Theor Appl Climatol (2014) 115:703–712
DOI 10.1007/s00704-013-0916-y
ORIGINAL PAPER
Spatiotemporal variations of precipitation regimes
across Yangtze River Basin, China
Qiang Zhang & Juntai Peng & Chong-Yu Xu & Vijay P. Singh
Received: 20 February 2013 / Accepted: 22 April 2013 / Published online: 26 May 2013
# Springer-Verlag Wien 2013
Abstract Daily precipitation data during the period of 1960
to 2005 from 147 rain gauging stations over the Yangtze
River Basin are analyzed to investigate precipitation variations based on precipitation indices and also consecutive
rainfall regimes in both space and time. Results indicate
decreasing annual/monthly mean precipitation. Distinct decreases in rainfall days are observed over most parts of the
Yangtze River Basin, but precipitation intensity is increasing
over most parts of the Yangtze River Basin, particularly the
lower Yangtze River Basin. Besides, durations of precipitation regimes are shortening; however, the fractional contribution of short-lasting precipitation regimes to the total
precipitation amount is increasing. In this sense, the precipitation processes in the Yangtze River Basin are dominated
by precipitation regimes of shorter durations. These results
indicate intensified hydrological cycle reflected by shortening precipitation regimes. This finding is different from that
in Europe where the intensifying precipitation changes are
Q. Zhang : J. Peng
Department of Water Resources and Environment, Sun Yat-sen
University, Guangzhou 510275, China
Q. Zhang : J. Peng
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 (*) : J. Peng
School of Geography and Planning, and Guangdong Key
Laboratory for Urbanization and Geo-simulation, Sun Yat-sen
University, Guangzhou 510275, China
e-mail: zhangq68@mail.sysu.edu.cn
C.<Y. Xu
Department of Geosciences, University of Oslo, P.O. Box 1047,
Blindern, 0316 Oslo, Norway
V. P. Singh
Department of Biological & Agricultural Engineering
and Department of Civil and Environmental Engineering, Texas
A & M University, College Station, TX 77843-2117, USA
reflected mainly by lengthening precipitation regimes, implying different regional responses of hydrological cycle to
climate changes. The results of this study will be of considerable relevance in basin-scale water resources management, human mitigation of natural hazards, and in
understanding regional hydrological responses to changing
climate at regional scales.
1 Introduction
Knowledge of magnitudes, frequencies, and durations
of consecutive wet days of precipitation regimes is
essential for the design of water conveyance and flood
protection structures and the management of agricultural development, such as irrigation. Also, an investigation of precipitation changes is the first step in the
understanding of hydrological responses to climate
changes at the local, regional, and even global scales.
It is believed that the projected global climate changes
have the potential to accelerate the global hydrological
cycle (e.g., Ziegler et al. 2003; Allan and Soden 2008).
The accelerated hydrological cycle may further enhance
uneven spatiotemporal distribution of water resources
and the changing patterns of extreme weather events in
both time and space, which will have tremendous impacts on the human society. That is perhaps why the
changing properties and related impacts of precipitation extremes on human society under the influence of changing
climate and intensifying human activities have attracted great
concerns from hydrologists and policymakers (Milly et al.
2002; Qian et al. 2007; Allan and Soden 2008; Min et al.
2011; Kumar and Jain 2011).
There are many studies pertaining to statistical properties of precipitation extremes (Easterling et al. 2000;
Christensen and Christensen 2004; Zolina et al. 2008;
Zhang et al. 2011a) based on precipitation indices. Also,
precipitation changes and related relations to streamflow
704
changes in the upper, middle, and lower Yangtze River
Basin, respectively, have been investigated in recent
years (e.g., Zhang et al. 2008). Furthermore, spatiotemporal patterns of trends of precipitation maxima in the
Yangtze River Basin during 1960–2005 have been analyzed using the Mann–Kendall trend test. Also studied
has been the related association of changing patterns of
precipitation maxima with large-scale circulation using
NCEP/NCAR reanalysis data. Abrupt changes of precipitation maxima were found in mid-1970s, and a significant increasing trend of precipitation intensity was
detected in the middle and lower Yangtze River Basin.
