Stoch Environ Res Risk Assess (2010) 24:349–358
DOI 10.1007/s00477-009-0324-0
ORIGINAL PAPER
Climate changes and their impacts on water resources in the arid
regions: a case study of the Tarim River basin, China
Qiang Zhang Æ Chong-Yu Xu Æ Hui Tao Æ
Tao Jiang Æ Yongqin David Chen
Published online: 25 June 2009
Ó Springer-Verlag 2009
Abstract Streamflow series of five hydrological stations
were analyzed with aim to indicate variability of water
resources in the Tarim River basin. Besides, impacts of
climate changes on water resources were investigated by
analyzing daily precipitation and temperature data of 23
meteorological stations covering 1960–2005. Some interesting and important results were obtained: (1) the study
region is characterized by increasing temperature, however, only temperature in autumn is in significant increasing trend; (2) precipitation changes present different
properties. Generally, increasing precipitation can be
detected. However, only the precipitation in the Tienshan
mountain area is in significant increasing trend. Annual
streamflow of major rivers of the Tarim River basin are not
in significant trends, except that of the Akesu River which
is in significantly increasing trend. Due to the geomorphologic properties of the Tienshan mountain area, precipitation in this area demonstrates significant increasing
Q. Zhang (&) T. Jiang
Department of Water Resources and Environment,
Sun Yat-sen University, 510275 Guangzhou, China
e-mail: zhangqnj@gmail.com
C.-Y. Xu
Department of Geosciences, University of Oslo,
PO Box 1047, Blindern, 0316 Oslo, Norway
H. Tao
Nanjing Institute of Geography and Limnology,
Chinese Academy of Science, 210008 Nanjing, China
Y. D. Chen
Department of Geography and Resource Management,
The Chinese University of Hong Kong, Hong Kong, China
trend and which in turn leads to increasing streamflow of
the Akesu River. Due to the fact that the sources of
streamflow of the rivers in the Tarim River basin are precipitation and melting glacial, both increasing precipitation
and accelerating melting ice has the potential to cause
increasing streamflow. These results are of practical and
scientific merits in basin-scale water resource management
in the arid regions in China under the changing
environment.
Keywords Climate change Mann–Kendall trend test Water resources The arid regions Tarim River basin
1 Introduction
Water plays the key role in human society and nature
which greatly underscores the better understanding of how
changes in climate could affect regional water supplies,
particularly in the arid regions (Houghton et al. 2001; Xu
and Singh 2004; Hagg et al. 2007). The well-evidenced
global warming and associated impacts on human society
have drawn considerable concerns from academic circles,
public and governments. Labat et al. (2004) indicated that
the global warming led to alterations of the global hydrological cycle and to the increase amplitude of the global
and continental runoff. Higher air temperatures result in
higher evaporation rates, higher atmospheric water vapor
content, and consequently, an accelerated hydrological
cycle (Menzel and Bürger 2002; Xu et al. 2006; Zhang
et al. 2008a, b). Among the most significant potential
consequences of regional climate change are alterations in
regional hydrological cycles and subsequent changes in
river regimes. However, the model intercomparison
revealed that the relationship between the intensity of the
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350
global hydrological cycle and global warming is not very
robust (Douville et al. 2006). In terms of a specific regional
scale, many studies reported large uncertainties in response
of precipitation changes to global warming (e.g. Douville
2006). Even though several studies indicated that the
anticipated global increase in precipitation may not be in
association with accelerated or accelerating water cycle as
a result of global warming (Bosilovich et al. 2005), many
studies have shown that the impacts of climatic changes on
global/regional water resources hinge on the influences of
climatic changes on the spatial and temporal distribution of
precipitation (e.g. Gao et al. 2007). Booij (2005) studied
the impact of climate change on floods in the river Meuse
(in western Europe), investigating variability and uncertainty of impacts of climate changes on river floods. Thus,
it is necessary to better understand climate changes and
possible impacts on water resource from the viewpoint of
regional scale.
