Modeling decadal snow and ice dynamics and their hydrological impacts in the Balkhash Lake Basin, Central Asia

doi:10.1016/j.jaridl.2026.04.001

Journal of Arid Land

2026, Vol. 18

Issue (4): 547-567 DOI: 10.1016/j.jaridl.2026.04.001 CSTR: 32276.14.JAL.20250285

Research article

Modeling decadal snow and ice dynamics and their hydrological impacts in the Balkhash Lake Basin, Central Asia

GAN Guojing¹^,²^,³^,⁴, WU Jinglu¹^,³^,⁴^,^*(

), YANG Ruibiao¹^,³^,⁴, GAO Yanchun⁵, SHEN Beibei⁶

¹ State Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China
² Key Laboratory of Watershed Geographic Sciences, Chinese Academy of Sciences, Nanjing 211135, China
³ University of Chinese Academy of Sciences, Beijing 100049, China
⁴ College of Nanjing, University of Chinese Academy of Sciences, Nanjing 211135, China
⁵ Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
⁶ College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China

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Abstract

The Balkhash Lake Basin (BLB), a vital Central Asian watershed, faces hydrological uncertainty under climate warming. This study integrated multi-source remote sensing data (Sentinel-1 snow depth, Randolph Glacier Inventory (RGI) v.7.0 glacier inventory, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) mass balance) with a degree-day model to reconstruct decadal snow and ice dynamics across 13 sub-basins and analyzed their hydrological impacts from 1950 to 2014. The results showed that: (1) while flows from the downstream river of the BLB decreased from 1950 to 1982 due to land surface changes, runoff increased significantly after 1982 in the Ili River (18.0%) and moderately increased in most rivers in the east (1.3%-8.3%), driven by increased precipitation and glacier melt. Runoff in the Ayaguz catchment (no glaciers with the highest climate warming) declined (10.5%); (2) climate warming reduced precipitation falling as snow caused snow melt water to decline (0.03-0.22 mm/a) across the BLB, leading to downward shifts in runoff and runoff coefficient, especially in the rivers in the east. However, snow melt during April-June positively correlated with runoff coefficient, contributing to an upward shift in the Ili River Basin; and (3) meltwater from glacierized areas (<5.0% of basin area) contributed to 14.3% of total ablation water. Net glacier melt provided substantial excess flows (11.6 m³/s in the Ili River and <1.0 m³/s in the rivers in the east), generally counterbalancing the negative effect of rising potential evaporation at decadal scales and positively correlating with the runoff coefficient. Therefore, water stress in the BLB may be more severe in the future due to the accelerating glacier melt after the abrupt increase in air temperature in 2000, the continuing decline in snow melt, and the significant inter-annual variations in precipitation.

Key words： runoff trend snow and ice dynamics degree-day model remote sensing Balkhash Lake Basin

Received: 22 June 2025 Published: 30 April 2026

Corresponding Authors: ^*WU Jinglu (E-mail: w.jinglu@niglas.ac.cn)

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	GAN Guojing
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Cite this article:

GAN Guojing, WU Jinglu, YANG Ruibiao, GAO Yanchun, SHEN Beibei. Modeling decadal snow and ice dynamics and their hydrological impacts in the Balkhash Lake Basin, Central Asia. Journal of Arid Land, 2026, 18(4): 547-567.

URL:

http://jal.xjegi.com/10.1016/j.jaridl.2026.04.001 OR http://jal.xjegi.com/Y2026/V18/I4/547

Fig. 1 Elevation and river networks of the study area. Note that the figure is based on the standard map (GS(2024)0650) of the Map Service System (https://cloudcenter.tianditu.gov.cn) marked by the National Platform for Common Geospatial Information Services, and the boundary of the standard map has not been modified. DEM, digital elevation model.

Table 1 Information summary of the hydrological stations

Fig. 2 Annual air temperature (a-e), precipitation (f-j), and f_s (the ratio of snow to precipitation; k-o) across five river basins in the Balkhash Lake Basin (BLB) from 1950 to 2014. The Z value is the trend of the Mann-Kendall (MK) test, and k is the slope in different periods. Different colors represent different periods determined by the MK test method. ^*, ^**, and ^*** represent the 0.10, 0.05, and 0.01 significant levels, respectively.