This result is due to the decreasing strength of East
Asian summer monsoon during 1975–2005 as compared
to that during 1961–1974 and increasing geopotential
height in the North China, South China Sea, and West
Pacific regions. The Yangtze River Basin is the largest
river in China and is the third largest river in the world.
Flood hazards have negatively influenced the ecosystem
and socioeconomy of the Yangtze River Basin. In 1998,
disastrous floods occurred in the entire Yangtze River
Basin, which was the largest flood since 1954. The
economic loss was 166 billion yuan (about 20 billion
US dollars). This flood hazard was the direct result of
unusually high precipitation that occurred between June
and August (670 mm) due to a strong El Niño event
(Yin and Li 2001).
It should be noted here that spatiotemporal variations of
floods and droughts are closely related to precipitation characteristics, such as consecutive rainfall days, and fractional
contribution of precipitation regimes to total precipitation
amounts. Therefore, some investigators attempted to scrutinize the changing precipitation features. In a recent study,
the duration of consecutive wet days or the wet period and
precipitation intensity has been investigated (e.g., Zolina et
al. 2010). Zolina et al. (2010) indicated that longer wet
periods and higher precipitation intensities should have a
significant impact on the terrestrial hydrologic cycle, including subsurface hydrodynamics, surface runoff, and
European flooding. Further, dry spells defined as a
period of consecutive days of exactly, say x, dry days
immediately preceded and followed by a wet day have
also aroused a great deal of interest as an important
component of the precipitation process (Zin and Jemain
2010). Moreover, analysis of precipitation structure has
been done for the Pearl River Basin (Zhang et al.
2012) and even over China (Zhang et al. 2011b).
However, no such study has been reported for the
Yangtze River Basin. For water resources management
and mitigation of natural hazards in the Yangtze River
Basin, it is important to understand the changing precipitation characteristics and the influence of climate
change in order to evaluate the possible occurrences
Q. Zhang et al.
of floods or droughts and hydrological responses to
climate changes over the basin. This is the major
motivation of this study.
In this study, daily precipitation data from 117 rain gauge
stations over the Yangtze River basins were analyzed (1) to
understand the changing properties of precipitation regimes
defined by consecutive wet days in both space and time in
terms of duration and precipitation intensity and (2) to
evaluate fractional contribution of precipitation regimes to
the total precipitation. The study will help to shed new light
on precipitation changes across the Yangtze River Basin and
understand the basin-scale hydrological response to climate
change.
2 Data
The Yangtze River Basin (Fig. 1) (91°E~122°E, 25°N~
35°N) is 1,808,500 km2 in drainage area. The climate of
the basin is of the subtropical monsoon type (Zhang et al.
2005). The southern part of the basin is climatically close to
tropical climate, and the northern part is near to the temperate zone. The annual mean temperature in the southern and
northern parts of the middle and lower Yangtze River
Basin is 19 and 15 °C, respectively. Summer (June to
August) is the main flooding season for the Yangtze
River Basin. Daily precipitation data for 1960–2005
from 147 rain gauge stations were obtained from the
National Climate Center of the China Meteorological
Administration. The spatial distribution of rain gauge
stations over the Yangtze River Basin is shown in
Fig. 1. The missing data of 1 or 2 days were replaced
by the average precipitation values of the neighboring
stations. The homogeneity of the precipitation series was
tested, and all the data were homogeneous at >95 % confidence level (Zhang et al. 2008). The precipitation indices are
defined and displayed in Table 1.
3 Methodologies
In this study, the modified Mann–Kendall test (MMK test
hereafter) (Mann 1945; Kendall 1955; Hamed and Rao
1998) was employed to detect trends. The original MK test
is a nonparametric method and is recommended by the
World Meteorological Organization (Mitchell et al. 1966).
However, the persistence in the hydrometeorological series
contaminates the MK test results. Hence, Hamed and Rao
(1998) modified the MK test by considering the lag-i autocorrelation in the hydrometeorological series. The modified
MK test has been shown to be robust in the study of trends
in hydrometeorological series (Hamed and Rao 1998;
Daufresne et al. 2009). The MMK method is introduced
Precipitation regimes across Yangtze River Basin, China
Fig. 1 The Yangtze River
Basin and rain gauging stations
705
90° E
35° N
100° E
110° E
120° E
O
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30° N
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#
25° N
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# station
# #
# #
Elevation
7143m
0
here for the sake of completeness of this study (Daufresne et
al. 2009).