Global warming has the potential to alter the spatial and
temporal distribution of water resource, which exerts tremendous influences on the ecological environment and the
agriculture development. Furthermore, the arid regions are
more sensitive to variability and availability of water
resource (in this study we only focus on ground-surface
water) when compared to the humid regions. Therefore,
good knowledge of variations of the water resource under
the changing climate by taking a typical arid region as a
case study is of great scientific and practical merits in
sound understanding of the hydrological response to the
climate changes and also in the water resource management in the arid regions of the world. This is the major
motivation of this study. The north-west China is characterized by arid and semi-arid climate. Variability and
availability of water resources have direct influences on
local eco-environmental conservation and sustainable
socio-economic development. The Tarim River is the
longest inland river in China with an annual flow of 4–6
billion cubic meters. About 10 million population including
ethnic minorities of Uyghurs and Mongolians live in this
valley. The climate of this river basin is characterized by
precipitation deficit and strong evaporation. Scientific
problems of climate changes and water resources have
drawn considerable concerns from academic circle (Feng
et al. 2001; Song et al. 2002; Ye et al. 2006). Shi et al.
(2003) indicated a transition from dry and warm climate to
wet and warm climate in the north-west China. Due to
paramount role of water resource in the sustainable
development of socio-economy in the northwest China and
distinct influences of climate changes on variability of
water resource, it is desirable to analyze climate changes of
the past decades, focusing on changes of precipitation and
temperature, and the possible influences on streamflow
variations, which forms the objective of the present study.
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Stoch Environ Res Risk Assess (2010) 24:349–358
2 Study region: the Tarim River basin
The Tarim River is 1,321 km in length, running west to
east along the northern edge of the Taklimakan Desert. The
drainage area of the Tarim River Basin is 1.02 9 106 km2,
it is the largest inland river in China and is highly dependent on the water supply by the TienShan, Kunlun, Eastern
Pamir and Karakorum high mountains that surround the
basin. There are 114 rivers in the Tarim River Basin,
forming 9 drainage systems: Aksu, Hotan, Yarkant,
Qarqan, Keriya, Dina, Kaxgar, Kaidu–Konqi Rivers. There
are only four headstreams (Hotan, Yarkand, Akesu and
Kaidu Rivers) feeding the mainstream of the Tarim River.
The annual mean air temperature is 10.6–11.5°C. Monthly
mean temperature is between 20 to 30°C in July and -10 to
-20°C in January. The extreme maximum and minimum
temperature of the Tarim River basin are 43.6 and
-27.5°C, respectively. The multi-annual mean precipitation
is 116.8 mm, wherein more than 80% of total precipitation
falls during May–September. The river is the most
important source of water in the arid lowlands of Tarim
Basin, with more than 8 million people living in oases
clustered along its banks and in an alluvial plain downstream. Due to its exceptional role in sustainable development of local socio-economy, the central government of
China launched a five- year emergency water diversion
program in 2000 with 10.7 billion yuan (US$1.3 billion)
earmarked for the reclamation of the river and Taitema
Lake (Tao et al. 2008). There are some studies focusing on
the impacts of climate changes on water resource in the
Tarim River basin (e.g. Chen et al. 2006). However, the
previous studies focused on site-specific station, but not
comprehensive study in space and time, which tends to
limit our understanding of influences of climate changes on
water resources from the viewpoint of time and space.
Actually, climate changes do impact water resource variability in space and time. Therefore, it is necessary to
comprehensively analyze the climate changes and associated influences on water resource changes in time and
space. However, no such reports are available from viewpoint of both space and time.
3 Data and methods
3.1 Data
Daily precipitation and temperature data for 1960–2005
were collected from 24 national standard rain stations in
the Tarim River basin (Fig. 1). There are a few missing
data in the daily precipitation and temperature dataset (less
than 0.01% of the total observations). The missing precipitation and temperature data are filled by the mean
Stoch Environ Res Risk Assess (2010) 24:349–358
351
Fig. 1 Location of the Tarim
River basin, rain gauging
stations and hydrological
stations
values of the neighboring days. If more than two days have
missing data, we filled them with values of its neighboring
stations by building regressive relations between stations.
