Examining the influence of river–lake interaction on the drought

Examining the influence of river–lake interaction on the drought
Journal of Hydrology 522 (2015) 510–521
Contents lists available at ScienceDirect
Journal of Hydrology
journal homepage: www.elsevier.com/locate/jhydrol
Examining the influence of river–lake interaction on the drought
and water resources in the Poyang Lake basin
Zengxin Zhang a,b,⇑, Xi Chen c, Chong-Yu Xu d,e, Yang Hong f, Jill Hardy f,g, Zhonghua Sun h
a
Joint Innovation Center for Modern Forestry Studies, College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu 210037, China
Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China
c
State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, Hohai University, Nanjing 210098, China
d
Department of Geosciences, University of Oslo, Norway
e
Department of Earth Sciences, Uppsala University, Sweden
f
School of Civil Engineering and Environmental Sciences, The University of Oklahoma, Norman, OK 73019, USA
g
School of Meteorology, The University of Oklahoma, Norman, OK 73019, USA
h
Network and Information Center, Changjiang Water Resources Commission, Wuhan 430010, China
b
a r t i c l e
i n f o
Article history:
Received 9 April 2013
Received in revised form 2 January 2015
Accepted 4 January 2015
Available online 13 January 2015
This manuscript was handled by
Konstantine P. Georgakakos, Editor-in-Chief,
with the assistance of Michael Bruen,
Associate Editor
Keywords:
Extreme droughts
Poyang Lake
Yangtze River
The Three Gorges Dam
River–lake interaction
s u m m a r y
In recent years, the Poyang Lake basin is in a prolonged drought which has placed immense pressure on
the water resources utilization. In this paper, we explore the spatial and temporal distributions of
extreme droughts in the Poyang Lake basin by using the methods of SPI (Standardized Precipitation
Index) and EOF (Empirical Orthogonal Function) for the period of 1956–2009, which are influenced by
regional precipitation anomalies and river–lake interaction due to water impounding of the Three Gorges
Dam (TGD). The results show that: (1) the Poyang Lake basin experienced six extreme droughts during
the past 60 years, which lead to decreases in streamflow from five tributary rivers down to the Poyang
Lake. The droughts in the 1960s and the 2000s were the most serious ones. However, there was an
increasing trend of streamflow in the upper and middle Yangtze in the 1960s, and a decreasing trend
appeared in the 2000s. The decline of streamflow in the upper Yangtze reaches has lowered the water
level of lower Yangtze River which has caused more outflow from the Poyang Lake to the Yangtze River;
(2) the operation of the Three Gorges Dam (TGD) has altered the seasonal pattern of flow regimes in the
Poyang Lake and significantly reduced the water level in the lower Yangtze River during the TGD
impounding period from late September to early November; and (3) the conjunction of extreme droughts
in the Poyang Lake and the upper Yangtze reaches coincided with the impounding of the TGD is the main
cause of the low water level in the Poyang Lake. Although the impact of the recent droughts in the Poyang
Lake and upper Yangtze reaches has played a crucial role in the low water level of Poyang Lake, more
attention should be paid to its sensitivity to the influence of the large dam-induced changes in the interaction between river and lake, particularly during impounding periods.
Ó 2015 Elsevier B.V. All rights reserved.
1. Introduction
‘‘Drought’’ as a natural hazard is mainly caused by large-scale
climatic variability while water scarcity is more a result of human
influence. Making the distinction between them is not trivial
because they often occur simultaneously (Van Loon and Van
Lanen, 2013). Evaluation of drought conditions in a particular area
is the key step for planning water resources. Numerous drought
⇑ Corresponding author at: Joint Innovation Center for Modern Forestry Studies,
College of Biology and the Environment, Nanjing Forestry University, Nanjing,
Jiangsu 210037, China. Tel./fax: +86 25 85428963.
E-mail address: [email protected] (Z. Zhang).
http://dx.doi.org/10.1016/j.jhydrol.2015.01.008
0022-1694/Ó 2015 Elsevier B.V. All rights reserved.
indices have been developed to monitor droughts (Rossi et al.,
2007), including the worldwide used indices of the Standardized
Precipitation Index (SPI, e.g. Mckee et al., 1993; Zhang et al.,
2012; Portela et al., 2015), the Normalised Flow Index (NFI, e.g.
Gosling, 2014), the Reconnaissance Drought Index (RDI, e.g.
Takiris and Vangelis, 2005; Rahmat et al., 2015), and the Palmer
Drought Severity Index (PDSI, e.g. Palmer, 1965). These indices
have been developed to evaluate the water supply deficit in relation to the time duration of precipitation shortage. However, the
characteristics of drought in different climate zones may be different. A standardized index is often used to compare drought
conditions in different areas. For example, the Standardized Precipitation Index (SPI) is one of the most powerful indices which can be
Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
computed on different time scales (Bordi and Sutera, 2007). The SPI
has been used in many studies (e.g., Hayes et al., 1999; Bordi et al.,
2004; Chen et al., 2009; Zhang et al., 2011b) and it has proved to be
a useful tool in the estimation of the intensity and duration of
drought events (Bordi et al., 2004). SPI was also applied to examine
the effects of large dam on hydrological droughts by comparing the
drought index before and after the dam construction (Cancelliere
et al., 1998; López-Moreno et al., 2009; Lorenzo-Lacruz et al.,
2010).
Poyang Lake, China’s largest freshwater lake, is located on the
southern bank of the lower Yangtze River. The water level of the
Poyang Lake depends on watershed runoff from the five tributary
river basins and the water exchanges with the Yangtze River (Li
et al., 2015a; Zhang et al., 2014). It varies greatly both in area
and volume with seasonal and inter-annual changes. The lake level
is elevated to the extent that all floodplains are inundated, thus
forming a vast lake. In the drier season, lake level declines and lake
water recedes into sublacustrine channels and the floodplains are
exposed, resulting in the lake surface almost dwindling to a meandering line. At the moment, the Poyang Lake is effectively just a
river channel (http://www.jxsl.gov.cn/).
The impact of climate variability and change on the Poyang Lake
outflows, particularly on the floods, has been extensively studied
(e.g., Jiang and Shi, 2003; Shankman et al., 2006; Guo et al.,
2008; Zhang et al., 2011a; Zhao et al., 2010; Li et al., 2015b). Different conclusions have been drawn by previous studies which were
undertaken at different time and used different methods and data.
The river–lake interaction related to flood storage ability of the
lake and TGD was investigated by Nakayama and Shankman.