For an ordered set of n observations X=x1, x2,…, xn, the
Mann–Kendall trend statistic S is calculated as
X
S¼
ð1Þ
i
where
sgn xj
nðn
ð2Þ
1Þð2n þ 5Þ
18
900
Km
1,200
-142m
in a time series. To eliminate the persistence effects, Hamed
and Rao (1998) recommend to subtract a nonparametric
trend estimator from the initial time series X and to evaluate
the autocorrelation between the ranks of the new time series.
Autocorrelation coefficients ρs(i) at lag (i) that are significantly different from zero at the 5 % level are then used to
evaluate the modified variance of S, V*(S) as
ð4Þ
where Cor represents a correction due to autocorrelation in
the data, and
Cor ¼ 1 þ
ð3Þ
The significance of the trend is tested by comparing the
standardized test statistic Z=S/[var(S)]0.5 with the standard
normal variate at the desired significance level. Hamed and
Rao (1998) showed that the estimate of the variance of S is
biased when significant temporal autocorrelations occurred
Table 1 Definitions and units of
precipitation indices
600
V * ðSÞ ¼ varðSÞCor
8
< 1 xj > xi
0 xj ¼ xi
xi ¼
:
1 xj < xi
The variance of S is given by Kendall (1975):
varðSÞ ¼
300
nð n
n 1
X
ðn
2
1Þðn
1Þ ð n
2Þ
i
1Þ ð n
i
2Þρs ðiÞ
ð5Þ
i¼1
The significance of trends by the MMK test is evaluated
at a 5 % significance level.
Indices
Definitions
Units
AMP/MMP
AMD/MMD
AMI/MMI
Annual/monthly mean precipitation
Annual/monthly mean rainy days
Annual/monthly mean
precipitation intensity
Annual/monthly mean
consecutive rainy days
Annual mean maximum daily precipitation amount
Annual mean maximum consecutive precipitation amount
Annual mean maximum consecutive rainy days
No. of rainy days with precipitation exceeding 90 % percentile
No. of rainy days with precipitation exceeding 95 % percentile
No. of rainy days with precipitation exceeding 99 % percentile
Precipitation amount of consecutive wet days
Frequency of consecutive wet-day with different durations
Fractional contribution of consecutive wet days with different
durations to the annual total precipitation amount
mm
day
mm/
day
day
AMWP/MMWP
MAXP
MCP
MCD
P90
P95
P99
WP
OCC
CON
mm
mm
day
day
day
day
mm
%
%
706
Q. Zhang et al.
90° E
100° E
!
!
!
!
!
AMP
!
2290mm-265mm
100° E
110° E
!
!
!
! !
!
!
AMI
!
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! ! !! ! ! ! ! ! !! !
!
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
120° E
!
!
!
!
15.82 - 4.48 mm/d
!
!
!
!
AMD
!
163d - 58d
90° E
!
110° E
120° E
!
!
!
! !
!
!
AMWP
2.90d - 1.57d
!
Increasing trend
120° E
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! ! !! ! ! ! ! ! !! !
!
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
100° E
D
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
!
! !
! !
! !
! ! !
!
! !
! ! !! !
! ! ! !! ! ! ! ! ! !! !
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
110° E
!
! !
35° N
90° E
!
100° E
B
!
! !
C
90° E
30° N
!
120° E
25° N
A
110° E
!
!
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! ! !! ! ! ! ! ! !! !
!
!
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! ! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
! !
!
!
! !
Decreasing trend
Fig. 2 Spatial distribution of annually precipitation indices (value and trend) across the Yangtze River Basin. Circles with black dots show
significant trends at the 95 % confidence level. A AMP, B AMD, C AMI, D AMWP
4 Results and brief discussions
4.1 Annual precipitation regimes
The precipitation indices of annual mean precipitation
(AMP), annual mean precipitation intensity (AMI), annual
mean rainy days (AMD), and annual mean consecutive
rainy days (AMWP) are defined and displayed Table 1,
and Fig. 2 shows their spatial distributions. It can be
observed from Fig. 2 that increasing AMP can be found
east of 110°E and west of 100°E in the Yangtze River Basin.