The results show the R2 value as high as [0.85. We consider the gap filling method will have no influence on the
long-term temporal trend. Furthermore, the data consistency was checked by the double-mass method and the
result revealed that all the data series used in the study are
consistent. Moreover, annual total streamflow dataset for
1957–2003 from six hydrological stations are collected and
analyzed to demonstrate long-term trend of streamflow
variations. Locations of these six hydrological stations can
be referred to Fig. 1 and more detailed information can be
referred to Table 1. The trends in this study only represent
the time interval considered in this study.
trend detection. However, non-parametric trend detection
methods are less sensitive to outliers than are parametric
statistics such as Pearson’s correlation coefficient. Moreover, the rank-based nonparametric Mann–Kendall test
(Kendall 1975; Mann 1945) can test trends in a time series
without requiring normality or linearity, and is therefore
highly recommended for general use by the World
Meteorological Organization (Mitchell et al. 1966). The
Mann–Kendall trend test has been widely used in detection
of trends in meteorological and hydrological series (Chen
et al. 2007; Burn 2008). This paper also uses the Mann–
Kendall (MK) test method to analyze trends within the
precipitation, temperature and annual streamflow series
across the Tarim River basin. The procedure of MK trend
test adopted in this study is as follows:
First the MK test statistic is calculated as
3.2 Methodology
There are many statistical techniques available to detect
trends within the time series such as moving average, linear
regression, Mann–Kendall trend test, filtering technology,
etc. Each method has its own strength and weakness in
S¼
n1 X
n
X
sgnðxj xi Þ
8
< þ1; xj [ xi
0; xj ¼ xi
where sgnðxj xi Þ ¼
:
1; xj \xi
ð1Þ
i¼1 j¼iþ1
Table 1 Annual streamflow changes in the headstreams of Tarim River basin (1957–2005)
Water system
Hotan River
Aksu River
Hydrological stations
Drainage
area (km2)
Multi-annual
average streamflow
(108m3)
Percentage of
melting ice (%)
Significance
(0.05)
M–K
trend
Tommguziluoke
14,575
22.27
61.11
No
-0.52
Wuluwati
19,983
21.39
45.91
No
-0.46
Xiehela
12,816
48.67
21.9
Yes
4.41
Shaliguilanke
19,166
27.67
28.9
Yes
3.88
Yarkant River
Kaqun
50,248
65.43
56.2
No
1.11
Kaidu River
Dashankou
19,000
34.2
14.6
No
1.79
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Stoch Environ Res Risk Assess (2010) 24:349–358
VðSÞ ¼
nðn 1Þð2n þ 5Þ ð2Þ
Pn
i¼1 ti iði
18
1Þð2i þ 5Þ
ð3Þ
where ti is the number of ties of extent i.
The standardized statistics (Z) for one-tailed test is
formulated as:
8 S1
pffiffiffiffiffiffiffiffiffiffiffiffi S [ 0
>
< VarðSÞ
0
S¼0
Z¼
>
Sþ1 ffi
: pffiffiffiffiffiffiffiffiffiffiffi
S\0
VarðSÞ
ð4Þ
At the 5% significance level, the null hypothesis of no
trend is rejected if |Z| [ 1.96.
Influence elimination of serial correlation (if it is significant at [95% confidence level) on the Mann–Kendall
(MK) test has been discussed (Khaled and Rao 1998; Yue
and Wang 2002). In this paper, effective sample size (ESS)
proposed by Yue and Wang (2004) is used to modify the
variance of the MK statistic to reduce the influence of the
presence of serial correlation on the MK test. The procedure is as follows (Yue and Wang 2004): (1) remove the
existing trend from the series if it exists; (2) the sample
serial correlation is estimated using the detrended series;
and (3) the MK test modified by ESS is applied to assess
the significance of trend in the original time series. The
significance of the trend was tested at [95% confidence
level.