(2013a), and they pointed out that the TGD will increase flood risk
during the early summer monsoon, in contrast to the original justifications for building the dam, due to complex river–lake–
groundwater interactions. Hu et al. (2007) reported that basin
effect (basin discharge generated by rainfall) has played a primary
role influencing the water level of Poyang Lake and development of
severe floods, while the Yangtze River played a complementary
role of blocking outflows from the lake. Zhang et al. (2011a) also
found that the occurrence of water intrusion from the Yangtze
River to the Poyang Lake was heavily influenced by hydrological
processes of the Poyang Lake basin. Guo et al. (2011) found that
the Poyang Lake has the largest outflow to the Yangtze River and
exerts a strong pressure on the mainstream during April–June,
and the Yangtze River’s blocking and/or reversed flow to the Poyang Lake are the strongest during July–September.
Currently, the most severe droughts in the Poyang Lake basin
have drawn people’s attention to the water resources shortage
problem along the lower reaches of the Yangtze River. The lower
reaches of the Yangtze River, covering eight provinces of both Central and Southern China, are usually considered to be an area with
relatively abundant water resources. However, the continuous
droughts in this region have changed this situation and the Poyang
Lake is facing the danger of water shortage. The precipitation in
this region during November 2010–May 2011 was the lowest in
the past 60 years. The Poyang Lake shrank to its smallest area of
1326 km2 in May 2011, reducing about two-thirds of its normal
surface area of 3585 km2. Meanwhile, the prolonged drought in
the Yangtze River basin coincides with the water level rising of
the Three Gorges Dam (TGD) from 135 to 175 m. Recently, low
water levels in the drier season of the lower Yangtze River have
started earlier and lasted longer, which aroused a debate over
whether the TGD contributed to the decrease in water level of
the Poyang Lake (Zhang et al., 2014). Some researchers suggested
the TGD, along with the droughts, had caused the water level
decline in the Poyang Lake in the drier season (Dai et al., 2008;
Guo et al., 2011, 2012). Guo et al. (2011) reported that the influence of the TGD has resulted in less than 10% of the variation in
511
the Yangtze River flow in most of the seasons. Dai et al. (2008)
pointed out that 54% of the water flux was lost at Datong station
during September 20–October 27, 2006, in comparison with the
same period in 2005. It can be estimated that the impounding of
TGD and the extreme drought in 2006 contributed 9% and 45% of
this loss, respectively. Meanwhile, Guo et al. (2012) suggested that
the impacts of large dams in the Yangtze River should alter from
the previous studies in the dam-river setting to a new damriver–lake construction. Nevertheless, Lai et al. (2014) also suggested that the effects of the TGD on downstream rivers and lakes
will be intensified in the foreseeable future when many ongoing
and planned large-scale dams located in the upstream tributaries
in the Yangtze River, with a combined water storage capacity far
larger than the TGD, will be put into operation in the near future.
On the other hand, the Government of Jiangxi province situated
in Poyang Lake area has stirred up another controversy by pushing
to build a dam at the outlet of the Poyang Lake to prevent water
from flowing into the Yangtze River. So water shortage is becoming
one of the most serious problems in the Poyang Lake.
Although there are some studies about the influences of
drought and TGD impounding on the lower Yangtze River (e.g.
Chen et al., 2001; Dai et al., 2008; Guo et al., 2011), question like,
‘‘How do the droughts in the Poyang Lake basin together with
the associated streamflow of the upper Yangtze River affect the
water resources of Poyang Lake?’’, has not yet been analyzed thoroughly, which is of great scientific merit in understanding the
causes of current water shortage in the Poyang Lake. The scientific
problems to be investigated in this paper include: (1) Are there any
regularity of the extreme droughts in the Poyang Lake basin and
how do they affect the water resources? (2) To what extent does
the low streamflow of the Yangtze River affect the water resources
in the Poyang Lake? (3) Are there any differences in the interaction
of the Yangtze River and the Poyang Lake before and after the
impoundment of the TGD? In this study, we attempt to address
these problems based on a thorough analysis of long-term hydrological and precipitation datasets across the Yangtze River basin.
This study is of importance in further understanding the impacts
of the droughts coincided with the dam-induced river–lake interaction on hydrological processes of the Poyang Lake.
2. Data and methodology
2.1. Study area and data
Poyang Lake basin, located in Jiangxi province, has an area of
162,200 km2, occupying 9% of the Yangtze River basin. The water
balance at the Poyang Lake is mainly dominated by five main tributary rivers: Ganjiang River, Fuhe River, Xinjiang River, Raohe River
and Xiushui River, and several smaller rivers (as shown in Fig. 1). In
addition, inflow from the Yangtze River to the Poyang Lake also
plays an important supplementary role in maintaining the water
resources stability of the Poyang Lake (Hu et al., 2007). Thus, the
inflow of the Poyang Lake should include two parts: the inflow
from the five tributary rivers and inflow from the Yangtze River.
The Hukou station is the junction of the Poyang Lake basin with
the Yangtze River, and streamflow from this station is regarded
as the outflow of the Poyang Lake. The highest recorded lake level
at Hukou hydrological station is 22.59 m. The corresponding lake
area is approximately 4500 km2 with the lake volume reaching
34 billion m3. The lowest lake level at the same station is 5.90 m,
and its corresponding lake area and lake volume are 146 km2 and
450 million m3, or rather, 1/32 and 1/76 of the largest area and volume, respectively.
Daily mean streamflow and water level data from 16 hydrological stations during the period of 1956–2009 and 215 daily
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Fig. 1. Location of the study area and concerned hydro-meteorological stations ((a) the location of the Yangtze River basin; (b) the location of the Poyang Lake basin).
precipitation stations (of which 83 stations are located in the Poyang Lake basin) from 1957 to 2009 in the Yangtze River basin are
used in this study. A few missing precipitation data are interpolated by the average value of its adjacent stations. The sum of
the five tributary rivers in the Poyang Lake River basin was
chosen as the inflow to the Poyang Lake. The key hydrological
stations of Cuntan, Yichang, Hankou, Jiujiang and Datong in the
main Yangtze River were selected to analyze the streamflow
variabilities of the Yangtze River, and the Hukou station was
selected to analyze the water exchange between the Poyang Lake
and the Yangtze River (Referring to Fig. 1 and Table 1 for the
location and basic data of the Poyang Lake basin and the gauging
stations).
