Meteorol Atmos Phys (2015) 127:273–288
DOI 10.1007/s00703-014-0360-2
ORIGINAL PAPER
Variations of annual and seasonal runoff in Guangdong Province,
south China: spatiotemporal patterns and possible causes
Qiang Zhang • Mingzhong Xiao • Vijay P. Singh
Chong-Yu Xu • Jianfeng Li
•
Received: 2 March 2014 / Accepted: 25 November 2014 / Published online: 4 December 2014
Springer-Verlag Wien 2014
Abstract In this study, we thoroughly analyzed spatial
and temporal distributions of runoff and their relation with
precipitation changes based on monthly runoff dataset at 25
hydrological stations and monthly precipitation at 127
stations in Guangdong Province, south China. Trends of the
runoff and precipitation are detected using Mann–Kendall
trend test technique. Correlations between runoff and precipitation are tested using Spearman’s and Pearson’s correlation coefficients. The results indicate that: (1) annual
maximum monthly runoff is mainly in decreasing tendency
Responsible Editor: C. Simmer.
Q. Zhang (&) M. Xiao
Department of Water Resources and Environment,
Sun Yat-sen University, Guangzhou 510275, China
e-mail: zhangqnj@gmail.com; zhangq68@mail.sysu.edu.cn
Q. Zhang M. Xiao
Key Laboratory of Water Cycle and Water Security in Southern
China of Guangdong High Education Institute, Sun Yat-sen
University, Guangzhou 510275, China
Q. Zhang
School of Earth Sciences and Engineering, Suzhou University,
Anhui 234000, China
V. P. Singh
Department of Biological and Agricultural Engineering and
Zachry Department of Civil Engineering, Texas A&M
University, College Station, Texas, USA
C.-Y. Xu
Department of Geosciences, University of Oslo, P O Box 1047,
Blindern, 0316 Oslo, Norway
J. Li
Department of Geography and Resource Management, and
Institute of Environment, Energy and Sustainability, The
Chinese University of Hong Kong, Hong Kong, China
and significant increasing annual minimum monthly runoff
is observed in the northern and eastern Guangdong Province. In addition, annual mean runoff is observed to be
increasing at the stations located in the West and North
Rivers and the coastal region; (2) analysis of seasonal
runoff variations indicates increasing runoff in spring,
autumn and winter. Wherein, significant increase of runoff
is found at 8 stations and only 3 stations are dominated by
decreasing runoff in winter; (3) runoff changes of the
Guangdong Province are mainly the results of precipitation
changes. The Guangdong Province is wetter in winter,
spring and autumn. Summer is coming to be drier as
reflected by decreasing runoff in the season; (4) both precipitation change and water reservoirs also play important
roles in the increasing of annual minimum monthly
streamflow. Seasonal shifts of runoff variations may pose
new challenges for the water resources management under
the influences of climate changes and intensifying human
activities.
1 Introduction
Climate variability and change characterized by global
warming exert tremendous influences on our planet, and it is
also the case for the hydrological cycle (IPCC 2007). Arnell
(1999) indicates that under the influences of global warming, the hydrological cycle will be intensified with more
evaporation and more precipitation and the extra precipitation will be unequally distributed around the globe,
resulting in more frequent floods and droughts. Some
researches tend to advocate that the present warming tendency led to changes of the global hydrological cycle and to
the amplitude of the increase of global and continental
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274
runoff (e.g., Labat et al. 2004; Semenov and Bengtsson
2002). Projected global climate changes will probably further accelerate the global hydrological cycle, and which in
turn will alter the spatiotemporal patterns of the flood/
drought hazards in both the global and the regional scales.
Previous studies have shown that under the influence of the
well-evidenced global warming situation, precipitation
patterns are expected to change and extreme weather events
(e.g., floods, droughts, and rainstorms) are likely to occur
more frequently (WMO 2003). This situation is worsening
by the sharp increase in water consumption owing to the
population explosion, unprecedented rise in standard of
living, and enormous economic development (Xu and Singh
2004).
The hydrologic regime of a stream under specific geomorphic conditions represents the integrated basin response
to various climatic inputs, with precipitation and temperature being very important ones (Zhang et al. 2001).
Investigations of statistical properties of runoff variations
are critical for evaluation of regional availability and variability of water resources and have been attached considerable importance (Zhang et al. 2001; Burn and Elnur
2002; Birsan et al. 2005; George 2007; Brabets and Walvoord 2009). Yang and Tian (2009) indicate that runoff in
Haihe River basin of China is steadily declining due to
climate change and human activity. Annual runoff and
annual sediment load of the Yangtze River basin were
systematically studied using Mann–Kendall trend method.