Moreover, the simple linear regression method, a
parametric T test method, is also used in this paper to
detect long-term trends within the hydro-meteorological
series. The computation procedure consists of two steps,
fitting a linear simple regression equation with the time t
as independent variable and the hydrological variable (in
this case areal average temperature, precipitation and
annual streamflow series), Y as dependent variable, and
testing the statistical significance of the slope of the
regression equation. The parametric T test requires the
data to be tested is normally distributed. The normality
of the data series is first tested in the study by applying
the Kolmogorov–Smirnov test. The method first compares the specified theoretical cumulative distribution
function (in our case normal distribution) with the
sample cumulative density function based on observations, then calculates the maximum deviation, D, of the
two. If, for the chosen significance level, the observed
value of D is greater than or equal to the critical tabulated value of the Kolmogorov–Smirnov statistic, the
hypothesis of normal distribution is rejected.
123
A
0.6
0.4
0.2
0
1
2
3
4
5
6
7
8
9
10
11
12
2
3
4
5
6
7
8
9
10
11
12
30
Temperature ( oC)
EðSÞ ¼ 0
0.8
Precipitation (mm)
and n is the sample size. The statistics S is approximately
normally distributed when n C 8, with the mean and the
variance as follows:
20
B
10
0
−10
1
Fig. 2 Long term areal monthly average precipitation (a) and
temperature (b) of the Tarim River basin (1960–2005)
4 Results and discussion
4.1 Precipitation and temperature changes
In the Tarim River basin, precipitation mainly occurs during
May–August. November, December, January and February
are the dry months (Fig. 2). High monthly mean temperature
is observed mainly during June-August and low monthly
mean temperature in December, January and February
(Fig. 2). Before further trend detection analysis, we performed thorough analysis on the serial persistence within the
meteor-hydrological series station by station in the Tarim
River basin. For the size of this paper, we can not demonstrate all the results here. Thus, we just show autocorrelation
analysis results of three series randomly selected from the
dataset. Figure 3 illustrates parts of the results for case
studies. It can be seen from Fig. 3 that the series include
independent observations both for annual streamflow series
and for annual mean temperature and annual precipitation
series at 95% confidence level. This result justifies the
application of MK trend detection technique in this study.
Even so, we still considered possible influences of serial
persistence within the series on the MK trend detection based
on the method mentioned in the Methodology section.
4.2 Spatial distribution of trends of precipitation
and temperature changes
Precipitation and temperature changes exert considerable
influence on availability of water resources from the
viewpoint of space and time. Figures 4 and 5 demonstrate
spatial patterns of seasonal precipitation and temperature
changes in the Tarim River basin. It can be seen from
Stoch Environ Res Risk Assess (2010) 24:349–358
353
1
ACF
Autocorrelation analysis for annual streamflow series
0.5
0
−0.5
0
5
10
15
1
ACF
Autocorrelation analysis for annual precipitation series
0.5
0
−0.5
0
5
10
15
ACF
1
4.3 Changes of streamflow and glacier in the main
tributaries
Autocorrelation analysis for annual temperature series
0.5
0
−0.5
0
5
10
winter. This point is further corroborated by our previous
study (Zhang et al. 2008c). In autumn, 22 out of 24 stations
show significant increasing temperature trend, accounting
for 91.7% of total stations studied in this paper. In general,
more significant increasing temperature trends are identified in autumn and winter. In summer, 16 out of 24 stations
exhibit significant increasing temperature trends, accounting for 66.7% of the total stations studied in the paper.
Generally, stations characterized by no significant temperature trends are found mainly in the west part of the
Tarim River basin.