2.2. Methodology
The SPI is a drought index based on the probability of an
observed precipitation deficit occurring over a given prior time
period (McKee et al., 1993). It is a useful tool for monitoring
dry and wet periods on multiple time scales and for comparing
climatic conditions of areas governed by different hydrological
regimes. The assessment periods are considered to range from 1
to 36 months where the shorter time scales may represent agricultural drought and the longer time scales relate to hydrological
drought. The SPI at a 24-month time scale is used in this work
and it is usually considered as a hydrological drought index
which can be used to monitor surface water resources, e.g., river
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Table 1
Characteristics of the hydrologic records of stations at the Poyang Lake River basin and the main stream of Yangtze River basin.
River
Sub-basins
Station
Poyang Lake
Xiushui R.
Qiujin
Wangjiabu
Waizhou
Lijiadu
Meigang
Dufengkeng
Hushan
Xingzi
Duchang
Ganjiang R.
Fuhe R.
Xinjiang R
Raohe R.
Lake Region
Control station of Poyang Lake
Hukou
Mainstream
Cuntan
Yichang
Hankou
Jiujiang
Datong
Upper Yangtze
Middle Yangtze
Lower Yangtze
Area (104 km2)
9914
3548
80,948
15,811
15,535
5013
6374
265
107
1986
379
543
147
220
Annual mean water level (m)
22.90
18.43
25.98
19.30
22.49
20.79
13.43
13.84
162,200
4593
12.77
866,559
1,010,000
1,488,036
1,523,000
1,705,383
10,964
13,752
22,163
23,125
27,876
156.80
42.99
18.97
13.49
8.58
flows (Hayes et al., 1999). A clear and detailed description of the
steps required to calculate the SPI is provided in Lloyd-Hughes
and Saunders (2002). The SPI calculation for any location is based
on the long-term precipitation record for a desired period. This
long-term record is fitted to a probability distribution, which is
then transformed into a standard normal distribution so that
the mean SPI for the location and desired period is zero
(Edwards and McKee, 1997) (http://drought.mssl.ucl.ac.uk/spi.
html). The gamma distribution was tested to be a good candidate
probability distribution function for the precipitation amount in
the Yangtze River (result not shown) and it is used for calculation
of SPI in this paper. The drought is classified into four categories –
mild, moderate, severe and extreme drought (Mckee et al., 1993;
Chen et al., 2009). Standardized Runoff Index (SRI) is also adopted
in this research to calculate the hydrologic droughts (Gosling,
2014).
To compare the drought characteristics between different
drought periods in the Poyang Lake, the drought duration (D)
and drought magnitude (M) are adopted in this study. The
drought duration (D) can be defined as the cumulative months
when a continuous drought occurs (SPI (i)< 1.0 is used at the
beginning and ending of a drought and SPI (i)< 2.0 is regarded
as an extreme drought event). The drought magnitude (M) is
defined as:
D
X
M ¼ SPIðiÞ
Annual mean stremaflow (m3/s)
3. Results
3.1. The impacts of extreme droughts on the Poyang Lake’s water
resources
The aspects of drought over the Poyang Lake basin during the
last several decades have been evaluated by computing the SPI
and SRI on a 24-month time scale using the observed monthly
precipitation and runoff datasets. Fig. 2a shows the temporal
ð1Þ
i¼1
where SPI(i) is the SPI value, and i is the sequential month of a time
series of a drought (Chen et al., 2009).
To examine more details on temporal variability of hydrological time series, cumulative curve analysis is performed. The
cumulative curve method was first used by Hurst (1951) to
determine the storage capacity of reservoirs on the Nile River.
The cumulative departure is used in this paper to detect the
streamflow and water level variability in different regions for a
long time.
The Empirical Orthogonal Function (EOF) method is used to
analyze the main drought features of spatial and temporal variability in the Poyang Lake basin. The EOF analysis is a statistical technique that linearly transforms an original set of variables into a
substantially small set of uncorrelated variables representing most
of the information of the original set of variables (North, 1984; von
Storch, 1995,1999). Basically, the goal of EOF analysis is to reduce
the dimensionality of the original data set (Jolliffe, 2002; Wilks,
2006; Hannachi et al., 2007).
Fig. 2. The SPI and SRI in the Poyang Lake basin and Yangtze River basin during
1957–2009 ((a) the first PC of the SPI-24 in the Poyang Lake and the SRI-24 of
Waizhou station; (b) the SRI-24 of Yichang and Hankou station; (c) the first PC of
the SPI-24 in the Poyang Lake basin and the SRI-24 in Yichang station).
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Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
Table 2
The drought characteristics for six extreme droughts in the Poyang Lake basin during the past 60 years (D, drought duration, unit: month; M, drought magnitude, unit: SPI value).
D
M
M/D
1963/5–1967/2
1971/8–1973/1
1978/3–1980/10
1985/3–1988/4
2004/3–2005/11
2007/1–2009/11
45
172
3.8
17
51
3
31
105
3.4
37
118
3.2
21
60
2.9
35
129
3.7
Fig. 3. The amount of accumulated lake inflow and lake outflow anomalies compared to the reference period of 1956–2009 for six different extreme drought events in the
Poyang Lake basin.
distributions of the dryness and wetness of SPI in the Poyang Lake
basin by using the EOF method. It is noted that the first principal
component (PC1) explains more than 60% of the total variation of
the SPI-24. The PC1 can present the long-term features of dryness
and wetness in the Poyang Lake basin as a whole. The Ganjiang
River basin is the biggest tributary river in the Poyang Lake basin
with an area of 80,948 km2, occupying 49.9% of the Poyang Lake
basin. This is much greater than the second biggest tributary river,
the Fuhe River basin, with an area of 15,811 km2, occupying 9.8% of
the Poyang Lake basin. So the SRI of Waizhou station at the control
hydrological station of Ganjiang River basin might present the
main hydrologic droughts of the Poyang Lake to a great extent.
Fig. 2a also shows that the SRI-24 of Waizhou station has a similar
pattern of extreme dryness and wetness to that of the SPI-24 in the
Poyang Lake basin. In other words, it indicates that the SPI can be
used in the calculation of extreme droughts in the Poyang Lake
basin by comparison of the SPI and SRI (Fig. 2a). From this figure,
six continuous extreme drought events are found in the Poyang
Lake basin during the past 60 years (Fig. 2a). Table 2 shows the
drought characteristics of the six extreme drought events. Four
continuous extreme drought events in the Poyang Lake basin
exceed 30 months during the past 60 years. The droughts in the
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Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
Table 3
The amount of lake inflow, lake outflow and water level of Poyang Lake in October during the droughts of the 1960s and 2000s (DQ, lake inflow minus lake outflow).
