The Spatiotemporal Regime of Glacier Runoff in Oases Indicates the Potential Climatic Risk in Dryland Areas of China

<jats:p>Abstract. Glaciers continuously affected by climate change are of great concern; their supply and runoff variation tendency under the pressure of increasing populations, especially in dryland areas, should be studied. Due to the difficulty of observing glacier runoff, little attention has been given to establishing high-resolution and long-term series datasets established for glacial runoff. Using the latest dataset using digital elevation models (DEMs) to obtain regional individual glacier mass balance, simulating the spatiotemporal regime of glacier runoff in oases that support almost the entire income in the dryland areas of China (DAC) could be possible. The simulations quantitatively assess glacier runoff, including meltwater runoff and delayed runoff, in each basin of the DAC at a spatial resolution of 100 m from 1961 to 2015, classify glaciers according to the potential climatic risks based on the prediction results. The total glacier runoff in the DAC is (98.52 ± 67.37) × 108 m3, in which the meltwater runoff is (63.43 ± 42.17) × 108 m3, accounting for 64.38 %. Most basins had continuously increasing tendencies of different magnitudes from 1961 to 2015, except for the Shiyang River basin, which reached its peak in approximately 2000. Glacier runoff nurtured nearly 143,939.24 km2 of oasis agricultural areas (OAA) until 2015, while 19 regions with a total population of 14 million were built alongside the oases, where glacier runoff occupies an important place in agricultural, industrial and municipal water consumption. Therefore, providing a long time series of glacier runoff for different river basins is of great significance to the sustainable development of the oasis economy in the arid zones.                         </jats:p>

section_content: warming, the rapid change in the cryosphere and its interactions with the biosphere, lithosphere, hydrosphere, atmosphere, and anthroposphere are increasingly intensified, having especially extensive and profound impacts on hydrology, water resources, ecosystems (Sun et al., 2020; Zhang, Liu, et al., 2019), and the sustainable development of the human economy and society (Lin et al., 2020). 

Field observation is by far the most accurate method used to obtain individual glacier mass balance and was used to establish the first and second glacier catalogs in China in the 1970s and the early 21 st century, respectively (Liu et al., 2015; Sun et al., 2018). Continuous yearly mass balance data for long time series could not be calculated effectively due to the time consumption and high energy consumption of field observations (Brun et al., 2017; Shean et al., 2020). Therefore, the energy balance equation was used to reconstruct the glacier mass balance (Sakai et al., 2015; Yao et al., 2010) based on remote sensing datasets (Hussain et al., 2019) or imagery (Tak & Keshari, 2020), and the snow line was identified to be approximately the same as the equilibrium-line altitude (ELA). Another method used to calculate glacier runoff focuses on establishing the relationship between runoff and air temperature through meteorological station data with the degree-day factor model to better reflect the role of temperature in meltwater (Li et al., 2020; Liu, Zhang, et al., 2019). Semi-distributed hydrological models were also used to estimate the contribution of meltwater runoff to river flow, and similarly, river isotopic studies (Duan et al., 2020; Garee et al., 2017; Zhang, Luo, et al., 2016). However, some limitations were obvious: the relationship between stations and the degree-day factor model was too difficult to establish in large regions, while the energy balance model could be applied in large regions but with low resolution (such as 0. 25 degrees (Sakai et al., 2015) ). Semi-distributed hydrological models semiquantitatively calculated the proportion of meltwater runoff to total runoff without time series. Taking advantage of digital elevation models (DEMs), some studies (Brun et al., 2017; Shean et al., 2020) have published mass balance datasets with high resolution; the former were 30 m based on the single-source Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) inventory (Sakai, 2018), and the latter were accurate to each individual glacier based on the multisource Randolph Inventory (RGI Consortium, 2017), which makes estimating high-resolution glacier runoff data possible. 

https://doi. org/10. 5194/hess-2021-377 Preprint. Discussion started: 22 September 2021 c Author(s) 2021. CC BY 4. 0 License. glaciers was obtained from the Science Data Bank (http://www. sciencedb. cn/dataSet/handle/747) at a spatial resolution of 0. 5° in High Mountain Asia and contained snow-melt and ice-melt degree-day factor distributions. Oases information was obtained from Copernicus Global Land Service (CGLS) LC100 collection 3 at a spatial resolution of 100 m on Google Earth Engine (GEE) (http:/land. copernicus. eu/global/products/lc).