15
Lag time
Fig. 3 Autocorrelation analysis of meteor-hydrological series of the
Tarim River basin. All the meteor-hydrological series of the Tarim
River basin were analyzed station by station for serial persistence
detection. The series in this figure are shown as a case study. The
dashed lines denote 95% confidence level. ACF means autocorrelation functions
Fig. 4a that stations characterized by significant increasing
annual precipitation changes mainly concentrated in the
regions north to the Taklimakan Desert. Specifically, significant increasing precipitation can be observed mainly in
the Toxkan River, Kargar River, Weigan River and Kaidu
River. No significant annual precipitation changes can be
detected in west, south-west and south parts of the Tarim
River basin. With respect to precipitation changes in spring
(Fig. 4b), summer (Fig. 4c), autumn (Fig. 4d) and winter
(Fig. 4e), more stations show significant increasing precipitation in summer when compared to other three seasons, i.e. spring, autumn and winter. In summer, 10 out of
24 stations exhibit significant increasing precipitation,
accounting for 41.7% of total stations studied in this paper.
Only 1–3 stations show significant increasing precipitation
in other three seasons (Figs. 4b, d, e). Stations with significant increasing precipitation in summer distribute sporadically and widely across the whole Tarim River basin.
However, comparatively, stations also seem to converge to
the north parts of the Tarim River basin, Weigan and Dina
rivers in particular. Stations with significant precipitation in
winter also concentrate in this area (Fig. 4e).
When compared to precipitation changes, more stations
in the Tarim River basin show significant increasing temperature (Fig. 5). For annual temperature changes, only 3
out of 24 stations show no significant temperature trends.
Comparatively, more stations show no significant temperature changes in spring than in summer, autumn and
Generally speaking, streamflow changes are mainly the
results of precipitation changes. Runoff in the June–August
flood season accounts for 60–80% of the annual total
runoff (Chen et al. 2003). However, due to unique climatic
properties and geographical location of the Tarim River
basin, streamflow changes of the Tarim River basin are also
partly influenced by temperature changes due to the fact
that temperature can impact melting of glacier and evaporation variations. Glacier melt and snowmelt make up
48.2% of the total runoff of the river (Chen et al. 2006).
Glaciers, snowmelt and precipitation in the surrounding
mountains are the source of runoff for the Tarim River.
Therefore, it is important to analyze the streamflow changes and possible impacts from temperature and melting ice,
and to discuss possible contribution of snowmelt to the
changes of streamflow variations of the Tarim River basin.
It can be seen from Fig. 6 that different changing
characteristics can be observed for streamflow changes of
hydrological gauging stations in the main tributaries of the
Tarim River basin. More detailed information of these
hydrological stations and significance of trends can be
referred to Table 1. Increasing streamflow trends can be
detected in Xiehela station, Shaliguilanke station, Kaqun
station and Dashankou station and it is particularly the case
for the Xiehela, Shaliguilanke and Dashankou stations.
Figure 1 shows that these three stations are located in the
north Tarim River basin. Figure 6 also demonstrates larger
increasing magnitude of streamflow of the Xiehela,
Shaliguilanke and Dashankou stations can be found after
about 1990s when precipitation and temperature are also
characterized by abrupt increase (Xu et al. 2004).
Decreasing trends of streamflow changes can be identified
in Tommguziluoke station and Wuluwati station (Fig. 6).
Table 1 indicates that significant trends can be detected
only for Xiehela station and Shaliguilanke station of the
Aksu River. The streamflow changes of other four stations
are not significant at [95% confidence level. Figure 6 also
indicates slight trough values of streamflow for the six
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354
Stoch Environ Res Risk Assess (2010) 24:349–358
A
B
C
D
E
Fig. 4 Spatial distribution of MK trends within precipitation changes
in the Tarim basin, China. a Annual, b spring, c summer, d autumn,
e winter. Filled triangle denotes significant increasing trend; filled
inverted triangle denotes significant decreasing trend; and open circle
denotes no significant trend
hydrological stations during about 1980–1995. Figures 1
and 4 indicate that hydrological stations with significant
increasing streamflow changes are located in the regions
where stations with significant increasing annual precipitation stand. Because most stations show significant
increasing temperature trends and these stations distribute
sporadically and widely across the Tarim River basin, no
fixed and confirmed relations can be established between
streamflow changes and temperature changes. Decreasing
streamflow of Tommguziluoke station and Wuluwati
station may be partly due to no significant precipitation
trends in the west and southwest parts of the Tarim River
basin. Furthermore, although the glacial meltwater account
a large proportion of the streamflow of Hotan river
(Table 1), most of the glaciers of this sub-basin mainly
locate in the temperature dropping belt in the north of
Tibetan Plateau (Shi et al. 2006). This result also further
elucidated the possible causes behind the decreasing
streamflow in Wuluwati and Tommguziluoke stations.
