower generation in the upstream mountainous areas, agriculture in the midstream and downstream oasis areas, and lake environments in the downstream areas. Fisheries and transboundary water resources management are directly dependent upon alpine water towers. The anthroposphere will need to adapt to future hydrological changes in annual water redistribution caused by earlier snowmelt [54,55], increasing snowmelt contribution rates [52], and decreasing glacial meltwater inputs [49] that are a response to warmer meteorological conditions.

4.2.1. Hydropower

There are four primary hydropower stations in the SAM, with a total capacity of about 336 MW and an annual generating capacity of 1.26 billion KWH, or about 44.7% of the average electricity consumption in 2018. The electricity consumption rates increased by 13.62% and 19.62% in 2018 and 2019, respectively, with higher energy demand in summer than in other seasons. Hydropower production potential is expected to increase in spring and decline in summer due to the earlier snowmelt and reduced water discharge from glaciers, which will further aggravate the imbalance between regional power supply and demand. Moreover, alternative energy sources must be sought to meet the rapidly increasing demands on the current hydropower generating capacity.

4.2.2. Agriculture

Agricultural areas that rely on meltwater for irrigation will be affected by the redistribution of water resources caused by changes in the timing of snow and ice melt [18,52,56,57]. Edible sunflower, which is planted in early May and harvested in late September, is the most important agricultural crop in the SAM. Our field investigations indicate that the Edible sunflower is irrigated nine times during the growing season (May–September), with the highest irrigation demand occurring between late June and early August (Figure 7a). A forward shift in the water distribution caused by an earlier melt (Figure 5) requires an additional increase in the storage capacity of reservoirs to store more meltwater in spring to meet the irrigation demand in summer. Furthermore, the rapid expansion of agricultural acreage in the Ulungur River Basin (Figure 7b) will lead to additional increases in water stress.

4.2.3. Tail-End Lakes and Fisheries

The fate of tail-end lakes in the inland river basins is directly controlled by the upstream inflow and water resource management across the entire basin. For example, the shrinking of the Aral Sea was caused largely by the diversion of water from the Amu Darya and Syr Darya rivers for land irrigation [58,59]. The water level of Ulungur Lake, the tail-end lake of the Ulungur River, has also followed a continuous shrinking trend because of the increase in local irrigation (Figure 7b), and the lake level began to recover since 2009. Ulungur Lake, the largest lake and fishery production center in northern Xinjiang, will be placed into a more precarious position in the future by the increased extraction from the Ulungur River and evaporation under warmer meteorological conditions.

4.2.4. Transboundary Water Resources Management

Water conflicts are becoming increasingly serious because of intensifying demands for water resources around the world [60,61,62]. Climate change is often seen as a sign of regional conflict in the transboundary river basins fed by snow and glacial meltwater, such as the Indus River Basin, because of the sensitivity of cryospheric water resources [63,64,65]. The Altai Mountains are the ‘Water Tower’ of a wider region, where the populations of four nations that live in the highland- to lowland-areas surrounding the Altai Mountains depend on river, stream, and lake water for economic activities. Two key river systems originate in the SAM: the Irtysh River flows from China to Kazakhstan, and the Ulungur River flows from Mongolia to China. Although these three countries have their interests, visions, and sustainable development and strategic plans, transboundary water resource management remains an outstanding issue of concern [66]. The dual pressures of ecological/environmental protection and increasing water demand for economic development will further elevate the potential for severe water shortages. Increasing uncertainties concerning cryospheric water availability related to the impacts of global warming may exacerbate the risk of regional water conflicts in the SAM.

4.3. Snow Drought and Snowmelt Flood

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].

4.3.1. Snowstorms and Snowdrifts

An analysis of the number of affected livestock crop areas and economic losses during the period 1955–2017 indicates that the SAM was at the center of snowstorm activity in Xinjiang Province, with the highest frequency of snowstorms occurring in January [71]. The risk of snowstorms in the SAM is increasing due to the significant increase in winter precipitation (Figure 2b) and subsequent rise in maximum snow thickness (Figure 3a) since the 1960s. Snow drifts are another common type of winter hazard in the SAM, with grid devices installed on both sides of the road in the mountains to mitigate drifting [70]. Continued growth in winter economic activities and their contribution to the annual GDP poses the challenge of determining how to effectively mitigate the impacts of snow hazards, such as snowstorms and drifts, on the winter economy of the SAM.