Increasing annual runoff, especially in the lower Yangtze
River basin was identified (Zhang et al. 2006). Zhang et al.
(2009a) indicate that the runoff of the Yellow River basin
is decreasing and water resource deficit tends to be more
serious from the upper to the lower Yellow River basin.
Zhang et al. (2008) analyzed annual water discharge and
sediment load series (from the 1950 to 2004) at nine stations in the main channels and main tributaries of the
Zhujiang (Pearl River), demonstrating that water discharges at all stations in the Zhujiang Basin show no significant trend or abrupt shift. Annual water discharges in
the Pearl River basin are mainly influenced by precipitation
variability. However, Lu (2004) indicates that water discharge in most Chinese rivers has experienced great
changes due to climate change and anthropogenic impacts
in the drainage basins.
Guangdong Province involves the Pearl River Delta and
the lower Pearl River basin, being the highly developed
region in terms of social economy in China. Thorough
evaluation of the availability and changes of water
resources, in particular runoff, across the Guangdong
Province, is of great scientific and practical merits, and the
importance and significance of this current study are evident. However, to the best of our knowledge, changing
properties of runoff in both time and space in the region
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Q. Zhang et al.
have not been thoroughly investigated. This is the major
motivation of this study. Therefore, the major objective of
this study is to analyze trends in various discharge
parameters observed at 25 hydrological stations over the
past 31–45 years across the Guangdong Province. Possible
underlying causes behind the runoff variations are also
discussed.
2 Data
Seven data series, i.e., annual maximum and minimum
monthly runoff, annual and seasonal mean runoff at 25
hydrological stations are selected for analysis. The detailed
information of the dataset is displayed in Table 1. The
locations of the discharge stations can be shown in Fig. 1.
In the hydrological data, there is no missing data. To
investigate possible influences of climate changes and
human activities, precipitation from 127 rain stations and
the information of the large- and middle-size water reservoirs covering 1956–2000 are collected. The locations of
the precipitation stations are also illustrated in Fig. 1. The
precipitation and discharge data before 1989 are extracted
from the Hydrologic Year Book (published by the
Hydrologic Bureau of the Ministry of Water Resources of
China) and those after 1989 are provided by the Hydrological Bureau of Guangdong Province. Missing data in the
precipitation dataset, accounting for \0.01 % of the total
data, were found in March during 2001–2008 and were
filled in with average values of neighboring months (Zhang
et al. 2011). Xinfengjiang Reservoir and Fengshuba Reservoir are also taken into account to tentatively study the
influences of the construction and operation of water reservoirs on the streamflow. Both reservoirs locate in the East
River basin, a highly developed water basin in the south
China. Table 2 displays the details about these two reservoirs. The information of reservoirs is extracted from the
previous study (Zhou et al. 2012).
3 Methodology
There are many statistical techniques available to detect
trends within the time series such as moving average, linear
regression, Mann–Kendall trend test (M–K), and filtering
technology. Each method has its own strength and weakness in terms of detection of trends. However, non-parametric trend detection methods are less sensitive to outliers
than parametric statistics. In addition, the rank-based
non-parametric M–K test (Mann 1945; Kendall 1975) can
test trends without requiring normality or linearity (Wang
and Zhou 2005). Therefore, this method was highly recommended for general use by the World Meteorological
Variations of annual and seasonal runoff in Guangdong Province
Table 1 Detailed information
of hydrological data analyzed in
this study and major statistical
properties of streamflow series
in the study region
No.
275
Drainage
area (km2)
Length of
streamflow
series
Annual streamflow
23.03
351,535
1956–2000
2,217.05
0.19
23.34
8,273
1956–2000
81.80
0.26
Hydrological
stations
Long.