Year
Lake streamflow (108 m3)
Inflow
Water level (m)
Outflow
DQ
Hukou
Jiujiang
Datong
1960s
1964
1965
1966
35
45
23
91
91
60
56
46
37
17.7
15.9
13.2
17.3
17.1
15.7
12.5
11.1
8.8
2000s
2007
2008
2009
27
38
22
116
120
46
89
82
24
12.3
12.7
9.7
16.7
17.5
14.8
8.4
8.7
6.4
1960s
2010s
34
29
81
94
47
65
15.6
11.6
16.7
16.3
10.8
7.8
3.2. The impacts of Yangtze river–lake interaction on the Poyang
Lake’s water resources
Fig. 4 shows the percentage of monthly mean streamflow in the
upper Yangtze (Yichang station), middle Yangtze (Hankou station)
and Poyang Lake basin (Hukou station) to the whole Yangtze basin
(Datong station). The amount of annual mean streamflow in the
upper and middle Yangtze and Poyang Lake basin are 46.1%,
79.5% and 15.6% of the whole Yangtze basin, respectively, for
1957–2009. Fig. 4a indicated that the seasonal percentage of the
streamflow in the upper and middle Yangtze to the whole Yangtze
basin varies greatly and the higher proportion appears in July,
August and September while the lower proportion occurs in February, March and April. However, the percentages of the streamflow
in the Poyang Lake to the whole Yangtze basin are opposite, the
higher proportion appears in spring (MAM) and lower proportion
can be found in August, September and October. Fig. 4b shows
the correlations between the streamflow at Yichang, Hankou and
Datong stations and water level at Hukou station. Higher correlations can also be found between the streamflow in the upper
100
Hukou
Yichang
Hankou
(a)
Percent (%)
80
60
40
20
0
1
2
3
4
5
6
7
8
9
10 Nov
11
12
13
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Dec
Ann
Yichang
Hankou
Datong
(b)
1.0
Correlations
1960s and 2000s were the most severe ones, with the longest
drought duration (D) records of 45 and 56 months, and the largest
drought magnitude (M) of 172 and 189, respectively. The
extreme droughts in the 2000s occurred during 2004/3–2005/11
and 2007/1–2009/11. As mentioned above the characteristics of
droughts during the 2000s are similar to those of the 1960s in
terms of the drought magnitude (M), drought duration (D) and
drought intensity (M/D) (Table 2). However, there is an interval
of one year between the two extreme droughts in the 2000s, while
the extreme droughts occur consecutively in the 1960s.
The annual and seasonal mean inflow (the sum of the streamflow from the five tributary river basins) agrees well with the outflow (Hukou station) in the Poyang Lake basin. To reveal the
difference between the inflow and outflow of the Poyang Lake during different drought periods, the accumulated inflow and outflow
departures compared with the average over 1956–2009 were further analyzed (Fig. 3). It shows a decline of lake inflow and lake
outflow during the six extreme drought events. The amount of
accumulated decrease in the inflow of Poyang Lake is over 3 billion m3 for both major droughts in the 1960s and 2000s (Fig. 3a
and f). However, there are distinct dissimilarities between them.
Although the amount of accumulated lake inflow anomalies in
the droughts of the 2000s is somewhat similar to that of the
1960s, the amount of accumulated lake outflow anomalies in the
1960s are larger than that of the 2000s, which indicates the water
remaining in the Poyang Lake during the droughts of the 2000s is
less than that of the 1960s. Similar results can be found in Table 3.
The much lower water level at Hukou station in October during the
droughts of the 2000s led to a significant increase of the Poyang
Lake outflow compared with that of the 1960s.
0.8
0.6
0.4
0.2
0.0
1
2
3
4
5
6
7
8
9
10 Nov
11
12
13
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Dec
Ann
Yichang
Hankou
Datong
(c)
1.0
Correlations
Average
0.8
0.6
0.4
0.2
0.0
1
2
3
4
5
6
7
8
9
10 Nov
11
12
13
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Dec
Ann
Months
Fig. 4. Correlations of monthly streamflow and water level between different
hydrological stations in the Poyang Lake and main stream of Yangtze River. The red
dotted line indicates the trend is statistically significant at the 5% significance level.
(a) the percentage of monthly and annual mean streamflow at Yichang, Hankou and
Hukou stations to the streamflow at Datong station; (b) the correlations between
the streamflow of Yichang, Hankou, Datong and water level at Hukou station; (c)
same as (b) but for Duchang station).
Yangtze and the water level at Hukou station in summer (JJA)
and autumn (SON). The correlations between the streamflow in
the upper-middle Yangtze (Yichang and Hankou in Fig. 4b) and
the water level at Hukou station are the highest with less seasonal
variations. Similar results can be obtained for the correlation
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Fig. 5. The composite monthly mean higher water level (L P 18 m, n = 16 years), lower water level (L 6 16.5 m, n = 17 years) and middle water level (16.5 < L < 18 m,
n = 20 years) at the Poyang Lake during 1957–2009 and the corresponding water level variability at (a) Jiujiang, (b) Hukou, (c) Xingzi and (d) Duchang (stations. (n is the years,
L is the monthly mean water level in August).
Fig. 6. The accumulated monthly streamflow anomalies compared with the
average over 1956–2009 in the Yangtze River basin. The inflow and outflow of
Lake represent the water balance of the Poyang Lake.
between the streamflow at Yichang, Hankou and Datong stations
and water level at Duchang station (Fig. 4c).
The composite analysis of higher water level, middle water level
and lower water level at Jiujiang station, which is very close to that
of Hukou station (32 km upstream), was made to uncover the
impacts of the Yangtze River on the Poyang Lake’s water resources.
