Trends in Runoff Versus Climate Change in Typical Rivers in the Arid Region of Northwest China

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Trends in runoff versus climate change in typical rivers in the arid region of northwest China

Baofu Li a,b, Yaning Chen a,*, Zhongsheng Chen a, Weihong Li a a State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China b Graduate University of Chinese Academy of Sciences, Beijing 100049, China article info abstract

Article history: To clarify runoff and climate change trends and its relation in typical rivers in the arid region of Available online xxx northwest China (ANC), this study takes the runoff and meteorological data of 11 rivers in 5 typical river areas from mountain-pass as the research objects. The ManneKendall test, Extrapolation of Variance Analysis of Time-series Period and Correlation Analysis Method are applied to analyze the temporal and spatial variations of climate and runoff. The results show that in the past 50 years, the temperature, precipitation and runoff in the each river area exhibited an upward tendency. However, the runoff from the south slope of Altai Mountains and the north slope of Kunlun Mountains and the precipitation on the north slope of Qilian Mountains, the north slope of Kunlun Mountains and the south slope of Tianshan Mountains show inconspicuous changes. The increasing rates of temperature and precipitation in the river area of Northern Xinjiang is the largest, an average of 0.44 C/10a and 15.39 mm/10a; followed by that in the river area of Hexi Corridor, 0.29 C/10a and 7.64 mm/10a. The lowest one is in the river area of Southern Xinjiang, only 0.24 C/10a and 5.50 mm/10a. However, the increasing rate of runoff is the slowest in Northern Xinjiang while that in Southern Xinjiang is the fastest, mainly related to runoff recharge difference. The runoff recharge proportions from glaciers and precipitation have great effects on the relation between runoff and temperature and precipitation. Ó 2012 Elsevier Ltd and INQUA. All rights reserved.

1. Introduction change on agriculture in semi-arid regions. Cueto et al. (2010) studied the climate change trend of urban areas in arid regions. Nowadays, climate change is a hot topic of scientific research, Recently, the regional climate change and the impact of different which results in hydrological and water resource changes, and underlying surfaces have been investigated (Krol and Bronstert, therefore researchers pay great attention to climate change 2007; Cabre et al., 2010; Mahlstein and Knutti, 2010; Samuels (Barnett et al., 2005; Chen and Xu, 2005; Shen and Chen, 2010; Xu et al., 2010; Bukovsky and Karoly, 2011; Chen et al., 2011; Roy et al., 2010). The changes in processes of hydrology and water et al., 2011). Most studies mainly focused on runoff and its influ- resources and the climate conditions are sensitive to global climate ence factors in rivers (Wang and Meng, 2008; Chen et al., 2010, change in arid regions (Stewart et al., 2004). Shi and Zhang (1995) 2011; Xu et al., 2010; Chen et al., 2011; Xu et al., 2011). However, analyzed climate change in the arid region of northwest China and there has been little research on comparative analysis of runoff found a gradual tendency to warmer and wetter climate. Chen et al. change trends in several rivers. (2010) and Xu et al. (2010, 2011) stated that climate change had The main driving factors of runoff include climate changes and a significant impact on water resources of a typical basin in the arid human factors (Zhang et al., 2011). The arid region of northwest region, but they did not make a comparative analysis on water China has a large area, small population, more deserts and fewer resources in different rivers. Ding et al. (2006) explored glacier oases. Temperature and precipitation have significant effects on change trends under the condition of climate change, which maintaining runoff in the inland river area (Rauscher et al., 2008; Li resulted in glacial retreat and increased glacial melt water runoff. et al., 2010; Zhou et al., 2010). In addition, climate changes in Al-Bakri et al. (2011) discussed the impact of regional climate different regions and their impacts on the runoff of river are not consistent (Bergstrom et al., 2001; Arnell et al., 2003). Therefore, it is necessary to analyze the temperature and precipitation changes * Corresponding author. in different regions and their impacts on runoff. Taking the main E-mail address: [email protected] (Y. Chen). typical basin in northwest China as study subject, this study