section_content: By using the ratio data of annual precipitation to annual evapotranspiration (aridity index, AI), the DAC was obtained relying on drought zoning supported by the United Environment Programme (UNEP), which erased the range of the Tibetan Plateau, which is discussed separately. There are seven glacier regions around the DAC, including the Qilian Shan, Eastern Kunlun, Western Kunlun, Eastern Tien Shan, Western Tien Shan, Karakoram, and Pamir, which include approximately 42,000 glaciers involving four provinces: Inner Mongolia, Xinjiang, Gansu and Qinghai. The 7 glaciers affect 22 tertiary watersheds in the DAC, including 6 drainage basins which all originated directly from glaciers and across arid and hyper-arid regions (hereafter, AH). 2 river basins were both completely in the arid zone while 11 drainage basins were in both semiarid and arid regions (hereafter, SA). The Datong River above the Hall basin was the single basin entirely in the semiarid zone, and the Qarqan Rivers Basin was across semiarid, arid and hyper-arid zones (hereafter SAH). As Table 1 shows, the area of OAAs in each watershed in the DAC reached a maximum of 21,699. 18 km 2 (Middle Rivers basin), with an average of 6543. 692 km 2, while the precipitation in the DAC reached a maximum of 323. 09 mm (Qinghai Lake Drainage System), with an average of 134. 56 mm, which revealed that runoff in the DAC was extremely important, especially in some basins where runoff originated almost entirely from glaciers. The study area is shown in Fig. 1.
section_name: Study Area

section_content: We used geodetic mass balance estimates in the high-mountain Asia (HMA) between 2000 and 2018 by combining reprocessing ASTER DEMs (hereafter Shean estimation (Shean et al., 2020) ) to simulate high-altitude precipitation. The mass balance, (m), is the sum of accumulation, (m), and ablation, (m), at a yearly time step following Eq. (1): The degree-day factor (DDF) is an important parameter reflecting the amount of ice and snow melt generated by the unit positive accumulated temperature (Kaser et al., 2010; Kraaijenbrink et al., 2017). Previous studies have generally used 2 mm °C-1 d -1 as the DDF for snow melt (Azam et al., 2012; Immerzeel et al., 2015). The spatial variation in the DDF has a great influence on the accuracy of simulating the snow melt process. This paper used the spatial distribution of snow melt data with a resolution of 0. 5° based on a formula built by investigations and observations of 40 different glaciers in the HMA, and the dataset verified the accuracy (Zhang et al., 2006). Considering that the spatial resolution of this paper was 100 m, monthly positive-degree days ( ) were chosen instead of absolute (Braithwaite & Olesen, 1993), and they were the summed positive daily average temperatures. The monthly spatial distribution of ablation,, (m), was calculated by the product of DDF and when the sum of the twelve months was the yearly spatial distribution of ablation,, (m). The accumulation at a daily step depends on temperature, while precipitation is separated into solid (snow, (m)) and liquid (rain) by temperature. The relationship between snowfall and temperature was as follows: the temperature at which all precipitation becomes liquid was assumed to be 4°C, 1 (°C), the actual temperature, (°C) and the daily corrected precipitation,, (m) (Fujita & Nuimura, 2011; Sakai et al., 2015) following Eq. (2):

The maximum rainfall height and maximum elevation of glaciers around the DAC were obtained from RGI v6. 0 and used as the basis for high-altitude precipitation estimation by calculating the vertical precipitation gradient (Immerzeel et al., 2015). 

We used the Shean estimation to optimize the precipitation gradient per glacier. At each glacier affecting the DAC, the corrected precipitation,, (m), was calculated as a function of original precipitation data from APHRODITE_MA_v1101_EXR1,, (m), the vertical precipitation gradient, (% m -1 ), at a daily time step with the maximum precipitation altitude, (m), maximum elevation, (m), and terrain elevation, (m), for each individual glacier, using the following Eq. (3) and Eq. ( 4 ): Each glacier from seven regions of glaciers around the arid area of China was simulated, and then the vertical precipitation gradients that were generated were interpolated to obtain a wide range of vertical precipitation gradients representing the change in precipitation with altitude. By using the nearest neighbor algorithm for aggregating (López-Granados et al., 2005), the vertical precipitation gradient at a spatial resolution of 0. 25° was obtained.
section_name: Reconciling High-altitude Precipitation

section_content: Glacier runoff is defined as the flow of meltwater from a glacier through ice, in and under ice and then into a river channel (Qin et al., 2021). Based on the definition of glacier runoff, the runoff includes two parts. One is the precipitation on glaciers stored in the non-melting season and released in the melting season, which is called delayed runoff (Kaser et al., 2010; Pritchard, 2019; Shean et al., 2020). The monthly delayed runoff during the ablation seasons, ∆ (m), was calculated by the difference in the proportion of total annual corrected precipitation,, (m), allocated to the ablation season runoff, (), according to the proportion of monthly, and yearly,. The ablation season was defined as all months in which the monthly temperature was above. was calculated as the following Eq. ( 5 ):

When the temperature was above, freezing did not occur on the surfaces of the glaciers, and precipitation occurred as liquid rainfall on the glacier that flowed out of the glacier systems in the form of runoff. If the runoff allocated in the month, (), was more than the corrected precipitation in the month,, (), delayed runoff, ∆ (m), occurred while the glaciers stored the solid precipitation in the accumulation seasons and released it in the ablation seasons following Eq. ( 6 ):

The delayed runoff calculation method was proposed by Kaser et al. (Kaser et al., 2010) and improved by Pritchard (Pritchard, 2019) for regional calculations. This method, where the precipitation dataset is the most important component, provides the possibility of calculating the monthly delayed runoff for a long time series and on a regional scale. 