The highest water level at Jiujiang station appears in July and
August, where the water level L P 18 m in August was regarded
as the highest water level year, L 6 16.5 m was the lowest water
level year, and a level of 16.5 < L < 18 m was a middle water level
year. Statistical results during the period of 1957–2009 indicate
that there are 16, 20 and 17 of the highest, middle and lowest
water level years, respectively. For the higher water level years,
the average water level at Jiujiang station in July and August is over
19 m and then falls slowly to a minimum water level of 9 m in January. For the lower water level years, the average water level is
reduced to approximately 17 and 15 m in July and August, respectively. The averaged water level for the middle water level years is
between the higher water level and lower water level from July to
December (Fig. 5a). For the higher water level years at Jiujiang station, the composite monthly averaged water level at Hukou and
Xingzi stations (Xingzi station is quite close to the Hukou station
in the Poyang Lake) from July to December is also higher than that
of lower water level years (Fig. 5b and c). Furthermore, the changing pattern of water level at Hukou and Xingzi stations are very
close to that of Jiujiang station. However, there is a little difference
between the composite higher water level years and lower water
level years at Duchang station located in the central area of Poyang
Lake, which indicates that the influences of the Yangtze River on
the Poyang Lake’s water level reduce gradually with distance away
from the Yangtze River (Fig. 5d).
Fig. 6 shows the accumulated streamflow anomalies in the Poyang Lake basin and the upper and middle Yangtze River basin at
Cuntan, Yichang and Hankou stations, respectively. The trends of
streamflow in the upper and middle Yangtze reaches show a similar tendency: streamflow anomalies increase in the 1960s, 1980s
and at the turn of the 21th century, and decrease in the 1970s,
the early and middle of 1990s and the latter half of the 2000s.
However, the inflow and outflow of the Poyang Lake basin are
opposite to the upper Yangtze reaches in the 1960s. During the
droughts of the 1960s, the inflow and outflow of the Poyang Lake
decreased sharply; however, there was a marked increase in the
streamflow in the upper and middle Yangtze reaches. As for the
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Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
Precipitation Anomalies
(mm)
<= -700
-400 - -699
- 200 - -399
-100 - -199
-99 - 99
100 - 199
200 -300
>=300
Precipitation Anomalies
(mm)
<= -700
-400 - -699
- 200 - -399
-100 - -199
-99 - 99
100 - 199
200 -300
>=300
Fig. 7. The accumulated monthly precipitation anomalies during the drought period of (a) 1963–1967 and (b) 2007–2009, compared with the average over 1956–2009 in the
Yangtze River basin.
droughts in the 2000s, the situation was completely different from
that in the 1960s. The streamflow decreased obviously in the Poyang Lake and also decreased in the upper and middle Yangtze
reaches. Similar results can also be found in comparison between
the extreme droughts and pluvials in the Poyang Lake and in the
upper and lower Yangtze reaches by using the methods of SPI
and SRI (Fig. 2).
The accumulated precipitation anomalies during the droughts
of the 1960s and 2000s might partly explain the difference
between them (Fig. 7). Greater negative precipitation anomalies
can be found both of them in the Poyang Lake basin, while in the
upper and middle Yangtze, positive precipitation anomalies can
be found in the 1960s and negative precipitation anomalies appear
in the 2000s.
The inconsistent variation of streamflow in the Poyang Lake
basin to the upper Yangtze reaches during the droughts of the
1960s increased the blocking and/or reversing flow from the Yangtze River to the Poyang Lake. During the droughts of the 1960s,
the blocking and/or reversing flow lasted 181 days with the
amount of water intrusion from Yangtze River to the Poyang Lake
was 24.9 billion m3, and the largest monthly amount of water
intrusion was detected in September 1964 with a value of over
7.1 billion m3. For the droughts of the 2000s, the blocking and/or
reversing flow was only 69 days with the amount of 7.8 billion m3
water intrusion from the Yangtze River to the Poyang Lake in the
years of 2007 and 2008, and almost no water intrusion from the
Yangtze River to the Poyang Lake in 2009.
3.3. The impacts of TGD on the Poyang Lake’s water resources
The operation of the TGD has changed the seasonal variations of
the Poyang Lake and the Yangtze River forcing. The strongest influence of the TGD on the lower Yangtze reaches occurs mainly from
Table 4
Reservoir inflow and outflow of the Three Gorges Dam (TGD) in October during the
period of 2006–2009 (4Q, TGD outflow minus TGD inflow, QJj is the streamflow at
Jiujiang station, DQ/QJj means the impoundment of TGD account for the streamflow
loss in the lower Yangtze. The reservoir inflow and outflow of the TGD data comes
from: China Three Gorges Corporation, http://www.ctgpc.com.cn/).
Year
2006
2007
2008
2009
Reservoir streamflow (108 m3)
Percentage DQ/QJj (%)
Inflow
Outflow
DQ
350
358
398
330
283
308
300
222
66
50
97
108
19
11
20
31
September to October when the TGD impounds each year. The TGD
influence can be seen from the following evidence: (1) the
impounding of water by the Three Gorges Projects (TGP) lasted
from September 20 to October 28, 2006, which raised the water
level in the front of the dam from 135 to 156 m over this period.
The total impounded water in the TGD was around 66 108,
50 108, 97 108 and 108 108 m3 in October during the years
of 2006, 2007, 2008 and 2009, respectively; and the total
impounded water by TGD in October 2008 and 2009 might contribute around 20% and 31%, respectively, of the streamflow at
Jiujiang station (Table 4). The impounding of the TGD caused over
3 billion m3 water flow from the Poyang Lake to the Yangtze River
in October 2008 which is more than that of 1958 and 1991; (2)
Cumulative probabilities of streamflow and water levels for the
Poyang Lake and lower Yangtze River in October during the preTGD (1957–2002) and the post-TGD (2003–2009) periods demonstrate impacts of the TGD on the Poyang Lake outflow (Fig. 8).
Although the Poyang Lake inflow of the pre-TGD period is larger
than that of the post-TGD period, the lake outflow of the postTGD period is significantly larger than that of the pre-TGD period
518
Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
14000
14000
(a) Inflow of Poyang Lake
Streamflow (m /s)
10000
3
3
Streamflow (m /s)
12000
8000
6000
4000
P (pre-TGD)
P (post-TGD)
10000
8000
6000
4000
2000
0
P (pre-TGD)
P (post-TGD)
-2000
2000
0
(b) Outflow of Poyang Lake (Hukou)
12000
-4000
0
20
40
60
80
100
0
20
40
P (%)
24
(c) Xingzi
22
22
20
20
Water level (m)
Water level (m)
24
60
18
16
14
12
10
100
(d) Hukou
18
16
14
12
10
P (pre-TGD)
P (post-TGD)
8
P (pre-TGD)
P (post-TGD)
8
6
6
0
20
40
60
80
100
0
20
40
P (%)
24
60
24
(e) Jiujiang
22
22
20
20
18
16
14
12
10
P (pre-TGD)
P (post-TGD)
8
18
16
14
12
10
P (pre-TGD)
P (post-TGD)
6
20
40
100
(f) Datong
8
6
0
80
P (%)
Water level (m)
Water level (m)
80
P (%)
60
80
100
0
20
40
60
80
100
P (%)
P (%)
Fig. 8. Cumulative probabilities of streamflow and water levels for pre-TGD (1957–2002) and post-TGD (2003–2009) period in the Poyang Lake and lower Yangtze River.
