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Sciences in Cold and Arid Regions ›› 2019, Vol. 11 ›› Issue (6): 435-447.doi: 10.3724/SP.J.1226.2019.00435.

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Characteristics of climate and melt runoff in the Koxkar Glacier River Basin, south slope of the Tianshan Mountains, Northwest China

Min Xu1,3(),HaiDong Han2,3(),ShiChang Kang1,3,Hua Tao3   

  1. 1. State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    2. Division of Hydrology Water-Land Resources in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou, Gansu 730000, China
    3. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
  • Received:2019-08-16 Accepted:2019-12-17 Online:2019-12-31 Published:2020-01-07
  • Contact: Min Xu,HaiDong Han E-mail:hhd@lzb.ac.cn;xumin@lzb.ac.cn

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Abstract:

Hydrology of the high glacierized region in the Tianshan Mountains is an important water resource for arid and semiarid areas of China, even Central Asia. The hydrological process is complex to understand, due to the high variability in climate and the lack of hydrometeorological data. Based on field observations, the present study analyzes the meteorological and hydrological characteristics of the Koxkar Glacier River Basin during 2008-2011; and the factors influencing climate impact on glacier hydrology are discussed. The results show that precipitation at the terminus of the glacier was 426.2 mm, 471.8 mm, 624.9 mm, and 532 mm in 2008, 2009, 2010, and 2011, respectively. Discharge increases starting in May, reaches its highest value in July and August, and then starts to decrease. The mean annual discharge was 118.23×106 m3 during the four years observed, with 87.0% occurring in the ablation season (May-September). During the study period, the runoff in August accounted for 29% of total streamflow, followed by July (22%) and June (14%). The runoff exhibited obviously high interannual variability from April to September, induced by drastic changes in climate factors. Discharge autocorrelations are very high for all the years. The climate factors show different influences on discharge. The highest correlation R between daily temperature and discharge was for a time lag of 2-3 days on the Koxkar Glacier (0.66-0.76). The daily depth of runoff to daily temperature and daily water vapor pressure had an R 2 value of 0.56 and 0.69, respectively, which could be described by an exponential function. A closer relationship is found between runoff and either temperature or water vapor pressure on a monthly scale; the R 2 values are 0.65 and 0.78, respectively. The study helps us to understand the mechanisms of the hydrological-meteorological system of typical regional glaciers and to provide a reference for glacier-runoff simulations and water-resource management.

Key words: melt runoff, Koxkar Glacier, hydrometeorological, observation, relationship

Figure 1

Location of the Koxkar Glacier (KG) (a); meteorological and hydrological stations at the end of KG (b), (c), (d)"

Figure 2

Daily variations of precipitation (a), temperature (b), total solar radiation (c), wind speed (d), relative humidity (e), and water vapor pressure (f), from 2008 to 2011 on KG"

Table 1

Characteristics of daily temperature, relative humidity, wind speed, and total solar radiation during the period of ablation (May to September) from 2008 to 2011"

Year Temperature (°C) Relative humidity (%) Wind speed (m/s) Net radiation (MJ/(m2·d))
Max Min Mean Max Min Mean Max Min Mean Max Min Mean
May 14.2 3.6 9.4 12.5 2.3 8.0 6.0 1.8 3.0 27.8 20.6 24.8
June 16.0 9.4 12.2 13.9 7.4 10.7 4.7 2.0 2.8 28.5 23.1 25.4
2008 July 15.2 7.5 12.0 14.2 6.0 10.6 5.3 1.9 2.7 28.8 23.0 26.1
Aug. 17.6 8.1 12.9 16.2 5.5 11.4 5.4 1.7 3.1 29.1 20.2 25.7
Sep. 11.7 1.8 7.7 10.0 1.1 6.3 4.0 1.3 2.7 26.2 20.6 23.9
May 11.9 3.0 7.2 10.1 1.1 5.4 37.4 2.0 3.8 26.9 18.0 22.9
June 13.2 7.6 10.7 11.9 5.5 9.2 5.1 1.8 3.1 27.6 20.6 24.8
2009 July 16.0 8.1 11.8 14.1 5.4 10.3 4.6 1.9 2.7 27.9 21.7 25.2
Aug. 15.9 7.8 12.1 14.2 6.2 10.4 4.9 1.9 2.9 28.3 21.9 25.3
Sep. 11.3 2.1 7.4 9.4 0.6 5.8 4.6 1.3 2.9 27.5 20.3 23.9
May 12.7 -1.5 5.8 10.6 -3.2 4.2 13.4 1.3 2.9 / / /
June 13.7 5.1 10.4 11.6 4.4 8.9 4.0 2.1 2.6 / / /
2010 July 17.5 8.9 12.4 15.5 7.7 10.9 3.4 1.4 2.6 / / /
Aug. 18.2 9.8 13.5 16.1 9.7 11.9 6.3 1.6 2.6 / / /
Sep. 14.1 2.6 7.4 12.3 1.3 5.9 4.0 1.6 2.4 / / /
May 14.7 2.8 7.8 13.6 0.8 5.9 13.7 1.0 2.9 27.2 20.0 24.6
June 14.1 6.3 10.8 12.9 5.0 9.2 5.1 2.0 2.7 29.2 23.0 25.7
2011 July 16.5 0.0 12.8 15.1 1.8 11.2 5.4 6.4 2.8 29.1 22.3 25.7
Aug. 18.1 7.2 12.6 16.1 5.9 11.1 4.3 1.7 2.6 29.4 22.6 26.1
Sep. 12.5 3.1 8.4 10.6 2.0 6.8 4.6 1.6 2.6 28.1 20.9 24.5