Please cite this article in press as: Li, B., et al., Trends in runoff versus climate change in typical rivers in the arid region of northwest China, Quaternary International (2012), http://dx.doi.org/10.1016/j.quaint.2012.06.005 2 B. Li et al. / Quaternary International xxx (2012) 1e9 presents a comparative analysis on temperature, precipitation and The weather station data is maintained according to the stan- runoff changes in each river since 1957, which is expected to lay dard methods of the National Meteorological Administration of a scientific basis for sustainable use of water resources in ANC. China, having high-quality data, with data quality control (including extreme inspection and time consistency checks) before releasing these data. The runoff data in each river is derived from 2. Material and methods local Hydrology Bureaus. 2.1. Material 2.2. Methods The arid region of northwest China is located in the hinterland of 2.2.1. ManneKendall test the Eurasian continent, the vast region in the western Helan The ManneKendall non-parametric statistical test (Mann, 1945; Mountain-Zaocys Ridge line and northern Kunlun Mountains Kendall,1975) was adopted to analyze air temperature, precipitation (Fig. 1), including the Xinjiang Uygur Autonomous Region, the and runoff trends in the past 50 years. The testing method is used to Midwest Inner Mongolia Autonomous Region and most areas of estimate time-series trend without sample following a certain Ningxia Hui Autonomous Region and Hexi Corridor in Gansu distribution, which is applied widely for trend analysis (Yue et al., province, which is about 2.5 million km2, accounting for over 25% of 2002). In the method, H0 represents Distribution of random vari- the area of China. The area with sunshine and strong radiation has ables, and H1 represents possibility of bi-directional changes. S as very abundant solar energy resources. As a rule, the solar radiation Kendall’s statistic is described by the following equation: is 5400e6300 MJ/(m2 a). Annual sunshine is 2500e3000 h in the area, even up to 3549 h in Xingxingxia adjacent to Gansu and nX1 Xn Xinjiang. The high photosynthetic productive potential is condu- ¼ ð Þ S sgn xk xi (1) cive to the use of solar energy. However, the area belongs to typical i ¼ 1 k ¼ iþ1 arid eco-fragile area due to water resources shortage, widespread ¼ .. desertification, and sparse vegetation. Annual rainfall is less than xi denotes a time-series from i 1, 2 .n 1, and xj denotes ¼ þ . 300 mm on average, gradually decreasing from east to west. another time-series from j i 1, , n, which each point xi is used In this paper, the research objects are 11 rivers of five typical as a reference point of xj, using the following equation: river areas in three typical areas in ANC (Table 1), including 8 < 1; q>0 northern Xinjiang (the south slope of Altai Maintains, the north sgnðqÞ¼ 0; q ¼ 0 (2) slope of Tianshan Mountains), southern Xinjiang (the north slope of : 1; q < 0 Kunlun Mountains, the south slope of Tianshan Mountains) and the Hexi Corridor (the north slope of Qilian Mountains), which basically If the dataset is completely independent, it is S ¼ 0. S0 is calcu- cover the main inland rivers in ANC (Fig. 1). To minimize the impact lated as follows: of human activities and make the regional climate changes clear, " #, under the premise of available data, the selected hydrological X ½ ¼ ð Þð þ Þ ð Þð þ Þ station data represent runoff from mountain-passes in each river var S n n 1 2n 5 t t 1 2t 5 18 (3) t and the selected weather station data represent climate changes of each mountains area. The mean values of weather and hydrological n denotes the length of the dataset or the number of years in the stations data are used to represent runoff, temperature, and dataset, t denotes the extent of any given tie, S denotes the sum of precipitation. all the “knot”.

Fig. 1. Meteorological and hydrological stations of rivers in the arid region of northwest China.

Table 1 Rivers, meteorological and hydrological stations in the arid region of northwest China.