Table 5
Observed streamflow and water level of the Poyang Lake, and simulated water level at Hukou station in October for the selected drought years. The selected years before and after
TGP are with similar lake inflow and streamflow of middle and lower Yangtze River, and similar water level at Hukou, Jiujiang and Datong stations in October (Obs, observed
water level; Scenario-1, simulated water level at Hukou station using the observed streamflow at Datong station according to the correlations between the streamflow at Datong
station and water level at Hukou station; Scenario-2, same as Scenario-1, but using the streamflow of Datong plus the impoundment of TGD; DH, water level of Scenario-2 minus
that of Scenario-1).
Year
Streamflow (108 m3)
Lake inflow
2007
1960
2008
2001
2009
1978
27
24
38
33
22
16
Hukou
116
77
120
80
46
27
Water level (m)
Hankou
538
568
583
696
389
453
Datong
700
703
737
802
470
501
for the extreme drought years (P < 20% in Fig. 8b). Moreover, the
backward flow from the Yangtze River to the Poyang Lake (negative value in Fig. 8b) was found during the pre-TGD period but it
Jiujiang
12.8
13.5
13.2
14.4
10.4
11.8
Datong
8.4
8.5
8.7
9.4
6.4
7.0
Hukou
Obs
Scenario-1
Scenario-2
DH
12.3
12.6
12.7
13.7
9.7
10.8
12.8
13.0
13.3
14.1
10.5
10.8
13.3
0.5
13.8
0.5
12.0
1.5
disappeared for the post-TGD period. The cumulative probabilities
of the water levels at the Poyang Lake (Xingzi station), outlet of the
Poyang Lake (Hukou station) and the lower Yangtze (Jiujiang and
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Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
Fig. 9. The correlations between daily water level at Hukou station and streamflow
at Datong station during the recession period (from 1st August to 31st December) of
1957–2009.
2004
20
Datong stations) during the post-TGD period (Fig. 8c–f) are always
lower than those of the pre-TGD period; (3) the lake inflow and
water level for the six drought years with similar streamflow of
middle and lower Yangtze River, and similar water level at Hukou,
Jiujiang and Datong stations in October represent different behaviors before and after the TGP impounding (e.g. 2007 vs. 1960, 2008
vs. 2001, 2009 vs. 1978 in Table 5). Although the amount of lake
inflow in October for the post-TGD years was larger than that of
the pre-TGD period, the lake level (Obs. at Hukou station in Table 5)
for the post-TGP period was lower than that of the pre-TGP period
due to the increased Poyang Lake outflow.
The influence of the TGD impounding on the water level of the
Poyang Lake is further estimated by correlation analysis. As shown
in Fig. 9, a good relationship between water level at Hukou station
and streamflow at Datong station can be found during the past several decades. Therefore, the correlation between them during the
recession period (from 1st August to 31st December) is adopted
to reveal the impacts of the TGD impounding on the water level
of Poyang Lake (Fig. 9). Fig. 10 shows the observed and simulated
water levels at the outlet of Poyang Lake (Hukou station) during
12
Aug 1
Observed
Scenario 1
Scenario 2
Sep 1
Oct 1
Nov 1
Dec 1
14
12
10
Aug 1
18
18
16
16
Observed
Scenario 1
Scenario 2
14
12
8
Aug 1
Oct 1
Nov 1
Dec 1
2008
20
Oct 1
Dec 1
2007
10
(d)
Observed
Scenario 1
Scenario 2
Sep 1
Oct 1
Nov 1
Dec 1
2009
20
(e)
Nov 1
12
Aug 1
(f)
18
Water level (m)
18
16
14
12
8
Observed
Scenario 1
Scenario 2
Aug 1
Sep 1
10
Sep 1
14
8
Sep 1
Observed
Scenario 1
Scenario 2
20
(c)
10
Water level (m)
16
8
2006
20
Water level (m)
Water level (m)
14
Water level (m)
Water level (m)
16
8
(b)
18
18
10
2005
20
(a)
16
14
12
10
8
Oct 1
Nov 1
Month/Day
Dec 1
Aug 1
Observed
Scenario 1
Scenario 2
Sep 1
Oct 1
Nov 1
Dec 1
Month/Day
Fig. 10. The observed and simulated water levels in two scenarios with and without the TGD impounding at the outlet of the Poyang Lake during the recession period of
2004–2009 (Scenario-1, the water level at Hukou station with the impounding of TGD; Scenario-2, the water level at Hukou station without the impounding of TGD).
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Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
the recession period of 2004–2009 for the two scenarios with and
without the TGD impounding. For Scenario-1, the water level at
Hukou station with the impounding of TGD was simulated by the
observed streamflow at Datong station using the relationship
between the streamflow at Datong station and water level at
Hukou station. For Scenario-2, the water level at Hukou station
without the impounding of TGD was simulated by the reconstructed streamflow at Datong station using the same relationship.
Because the distance between Datong station and TGD is approximately 1,129 km, it takes 12 days for the water flowing from TGD
to Datong station (http://www.cjw.com.cn/). The reconstructed
streamflow at Datong station was estimated as the total of the
impounding of TGD (TGD inflow minus TGD outflow) and the
streamflow of Datong with a lag of 12 days.
The reliability of the simulated results by the correlation analysis was tested by comparison of the simulated and observed water
levels at Hukou station. The simulated water levels agree well with
the observed water levels at Hukou for the years of 2004–2009
(Scenario-1 vs. observation in Fig. 10). The simulated water levels
were quietly close to the observed water levels in October for the
selected drought years before and after the TGP operation periods
(Scenario-1 vs. observation in Table 5). Therefore, the correlation
analysis is reliable to estimate the influence of the impounding
of the TGD on the water level of the Poyang Lake. Fig. 10 shows that
the simulated water levels in Scenario-2 without the impounding
of TGD are higher than those of the Scenario-1 with the impounding of TGD during the period of 2006–2009. The difference of the
simulated water levels between Scenarios-1 and Scenarios-2 at
the outlet of Poyang Lake (Hukou station in Table 5) indicates that
the water level in October declined from 0.5 m in 2007 and 2008 to
1.5 m in 2009 due to the impounding of TGD.