Based on the verification precipitation data (V2. (Jie & Kun, 2016) ) and had the best applicability in Tien Shan of China. Han and Zhou (2012) found that the correlation coefficient between APHRODITE and ground gauge observed precipitation was more than 0. 9, and APHRODITE explained spatial heterogeneity better (Yatagai et al., 2014) because it considered topography in the process of spatial interpolation (Yang et al., 2014). Li et al. showed that APHRODITE reflected the spatial and temporal distribution characteristics of precipitation in inland river basins and then compensated for the shortage of spatial precipitation data in the study area (Li et al., 2014). information-using-artificial) on the Tibetan Plateau and its surrounding areas and found that APHRODITE performed best with the longest time span (> 50 years) and had a higher R 2 with a lower MAE and RMSE than that of CHIRPS and PERSIANN-CDR (Tan et al., 2020). APHRODITE had the best performance in the DAC, including the Heihe River basin (Tang et al., 2017), Qinghai Lake drainage system (Zhang et al., 2014), Xinjiang (Wang, Sun, et al., 2020), upper reaches of the Yellow River (Guan et al., 2020) and other mountainous areas (Mishra et al., 2019). Therefore, we used APHRODITE, which has been verified many times and is one of the most accurate precipitation records in the DAC, in this paper. 

The precipitation was corrected by the Shean estimation for high-altitude precipitation gradients in this paper for the glaciers affecting the DAC. Reconciling high-altitude precipitation and then recycling the former method to calculate the delayed runoff at a one-month time step for each glacier basin would be more persuasive without relying on the original products (Wortmann et al., 2018). Sakai et al. (Sakai et al., 2015) corrected the on-glacier precipitation by assuming that the average mass balance from 1979 to 2007 was equal to 0 at the ELA, referring to the median elevations of glaciers larger than 1 km 2 and the areaweighted average in each 0. 5 grid using the glacier inventory (GGI) in High Mountain Asia on the basis of APHRODITE. The ELA is called the L-elevation, and the on-glacier precipitation was adjusted by one ratio at a resolution of 0. 5°, while the ratios in the seven glacier regions affecting the DAC were 1-3 (Qilian Shan), 0-7 (Eastern Tien Shan), 0-4 (Western Tien Shan), 3- The second type of glacier runoff was runoff from melting glaciers called excess meltwater runoff. Pritchard (Pritchard, 2019) calculated the excess flow of meltwater provided to the HMA river basins through a regional geodetic study of glacier volume changes from 2000 to 2016 by Brun (Brun et al., 2017), namely, the Brun estimation. Unlike delayed runoff due to precipitation, excess meltwater runoff is based on measured mass balance changes in glaciers rather than on average climate, so this runoff component is also called an unbalanced component, while the runoff caused by precipitation is called a balanced component (Rounce, Hock, et al., 2020; Rounce, Khurana, et al., 2020). With the Brun estimation, due to the time limit from 2000 to 2016, the contribution of unbalanced components to water input at the start of the 21 st century compared with the balance components such as long-term precipitation could be obtained. Brun estimated that the excess water in the catchments controlled by the HMA, including the Yangtze, Mekong, Salween, Brahmaputra, Ganges, Indus, Amu Darya, Tarim, Syr Darya, Ili, and Inner Tibetan Plateau, was (-14. 7 ± 3. 2) km 3 a -1 equivalent during 2000-2016 (Brun et al., 2017), which was approximately 70% of the balance component calculated above. The regional basin-scale imbalance uncertainty ranged from 26% to 77%. The Shean estimation estimated that the total excess water flow for all of the river basins originating from 2000 to 2018 was (-22. 71 ± 3. 01) Gt per year (Shean et al., 2020), where the additional basins considered included the Yellow River, Inner Tibetan Plateau Extended and Irrawaddy. The basin-scale imbalance uncertainty ranged from 12% to 52%. In conclusion, the yearly total glacier runoff, (m), was calculated by the following Eq. ( 7 ): than the mean meltwater in a certain period of time (Pritchard, 2019; Shean et al., 2020). Time series data have unique advantages for studying the change trend and can also more clearly observe the change in meltwater within any required time period. 