Areas Typical river areas Rivers Weather stations (Information sessions) Hydrological stations (Information sessions) Hexi Corridor The north slope of Qilian Mountains Heihe River Qilian (1957e2010) Yingluoxia (1957e2009) Shiyang River Wushaoling (1957e2010) Zamusi (1957e2009) Shule River Tuole (1957e2010) Changmabao (1957e2009) Northern Xinjiang The south slope of Altai Mountains Kelan River Altai (1957e2005) Altai (1957e2005) The north slope of Tianshan Mountains Urumqi River Daxigou, Yingxiongqiao (1957e2006) Yingxiongqiao (1957e2006) Manas River Ken Watt (1957e2006) Hongshanzui (1957e2006) Kuitun River Jialeguola (1957e2006) Jialeguola (1957e2006) Southern Xinjiang The south slope of Tianshan Mountains Aksu River Toergate, Aheqi (1957e2010) Xiehela, Shaliguilanke (1957e2008) Kaidu River Bayinbuluke (1957e2010) Dashankou (1957e2008) The north slope of Kunlun Mountains Hotan River Hotan (1957e2010) Tongguluozike, Wuluwati (1957e2008) Yarkand River Taxkorgan (1957e2010) Kaqun (1957e2008)

For a long time-series, statistical value S can be transformed into where 1 < j < i < n, a positive value of b means an “upward trend”; Zc, the calculation equation is as follows: a negative value of b denotes a “downward trend”, ManneKendall 8 test is as follows: > pSffiffiffiffiffiffiffiffiffiffiffiffiffiffi1 ; > > S 0 Null hypothesis H0: b ¼ 0 < varðSÞ If jZcjiZ1a=2, oppose to H0 assumption. Zc ¼ 0; S ¼ 0 (4) > Where Z a= is standard normal variance, a is significant test > S þ 1 1 2 : pffiffiffiffiffiffiffiffiffiffiffiffiffiffi; S < 0 level. varðSÞ

Besides identifying whether a trend exists, it is also vital to 2.2.2. Extrapolation of Variance Analysis of Time-series Period determine the magnitude of a trend, the trend magnitude b can be The Extrapolation of Variance Analysis of Time-series Period deﬁned as follows: (EVATP) is used to calculate the change periodic of air temperature, precipitation and runoff trends in the past 50 years. The basic x x b ¼ i j ; c < principles are as follows: based on the assumption that X(t) Median j i (5) i j represents time-series of an event, X is divided into “r” groups

Fig. 2. Temperature anomalies trends in typical river areas in the arid region of northwest China.