Regions between 110°E and 100°E are characterized by
decreasing AMP (Fig. 2a). However, the entire Yangtze
River Basin is dominated by decreasing AMD, except the
upper basin (Fig. 2b). The number of stations characterized
by increasing AMD is 30, accounting for 20 % of the total
rain gauge stations analyzed. However, the decrease of
AMD is more significant than that of AMP, which is
200
15
MMP
MMD
150
(d)
(mm)
10
100
5
50
0
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2.5
MMI
MMWP
2
1.5
10
(d)
(mm/d)
15
1
5
0.5
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Fig. 3 Monthly changes of a MMP, b MMD, c MMI, and d MMWP across the Yangtze River Basin
Precipitation regimes across Yangtze River Basin, China
707
MMP
MMD
MMI
MMWP
%
100
74
50
37
0
0
Number
Increasing
37
50
74
100
Significant
Decreasing
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Fig. 4 Number of stations with trends of monthly precipitation indices across the Yangtze River Basin
reflected by more stations being characterized by the significant increase of AMD than AMP (Fig. 2a and b). It can be
90° E
100° E
!
!
!
!
!
MAXP
!
142mm-20mm
90° E
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! ! !! ! ! ! ! ! !! !
!
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
100° E
!
120° E
!
!
!
!
!
!
P95
!
33.3mm-5.0mm
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
!
! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! !! ! ! !! ! ! ! ! ! !! !
! !
!
!
!
!
!
!! ! !
!
! ! ! ! !! ! !! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
! !
!
!
! !
100° E
110° E
120° E
35° N
90° E
!
110° E
!
!
!
!
! !
!
!
MCP
325mm-45mm
!
!
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
!
!
!
!
! !
! !
! !
! !
! ! !! ! !
! ! !! ! ! !! ! ! ! ! ! !! !
!
!
! ! !
! !
!! ! !
! ! ! ! !! ! !! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
!
!
!
! !
!
!
!
Increasing trend
!
!
!
P90
!
2.4mm-9.0mm
90° E
!
!
!
!
!
P99
!
75.0mm-11.4mm
90° E
120° E
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
!
! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
!
!
!
!
! !
! !
! !
!
! !
! ! !! !
! ! !! ! ! !! ! ! ! ! ! !! !
!
!
!
!
! !
!! ! !
!
! ! ! ! !! ! !! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
! !
!
!
! !
100° E
!
110° E
!
! !
G
120° E
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! ! !! ! ! ! ! ! !! !
!
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
100° E
!
110° E
!
! !
D
! !
F
100° E
B
!
! !
C
90° E
110° E
120° E
!
!
!
! !
30° N
!
120° E
25° N
A
110° E
seen from Fig. 2c that most regions of the Yangtze River
Basin are covered by the significant increase of AMI.
!
!
MCD
13.1d - 4.7d
!
!
!
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
!
! !
! !
! !
! ! !
! !
! ! !! ! !
! ! ! !! ! ! ! ! ! !! !
! !
!! ! ! ! ! ! !! ! ! ! !! ! ! !
!
! !
! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
!
! ! !
! !
Decreasing trend
Fig. 5 Spatial distributions of trends of annually extreme precipitation indices across the Yangtze River Basin. Circles with black dots show
significant trends at the 95 % confidence level. A MAXP, B P90, C P95, D P99, E MCP, F MCD
0
0
10
10
20
20
30
30
40
40
Ocurrence
50
1
2
3
4
5
6
7
Fraction Contribution
8
9
(%)
Q. Zhang et al.
(%)
708
50
10
150
(mm)
WP
100
50
0
Duration(days)
Fig. 6 Occurrences and fractional contributions of WP durations across the Yangtze River Basin
Increasing AMI is found mainly in the regions east of
110°E and the southwest corner of the Yangtze River
Basin. Figure 2d indicates generally decreasing AMWP
which is in accordance with AMD. Therefore, the precipitation process in the Yangtze River Basin is evidently intensifying, being reflected by decreasing AMD and
AMWP, but increasing AMI. The precipitation process
in Europe is also intensifying but is reflected by lengthening consecutive wet periods (Zolina et al. 2010),
which may imply different regional responses of the
hydrological cycle to the changing climate.