1
Gaoyao
112.28
2
Gulan
111.41
3
Guanliang
111.40
22.50
3,164
1956–2000
26.30
0.28
4
Yaogu
113.41
24.52
1,776
1959–2000
16.76
0.28
5
Lishi
113.16
23.51
6,976
1956–2000
60.46
0.30
6
Changba
112.57
23.34
6,794
1956–2000
60.60
0.28
7
8
Gaodao
Hengshi
113.32
113.10
24.53
24.09
9,007
34,013
1956–2000
1956–2000
106.54
344.80
0.26
0.26
9
Shijiao
115.15
24.07
38,363
1956–2000
421.20
0.25
10
Longchuan
114.42
23.44
7,699
1956–2000
64.38
0.30
11
Heyuan
114.18
23.10
15,750
1956–2000
148.31
0.27
12
Boluo
113.51
23.21
25,325
1956–2000
237.42
0.24
13
Hengshan
112.48
23.07
12,624
1956–2000
100.70
0.30
14
Shuikou
112.50
23.10
6,480
1956–2000
51.01
0.29
15
Xikou
115.54
23.59
9,228
1956–2000
87.62
0.25
16
Chao’an
116.21
24.28
29,077
1956–2000
252.12
0.26
17
Ciyao
116.39
23.40
820
1956–2000
11.03
0.33
18
Jiaokeng
116.39
24.32
1,104
1956–2000
19.14
0.27
19
Dongqiaoyuan
116.08
23.29
2,016
1956–2000
27.80
0.27
20
Shuangjie
116.01
23.05
4,345
1956–2000
58.95
0.28
21
Huazhou
115.38
23.02
6,151
1956–2000
49.20
0.32
22
23
Gangwayao
Qilinzui
111.48
110.38
21.57
21.39
3,086
2,866
1970–2000
1956–2000
17.55
38.31
0.46
0.29
24
Sanshui
110.04
21.30
–
1959–2000
437.78
0.37
25
Makou
112.17
22.52
–
1959–2000
2,321.45
0.17
Organization (Mitchell et al. 1966). This paper also uses
the M–K test method to analyze trends within the runoff
series over the Guangdong Province. It should be noted
here that the result of the M–K test is heavily affected by
serial correlation of the time series. To eliminate the effect
of serial correlation on M–K results, von Storch and Navarra (1995) suggested the ‘‘pre-whitened’’ technique in the
removal of effects of serial correlation before M–K analysis. Following Zhang et al. (2001), the statistically significant trend of the runoff series (x1, x2, x3, …, xn) is
detected by following the procedure: (1) Compute the lag-1
serial correlation q1; (2) if q1 \ 0.1, the M–K test is
applied to the time series directly; otherwise, (3) the M–K
test is applied to the ‘‘pre-whitened’’ time series, i.e.,
x2 -q1x1, x3 -q1x2, …, xn -q1xn-1. The confidence level
of 95 % is used to evaluate the significance of the trends,
and the trend analysis was done on the entire period.
To quantitatively evaluate the relations between runoff
and precipitation variables, Spearman’s rank correlation
analysis and Pearson’s correlation analysis are performed
on the areal average precipitation and runoff variations.
The Spearman rank correlation coefficient can be used to
Lat.
Mean (108 m3)
Cv
measure monotone association of two variables when the
distribution of the data makes Pearson’s correlation coefficient undesirable or misleading.
Mann–Whitney U test, also called Wilcoxon rank-sum
test, is a non-parametric statistical test (Mann and Whitney
1947). Let f and g be the continuous cumulative distribution functions of two random variables x and y, respectively. The Mann–Whitney U test is to test the null
hypothesis f = g against the alternative that x is stochastically smaller than y. The Mann–Whitney U test is used to
assess whether the distributions of streamflow series before
and after water reservoir construction are different, which
indicates whether the construction of water reservoir alters
the statistical behaviors of streamflow.
4 Results
4.1 Seasonal patterns of precipitation and runoff
The mean annual precipitation for the study period
(1956–2000) is about 1,500–2,000 mm in the region.
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Q. Zhang et al.
Fig. 1 Location of the study
region, the hydrological stations
(triangles) and the rain stations
(dots) over the Guangdong
Province
Table 2 Detailed information of reservoirs
Reservoir
Construction
time
Drainage
area (km2)
Storage capacity
(billion m3)
Xinfengjiang
1958–1962
5,740
13.98
Fengshuba
1970–1974
5,150
1.94
Precipitation mainly occurs between April and September.
Figure 2 illustrates the distribution of streamflow at Gaoyao station (No. 1 hydrological stations in Fig. 1). Figure 2a shows that higher runoff is found between April and
September, particularly during June and August. Occurrence of high runoff is in good line with rainy season
(Fig. 2b). More detailed examination of the relation
between precipitation and discharge is provided in the
discussion section.
4.2 Trends of annual maximum/minimum runoff
and annual mean runoff
In this study, the trends of annual maximum/minimum
runoff and annual mean runoff have been analyzed. The
spatial distribution of the temporal trend of annual minimum monthly runoff, i.e., the smallest monthly runoff of
1 year is demonstrated in Fig. 3. It can be observed from
figure that the Guangdong Province is dominated by
increasing annual minimum monthly runoff. Decreasing
annual minimum monthly runoff, but non-significant at
[95 % confidence level, can be found at two stations, i.e.,
Makou and Ciyao stations. Increasing annual minimum
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monthly runoff is observed at 23 stations, accounting for
92 % of the total stations considered in this study. Significant increasing trends can be detected at 9 stations,
accounting for 36 %. Stations with significant increasing
annual minimum monthly runoff are found mainly in the
eastern and northern Guangdong Province (Fig. 3). Specifically, significant increasing trend of annual minimum
monthly runoff can be found in the upper East River, upper
North River, and eastern Guangdong Province.