4. Discussions and conclusions
Severe water shortages of Poyang Lake have aroused wide concern recently and raised the possibility of the TGD being responsible for the low water level at the Poyang Lake. Despite various
studies revealing the considerable effects on the water level of Poyang Lake (Dai et al., 2008; Guo et al., 2011; Lai et al., 2014), the
TGD’s impact needs to be further assessed combined with the
extreme droughts in the Poyang Lake basin and the upper Yangtze
reaches. It remains unknown whether the shortage of water in the
Poyang Lake is a trend or a regime shift, and how the TGD operation contributes it, which is of high importance for policymakers
as it may lead to different decisions.
This work quantifies the extreme drought events and the TGD’s
contributions to recent low water levels at the Poyang Lake by
using a five-decade record of the streamflow and precipitation data
in the Yangtze River basin. Continuous low water levels at the Poyang Lake in recent years are relevant to the conjunction of extreme
droughts in the Poyang Lake basin and the upper Yangtze River
basin. Comparison between the droughts of the Poyang Lake in
the 1960s and 2000s explains how the extreme droughts affect
the water resource in the Poyang Lake. Both of the droughts in
the 1960s and 2000s in the Poyang Lake basin have caused an obvious decrease of streamflow from five tributary river basins to the
Poyang Lake. However, the streamflow in the upper Yangtze
reaches sharply decreased during the droughts of the 2000s while
it increased obviously in the droughts of the 1960s compared to
the period of 1957–2009. The decline of streamflow in the upper
Yangtze reaches has lowered the water level in the lower Yangtze
River. As an overflow lake with the seasonal characteristic pattern
of taking in and sending out water, the water level in the lower
Yangtze River plays a major role in the lake outflow of the Poyang
Lake during the recession period. Less water flows backward into
the Poyang Lake from the Yangtze River during the drought of
the 2000s compared to that of the 1960s. As a result, the outflow
from Poyang Lake to the Yangtze River increases greatly in the
droughts of the 2000s with the amount of 195 billion m3 compared
to that of the 1960s (138 billion m3). These results agree well with
the research of Lai et al. (2014) who pointed out that the recent
extremely low water levels at lower Yangtze River were mainly
because of the remarkable decline in streamflow from the middle
and upper Yangtze reaches resulting from precipitation changes
and possible human activities by using a newly developed hydrodynamic model. Guo et al. (2008) also pointed out that the interaction between the Poyang Lake and the Yangtze River strongly
affects the Poyang Lake water resources and drought potentials
in the lake basin.
The TGD’s operation has altered the seasonal pattern of flow
regimes and significantly reduced the water level mainly in the
drought period of October when the TGD is impounding each year
(Guo et al., 2012; Lai et al., 2014). This study demonstrates that the
lake outflow for the post-TGP period is higher than that of pre-TGP
period for the corresponding drought years before and after TGP
impounding (e.g. 2007 vs. 1960, 2008 vs. 2001, and 2009 vs.
1978) although the lake inflow from the five tributaries of the
watershed for the post-TGP period is less than that of the preTGP period. It was proven by the cumulative probabilities that
the lake outflow in October for the post-TGD period was significantly larger than that of the pre-TGD period for the extremely
drought years. This larger outflow from the Poyang Lake during
the post-TGP period results from the decline of water levels in
the lower Yangtze reaches due to the TGD impounding. The TGD
impounding induced water level declines in 0.5, 0.5 and 1.5 m at
Hukou station in October in 2007, 2008 and 2009, respectively,
according to correlation analysis in this study. This study shows
that, although the operation of TGD has altered the seasonal pattern of flow regimes in the lower Yangtze reaches, the conjunction
of extreme droughts in the Poyang Lake basin and lack of rain in
the upper Yangtze River basin is the main cause of the low water
level in the Poyang Lake. Some researches show that groundwater
also affects this hydrologic change, in particular, in drought seasons and after construction of TGD (Dai et al., 2010; Nakayama
and Shankman, 2013b).
With more and more big dams have been and are being built in
China and other countries, dams have major impacts on river
hydrology and produce a hydrologic regime differing significantly
from the pre-impoundment natural flow regime. Interaction
between large rivers and reservoirs as well as natural lakes directly
connecting to the rivers is an issue of international significance. For
example, Al-Faraj and Scholz (2014) found that the upstream dams
and large-scale water withdrawal have made great impacts on
temporal river flow regimes for the downstream countries in West
Asia. Peters and Buttle (2010) also pointed out that the strength of
the relationships between the Lake Athabasca and Peace River,
Canada has been significantly changed because the runoff from
the Peace River headwaters has been stored in the man-made Williston Lake since 1968. The estimated average duration of obstruction was shortened more than two weeks and reverse flow volume
was reduced largely under a regulated regime compared to the
simulated natural flow. Therefore, the research methods of this
paper might be applied for the above mentioned areas and other
relevant areas. The results of this study also call for more attention
on the conjunction of dam impounding and abnormal climate for a
river regime.
Acknowledgements
This paper is financially supported by the State Key Development Program for Basic Research of China (Grant No.
Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521
2012CB417006), Project supported by the State Key Program of
National Natural Science of China (Grant No. 40930635), National
Natural Science Foundation of China (Grant Nos. 41171020,
51190090). The project supported by the Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of
Information Science and Technology (KLM101) and the Priority
Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The third author was also supported by the Program of Introducing Talents of Discipline to Universities—the 111
Project of Hohai University. We would like to thank the National
Climate Centre in Beijing for providing valuable climate datasets.
References
Al-Faraj, F.A.M., Scholz, M., 2014. Assessment of temporal hydrologic anomalies
coupled with drought impact for a transboundary river flow regime: The Diyala
watershed case study. J. Hydrol. 517, 64–73.
Bordi, I., Fraedrich, K., Gerstengarbe, F.W., Werner, P.C., Sutera, A., 2004. Potential
predictability of dry and wet periods: Sicily and Elbe-Basin (Germany). Theoret.
Appl. Climatol. 77 (3–4), 125–138.
Bordi, I., Sutera, A., 2007. Drought monitoring and forecasting at large scale. In:
Rossi, G., Vega, T., Bonaccorso, B. (Eds.), Methods and Tools for Drought Analysis
and Management. Water Science and Technology Library, Springer,
Netherlands, pp. 3–27.