4.2 Monthly precipitation regimes
As regards monthly distribution of precipitation regimes, it
can be seen from Fig. 3 that monthly mean precipitation
(MMP), monthly mean precipitation intensity (MMI),
monthly mean rainy days (MMD) and monthly mean consecutive rainy days (MMWP) are the largest or dominant in
June and July, wherein differences in MMWP among different months are not so evident. Figure 4 illustrates the
number of stations with different trends of monthly precipitation indices for each individual month. It can be seen
10
9
Duration(d)
8
7
6
5
4
3
2
1
1965
1970
-1
1975
-0.8
-0.6
1980
-0.4
-0.2
1985
0
1990
0.2
0.4
1995
0.6
2000
0.8
1
Fig. 7 Temporal evolution of the normalized occurrences of anomalies in different WP durations across Yangtze River Basin
2005
Year
Precipitation regimes across Yangtze River Basin, China
709
10
9
Duration(d)
8
7
6
5
4
3
2
1
1965
1970
-1
1975
-0.8
-0.6
1980
-0.4
-0.2
1985
0
0.2
1990
0.4
1995
0.6
2000
0.8
2005
Year
1
Fig. 8 Temporal evolution of the normalized fractional contribution anomalies in different WP durations across Yangtze River Basin
from Fig. 4 that more stations are characterized by increasing MMP during January, February, June, July, and August
and during April, May, September, October, November, and
December. No significantly different changes can be found
for MMP in March. Hence, increasing MMP occurs mainly
in winter and summer. Autumn and spring are mainly dominated by decreasing MMP. Nevertheless, increasing MMP
is identified mainly during January and February. In this
sense, wetting tendency seems to be further corroborated
(Zhang et al. 2011a, b) which may be attributed to seasonal
shifts of precipitation regimes under the influence of climate
changes, particularly spatiotemporal alterations in the propagation of water vapor over East Asia (Zhang et al. 2011a).
Increasing MMD is observed mainly during January,
February, July, and August. Thus, MMD is decreasing generally across the Yangtze River Basin. Monthly MMI, however, is evidently increasing. It can be found from Fig. 4 that
the number of stations with increasing MMI is significantly
more than that of stations with decreasing MMI. Specifically,
monthly MMI of almost all months is increasing except during September and December. Thus, the increase of MMI is
evident. As for MMWP, the increase of MMWP can be
identified only during February, July, and August. Hence,
the decrease of MMWP is also distinctly evident.
4.3 Extreme precipitation changes
Extreme precipitation events are defined by annual mean
maximum daily precipitation amount (MAXP); number of
rainy days with precipitation exceeding 90 % percentile
(P90), 95 % percentile (P95), and 99 % percentile (P99);
annual mean maximum consecutive precipitation amount
(MCP), and annual mean maximum consecutive rainy days
(MCD) (Table 1). It can be seen from Fig. 5a that stations
with increasing MAXP and those with decreasing MAXP
are distributed sporadically and intermittently across the
Number
100
Ocurrence
Fraction Contribution
74
50
37
0
0%
50
37
Significant
100
1
2
74
3
4
5
6
7
8
Fig. 9 Number of stations for trends of precipitation indices (OCC and CON) across the Yangtze River Basin
9
10
Q. Zhang et al.
100° E
!
!
!
! !
!
!
!
90° E
!
110° E
!
! !
!
!
!
!
100° E
!
!
!
! !
!
90° E
D
!
110° E
120° E
!
!
!
! !
!
!
!
!
Increasing trend
120° E
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
! ! !! ! ! !! ! ! ! ! ! !! !
! !
!
!
!
!
!
!
!! !
!
! ! ! ! !! ! !! !
! ! ! ! !! ! ! ! ! ! ! ! ! ! !
! !
!
!
! !
100° E
!
! ! ! !! ! ! !! !
!
! ! ! ! ! ! !
!
! !! ! ! ! !
!
! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !
! ! ! ! !
! !
! !!!
!
!
! !
! !