Annual maximum monthly runoff changes over the
Guangdong Province (Fig. 4) are not statistically significant. Insignificant decreasing annual maximum monthly
runoff can be found along the coastal regions of the
Guangdong Province and in the East River basin. In total
18 stations are characterized by decreasing annual maximum monthly runoff, accounting for 72 %. Figure 3
(increasing annual minimum monthly runoff) and Fig. 4
(decreasing annual maximum monthly runoff) show that
the runoff variations over Guangdong Province have a
decreasing degree of dispersion, except at the stations
located in the northeastern Guangdong Province. Annual
mean runoff variations are illustrated in Fig. 5. It can be
seen from Fig. 5 that the eastern and northern Guangdong
Province is dominated by insignificant increasing annual
runoff, while opposition is true in the western Guangdong
Province. Specifically, annual mean runoff in the East
River basin and the North River basin is characterized by
increasing tendency. However, these increasing or
decreasing trends are non-significant at [95 % confidence
level.
Variations of annual and seasonal runoff in Guangdong Province
8
A
Streamflow (106 m3)
7
6
5
4
3
2
1
0
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
Month
600
Precipitation (mm)
500
B
400
300
200
100
0
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
Month
Fig. 2 Monthly allocation of streamflow at the Gaoyao station (a),
and of areal mean precipitation in Guangdong Province (b)
4.3 Trends of seasonal runoff
Figure 6 demonstrates spatial distributions of temporal
trends of runoff in spring (Fig. 6a) and autumn (Fig. 6b).
Generally, the Guangdong Province is dominated by
increasing runoff in these two seasons. Runoff series at one
station only, i.e., Sanshui station, is in significant increasing
trend. Only 4 stations are characterized by insignificant
decreasing trend in spring, accounting for 16 % of the total
stations. The hydrological stations dominated by increasing
runoff account for 84 %, though most of them are insignificant. Decreasing runoff in spring is found at the stations
located along the coastal regions of the Guangdong Province. Runoff variation patterns in spring are similar with
those of the annual mean runoff changes (Figs. 5, 6a).
Increasing runoff in spring is observed mainly in the eastern,
northern and northwestern Guangdong Province. Specifically, increasing runoff in spring can be found in the upper
East River, upper North River, and eastern Guangdong
Province. In autumn, there are 18 stations dominated by
277
increasing runoff, accounting for 72 % of the total hydrological stations studied in this study, and 3 of them are
dominated by significant increasing runoff trends (Fig. 6b).
In autumn, increasing runoff can be identified mainly in the
northern and eastern Guangdong Province, particularly in
the East and North River basins. Decreasing runoff can be
found mainly in the western Guangdong Province.
Spatial distribution of runoff changes in summer is
illustrated in Fig. 7a. The majority of Guangdong Province
is featured by insignificant decreasing summer runoff.
There are 17 hydrological stations characterized by insignificant decreasing summer runoff, accounting for 68 % of
the total stations considered in this study. Specifically, the
East River basin, the North River basin and the coastal
region are characterized by decreasing summer runoff.
Increasing summer runoff can be identified mainly in the
tributaries of the North River and in the northeastern corner
of the Guangdong Province. Runoff variations in winter
present distinctly different patterns in comparison with
those in summer (Fig. 7a, b). Decreasing winter runoff, but
not statistically significant, can be detected at only three
stations, i.e., Ciyao, Shuangjie and Makou (Fig. 7b). The
remaining 22 stations are dominated by increasing winter
runoff, accounting 88 % of the total hydrological stations.
In addition, eight stations are dominated by significant
increasing winter runoff, accounting for 32 %. Stations
characterized by significant increasing winter runoff are
found mainly in the West River basin, the East River basin
and in the eastern Guangdong Province.
The monthly runoff variations are also anatomized and
the results are shown in Fig. 8. It can be observed from
Fig. 8a that percentage of stations characterized by
increasing monthly runoff is the smallest in May and June.
The larger percentages of stations dominated by increasing
monthly runoff are found in December, January, February,
March and April, i.e., winter and spring in this study region.
Percentage of the stations with increasing monthly runoff is
moderate in August, September, October and November.
Percentage of stations featured by decreasing runoff is in
adverse changing patterns when compared to that of the
stations featured by increasing runoff. As for percentage of
stations dominated by significant runoff changing trends,
Fig. 8b shows that larger percentage of stations can be
found mainly in December, January, February, March, and
April. Smaller percentage of hydrological stations having
significant changing trend is observed in summer, particularly in May to August. Figure 8c shows that the percentages of stations characterized by the increasing trends of
monthly precipitation distribute very similar with Fig. 8a.