We provide a method to predict future total glacier runoff relying on temperature, precipitation and elevation data, as both of the goals of the Representative Concentration Pathway (RCP) and the Coupled Model Intercomparison Project (CMIP) are keeping the increase in temperature within a certain range. in this paper was obtained by interpolation using the mass balance algorithm and geostatistics method. Glacier runoff was divided into delayed runoff and excess meltwater runoff.
section_name: Glacier Runoff

section_content: According to the individual glacier uncertainty (including random error and systematic error) calculated in the Shean estimation, the uncertainty range of glacier mass balance changes could be obtained. The maximum and minimum values of a single mass balance were calculated through the uncertainty interval. Referring to the provided by the RGI and referred to previous studies and reasonable inference of in the RGI, the of each single glacier around the DAC was obtained by geographical simulation. After using the DDF model and the glacier mass balance model, the corrected precipitation and meltwater were obtained, which were the bases of delayed runoff and meltwater runoff, respectively. The uncertainty of glacier runoff was the precipitation gradient in the range obtained from the uncertainty of glacier mass balance
section_name: Uncertainty Analysis

section_content: The Mann-Kendall test (MK test) was recommended as an effective method to distinguish whether a natural process is in a natural fluctuation or has a definite trend of change especially for hydro-meteorological data with non-normal distribution (Mann, 1945; Kendall, 1975). Given a time series () of length with statistical hypothesis that the unadjusted data series was an independent random variable with the same distribution composed of elements. represented the cumulative number of () was greater than (), 1 ≤ ≤, and the statistic was defined as following Eq. ( 8 ):

The mean ( ) and variance ( ) was calculated by the following Eq. ( 9 ) and Eq. ( 10 ):

After standardizing, and can be calculated as following Eq. ( 11 ) and Eq. ( 12 ):

formed a curve and formed a curve, while the intersection point of the former two curves in the confidence interval was determined as the turning point. While > 0, it indicated an increasing trend of the sequence, on the contrary, it indicated a declining trend while < 0.
section_name: Trend Analysis

section_name: Results

section_content: In this paper, we used the Shean estimation to correct the high-altitude precipitation gradient and the DDF model to calculate the total glacier runoff around the DAC during 1961-2015 with a spatial resolution of 100 m, and we overcame the difficulty of large-scale geodetic mass balance assessment. Glacier runoff included delayed runoff that was stored rainfall in the cold seasons and released rainfall in the ablation seasons, while meltwater runoff was caused by glacier mass balance, which was also called excessive meltwater runoff or the imbalanced part of glacial runoff, as shown in Fig. 3. The average glacier runoff in the DAC for the period was (98. 52 ± 67. 37) × 10 8 m 3, where the meltwater runoff accounted for 64. 71%. Total glacier runoff had an increasing trend after the 1970s that was significant after the 1990s, with a confidence of 95% in the whole study area. Except for the Datong River above Hall, Heihe River basin and Shiyang River basin, the runoff of the other basins showed continuous increasing trends in the past 50 years, where the times of arrival of significant increase were different. Trends in the Ebinur Lake Drainage System and Kai-kong River basin were significant after the 2000s, the Hotan River basin and Kashgar River basin were significant after the 1980s, and the Qinghai Lake Drainage System, Shule River basin and Aksu River basin showed gradual increasing trends with no significance until 2015. The amount of glacier runoff in the Datong River above Hall began to decrease after the 1990s, and in the Heihe River basin, it decreased after 1995 with no significance according to the Mann-Kendall (MK) test. Glacier runoff in the Shiyang River basin began to decline in 2000 and even showed a significant declining trend in approximately 2010, which was consistent with previous studies (Zhang et al., 2015). The time series of delayed runoff and meltwater runoff for all basins were illustrated in Extended Data Fig. 1, 2 and 3.
section_name: Glacier Runoff during 1961-2015

section_content: Some studies (Barnett et al., 2005; Hussain et al., 2019; Li et al., 2018; Wang et al., 2015; Wu et al., 2018; Yang et al., 2015; Ye et al., 2017) simulated glacial runoff in the DAC by qualitative or semi-quantitative methods or by using models. This paper used these results to verify our estimations, although there were no data in any river basins or there were only trend studies in any river basins, as shown in Fig. 4. 

The upstream inflow of the Heihe River was mainly influenced by annual precipitation and glacier meltwater runoff (Jin et al., 2015). The percentage of glacier runoff recharge calculated by the DDF model was between 5% and 15% based on the first Chinese inventory and monthly precipitation and temperature data from the National Meteorological Centre (Gao et al., 2010). 