Figure 3

Coefficient variation (Cv) of precipitation, temperature, wind speed, relative humidity, and total solar radiation from 2008 to 2011 on KG"

Table 2

Characteristics of daily discharge and precipitation during the period of ablation (May to September) from 2008 to 2011"

Year Discharge (m3/s) Precipitation (mm)
May June July Aug. Sep. May June July Aug. Sep.
Max 3.1 10.6 9.5 20.4 6.4 19.3 5.8 40.9 4.2 10.2
2008 Min 0.6 3.1 3.7 6.5 2.1 0.0 0.0 0.0 0.0 0.0
Mean 1.5 7.5 6.2 11.4 3.3 2.0 0.9 4.1 0.5 1.1
Max 2.6 7.0 13.3 12.3 6.8 18.0 15.3 19.0 18.8 38.2
2009 Min 0.8 2.1 4.9 7.1 2.8 0.0 0.0 0.0 0.0 0.0
Mean 1.5 4.8 7.4 10.2 3.8 1.2 1.2 2.5 2.8 5.2
Max 2.3 11.7 24.9 24.0 16.5 14.7 28.0 25.5 21.3 19.4
2010 Min 1.3 2.5 5.9 13.3 3.3 0.0 0.0 0.0 0.0 0.0
Mean 1.7 5.7 11.6 19.1 8.6 2.8 6.3 3.8 1.3 3.7
Max 4.5 15.0 17.0 16.3 10.7 20.2 13.9 14.5 26.1 13.3
2011 Min 1.7 3.6 4.7 6.5 2.9 0.0 0.0 0.0 0.0 0.0
Mean 3.3 7.5 12.6 10.0 5.5 4.1 2.2 2.9 3.0 3.0

Figure 4

Distribution of daily discharge during the period of ablation (May to September) from 2008 to 2011 on KG"

Figure 5

Monthly distribution of discharge volume during the period of ablation (May to September) from 2008 to 2011 on KG"

Table 3

Mean monthly volume of discharge from 2008 to 2011 on KG (unit: ×106 m3)"

Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec. Total
2008 2.15 1.41 1.52 1.81 4.40 19.34 16.59 30.59 8.49 4.18 2.99 2.58 96.05
2009 2.27 1.84 1.91 2.06 4.09 12.47 19.86 27.26 9.88 7.83 4.50 3.18 97.15
2010 2.71 1.93 1.84 2.13 4.46 14.71 31.08 51.11 22.26 8.71 5.09 3.56 149.59
2011 3.01 2.18 2.08 2.82 8.85 19.40 33.62 26.79 14.34 6.53 5.77 4.72 130.11
Mean 2.54 1.84 1.84 2.21 5.45 16.48 25.29 33.94 13.74 6.81 4.59 3.51 118.23
Total 10.14 7.36 7.35 8.82 21.80 65.92 101.15 135.75 54.97 27.25 18.35 14.04 472.90

Table 4

Mean monthly depth of runoff from 2008 to 2011 on KG (unit: mm)"

Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec.
2008 18.4 12.0 13.0 15.6 34.6 165.4 141.9 261.7 72.6 35.8 25.6 22.0
2009 19.4 15.8 16.3 17.6 35.0 106.6 169.9 233.2 84.6 67.0 38.5 27.2
2010 23.2 16.4 15.7 18.2 38.2 125.8 265.9 437.2 190.4 74.5 43.5 30.4
2011 25.8 18.6 17.8 24.1 75.7 165.9 287.6 229.1 124.7 55.9 49.4 40.4
Mean 21.7 15.7 15.7 18.9 45.8 141.0 216.3 290.3 118.1 58.3 39.3 30.0

Figure 6

Interannual variability of monthly discharge, as reflected by Cv from 2008 to 2011 on KG"

Figure 7

Changes of Cv for discharge, temperature, and precipitation in different years"

Figure 8

Autocorrelation (ACF) plots of daily discharge in different years"

Figure 9

Cross-correlation (CCF) plots between daily discharge and daily temperature"

Figure 10

Cross-correlation (CCF) plots between daily discharge and daily water vapor pressure"

Figure 11

Relationship between daily melt depth and daily temperatures during 2008-2011"

Table 5

Regression equations between daily discharge and daily temperature, daily precipitation, and daily water vapor pressure, respectively, on KG"

Item Regression equation R2
Daily temperature y = 1.5544e0.10849 x 0.56 *
Daily precipitation y = 1.5286e0.0294 x 0.02
Daily water vapor pressure y = 0.3742e3.5387 x 0.69 *

Figure 12

Relationship between monthly melt depth and monthly temperatures from 2008 to 2011"

Table 6

Regression equations between monthly discharge and monthly temperature, monthly precipitation, and monthly water vapor pressure, respectively, on KG"

Item Regression equation R2
Monthly temperature y = 48.468e0.0971 x 0.65 *
Monthly precipitation y = 25.056e0.0134 x 0.38 *
Monthly water vapor pressure y = 9.7996e4.0636 x 0.78 *
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