The large percentages are also found in December, January,
February, March, and April, and smaller percentages are
observed in May and June. In September, October, and
November, more increasing trends of monthly runoff are
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278
Q. Zhang et al.
Fig. 3 Spatial distributions of
trends of minimum monthly
streamflow changes across the
Guangdong Province. Filled up
triangles significant increasing
trend; open up triangles nonsignificant increasing trend;
filled inverted triangles
significant decreasing trend;
open inverted triangles nonsignificant decreasing trend
Fig. 4 Spatial distributions of
trends of maximum monthly
streamflow changes across the
Guangdong Province. Filled up
triangles significant increasing
trend; open up triangles nonsignificant increasing trend;
filled inverted triangles
significant decreasing trend;
open inverted triangles nonsignificant decreasing trend
found (Fig. 8a). However, as for monthly precipitation,
more decreasing trends are found (Fig. 8c). A few stations
have significant trends of monthly precipitation (Fig. 8d).
The percentages of significant increasing trends peak in
April, and those of significant decreasing trends peak in
June. The percentages of significant decreasing trends of
monthly runoff and precipitation both peak in June,
123
indicating that the decreasing of precipitation is important
factor of the decreasing of runoff. As for the disparity in
autumn (September, October, and November), it may be
explained by the operation of water reservoirs. The water
reservoirs usually discharge water into river in autumn,
which increases the runoff in autumn even though the
precipitation decreases.
Variations of annual and seasonal runoff in Guangdong Province
279
Fig. 5 Spatial distributions of
trends of annual streamflow
changes across the Guangdong
Province. Filled up triangles
significant increasing trend;
open up triangles nonsignificant increasing trend;
filled inverted triangles
significant decreasing trend;
open inverted triangles nonsignificant decreasing trend
4.4 Case study of impacts of large water reservoirs
on streamflow in the East River
To analyze the possible impacts of water reservoirs on
runoff, how Xinfengjiang Reservoir and Fengshuba Reservoir influenced the runoff in Longchuan, Heyuan, and Boluo
stations is analyzed. It should be noted that Longchuan
station is in the downstream of Fengshuba Reservoir, but the
upstream of Xinfengjiang Reservoir, and the other two stations are in the downstream of both reservoirs. Zhou et al.
(2012) split the whole streamflow series into three segments
(1954–1957, 1963–1969, 1975–2009) to study the impacts
of Fengshuba Reservoir and Xinfengjiang Reservoir
according to their construction periods. In this study, as
Longchun station is only regulated by the Fengshuba Reservoir, its streamflow series is divided into two segments
(1956–1969, 1975–2000); as the other two stations are
influenced by both Fengshuba Reservoir and Xinfengjiang
Reservoir, their series are divided into three segments
(1956–1957, 1963–1969, 1975–2005). Mann–Whitney
U test is applied to assess whether or not the distributions of
the continuous two segments are different. The results of the
Mann–Whitney U test are listed in Table 3. In Table 3, the
change point ‘‘1975’’ denotes the distributions of 1963–1969
and 1975–2005 are significantly different, which was the
result of the construction of Fengshuba Reservoir. Change
point of annual streamflow is detected only in Heyuan, while
there are no change points for the other two stations. The
constructions of two reservoirs did not cause significant
alterations in the maximum monthly streamflow, as no
change point is detected in all three stations. However, the
minimum monthly streamflow in these three stations is
remarkably influenced by the constructions of the Fengshuba
Reservoir. No change point in 1963, caused by the
Xinfengjiang Reservoir, is detected. The absence of change
point in ‘‘1963’’ should be paid attention, because the
streamflow data before the construction of Xinfengjiang
Reservoir are very limited, which makes the results less
reliable. The results indicate that the large reservoir in the
East River had no impacts on the maximum monthly
streamflow, but had significant impacts on the minimum
monthly streamflow. Only annual streamflow in Heyuan
changed due to water reservoirs. The case study in the East
River sheds light on how the reservoirs influenced the
streamflow in south China.
5 Discussions
Runoff variations are the integrated results of geomorphological conditions of the river basin, precipitation changes,
human activities such as withdrawal of freshwater and
building of water reservoirs, land use changes and so on. To
confirm the important role played by precipitation variations, we first analyze spatial distribution of precipitation
changes (Fig. 9). Annual maximum monthly precipitation is
decreasing across the study region (Fig. 9a). Most of the
decreasing trends are insignificant, but four stations in the
middle of Guangdong have significant decreasing trends.