Wang et al. used the standardized streamflow index (SSI) and standardized precipitation evapotranspiration index (SPEI) to estimate that the percentage of glacier runoff recharge was 5. 2%. Obtaining the glacier runoff recharge by comparing observations of the Yingluoxia hydrological station out of the mountain and glacier runoff, the estimation in this paper was (8. 75 ± 5. 83) %, which was in line with previous studies from 2004 to 2015. 

In the Shiyang River basin, a previous study estimated that the glacier runoff was 0. 61 × 10 8 m 3 from 1961 to 2006 (Gao et al., 2010), while our estimation was (0. 31 ± 0. 16) × 10 8 m 3, which was lower than the former. The peak glacier runoff in the Shiyang River basin occurred in the early 21st century where the proportion of meltwater runoff was close to 100% (Zhang et al., 2015). According to the MK test in this paper, the turning point of meltwater runoff in the Shiyang River basin appeared in 2000, and the meltwater runoff in the Shiyang River basin began to decline in 2000. 

The Changmabao hydrological station stands out of the mountain pass in the Shule River. Li et al. calculated that glacier runoff in the Shule River basin accounted for 30. 5% of the total runoff (Li et al., 2019). The average runoff growth rate of the Changmabao hydrological station in each decade from 1960 to 2015 was 1. 075 × 10 8 m 3 (10a) -1 according to Li's calculation and 0. 91 × 10 8 m 3 (10a) -1 according to Yang's calculation (Yang et al., 2017). In comparison, we found that the increase in glacier runoff in the Shule River basin was (0. 66 ± 0. 56) × 10 8 m 3 (10a) Using hydrological datas from Ulurawati station and Tongguzilok station in the Hotan River, the MK test showed that the runoff of the Hotan River increased at a rate of 0. 084 × 10 8 m 3 a -1 from 1960 to 2016 (Liu, Long, et al., 2019). Based on APHRODITE, this paper found that the average rainfall in the Hotan River basin from 1961 to 2015 was 78. 82 mm with no obvious change. Meanwhile, the growth rate of glacier runoff calculated in this paper was (0. 078 ± 0. 059) × 10 8 m 3 a -1, which was similar. 

Based on the monthly runoff observation data and daily meteorological data of the Weigan River basin during 1960-2013, Qin et al. studied the runoff variation of the Weigan River basin in the last 54 years and reported a value of 1. 8× 10 8 m 3 (10a) -1, of which approximately 75% was caused by glacier meltwater (Qin et al., 2016). We calculated that the growth rate of total glacier runoff in the Weigan River basin during 1961-2015 was (0. 911 ± 0. 671) × 10 8 m 3 (10a) -1. A similar calculation found that the average glacier runoff in the Weigan River basin was 16. 66 × 10 8 m 3, while our estimate was (12. 69 ± 11. 19) × 10 8 m 3 (Duan et al., 2010). Glacier runoff in the Ili River basin was calculated to be 37. 18 × 10 8 m 3 (Li et al., 2010), while there was a prior different result 26. 14 × 10 8 m 3 (Liu, 1999; Yang et al., 1987). On the basis of the Soil Water and Assessment Tool (SWAT), glacier runoff in Ili River basin were simulated to be 8. 4 × 10 8 during 1966-1975 and 6. 5 × 10 8 m 3 during 2000-2008 (Xu et al., 2015). 

The glacier runoff calculated in this paper was (9. 16 ± 7. 33) × 10 8 m 3 from 1966 to 1975 and (9. 91 ± 7. 83) × 10 8 m 3 from 2000 to 2008, which were in line with estimations by SWAT (Xu et al., 2015). 

Using 1961 -1986 and 1987 -2000, respectively. Su et al. (2016) ) and Mardan et al. (2016) obtained a value of 14. 60 × 10 8 m 3 for the mountainous Ebinur Drainage System in the 1980s, and we estimated that the recharge of glacier runoff was (25. 19 ± 13. 53)%, which was in line with 24. 4% of Wang et al. (2019). 

Runoff changes in the Hami Basin (including the Toudaogou Sub-Basin, Guxiang Sub-Basin, and Yushugou Sub-Basin) originating in Eastern Tien Shan from 1979 to 2007 were found that in the Guxiang Sub-Basin and Sub-Yushugou Basin with glaciers were relatively small (Wang et al., 2015), which was consistent with the trend of meltwater runoff in this paper. During noted that temperature had a greater effect on runoff, with a correlation coefficient of 0. 6**, which was similar to the increase in meltwater runoff caused by the accelerated melting of glaciers due to the increased temperature. 