Fig. 3 Annual runoff at the 13 sub-basins in the BLB from 1950 to 2014. (a), Ushjarma; (b), Kapchagay; (c), Dobyn; (d), Yamate; (e), Kashi; (f), Kunes; (g), Tekes; (h), Ushtobe; (i), Tekeli; (g), Chann; (k), Lepsy; (l), Lepsinsk; (m), Ayaguz; ^*, ^**, and ^*** represent the 0.10, 0.05, and 0.01 significance levels, respectively.

Table 2 Decadal changes in rainfall, snowfall, glaciers, potential evaporation (ET₀), all other factors (n), and runoff (R) from 1950 to 2014

Fig. 4 Degree-day factor (DDF; a) for the snow and glaciers in all study catchments in the BLB. Figure b-g show the snow melt model performances with different DDF values. Figure b and c are the correlation coefficient (r) values during the calibration period, and d and e are the mean biases between the modeled snow water equivalent, which derived from the Sentinel measurements in the Ili River Basin (b and d) and the other river basins (c and e). The r values in Figure f (Ili River Basin) and Figure g (the other river basins) represent model performances from April to July.

Fig. 5 Inter-annual variations in snow melt and ice melt at the 13 sub-basins in the BLB from 1950 to 2014. The ice melt includes the meltwater from snow that falls on the glaciers and meltwater from the glaciers themselves. To make them comparable, we averaged all variables to the catchment scale. (a), Ushjarma; (b), Kapchagay; (c), Dobyn; (d), Yamate; (e), Tekes; (f), Kunes; (g), Kashi; (h), Tekeli; (i), Ushtobe; (g), Chann; (k), Lepsy; (l), Lepsinsk; (m), Ayaguz; (n), the pie chart shows the proportions of sublimation, snow melt, and ice melt in each hydrological station. ^*** represents the 0.01 significance level.

Fig. 6 Modeled ice mass balances of glaciers and glacier areas at the sub-basins in the BLB from 1950 to 2021. Glacier areas were derived from the study of Severskiy et al. (2016). (a), Ili River Basin; (b), other river basins. Shaded areas represent 95% confidence intervals.

Fig. 7 Attribution of the contributions of five factors, i.e., rainfall, snowfall, glacier melt, PET (potential evaporation), and n, to the runoff change (ΔR) between different periods. (a), 1951-1982 vs. 1983-2014; (b), 1951-1962 vs. 1963-1983; (c), 1963-1983 vs. 1984-1994; (d), 1983-1994 vs. 1995-2014.

Fig. 8 Relationship between runoff coefficient (runoff/precipitation (R/P)) and snow and ice amounts, represented by f_s, the ratio of snow melt to precipitation (f_{s_snow melt}), and the ratio of ice melt to precipitation (f_{s_ice melt}). (a-c), sub-basins of the Ili River; (d-f), sub-basins of the Karatal, Aksu, Lepsy, and Ayaguz rivers. The black dots in b and e denote the regression lines between f_{s_snow melt} and R/P in the Ili River Basin and the other four river basins, respectively.

Fig. S1 Monthly snow melt and ice melt at the 13 sub-basins in the Balkhash Lake Basin (BLB). (a), Ushjarma; (b), Kapchagay; (c), Dobyn; (d), Yamate; (e), Tekes; (f), Kunes; (g), Kashi; (h), Tekeli; (i), Ushtobe; (j), Chann; (k), Lepsy; (l), Lepsinsk; (m), Ayaguz. The curves represent the median values of snow melt and ice melt at a specific month within a certain period (i.e., 1951-1982 and 1983-2014). Bar represents standard deviation.

Fig. S2 Annual anomalies of water cycle components, including precipitation (P), evapotranspiration (ET), runoff (R), groundwater (Globgm), and terrestrial water storage (TWSA-CSR) in all five river basins in the BLB. (a), Ili River Basin; (b), Karatal River Basin; (c), Aksu River Basin; (d), Lepsy River Basin; (e), Ayaguz River Basin.


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