Few stations with increasing annual maximum monthly
precipitation distribute sporadically over the Guangdong
Province. Similar changing properties are identified in the
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280
Q. Zhang et al.
Fig. 6 Spatial distributions of
trends of seasonal streamflow
changes across the Guangdong
Province in spring (a) and
autumn (b), respectively. Filled
up triangles significant
increasing trend; open up
triangles non-significant
increasing trend; filled inverted
triangles significant decreasing
trend; open inverted triangles
non-significant decreasing trend
spatial distribution of summer precipitation changes
(Fig. 9d). Precipitation changes in winter (dry) season
(Fig. 9f) show different changing characteristics when
compared to those in summer. East Guangdong Province is
dominated by insignificant increasing precipitation. Regions
covered by stations characterized by increasing annual
monthly minimum precipitation extend to 112E in comparison with those in winter (Fig. 9b, f). More stations are
characterized by increasing, but non-significant precipitation
123
in spring (Fig. 9c) than in other seasons (Fig. 9d–f). Autumn
is featured by insignificant decreasing precipitation
(Fig. 9e). Although most of the trends are insignificant, the
spatial distribution of runoff is largely in good agreement
with that of precipitation changes, and it is particularly the
case for the runoff changes in winter.
In addition, we present the temporal variations of areal
average runoff and precipitation series (Fig. 10). The runoff and precipitation series are standardized with 0 mean
Variations of annual and seasonal runoff in Guangdong Province
281
Fig. 7 Spatial distributions of
trends of seasonal streamflow
changes across the Guangdong
Province in summer (a) and
winter (b), respectively. Filled
up triangles significant
increasing trend; open up
triangles non-significant
increasing trend; filled inverted
triangles significant decreasing
trend; open inverted triangles
non-significant decreasing trend
and unit standard deviation. Figure 10 clearly displays
generally consistent changing properties of precipitation
and runoff, showing considerable impacts of precipitation
on runoff variations. It is particularly true for the relations
between annual precipitation and annual runoff. To evaluate quantitatively the relations between runoff and precipitation, we analyze the Spearman’s rank correlations
coefficients and Pearson’s correlation coefficients of these
two variables, i.e., precipitation and runoff (Table 4). It can
be observed from Table 4 that the Spearman’s correlation
coefficients are all significant at [95 % confidence level
except between annual minimum monthly runoff and precipitation, while the Pearson’s correlation coefficient is
significant in all the cases. But the Pearson’s correlation
coefficient between annual minimum monthly runoff and
precipitation is also the smallest.
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282
Q. Zhang et al.
Fig. 8 Percentage of stations
showing increasing and
decreasing trends of monthly
streamflow (a), those showing
significant (at the 5 % level)
increasing and decreasing trends
of monthly streamflow (b),
those showing increasing and
decreasing trends of monthly
precipitation (c), and those
showing significant (at the 5 %
level) increasing and decreasing
trends of monthly precipitation
(d)
Table 3 Change points between continuous segments in Longchuan,
Heyuan and Boluo
Annual
streamflow
Maximum monthly
streamflow
Minimum
monthly
streamflow
Longchuan
N/A
N/A
1975
Heyuan
1975
N/A
1975
Boluo
N/A
N/A
1975
N/A no change point is detected
123
The linear relations between areal average precipitation
and runoff after being standardized are studied (Fig. 11).
R2 of maximum values, spring and summer are above 0.8,
indicating that precipitation and runoff are closely correlated. Whereas most correlations are positive, the relationship of minimum values is negative, whose R2 is only
0.009. Furthermore, Fig. 12 is double mass curves of areal
average precipitation and runoff before being standardized.
The relations between precipitation and runoff of the whole
series of annual maximum monthly series, spring, and
Variations of annual and seasonal runoff in Guangdong Province
283
Fig. 9 Spatial patterns of precipitation variables over the Guangdong Province. Filled up triangles significant increasing trend; open up triangles
non-significant increasing trend; filled inverted triangles significant decreasing trend; open inverted triangles non-significant decreasing trend
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Q. Zhang et al.