4.3.2. Snowmelt Flooding

Climate change and increasing economic losses have led to growing global concerns regarding flooding [72,73,74,75,76,77]. The shift from snowfall to rainfall and changes in the timing of snow accumulation and melt under a warmer climate have caused snowmelt floods to possess new characteristics [15,53,78,79], such as fewer ROS floods at lower elevations and more ROS floods at the higher elevations across western North America [10]. Both the frequency and intensity of snowmelt floods across the SAM tended to increase between the 1950s and 2000s [69,70]. However, the impacts of increased snow cover, shrinking river ice, and increased reservoirs on extreme hydrological processes in the SAM require further assessment. Therefore, the National Key Research and Development Program of China approved in 2019 ‘Research on key technologies for monitoring, forecasting and prevention of snowmelt flooding in arid areas’, to develop a comprehensive strategy to mitigate and prevent snowmelt flooding in the SAM.

4.3.3. Snow Droughts

Snowfall influences both flooding and drought due to its role in regulating the hydrological processes in snow-fed watersheds, with lower than normal winter snow accumulation resulting in a hydrological drought by reducing the water availability later in the hydrological year [80,81]. April–June water resources, which are supplied mainly by snowmelt, and annual water availability, are both positively correlated with the maximum snow thickness in the headwaters of the Irtysh River [33]. Interannual fluctuations in the maximum snow thickness were amplified after the early 1990s (Figure 3a), which led to frequent shifts in drought and flooding in the SAM.

4.4. The Role of the Cryosphere in SDGs in the SAM

The cryosphere, an emerging element within Earth system science, interacts strongly with the atmosphere, land, ocean, and lithosphere via physical, chemical, and biological processes, and has a significant impact on humans through the direct transfer and transformation of mass and energy [1,4]. To advance global sustainable development integrating both socio-economic and environmental concepts, the United Nations developed the 2030 Agenda for Sustainable Development in 2015 [17]. This included 17 Sustainable Development Goals (SDGs), and 169 specific targets [82]. Cryospheric changes are projected to pose challenges to livelihoods and other economic activities in mountain regions, including hydropower, agriculture, and tourism, particularly under future warmer climate scenarios [51]. This is likely to make the implementation of sustainable development in mountainous areas much more difficult. Defining a set of functions of the cryosphere, associated risks, and potential adaptive strategies will be required to guide the realization of mountain sustainable development goals [82].
Snow cover is the key parameter that determines the cryospheric function, service, and risk in the SAM, and influences the various hazards and water availability through hydraulic connectivity (Figure 8). Snow drought will lead to a decline in water availability in the mountain regions, which then induces a series of cascading effects on clean energy, agriculture, lake ecology, and fisheries. In contrast, extreme winter snowfall will increase the risk of snowstorms and subsequent spring snowmelt flooding. Meltwater changes that are induced by winter snow accumulation fluctuations (Figure 3a) have resulted in spring snowmelt floods and summer droughts (Figure 6). Cryospheric changes in the SAM directly affect SDG6 (Clean Water and Sanitation), with snowmelt also having a significant role in SDG7 (Affordable and Clean Energy), SDG14 (Life Below Water), and SDG15 (Life on Land), which then induces cascading effects into SDG1 (No Poverty), SDG2 (Zero Hunger), and SDG11 (Sustainable Cities and Communities), highlighting that cryospheric processes can be linked to various components in the regional socio-economic system, such as regulation, society and culture, and habitat. The 2019 Intergovernmental Panel on Climate Change Special Report on Ocean and Cryosphere in a Changing Climate (SROCC) highlighted that integrated water management approaches are needed to sustain clean energy production, agriculture, ecosystems, and drinking water supplies, and raise the potential for water reservoirs to meet the challenge of climate change in high-mountain regions [52]. Optimization of the storage and release of mountain meltwater by increasing the reservoir capacity in the SAM may be an effective way to mitigate the fluctuations in snow drought and flooding caused by interannual cryospheric changes. Transboundary cooperation between China, Kazakhstan, and Mongolia will further support efforts that address the potential risks to water resources in terms of their availability, access, and distribution governance.