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120° E
110° E
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30° N
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B
25° N
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90° E
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100° E
C
120° E
30° N
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110° E
25° N
A
35° N
90° E
35° N
710
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Decreasing trend
Fig. 10 Spatial distributions of trends of normalized occurrences of different WP durations over the Yangtze River Basin. a 1 day, b 3 days, c
5 days, d 7 days
entire Yangtze River Basin. Relatively speaking, more stations with increasing MAXP are found in the middle and
lower Yangtze River Basin, particularly in the lower
Yangtze River Basin. Moreover, the number of stations with
increasing MAXP is larger than that of stations with decreasing MAXP. Spatial distribution of P90 and P95 are
similar, i.e., stations with decreasing P90 and P95 are mainly located in the regions between 110°E and 100°E (Fig. 5b
and c)). Stations with increasing P90 and P95 are located in
the regions east to 110°E and west to 100°E, respectively.
100° E
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120° E
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90° E
D
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Increasing trend
120° E
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110° E
120° E
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25° N
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120° E
30° N
C
110° E
35° N
90° E
110° E
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25° N
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90° E
30° N
A
110° E
35° N
90° E
Spatial distribution of stations with increasing and decreasing P99 is not in a confirmative spatial pattern (Fig. 5d).
Stations with increasing or decreasing P99 are distributed
interchangeably across the entire Yangtze River Basin.
However, stations with increasing P99 account for 63 % of
the total stations considered in the study. In this sense, the
Yangtze River Basin is characterized by increasing P99.
Figure 5e shows the spatial patterns of MCP over the entire
basin. Stations with increasing MCP are located mainly in
the Yangtze Delta region. Besides, more stations are
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Decreasing trend
Fig. 11 Spatial distributions of the trends of normalized fractional contributions of different WP durations over the Yangtze River Basin. a 1 day, b
3 days, c 5 days, d 7 days
Precipitation regimes across Yangtze River Basin, China
characterized by increasing MCP, accounting for about 52 %
of the total stations analyzed. However, MCD is evidently
decreasing. There are 28 stations characterized by increasing
MCD, accounting for 19 % of the total stations. These
results are in agreement with those of monthly and annual
precipitation changes.
4.4 Fractional contributions of precipitation regimes
to the total precipitation amount
Scrutinizing precipitation processes from the viewpoint of
consecutive rain events are crucial in understanding hydrological responses to climate changes at regional and global
scales. In this case, considerable importance has been attached
to the investigation of precipitation structure. Figure 6 indicates that 1-day rain event occurs with the highest frequency,
2-day rain event occurs with lower frequency, and so on. The
precipitation amount is decreasing from 1- to 10-day rain
event. However, the fractional contribution of 2-day rain event
is the largest, followed by 1- and 3-day rain events. Figure 7
shows that the durations of consecutive rain events are decreasing, particularly after the 1980s. Specifically, three time
intervals characterized by different durations can be identified:
1960–1975, 1975–1990, and 1990–2005. The durations of
consecutive rain events are 6–9 days during 1960–1975, 3–
6 days during 1975–1990, and 1–3 days during 1990–2005,
respectively. The shortening consecutive rain days typically
mirror the intensifying precipitation processes and should be
further considered in water resources management of the
Yangtze River Basin. Fractional contributions of consecutive
rainfall events follow similar changing features. Consecutive
rainfall events with durations of 7–8 days have the largest
fractional contribution to the total precipitation amount before
the 1980s. Thereafter, however, consecutive rainfall events
with durations of 3–5 days have the largest fractional contribution to the total precipitation amount. In recent years, e.g.,
after 2000, consecutive rainfall events with durations of 1–
2 days have the largest fractional contribution to the total
precipitation amount. This kind of extreme tendency of precipitation processes will likely trigger a higher risk of floods
and droughts in the Yangtze River Basin.
Figure 8 illustrates that durations of consecutive rainfall
that have the largest fractional contribution to the total
precipitation amount are decreasing generally. The durations
are 6–9 days during 1960–1975, 3–5 days during 1975–
2000, and even about 2 days after 2000. Thus, the shortlasting rainfall events come to be dominant within the precipitation processes. Figure 9 further corroborates the findings that occurrence rates and fractional contributions of
short-duration rainfall events are increasing when compared
to the longer-duration rainfall events. It can be seen from
Fig. 9 that the occurrence and fractional contribution of 1and 2-day consecutive rainfall events are identified at a
711
larger number of stations when compared to longerduration consecutive rainfall events, such as 3-, 4-, and 5day consecutive rainfall events and even consecutive rainfall
events of longer durations.