Fig. 10 Temporal variations of
areal average runoff and
precipitation variables across
the Guangdong Province
2
3
Annual maximum monthly series
Annual minimum monthly series
2
1
0
0
−2
−1
1960
1970
1980
4
1990
2000
1960
1970
1980
2
Spring
1990
2000
Summer
2
0
0
−2
1960
1970
1980
3
2
1
0
−1
1990
−2
2000
1960
1970
1980
4
Autumn
1990
2000
Winter
2
0
1960
1970
1980
1990
2000
1960
1970
1980
1990
2000
2
Annual
Runoff
Precipitation
0
−2
1960
1970
1980
1990
2000
Table 4 Spearman’s rank correlation coefficients and Pearson’s correlation coefficients between areal average runoff and precipitation variables
Correlation
AM
Am
Spring
Summer
Autumn
Winter
Annual
Spearman
0.822
0.077*
0.890
0.747
0.697
0.622
0.887
Pearson
0.829
0.336
0.849
0.828
0.710
0.785
0.932
AM annual maximum monthly series (runoff or precipitation series), Am annual minimum monthly series (runoff or precipitation series)
* Correlation coefficient is non-significant at [95 % confidence level
Fig. 11 Streamflow vs.
precipitation relations over the
Guangdong Province
5
10
Maximum values
Streamflow (m3/s)
−5
−2
10
0
1
2
3
Spring
−4
−2
0
2
4
−2
Winter
−1
0
1
2
y=0.44x−0.68
R2=0.35
0
1
2
3
4
5
Annual y=0.98x−0.98
R =0.67
−2
−1
0
Precipitation (mm)
1
2
−10
−6
0
2
4
0
2
y=1.12x−2.39
R2=0.59
0
2
−5
−3
−2
y=0.81x+0.33
2
R =0.92
−5
−4
10
Autumn
0
−3
0
y=1.18x−0.74
R2=0.88
0
−5
−1
5
123
−10
−4
5
Summer
0
−10
−6
5
0
y=1.1x+0.51
R2=0.83
−1
y=−0.18x−4.69
R2=0.009
Minimum values
0
−4
−2
Variations of annual and seasonal runoff in Guangdong Province
285
Fig. 12 Double mass curves of
precipitation and runoff
variables across the Guangdong
Province
summer are in good agreement. Nevertheless, in the annual
minimum monthly series, the relationship of cumulative
precipitation and runoff is not so stable, and there is an
abrupt disturbance in the middle. This result is correspondent with Fig. 11.
Results of this study indicate that annual minimum
monthly precipitation and precipitation in winter increase
in the east Guangdong Province, though this increase is not
statistically significant. Precipitation in summer and annual
maximum monthly values are prevailingly decreasing.
Similar patterns can be identified in runoff variation in both
space and time. Zhang et al. (2009b) indicate that the
number of wet months in rainy season (April–September)
is decreasing; the number of wet months in winter (JFD) is
increasing, implying that the Pearl River basin tends to be
drier in the rainy season and comes to be wetter in winter.
123
286
The analysis results of precipitation and runoff variations
in this current study further corroborate the results by the
previous study (Zhang et al. 2009b). Besides, different
wetting and drying properties can be identified across the
basin: West parts of the basin tend to be drier; and southeast parts tend to be wetter (Zhang et al. 2009b).
In the Guangdong Province, the wetting tendency is
mainly reflected by increasing annual mean runoff, though
the increasing trends are non-significant statistically.
However, significant increasing annual minimum runoff
and also increasing runoff in December, January, February,
March, and November further corroborate the wetting
tendency of the winter, spring and autumn. Moisture content analysis based on NCAR/NCEP reanalysis dataset
indicated that increasing moisture content gives rise to an
increasing number of wet months in winter (Zhang et al.
2009b). In addition, we also investigated moisture budget,
moisture flux in the Pearl River basin and their influences
on the runoff variations and precipitation changes (Zhang
et al. 2009b). The results indicated close relations between
water vapor flux, precipitation and runoff, and which may
imply that the altered hydrological cycle in the Pearl River
basin is mainly manifested by seasonal shifts of water
vapor flux after early 1960s, and hence the seasonal transition of wet and dry conditions across the Pearl River
basin. The foregoing research results can greatly help to
clarify the circulation background of the runoff variations
in the Guangdong Province. Seasonal shifts of runoff may
be a new challenge for the water resource management in
the Guangdong Province.
Generally, precipitation changes are the major causes
behind the runoff changes in both time and space. Analysis
results of this study indicate that minimum monthly runoff is
increasing. Runoff in winter is also in increasing tendency
and some stations are dominated by significant increasing
runoff. However, the relations between precipitation and
runoff variables are not consistently even in both space and
time. Weaker correlation coefficients between annual minimum monthly runoff and precipitation imply other factors
besides precipitation exerting influences on the runoff variations. Most rivers in the Guangdong Province are within the
territory of the study region and only few stations control
flows from the outside of the Guangdong Province (Fig. 1),
which are excluded in the calculation of correlation coefficient between precipitation and runoff. Thus, it is not reasonable to attribute runoff changes for influencing factors
outside of the Guangdong Province.