Our results were consistent with those of most studies. However, there was a large difference between the runoff of previous Based on the time series of glacier runoff, linear regression was used to predict the runoff of each glacier in DAC in the next decade as shown in Fig. 5. The Hotan River Basin, Yarkand River Basin and Ili River Basin in Xinjiang Province contained more than 2,000 glaciers according to RGI. Glaciers larger than 1 km 2 were more stable in the face of potential climate change risks while the number of glaciers larger than 1 km 2 was strongly consistent with the total number of glaciers contained in the basin. In the next ten years, the runoff of most basins would continue to increase, including the Qinghai Lake Drainage System, Eastern Rivers Basin, Turpan Basin and Eastern Qaidam Basin. Linking "Reach the peak soon" and "Decrease continuously", the Hotan River Basin, and Kashgar River Basin and Kriya Rivers Basin where delayed runoff accounted for larger glacier
section_name: Glacier Runoff validation

section_name: Discussion

section_content: Some glaciology studies believed that two maximum rainfall heights could appear on one high mountain. For example, the Chinese Academy of Sciences (CAS) established eight rainfall observation points in the middle part of Tien Shan in 1959 and observed that maximum rainfall heights occurred at two altitudes, 1850 m and 5339 m (Zhang, Tuerxunbai, et al., 2019; Zhao et al., 2011). The same institute placed observation points in western Tien Shan in 1978 and found that the first maximum rainfall height was 2400 m, and the second was 3200 m (Kou & Su, 1981). A study on the change in precipitation with altitude in the Qilian Shan showed that the precipitation in coteau presented an "S" type distribution with increasing altitude (Tang, 1985). The second maximum rainfall height was believed to exist by studies on Tien Shan, North Slope of Karakoram, which is located in the alpine glacier region (Shen & Liang, 2006). 

Table 2. and used in this paper. in Eastern Kunlun and Western Kunlun were speculated by five other regions that had references about maximum rainfall height. refers to the average of the maximum height of each glacier in regions of RGI 6. 0.
section_name: Precipitation Correction at High-altitudes

section_name: Region

section_content: Qilian Shan 4200 (et al., 2018; Wang et al., 2009 ) 5500

Eastern Tien Shan 3000 (Zhang, Tuerxunbai, et al., 2019 ) 5000

Western Tien Shan 3000 (Zhang, Tuerxunbai, et al., 2019 ) 6000

Eastern Kunlun 4500 6500

Western Kunlun 4000 6500

Karakoram 2500 (Immerzeel et al., 2012 ) 7500

Pamir 3000 (Hewitt, 2007 ) 6500

However, other meteorological studies believed that there was only one maximum rainfall height on one high mountain because when the elevation was above the maximum rainfall height, the airflow continued to rise, but the water vapor rapidly decreased and the precipitation could not increase again generally. Some research (Immerzeel et al., 2015) took the maximum rainfall height as the reference height and believed that the average maximum rainfall height in the Indus River basin was 2500 m when calculating the precipitation on the glacier (Hewitt, 2007; Immerzeel, et al., 2012). Putkonen ( 2004 ) calculated that the maximum rainfall height on the Southern Slope of the Himalayas was approximately 3000 m, while a subsequent calculated that the maximum rainfall height zone on the July 1 glacier of the Qilian Shan was located at 4500-4700 m (Wang et al., 2009). 

There has always been controversy over whether there is one or two maximum altitudes in the mountains. Even in the same region, there are different results due to the limitations of the discipline, purpose, method, time or initial conditions of the study. Zhao et al. (2011) thought there was only a maximum rainfall height in the Northern Slope of Tien Shan, and a subsequent study which was by dividing the elevation zones by 100 m using TRMM, found that rainfall in Tien Shan peaked at an annual level of 3500 m even though zones were divided into different geomorphic units (Bai et al., 2017). The results of Bai et al. (2017) were different from those of the CAS in 1959 (3500 m vs. 1850 m and 5339 m). Additionally, observed at Gongga Shan, Zhang found that there were two maximum rainfall heights, one at 3500-4000 m and the other at 5000 m (Zhang, 2012). However, Thomas observed that there was only one maximum rainfall height at Gongga Shan, which existed at 2900-3200 m (Thomas, 1997). 

The maximum rainfall height was related to the data. In the Junggar Basin, APHRODITE showed a maximum rainfall height at 4200 m, while IMAGE showed a maximum height at 2600 m. The two maximum rainfall heights of ITPCAS were at 2810 m and 4260 m. PERSIANN and TRMM showed two maximum rainfall heights, which were both at 2600 m and 4200 m. In the Turpan Basin and Hami Basin, APHRODITE, TRMM and ITPCAS all showed two maximum rainfall heights, at 2740 m and 3800 m. There were two precipitation heights of APHRODITE in the Northern Tarim Basin: 2400-3100 m and 3600-4500 m. However, there was only one maximum rainfall height using IMAGE, which was at 4000-4800 m (Zhang, 2020). 