Figure 10 shows spatial distributions of occurrence trends
of consecutive rainfall events with different durations, i.e.,
1, 3, 5, and 7 days. There are 43 stations characterized by
increasing occurrences of 1-day rainfall events (Fig. 10a),
accounting for 29 % of the total rainfall stations. Therefore,
the occurrences of 1-day rainfall events are increasing
across the entire Yangtze River Basin. More stations are
dominated by decreasing occurrences of 3-day rainfall
events (Fig. 10b), and these stations are identified mainly
in the northeast parts of the Yangtze River Basin.
Specifically, there are 54 stations characterized by increasing occurrences of 3-day rainfall events (Fig. 10a), accounting for 36.7 % of the total rainfall stations. In comparison
with Fig. 10a and b), Fig. 10(c and d) indicates that the
number of stations with increasing occurrence of consecutive rainfall events with durations of 5 and 7 days is larger
than that shown in Fig. 10(a and b). These results show that
the rainfall events with shorter durations are in decreasing
occurrence. Figure 11 illustrates spatial distributions of
trends of the fractional contribution of rainfall events with
different durations of 1, 3, 5, and 7 days. The spatial patterns
of trends of fractional contributions are similar to those of
occurrence trends of rainfall events (Figs. 10 and 11).
Besides, the fractional contribution of short-duration rainfall
events is larger than that of long-duration rainfall events.
Thus, short-duration rainfall events are dominant in the
precipitation processes in terms of occurrence and fractional
contribution, implying intensified precipitation processes.
5 Conclusions
Precipitation changes in both space and time can mirror the
responses of hydrological cycle to the changing climate.
Besides, an understanding of precipitation changes is the
first step to the management of water resources and hydraulic engineering facilities. Floods occur in the Yangtze River
Basin in high frequency and inflict tremendous losses on the
socioeconomy of the basin. Since precipitation changes are
in close relation with floods and droughts within the basin
(Zhang et al. 2005), it is important to investigate precipitation changes. Analysis of daily precipitation datasets from
147 rainfall stations that cover the entire Yangtze River
Basin leads to the following conclusions:
1. Annual mean precipitation/rainfall days are decreasing.
However, the decrease of rainfall days is subjected to
larger magnitude which leads to increased precipitation
intensity. Precipitation amount and rainfall days are
712
increasing in January and February and are decreasing
in the months of spring and autumn, which imply seasonal shifts of precipitation changes, since summer is
usually the flood season, and winter, the dry season.
Moreover, risk of droughts during spring and autumn
will be higher.
2. Decreasing precipitation amount of the annual maximum consecutive rainfall periods and larger decrease
in the durations of annual maximum consecutive
rainfall periods combine to trigger larger precipitation
intensity. It is particularly true for the lower Yangtze
River Basin.
3. Those 1-day rainfall events are prevailing in the Yangtze
River Basin. However, fractional contribution of 2-day
rainfall events is the largest. The durations of the consecutive rainfall events are shortened, and the shorterduration rainfall events have the increased fractional
contribution to the total precipitation amount. The entire
Yangtze River is dominated by shortening precipitation
episodes, implying evident intensification of the hydrological cycle. This kind of intensification of the hydrological cycle is in accord with the general tendency of
the hydrological cycle changes over the globe (Ziegler
et al. 2003; Christensen and Christensen 2004; Allan
and Soden 2008).
4. The intensification of precipitation is more evident in
the lower Yangtze River Basin. The intensification of
precipitation processes will trigger a higher risk of
floods or droughts. The lower Yangtze River Basin,
particularly the Yangtze Delta, is one of the economically developed regions in China with many megacities,
such as Shanghai. In this sense, challenges of water
resources management and mitigation of natural hazards, such as floods and droughts, will greatly increase.
How to do water resources management and how to
mitigate water resources problems under the influences
of climate changes and human activities will be another
critical problem the human community within the
Yangtze River Basin will face.