5. Conclusions

In this study, we have illustrated the future opportunities and challenges on water resources that the SAM will face as a result of rapid cryospheric changes under a warmer climate. The SAM, which is located in the arid to semi-arid region of central Asia and is strongly influenced by the cryosphere, was selected as the research area to explore historical cryospheric changes and their potential effects on regional water resources and socio-economic environments.
There have been general trends in increased warming and precipitation since the 1960s in the SAM. Both the temperature and precipitation have risen over each year, with winter exhibiting the greatest increases. There has been a general decrease in the extent of the cryosphere, although there has also been an abnormal increase in snow cover. These snow cover variations are represented by increased fluctuations in the maximum snow thickness and stable duration of the snow cover, with the onset of snowmelt occurring earlier. The freezing duration of SFG has followed a declining trend, with an approximate 33-day reduction in its duration and a mean shrinking rate of the annual maximum frozen depth of 5.8 cm/10 yr. Both the duration and maximum thickness of river ice have also decreased rapidly. The average duration and maximum thickness of river ice declined by 16.5 days and 30.0 cm, respectively, from the 1980s to 2000s, and the mean rate of decrease in ice duration, of 12.7 days for every 1 °C increase in air temperature, was twice the global mean. There was also a 32.75% loss in the number of mountain glaciers, with a 35.78% decline in the SAM glacier area between the 1960s and 2000s.
Numerous challenges on water resources related to historical cryospheric changes have been identified in the SAM. Earlier snowmelt caused by rapid spring warming has led to the redistribution of annual surface runoff, which is now characterized by an increase in spring runoff and a decrease in summer runoff, and has further widened the time gap between water supply and demand. Dramatic interannual changes in cryospheric meltwater caused by variations in winter snow accumulation are a key source of risk in the region and may lead to more frequent snow-induced flooding and drought periods. These annual and interannual variations in cryospheric meltwater pose challenges to the hydropower generation, agriculture, livestock, fisheries, and tail-end lake environments.
The potential benefits derived from the cryosphere meltwater represent either a direct or indirect control on the realization of regional SDGs in the SAM, including SDG1, SDG2, SDG6, SDG7, SDG11, SDG14, and SDG15, with snow cover forming the key component of any sustainable environmental protection or socio-economic activity. Further expansion of the regulation capacity of the reservoirs as well as increased international cooperation in transboundary areas, will be important adaptive strategies under a warming climate if we are to meet the challenges presented by cryospheric changes in this region.