The maximum rainfall height was also related to the season. Previous research divided Xinjiang into different altitude zones according to meteorological stations' elevations, obtaining the regional variation characteristics of precipitation change with changing altitude; specifically, that in summer was 3900-4200 m, that in autumn was 3000-4000 m, and that in winter was less 1900-2300 m, that in winter would be 900-1300 m, and the average rainfall height was approximately 3000 m (Zhang, Tuerxunbai, et al., 2019). 

Fog, dew, frost and other weather phenomena are also known as horizontal precipitation, which can be seen year round in mountainous areas, especially at elevations greater than 3500 m. After condensation, this water vapor could be accepted only by the underlying surface but could not be captured by the common rain gauges commonly used for meteorological observations. Whether a rain gauge records precipitation in the high mountains correctly or not directly affects the correction of precipitation in mountainous areas. In this paper, was calculated according to the regional average, so this paper used as the standard for calculation. Bothe the and the are shown in Table 2.
section_name: 𝑯𝑯 𝒎𝒎𝒎𝒎𝒎𝒎 𝑯𝑯 𝒎𝒎𝒎𝒎𝒎𝒎

section_content: Our estimation revealed a strong heterogeneity of the median precipitation gradient in glaciers near the DAC, as shown in Fig
section_name: Distribution of High-altitude Precipitation Gradient

section_content: The median precipitation gradient for the seven glacier zones was -0. 0347% m -1, which meant that according to and, precipitation decreased by 0. 0347% for every 1 m increase in elevation. The median precipitation gradients in Karakoram, Eastern Kunlun, and Eastern Tien Shan (-0. 0064% m -1, 0. 0011% m -1, and -0. 0062% m -1, respectively) were obviously greater than the median precipitation gradients in Eastern Kunlun, Eastern Tien Shan, Qilian Shan, and Pamir (-0. 0223% m -1, -0. 0722% m -1, -0. 0999% m -1, and -0. 0025% m -1, respectively). We found that the median precipitation gradients of glaciers in the western part of the DAC were larger than those in the eastern part; for example, the median precipitation gradient of Western Kunlun was larger than that of Eastern Kunlun, similar to the relationship between Western Tien Shan and Eastern Tien Shan. Precipitation decreased by 9. 9% for every 100 m increase in elevation from the maximum rainfall height in the Qilian Shan, and precipitation increased by 0. 11% for the same increases in elevation in Eastern Kunlun. To better understand the distribution of precipitation gradients of glaciers around the DAC, the relationship between precipitation and ∆H, which is the difference between the maximum elevation and the maximum rainfall height, was analyzed in this paper. ∆ had the largest number of glaciers between 3000 m and 4000 m, with a median of -0. 0276% m -1 and a large range of maximum and minimum values. The ∆H between 6000 m and 8000 m had the highest median PG (-0. 0078% m -1 and -0. 0055% m -1 ), which was consistent with the suggestions that the higher the tropospheric height was, the stronger the interaction between altitude and precipitation of this precipitation type was. The fewest glaciers were located in the ranges of 1000 m to 2000 m and 5000 m to 6000 m, with median values of -0. 1084% m -1 and -0. 0319% m -1, respectively. With the increase in ∆, the median had a significant increase range at elevations of 1000 m to 4000 m, and the median increased by 0. 0269% for every 1000 m increase in elevation.
section_name: 8.

section_content: Some results have shown that both temperature and precipitation have increased significantly in the last 60 years, while the increasing trends have even obviously intensified (Javed et al., 2021; Zhang et al., 2021). of glacier change decreases with the distance from a water vapor supply source. Most studies also showed that temperature played a leading role in hydrothermal conditions, while precipitation played a weaker role (Azam & Srivastava, 2020; Ban et al., 2020; Baojuan et al., 2020; Noel et al., 2020).
section_name: Impact Factors

section_content: OAA in the DAC relied most on glacier delayed runoff and meltwater runoff to irrigate and maintain agriculture as well as to maintain soil moisture, vegetation growth and groundwater replenishment to maintain food security (Bury et al., 2013; Clouse et al., 2016; Rasul & Molden, 2019). The 22 glacier basins in the DAC have irrigated 143,939. 24 km 2 of OAA, supplying a total of 14 million people in 19 regions. The primary industry gross domestic product (GDP) of these regions in 2015 was nearly 111. 54 billion dollars, accounting for 14. 1% of the total GDP of these regions, which was twice that of the primary industry, accounting for 7% of the national GDP. Since the total primary industry GDP of the entire north western DAC was 40. 46 million dollars, OAAs constituted 79. 86% of it. Increasing glacier runoff could provide more water for agriculture and animal husbandry to ensure food security and purvey water for residential and industrial use, but the trend could not be sustained (Wang et al., 2021). 