Acknowledgments The research is financially supported by the National Natural Science Foundation of China (grant no. 41071020), the
Program for New Century Excellent Talents in University, and by the
Geographical Modeling and Geocomputation Program under the Focused Investment Scheme (1902042) of The Chinese University of
Hong Kong. Thanks should be owed to the National Climate Center
of China for providing the meteorological data. Our cordial gratitude
should be extended to the editor-in-chief, Prof. Dr. Hartmut Graßl, and
the reviewers for their professional, pertinent comments and suggestions which are greatly helpful for further improvement of the quality
of this paper.
Q. Zhang et al.
References
Allan RP, Soden BJ (2008) Atmospheric warming and the amplification of precipitation extremes. Science 321(5895):1481–1484
Christensen OB, Christensen JH (2004) Intensification of extreme
European summer precipitation in a warmer climate. Glob
Planet Chang 44:107–117
Daufresne M, Lengfellner K, Sommer U (2009) Global warming
benefits the small in aquatic ecosystems. Proc Natl Acad Sci U
S A 106(31):12788–12793
Easterling DR, Meehl GA, Parmesan C, Changnon SA, Karl TR,
Mearns LO (2000) Climate extremes: observations, modeling,
and impacts. Nature 289:2068–2074
Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for
autocorrelated data. J Hydrol 204:182–196
Kendall MG (1955) Rank correlation methods. Griffin, London
Kendall MG (1975) Rank correlation methods. Griffin, London
Kumar V, Jain SK (2011) Trends in rainfall amount and number of rainy
days in river basins of India (1951–2004). Hydrol Res 42(4):290–306
Mann HB (1945) Nonparametric tests against trend. Econometrica
13:245–259
Milly PCD, Wetherald RT, Dunne KA, Delworth TL (2002) Increasing
risk of great floods in a changing climate. Nature 415:514–517
Min S-K, Zhang X, Zwiers WF, Hegerl CG (2011) Human contribution
to more-intense precipitation extremes. Nature 470:378–381
Mitchell JM, Dzerdzeevskii B, Flohn H (1966) Climate change. WHO
Technical Note 79. World Meteorological Organization, Geneva, p 79
Qian W, Fu J, Yan Z (2007) Decrease of light rain events in summer
associated with a warming environment in China during 1961–
2005. Geophys Res Lett 34, L11705. doi:10.1029/GL029631
Yin HF, Li CA (2001) Human impact on floods and flood disasters on
the Yangtze River. Geomorphology 41:105–109
Zhang Q, Jiang T, Gemmer M, Becker S (2005) Precipitation, temperature and discharge analysis from 1951–2002 in the Yangtze
Catchment, China. Hydrol Sci J 50(1):65–80
Zhang Q, Xu C-Y, Zhang Z, Chen YD, Liu C-L (2008) Spatial and
temporal variability of precipitation maxima during 1960–2005 in
the Yangtze River basin and possible association with large-scale
circulation. J Hydrol 353:215–227
Zhang Q, Xu C-Y, Chen XH, Zhang ZX (2011a) Statistical behaviors of
precipitation regimes in China and their links with atmospheric circulation 1960–2005. Int J Climatol 31(11):1665–1678. doi:10.1002/
joc.2193
Zhang Q, Singh VP, Li JF, Chen XH (2011b) Analysis of the periods of
maximum consecutive wet days in China. Journal of Geophysical
Research 116(D23). doi: 10.1029/2011JD016088
Zhang Q, Singh VP, Peng JT, Chen YD (2012) Spatial-temporal
changes of precipitation structure across the Pearl River basin,
China. J Hydrol 440–441:113–122
Ziegler AD, Sheffield J, Maurer EP, Nijssen B, Wood EF, Lettenmaier DP
(2003) Detection of intensification in global- and continental-scale
hydrological cycles: temporal scale of evaluation. J Clim 16:535–547
Zin WZW, Jemain AA (2010) Statistical distributions of extreme dry
spell in Peninsular Malaysia. Theor Appl Climatol 102:253–264
Zolina O, Simmer C, Kapala A, Bachner S, Gulev SK, Maechel H
(2008) Seasonally dependent changes of precipitation extremes
over Germany since 1950 from a very dense observational network. J Geophys Res 113, D06110. doi:10.1029/2007JD008393
Zolina O, Simmer C, Gulev SK, Kollet S (2010) Changing structure of
European precipitation: longer wet periods leading to more abundant rainfalls. Geophys Res Lett 37, L06704