Author Contributions

Conceptualization, W.Z. and Y.S.; methodology, W.Z.; writing—original draft preparation, W.Z. and A.C.; writing—review and editing, W.Z. and X.W.; supervision, Y.S.; funding acquisition, W.Z., Y.S., A.C. and X.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded in part by the National Science Foundation of China [41971083], National Key R&D Program of China [2019YFC1510501, 2019YFC1510502] and National Science Foundation of China [41801035, 42071091]. Funding was also provided by State Key Laboratory of Cryospheric Science [SKLCS-ZZ-2022] and the Foundation for Excellent Youth Scholars of Northwest Institute of Eco-Environment and Resources, CAS.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors are sincerely grateful to the anonymous reviewers for their suggestions and feedback, which helped improve the paper significantly.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Map of the study area, with the locations of the meteorological and hydrological stations used in this study, as well as the reservoirs and lakes, cropland, and mountain glaciers indicated. The inset map shows the extent of the Altai Mountains (light brown), the location of the study area (box), and the major rivers in the region.
Figure 1. Map of the study area, with the locations of the meteorological and hydrological stations used in this study, as well as the reservoirs and lakes, cropland, and mountain glaciers indicated. The inset map shows the extent of the Altai Mountains (light brown), the location of the study area (box), and the major rivers in the region.
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Figure 2. Variations in anomalies of (a) monthly air temperature (°C) and (b) precipitation (%) between 1961 and 2015 observed by CMA in the SAM.
Figure 2. Variations in anomalies of (a) monthly air temperature (°C) and (b) precipitation (%) between 1961 and 2015 observed by CMA in the SAM.
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Figure 3. SAM Variations in (a) snow cover and (b) SFG during the period 1961–2015 observed by CMA, and in (c) river ice during the period 1981–2013 observed by the Ministry of Water Resources of the People’s Republic of China.
Figure 3. SAM Variations in (a) snow cover and (b) SFG during the period 1961–2015 observed by CMA, and in (c) river ice during the period 1981–2013 observed by the Ministry of Water Resources of the People’s Republic of China.
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Figure 4. Variations in the monthly soil temperature anomaly (°C) during the period 1961–2015 observed by CMA in the SAM.
Figure 4. Variations in the monthly soil temperature anomaly (°C) during the period 1961–2015 observed by CMA in the SAM.
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Figure 5. Observed changes in the monthly runoff distributions during the periods 1957–2015 at the (a) Kuwei and (b) Kelatashi hydrological stations in the SAM.
Figure 5. Observed changes in the monthly runoff distributions during the periods 1957–2015 at the (a) Kuwei and (b) Kelatashi hydrological stations in the SAM.
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Figure 6. Variations in the observed monthly streamflow anomalies (%) during the period 1957–2015 at the (a) Kuwei and (b) Kelatashi national hydrological stations in the SAM.
Figure 6. Variations in the observed monthly streamflow anomalies (%) during the period 1957–2015 at the (a) Kuwei and (b) Kelatashi national hydrological stations in the SAM.
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Figure 7. (a) Irrigation schedule (timing and frequency) for Edible sunflower (upper blue bars) and hydrograph separation of the various water sources in 2015 in the headwaters of the Irtysh River. (b) Variations in the Ulungur Lake water level during the period 1992–2015 (blue line) and cropland area in the Ulungur River Basin during the period 1980–2015 (red circles).
Figure 7. (a) Irrigation schedule (timing and frequency) for Edible sunflower (upper blue bars) and hydrograph separation of the various water sources in 2015 in the headwaters of the Irtysh River. (b) Variations in the Ulungur Lake water level during the period 1992–2015 (blue line) and cropland area in the Ulungur River Basin during the period 1980–2015 (red circles).
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Figure 8. Direct and cascading effects of cryospheric changes and their correlation with SDGs in the SAM.
Figure 8. Direct and cascading effects of cryospheric changes and their correlation with SDGs in the SAM.
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Table
Table 1. Information of meteorological and hydrological stations used in this study.
Table 1. Information of meteorological and hydrological stations used in this study.
Site TypeStation NameLongitudeLatitudeElevation (m)Data Range
Meteorological stationsHabahe48.05°86.40°532.61961–2015
Jimunai47.43°85.87°984.11961–2015
Buerjin47.70°86.87°473.91961–2015
Fuhai47.12°87.47°500.91961–2015
Altay47.73°88.08°735.31961–2015
Fuyun46.98°89.52°807.51961–2015
Qinghe46.67°90.38°1218.21961–2015
Hydrological stationsKuwei47.36°89.66°1375.01957–2015
Kelatashi48.22°89.45°590.01957–2015
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Zhang, W.; Shen, Y.; Chen, A.; Wu, X. Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China. Appl. Sci. 2022, 12, 1406. https://0-doi-org.brum.beds.ac.uk/10.3390/app12031406

AMA Style

Zhang W, Shen Y, Chen A, Wu X. Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China. Applied Sciences. 2022; 12(3):1406. https://0-doi-org.brum.beds.ac.uk/10.3390/app12031406

Chicago/Turabian Style

Zhang, Wei, Yongping Shen, An’an Chen, and Xuejiao Wu. 2022. "Opportunities and Challenges Arising from Rapid Cryospheric Changes in the Southern Altai Mountains, China" Applied Sciences 12, no. 3: 1406. https://0-doi-org.brum.beds.ac.uk/10.3390/app12031406

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