The proportion of glacier runoff in agricultural, industrial and municipal water consumption in each basin in the DAC was shown in Fig. 9. The agricultural water consumption at the watershed scale was obtained by averaging the agricultural water consumption statistical data to the land use types of agricultural land and then ranged regional statistics, which was the same with industrial and municipal water consumption. Compared with the industrial and municipal water consumption in each basin, the delayed runoff and meltwater runoff were both higher than the total industrial and municipal water consumption in this basin. Glacier runoff from the Middle Rivers Basin and Western Qaidam Basin could even provide the entire agricultural water consumption over the entire basin. When the ELA was higher than the altitude of the glacier itself, glacier runoff began to decrease, which might have adverse effects on downstream agriculture, animal husbandry, energy and livelihood. For example, due to increased temperatures and reduced glacier runoff, California, in the United States, experienced a severe drought from 2011 to 2015, where hydroelectric power generation decreased by two-thirds. The annual ecological service value in Tien Shan was 60. 2 billion yuan (~9. 26 billion dollars) (Zhang, Liu, et al., 2019), and that in Qilian Shan was 24. 354 billion yuan (~ 3. 75 billion dollars) (Sun et al., 2020). Glaciers such as the Urumqi No. 1 Glacier and July 1 Glacier in Qilian Shan have been developed as scenic plots to attract more tourists to the local area and increase the income of local residents. 

However, with the rise of the ELA, to protect the Urumqi No. 1 Glacier, the tourist service had been cancelled. In the future, glacier runoff will reach its peak when glacier tourism disappears (Warren & Lemmen, 2014). Even in some places, the water shortage caused by the reduction of glacier runoff has caused the risk of water pollution and the production of water-borne pathogens (Warren & Lemmen, 2014). In a study of the public perception of changes in the cryosphere in the Urumqi River basin, 58. 8% of the interviewees believed that as glacial runoff increased, income also increased (Deng et al., 2011). As quantifying the economic and social impact of changes in the cryosphere is essential for making public policies and influencing adaptation decisions, our estimations could support a quantified long-term time-series glacier runoff to be referred.
section_name: Socio-economic Consequences

section_content: This paper overcame the shortcomings of large-scale geodetic quality assessments. We used the Shean estimation and calculated the precipitation gradient to quantitatively study the seven major glacier regions around the DAC, which consisted of nearly 42,000 glaciers. The spatiotemporal changes in glacier runoff (delayed runoff and meltwater runoff) in OAAs located in 22 glacier watersheds with a spatial resolution of 100 m from 1961 to 2015 were established. 

1. This paper used the mass balance of the Shean estimation to obtain a high-altitude precipitation gradient with uncertainties and then calculated the long-term time series of glacier runoff, including delayed runoff and meltwater runoff, while the average total glacier runoff in the DAC was (98. 52 ± 67. 37) × 10 8 m 3. The average meltwater runoff was (63. 43 ± 42. 17) × 10 8 m 3, and the delayed runoff was (35. 09 ± 25. 20) × 10 8 m 3. 

2. Among all glacier watersheds, the Shiyang River basin was the most unique, which suggested a declining trend from 1961 to 2015. The Datong River above Hall and the Heihe Basin showed fluctuating trends, while the others showed different growth trends. Based on the time series of glacier runoff, linear regression was used to predict the runoff of each glacier in DAC in the next ten years which indicated the potential climatic risks. 

3. As a continental glacier, the glacier runoff studied in this paper was mainly regulated by hydrothermal regulation, in which temperature was the dominant factor, followed by precipitation. Since the water source of the oases in the DAC was mostly glaciers and the total GDP of the OAAs accounted for 76. 92% of that of the north western DAC, glacier runoff had a greater impact on local agriculture, animal husbandry, and economy. In the future, it is necessary to quantify the impact of each change in the cryosphere on social production factors more precisely.
section_name: Conclusion

section_content: Mann-Kendall Test of total glacier runoff with a confidence of 95%.
section_name: Figure 5

section_name: Region

section_content: Qilian Shan 4200 (Chen et al., 2018; Wang et al., 2009 ) 5500

Eastern Tien Shan 3000 (Zhang, Tuerxunbai, et al., 2019 ) 5000

Western Tien Shan 3000 (Zhang, Tuerxunbai, et al., 2019 ) 6000

Eastern Kunlun 4500 6500

Western Kunlun 4000 6500

Karakoram 2500 (Immerzeel et al., 2012 ) 7500

Pamir 3000 (Hewitt, 2007 ) 6500
section_name: 𝑯𝑯 𝒎𝒎𝒎𝒎𝒎𝒎 𝑯𝑯 𝒎𝒎𝒎𝒎𝒎𝒎