Changes of glacier and number of advancing glaciers
may well explain streamflow changes (Table 2; Liu et al.
2006). Table 2 lists glacier changes of four major tributaries: Aksu River, Kaidu River, Hotan River and Yarkant
River. The least percentage of glacier area changes and
large number of advancing of glaciers are observed in the
Hotan River basin. Glaciers in the Kaidu River and Aksu
River have the large percentage of changes and also large
number of advancing glaciers. This may be due to significant increasing precipitation and no significant changes
of temperature in this particular region. Streamflow of
Dashankou, Xiehela and Shaliguilanke stations is in
increasing trends and the increasing trends of streamflow
series of Xiehela and Shaliguilanke stations are significant
at 95% confidence level.
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Stoch Environ Res Risk Assess (2010) 24:349–358
355
A
B
C
D
E
Fig. 5 Spatial distribution of MK trends within temperature changes
in the Tarim basin, China. a Annual, b spring, c summer, d autumn,
e winter. Filled triangle denotes significant increasing trend; filled
inverted triangle denotes significant decreasing trend; and open circle
denotes no significant trend
5 Conclusions and discussions
summer. Increasing temperature seems to occur mainly in
winter when compared to other three seasons. Besides,
increasing temperature changes seem to be more prevailing
when compared to changes of precipitation. Significant
increasing precipitation can be observed mainly in the
regions north to the Taklimakan Desert. More stations
show significant increasing precipitation in summer when
compared to that in spring, autumn and winter. More stations show significant increasing temperature. Stations with
no significant increasing temperature locate in the west and
north parts of the Tarim River basin.
Distribution of annual precipitation changes match well
with distribution of stations with significant increasing
streamflow, showing considerable impacts of annual
precipitation changes on annual streamflow variations.
Larger-magnitude of increase of annual streamflow can be
detected at the Xiehela, Shaliguilanke and Dashankou
Based on daily temperature and precipitation dataset of 24
stations and annual streamflow series of 6 hydrological
stations in the Tarim River basin, the typical arid region in
China, we analyzed changing characteristics of seasonal
precipitation and temperature changes from the standpoint
of space and time. Possible impacts of snowmelt, precipitation and temperature on hydrological process of the
Tarim River basin during past 40 years have also been
discussed. Some interesting conclusions can be drawn in
terms of climatic changes and associated impacts on
availability and variability of water resource of the Tarim
River basin.
Climatic changes of the Tarim River basin are characterized by increasing precipitation and temperature.
Increasing precipitation can be observed mainly in
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Stoch Environ Res Risk Assess (2010) 24:349–358
Fig. 6 Annual streamflow
changes of major tributaries of
the Tarim River basin. Annual
streamflow changes of Xiehela
and Shaliguilanke are
significant at [95% confidence
level
Streamflow (108 m3)
356
35
30
25
25
20
20
15
15
Streamflow (108 m3)
1960
1970
1980
1990
2000
1960
40
Xiehela st.
1970
1980
1990
2000
Shaliguilanke st.
35
60
30
50
25
40
20
1960
Streamflow (108 m3)
Wuluwati st.
30
Tommguziluoke st.
1970
1980
1990
2000
1960
Kaqun st.
90
1970
1980
1990
2000
1990
2000
Dashankou st.