Up to the end of 2000, about 175 mid- to large-size
water reservoirs had been built in the Guangdong Province
with the regulating storage capacity of more than 28.95
billion cubic meters. These reservoirs have the potential to
change annual and seasonal location of streamflow variations. Water reservoirs may have altered the hydrological
123
Q. Zhang et al.
regimes. The case study in the East River shows that water
reservoirs make tremendous influences on the minimum
monthly streamflow. Thus, the increasing of minimum
monthly streamflow should be affected by both the precipitation changes and the water reservoirs. On the other
hand, water reservoirs have no influence on the maximum
monthly streamflow and little influence on the annual
streamflow.
The comparisons between the influences of precipitation
changes and reservoir constructions on the runoff indicate
that the precipitation changes are the primary causes for the
variability of the annual streamflow and the maximum
monthly streamflow, while both precipitation changes and
reservoir constructions altered the minimum monthly
streamflow. This study shows that precipitation changes are
still the main causes for the temporal and spatial variability
of runoff in the region.
6 Conclusions
Spatial and temporal distributions of runoff variations are
thoroughly analyzed using statistical techniques, Mann–
Kendall trend test in this study, based on monthly runoff
dataset at 25 hydrological stations in the Guangdong
Province. Possible impacts of precipitation changes on
streamflow changes across the Guangdong Province are
also investigated and compared with previous research
results. Some interesting and important conclusions are
drawn as follows:
1.
2.
Increasing annual minimum monthly runoff is
observed at a majority of the stations. Decreasing
annual maximum runoff is found at the hydrological
stations located along the coast regions of the Guangdong Province. Besides, increasing annual mean runoff
is observed at most of the hydrological stations,
particularly in the northern and eastern Guangdong
Province, specifically in the East River basins. In this
sense, we can conclude that the Guangdong Province is
getting wetter, but less extreme.
Investigation of trends of seasonal runoff indicates
increasing runoff in spring, autumn and winter.
Summer is dominated by decreasing runoff though
the trends are not statistically significant. Decreasing
runoff is observed mainly at the stations located along
the coastal regions, particularly in the southwestern
corner of the Guangdong Province. More stations are
characterized by significant increasing runoff in January, February, March, November and December than
in other months. Therefore, the wetting tendency is
detected mainly in winter, and also in spring and
autumn; however, the summer is coming to be drier.
Variations of annual and seasonal runoff in Guangdong Province
3.
4.
The dominating seasonal pattern in this region is that
the runoff is usually higher in summer than that in
winter. However, the results of this study indicate
seasonal shifts of the runoff variations. The runoff
changes are subject to large-scale circulation of
moisture flux and also moisture budget over the Pearl
River basin. Our previous analysis (Zhang et al. 2009b)
indicates a general wetting tendency in the lower Pearl
River basin, including the Guangdong Province considered in this study, which was well reflected by
increasing annual mean runoff, though annual maximum monthly runoff is decreasing. Significant increasing annual minimum monthly runoff may contribute
much to the wetting tendency of the Guangdong
Province and also the operations of water reservoirs
which usually discharge water into their lower rivers in
the dry season when annual minimum monthly runoff
most likely occurs. Increasing moisture content in
winter and decreasing moisture in summer are the
circulation background causing the seasonal shifts of
precipitation changes, dryness/wetness conditions and
also the runoff variations. Seasonal shifts of runoff
may pose new challenges for the water resources
management in the Guangdong Province, one of the
economically prosperous regions in China.
Precipitation changes are the major factors exerting
tremendous influences on runoff variations in both
space and time, which is reflected mainly by significant
correlation coefficients. Weaker correlation coefficient
between annual minimum monthly runoff and precipitation may indicate other factors played a role. The
water reservoir is another important factor, as in the
East River, significant change points in annual minimum monthly runoff are detected after the construction of the Fengshuba Reservoir. Nevertheless, more
comprehensive and systematical studies about the
influences of water reservoirs on runoff in the whole
South China should be carried out in the future. Hence,
we can tentatively conclude that the runoff changes in
the Guangdong Province are mainly controlled by
precipitation changes.
Acknowledgments This work is financially supported by the Key
International Collaboration Project (Grant No.: 51320105010), the
Leading Expert Program of Anhui Province, China, and is fully
supported by a grant from the Research Grants Council of the Hong
Kong Special Administrative Region, China (Project No.
CUHK441313). Our cordial gratitude is also extended to the editor,
Prof. Dr. Clemens Simmer, and also three anonymous reviewers for
their professional and pertinent comments and suggestions which are
greatly helpful for further improvement of the quality of this manuscript. Besides, we again owe our special thanks to the editor, Prof.
Dr. Clemens Simmer, for his hard work and his great efforts in processing this manuscript.
287
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