Table 2 slope of Kunlun Mountains, increasing by 0.24 C/10a, 0.24 C/10a Temperature trends and tests in different typical river areas in the arid region of and 0.25 C/10a, respectively. In addition, the ManneKendall test northwest China. showed (Table 2) that the temperature increasing trend in each river Areas Typical river areas Cv Zc Step change Periods area was statistically significant at P < 0.01 level. points (a) From the perspective of coefficient of variation, the temperature ** ** ** Hexi The north slope 1.252 4.68 1994 19 variation is the largest on the north slope of Qilian Mountains, Corridor of Qilian Mountains which shows strong variability; the second one is on the south Northern The south slope 0.327 5.53** 1984** 19** of Altai Mountains slope of Altai Mountains and Tianshan Mountains, with moderate Xinjiang The north slope 0.087 5.14** 1978** 17** variability; the temperature variation on the north slope of Tian- of Tianshan Mountains shan Mountains and Kunlun Mountains are the smallest, showing ** * Southern The south slope 0.148 2.65 None 20 weak variability (Table 2). of Tianshan Mountains Xinjiang The north slope 0.083 3.76** (1980, 1987)** 19** of Kunlun Mountains 3.1.2. Step change point ManneKendall test results (P < 0.01) showed (Table 2) that the Note: * significant at P < 0.05; ** significant at P < 0.01. temperature on the north slope of Qilian Mountains had step according to the length of period “n”, the sum of squares intragroup change point occurrence in 1994; that on the south slope of Altai (Q1) divided by the corresponding first degrees of freedom (f1) step change point occurred in 1984; and that on the north slope of equal to mean square intragroup; the sum of squares intergroup Tianshan occurred in 1978. There were two step change points on (Q2) divided by the corresponding second degrees of freedom (f2) the north slope of Kunlun Mountains, in 1980 and in 1987. equal to mean square intergroup, so that F ¼ intergroup difference/ However, there was no step change point on the south slope of intragroup difference ¼ (Q2/f2)/(Q1/f1), when F value is large Tianshan Mountains. enough, the intergroup difference is significant, that is to say, there is significant periodicity. 3.1.3. Period Temperature change period greatly affects the accuracy of 2.2.3. Coefficient of variation simulation and prediction. EVATP was used to explore temperature Coefficient of variation (Cv) is to measure variation statistics of change period in each river area. Similarly, the method was utilized observed value and variation degree of the variable in time-series. to analyze the precipitation and runoff changes as follows. The method is employed to explore runoff and climate changes in The temperature change periods on the north slope of Qilian recent 50 years. Assessments of the coefficient of variation are as Mountains, the south slope of Altai Mountains and the north slope follows: if Cv 0.1, it is weak variability, if 0.1 < Cv 1.0, it is medium of Kunlun Mountains are basically consistent, at 19a. That on the variability, if Cv > 1.0, it is strong variability (Lei et al., 1998). north slope of Tianshan Mountains is the shortest, 17a. That on the south slope of Tianshan Mountains is the longest, 20a. Generally 3. Results and analysis speaking, the temperature change period shows a little difference in each river area (Table 2). 3.1. Temperature 3.1.4. Temperature variations in different periods 3.1.1. Temperature trend The results show that the step change points of climate generally During the last five decades, the temperature in each river area occurred in the later part of 1980s in ANC (Shi et al., 2003; Chen and (the south slope of Altai Mountains, the north slope of Kunlun Xu, 2005; Zhang et al., 2010). Therefore, to further clarify the Mountains, the north slope of Qilian Mountains, the south and north temperature change of each river area in a historical period, this paper slope of Tianshan Mountains) has been increasing in a fluctuating makes a comparison of average temperature of the period 1990e2010 way with an average increase of 0.32 C per decade (Fig. 2). The with the historical period 1957e1989. Similarly, the method is temperature on the south slope of Altai Mountains rose the fastest, employed to analyze the precipitation and runoff change as follows. increasing by 0.64 C/10a; the second is on the north slope of Qilian The increasing amount of average temperature during Mountains, increasing by 0.29 C/10a; the slowest increases are on 1990e2010 on the south slope of Altai Mountains is the largest, the south and north slope of Tianshan Mountains and on the north compared with 1957e1989, showing an increase of 1.91 C(Fig. 3);

Fig. 3. Temperature variations in each river area in different periods in northwest China.