50
80
70
40
60
30
50
1960
1970
1980
1990
2000
1960
1970
1980
Table 2 Glacier changes in the main tributaries of the Tarim River in recent 40 years
Rivers
Time interval
Number
of glaciers
Glacial
area (km2)
Changes
of area
Percentage
of changes (%)
Number of advancing
glaciers
Aksu River
1963–1999
247
1760.7
-58.6
-3.3
126
Kaidu River
1963–2000
462
333.1
-38.5
-11.6
98
Hotan River
1968–1999
757
2620.6
-37.1
-1.4
204
Yarkant River
1968–1999
565
2707.3
-111.1
-4.1
85
stations. Increasing precipitation and temperature are also
found in these regions. Larger-magnitude of increase of
annual streamflow in this region after 1990s corresponds
well to the abrupt increase of precipitation and temperature. Southwest parts of the Tarim River basin where the
Tongguziluoke, Wuluwati and Kaqun stations locate are
dominated by not significant increasing precipitation and
temperature changes. Besides, the least percentage of
glacier area and large number of advancing of glaciers
observed in the Hotan River basin can also explain not
significant streamflow and even decreasing streamflow
changes in the southwest parts of the Tarim River basin.
What aforementioned further illustrates tremendous influences of climate changes on water resources within the
Tarim River basin. Increasing snowmelt also contributes to
the changes of streamflow. River basins with larger percentage of area changes of glacier are usually characterized
by significant increasing streamflow. Hydrological stations
in the Kaidu River, Aksu River and Yarkant River show
increasing streamflow series. However, decreasing
123
streamflow changes can be identified in the Hotan River
which seem to correspond to smaller percentage of area
changes of glacier.
It should be noted here that impacts of climatic
changes on water resources are complicated. Far more
driving factors than precipitation, temperature and snowmelt can influence spatial and temporal changes of water
resource of the Tarim River basin. Furthermore, complicated interplay can be expected between driving factors.
Increasing temperature may cause increasing snowmelt
and increasing precipitation may also give rise to
increasing area of glacier. It should be noted there that the
Tarim River basin is characterized by the extreme arid
climate with an annual rainfall of less than 50 mm but the
potential evaporation of more than 2,000 mm (Xu et al.
2004). Therefore, increasing temperature may cause
increasing evaporation and which may cause decreasing
loss of streamflow. Human activities, e.g. human withdrawal of water, irrigation, and so on, will further alter
availability of water resource. Large-scale anthropogenic
Stoch Environ Res Risk Assess (2010) 24:349–358
activities such as agriculture irrigation and random reclamation in the upper and middle reaches of the Tarim
River have triggered the disintegration of the natural
hydrology (Tao et al. 2008). However, increasing precipitation in the headwater source, to a certain degree,
may mitigate deficit of water resource in the Tarim River
basin. This will definitely benefit the development of local
agriculture activities. However, extensive agricultural
activities caused increasing diversion of the freshwater to
the new reclamation land. Therefore, the increasing
streamflow in the headwater of the Tarim River basin
may not satisfy the water demand of human activities,
particularly the agricultural development, in the middle
and lower Tarim River basin. Thus, it still calls for scientific, sound and effective water resource management
on the river basin scale aiming to cater for the booming
development of agriculture and fast population growth.
Investigation on the relationship between climate changes
and the availability of water resources is beneficial for the
efficient water resources management (Bordi and Sutera
2001). The results of this paper may provide scientific
framework for basin-scale water resource management
and human mitigation to water resource variability under
the changing environment in the Tarim River basin.
Acknowledgments The work described in this paper was financially supported by the ‘985 Project’ (Grant No.: 37000-3171315),
the innovative project from Nanjing Institute of Geography and
Limnology, CAS (Grant No.: CXNIGLAS200814), National Scientific
and Technological Support Program (Grant No.: 2007BAC03A0604),
Key Laboratory of Oasis Ecology and Desert Environment, Xinjiang
Institute of Ecology and Geography, CAS (Grant No.: 05710401), and
by Program of Introducing Talents of Discipline to Universities—the
111 Project of Hohai University. Cordial thanks should be extended to
the editor-in-chief, Prof. Dr. George Christakos and two anonymous
reviewers for their constructive suggestions and comments which
greatly helped to improve the quality of this paper.
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