Fig. 4. Precipitation anomalies trends in typical river areas of the arid region of northwest China. followed by those on the north slope of Qilian Mountains, the south Tianshan Mountains is statistically significant at P < 0.01 level. That slope of Tianshan Mountains and the north slope of Kunlun on the south slope of Altai Mountains is statistically significant at Mountains, increasing by 0.94 C, 0.81 C and 0.75 C, respectively. P < 0.05 level. Those on the north slope of Qilian Mountains, the That on the north slope of Tianshan Mountains is the smallest, only north slope of Kunlun Mountains and the south slope of Tianshan 0.63 C. Generally speaking, the increasing amount of average Mountains are not significant. temperature in northern Xinjiang is the largest, followed by that in During the past 50 years, the average increasing rate of the Hexi Corridor, and the smallest one is in southern Xinjiang. precipitation in each river area was 9.12 mm per decade. The increasing rates of precipitation on the north slope of Tianshan 3.2. Precipitation Mountains and the south slope of Altai Mountains are the fastest, 15.48 mm/10a and 15.30 mm/10a, respectively, followed by those 3.2.1. Precipitation trend on the north slope of Qilian Mountains and the south slope of The precipitation in each river area shows an increasing trend Tianshan Mountains, 7.64 mm/10a and 6.75 mm/10a, respectively; (Fig. 4). An increasing trend of precipitation on the north slope of the slowest one is on the north slope of the Kunlun Mountains, only 4.25 mm/10a. Table 3 The variation coefficient of precipitation in each river is not Precipitation trends and tests in typical river areas of the arid region of northwest China. high, ranging from 0.12 to 0.34, which belongs to moderate variability (Table 3). The variation coefficient of precipitation on Typical areas Typical river areas Cv Z Step change Periods c the north slope of Qilian Mountains is the smallest (0.12) points (a) while the largest one (0.34) is on the north slope of Kunlun Hexi Corridor The north slope 0.12 1.25 None 22** of Qilian Mountains Mountains. Northern The south slope 0.26 1.97* 1987* 18** Xinjiang of Altai Mountains 3.2.2. Step change point The north slope 0.17 2.64** 1992* 17* Table 3 showed that step change points in precipitation on the of Tianshan Mountains south slope of Altai Mountains, the north slope of Tianshan Southern The south slope 0.17 0.75 None 12* Xinjiang of Tianshan Mountains Mountains and the north slope of Kunlun Mountains occurred in The north slope 0.34 1.72 1999* 20** 1987, in 1992 and in 1999 (P < 0.05), respectively, while there were of Kunlun Mountains no step change points on the north slope of Qilian Mountains and Note: * significant at P < 0.05; ** significant at P < 0.01. on the south slope of Tianshan Mountains.

Fig. 5. Precipitation changes of each river in different periods in the arid region of China.

3.2.3. Period 3.2.4. Precipitation changes in different periods The precipitation period on the north slope of Qilian Mountains Compared with the period 1957e1989, the precipitation during is the longest (Table 3), 22a, followed by those on the north slope of the period 1990e2010 on the south slope of Altai Mountains Kunlun Mountains, the south slope of Altai Mountains and the increased the largest, increasing by 55.41 mm (Fig. 5), followed by north slope of Tianshan Mountains, about 20a, 18a and 17a, those on the north slope and south slope of Tianshan Mountains, respectively. That on the south slope of Tianshan Mountains is the increasing by 39.56 mm and 32.91 mm, respectively, Those on the shortest, only 12a. Generally, there are very great differences in north slope of Kunlun Mountains and the north slope of the Qilian precipitation period in each river area. Mountains were the smallest, increasing by 11.33 mm and

Fig. 6. Runoff anomalies trends in typical river areas of the arid region of northwest China.

Table 4 slope of Tianshan Mountains occurred in 1993, while there were no Runoff trends and tests in typical river areas of the arid region of northwest China. step change points on the south slope of Altai Mountains and the

Typical areas Typical river areas Cv Zc Step change Periods north slope of Kunlun Mountains (Table 4). points (a) Hexi Corridor The north slope 0.163 2.29* 2001* 22** 3.3.3. Period of Qilian Mountains Runoff change periods on the north slope of Qilian Mountains Northern The south slope 0.264 0.87 None 18* and on the north slope of Kunlun Mountains (Table 4) are 22a and Xinjiang of Altai Mountains The north slope 0.133 2.19* 1993* 19* 21a, respectively. The runoff change periods on the south slope of of Tianshan Mountains Altai Mountains and on the south and north slope of Tianshan Southern The south slope 0.136 3.58** 1993** 18* Mountains are 18a, 18a and 19a, respectively. Generally speaking, Xinjiang of Tianshan Mountains there is a little difference in precipitation change period in each The north slope 0.174 1.69 None 21** river area. of Kunlun Mountains fi < fi < Note: * signi cant at P 0.05; ** signi cant at P 0.01. 3.3.4. Runoff changes in different periods The runoff during 1990e2010 on the south slope of Tianshan 10.77 mm, respectively. In general, the increasing amount of Mountains increased the fastest, compared with 1957e1989, precipitation in northern Xinjiang is the largest, followed by that in increased by 18.12% (Fig. 7), followed by those on the north slope southern Xinjiang; the smallest one is in the Hexi Corridor. of Tianshan Mountains and the south slope of Altai Mountains, increasing by 12.56% and 10.26%, respectively, while those the 3.3. Runoff north slope of Qilian Mountains and the north slope of Kunlun Mountains increased the smallest, increased by 9.43% and 8.12%, 3.3.1. Runoff trend respectively. In general, the runoff in southern Xinjiang increased Runoff in each river area shows an increasing trend (Fig. 6). The most rapidly, followed by that in the northern Xinjiang, and the increasing trend of runoff on the south slope of Tianshan Moun- lowest one is in Hexi Corridor. tains is statistically significant at P < 0.01 level. Those on the north slope of Qilian Mountains and the north slope of Tianshan Moun- tains are statistically significant at P < 0.05 level, while those on the 3.4. Relations between runoff, and air temperature and south slope of Altai Mountains and the north slope of Kunlun precipitation Mountains are not significant (Table 4). In the past 50 years, the average increasing rate of runoff in each The correlation between precipitation and runoff is statistically river area was 1.03 108 m3 per decade. The increasing rates of significant at P < 0.01 level except for that on the north slope of runoff on the north slope of Kunlun Mountains and the south slope Kunlun Mountains. The correlation between runoff and tempera- of Tianshan Mountains are the fastest, 4.25 108 m3/10a and ture is statistically significant at P < 0.01 level except for that on the 2.90 108 m3/10a, respectively, followed by those on the north south slope of Altai Mountains (Table 5). The correlation analysis slope of Qilian Mountains and the north slope of Tianshan Moun- shows that the runoff change on the south slope of Altai Mountains tains, 0.42 108 m3/10a, 0.26 108 m3/10a, respectively, while the is mainly affected by precipitation. Temperature plays a dominant increasing rate of runoff on the south slope of Altai Mountains is the role in runoff change on the north slope of Kunlun Mountains. The slowest, only 0.15 108 m3/10a (Fig. 6). runoff changes on the north slope of Qilian Mountains, the south The variation coefficient of runoff in each river area is not high, and north slope of Tianshan Mountains are mainly affected by ranging from 0.133 to 0.264, moderate variability (Table 4). The temperature and precipitation. variation coefficient of runoff on the north slope of Tianshan The above results show that the correlations between runoff and Mountains is the lowest (0.133) while that on the south slope of temperature, precipitation are dissimilar in different regions, which Altai Mountains is the highest (0.264). may be related to runoff recharge proportions from glacial meltwater and precipitation. The recharge proportion from precipita- 3.3.2. Step change point tion on the north slope of Kunlun Mountain is approximately 20%, The step change point of runoff on the north slope of Qilian less than that from glacial melt water, more than 50% (Shi et al., Mountains occurred in 2001. Those on the south slope and north 2005; Chen, 2010). Temperature rise results in glacial melt water

Fig. 7. Runoff variations of each river in different periods in the arid region of northwest China.

Table 5 Correlations between runoff and temperature, precipitation in typical river of the arid region of northwest China.

Item The south slope of The north slope The south slope The north slope The north slope Altai Mountains of Tianshan Mountains of Tianshan Mountains of Kunlun Mountains of Qilian Mountains Runoff and Precipitation 0.56** 0.62** 0.35* 0.18 0.66** Runoff and Temperature 0.05 0.41** 0.52** 0.37** 0.44**

Note: * significant at P < 0.05; * * significant at P < 0.01. volume increase, so in terms of significance, the correlation grateful to editors and anonymous reviewers for their helpful between runoff and temperature is greater. Precipitation recharges comments on improving the manuscript. We are also grateful to runoff to some degree, but the precipitation is usually accompanied Baohuan Zhang for her help and suggestions at different stages of by cooling temperature, and the temperature decrease leads to this study. glacial melt water reduction. When precipitation is less than glacial melt water reduction, the correlation between runoff and precipi- References tation exhibits negative significance (0.18). The recharge proportion from glacial melt water on the south slope of Altai Mountains is Al-Bakri, J., Suleiman, A., Abdulla, F., Ayad, J., 2011. 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