Cancelliere, A., Ancarani, A., Rossi, G., 1998. Susceptibility of water supply reservoirs
to drought conditions. J. Hydrol. Eng. 3 (2), 140–148.
Chen, L., 2001. The role of anomalous snow cover over the Qinghai-Xizong Plateau
and ENSO in the great floods of 1998 in the Changjiang River valley. Chin. J.
Atmos. Sci. 25, 184–192 (in Chinese with English abstract).
Chen, S.-T., Kuo, C.-C., Yu, P.-S., 2009. Historical trends and variability of
meteorological droughts in Taiwan/Tendances historiques et variabilité des
sécheresses météorologiques à Taiwan. Hydrol. Sci. J. 54 (3), 430–441.
Dai, Z.-J., Chu, A., Du, J.-Z., Stive, M., Hong, Y., 2010. Assessment of extreme drought
and human interference on baseflow of the Yangtze River. Hydrol. Process. 24
(6), 749–757.
Dai, Z., Du, J., Li, J., Li, W., Chen, J., 2008. Runoff characteristics of the Changjiang
River during 2006: effect of extreme drought and the impounding of the Three
Gorges Dam. Geophys. Res. Lett. 35 (7), L07406.
Edwards, D.C., McKee, T.B., 1997. Characteristics of 20th Century Drought in the
United States at Multiple Time Scales, Climatology Report Number 97–2.
Colorado State University, Fort Collins, Colorado.
Gosling, R., 2014. Assessing the impact of projected climate change on drought
vulnerability in Scotland. Hydrol. Res. 45 (6), 806–816. http://dx.doi.org/
10.2166/nh.2014.148.
Guo, H., Hu, Q., Jiang, T., 2008. Annual and seasonal streamflow responses to climate
and land-cover changes in the Poyang Lake basin. China. J. Hydrol. 355 (1–4),
106–122.
Guo, H., Hu, Q., Zhang, Q., 2011. Changes in hydrological interactions of the Yangtze
River and the Poyang Lake in China during 1957–2008. Acta Geogr. Sinica 66 (5),
609–618 (in Chinese with English abstract).
Guo, H., Hu, Q., Zhang, Q., Feng, S., 2012. Effects of the three Gorges Dam on Yangtze
River flow and river interaction with Poyang Lake, China: 2003–2008. J. Hydrol.
416–417, 19–27.
Hannachi, A., Jolliffe, I.T., Stephenson, D.B., 2007. Empirical orthogonal functions
and related techniques in atmospheric science: a review. Int. J. Climatol. 27 (9),
1119–1152.
Hayes, M.J., Svoboda, M.D., Wilhite, D.A., Vanyarkho, O.V., 1999. Monitoring the
1996 drought using the standardized precipitation index. Bull. Am. Meteorol.
Soc. 80 (3), 429–438.
Hu, Q., Feng, S., Guo, H., Chen, G., Jiang, T., 2007. Interactions of the Yangtze River
flow and hydrologic processes of the Poyang Lake. China. J. Hydrol. 347 (1–2),
90–100.
Hurst, H., 1951. Long term storage capacity of reservoirs. Trans. Am. Soc. Civil Eng.
116, 770–799.
Jolliffe, I.T., 2002. Principal Component Analysis, second ed. Springer, New York.
Jiang, T., Shi, Y.F., 2003. Global warming and its consequences in Yangtze River
floods and damages. Adv. Earth Sci. 18, 277–284 (in Chinese with English
abstract).
521
Lai, X., Jiang, J., Yang, G., Lu, X.X., 2014. Should the three Gorges Dam be blamed for
the extremely low water levels in the middle–lower Yangtze River? Hydrol.
Process. 28 (1), 150–160.
Li, Y.L., Zhang, Q., Werner, A.D., Yao, J., 2015a. Investigating a complex lakecatchment river system using artificial neural networks: Poyang Lake (China).
Hydrol. Res. (in press).
Li, X.H., Zhang, Q., Xu C-Y, Ye, X.C., 2015b. The changing patterns of floods in Poyang
Lake, China: characteristics and explanations. Nat. Hazards (in press). http://dx.
doi.org/10.1007/s11069-014-1509-5.
Lloyd-Hughes, B., Saunders, M.A., 2002. A drought climatology for Europe. Int. J.
Climatol. 22 (13), 1571–1592.
López-Moreno, J.I. et al., 2009. Dam effects on droughts magnitude and duration in a
transboundary basin: the Lower River Tagus, Spain and Portugal. Water Resour.
Res. 45 (2), W02405.
Lorenzo-Lacruz, J. et al., 2010. The impact of droughts and water management on
various hydrological systems in the headwaters of the Tagus River (central
Spain). J. Hydrol. 386 (1–4), 13–26.
McKee, T.B., Doesken, N.J., Kleist, J., 1993. The relationship of drought frequency and
duration to time scales. In: Preprints, 8th Conference on Applied Climatology,
January 17–22, Anaheim, California, pp. 179–184.
Nakayama, T., Shankman, D., 2013a. Evaluation of uneven water resource and
relation between anthropogenic water withdrawal and ecosystem degradation
in Changjiang and Yellow River basins. Hydrol. Process. 27 (23), 3350–3362.
Nakayama, T., Shankman, D., 2013b. Impact of the three-Gorges Dam and water
transfer project on Changjiang floods. Global Planet. Change 100, 38–50.
North, G.R., 1984. Empirical orthogonal functions and normal modes. J. Atmos. Sci.
41 (5), 879–887.
Palmer, W.C., 1965. Meteorological drought, Research paper no. 45, US Department
of Commerce, Weather Bureau, Washington, DC.
Peters, D.L., Buttle, J.M., 2010. The effects of flow regulation and climatic variability
on obstructed drainage and reverse flow contribution in a Northern river–lake–
Delta complex, Mackenzie basin headwaters. River Res. Appl. 26 (9), 1065–
1089.
Portela, M.M., Santos, J.F., Silva, A.T., Benitez, J.B., Frank, C., Reichert, S.M., 2015.
Drought analysis in southern Paraguay, Brazil and northern Argentina:
regionalization, occurrence rate and rainfall thresholds. Hydrol. Res. (in
press), http://dx.doi.org/10.2166/nh.2014.074.
Rahmat, S. N., Jayasuriya, N., Bhuiyan, M., 2015. Assessing droughts using
meteorological drought indices in Victoria, Australia. Hydrol. Res. (in press),
http://dx.doi.org/10.2166/nh.2014.105.
Rossi, G., Castiglione, L., Bonaccorso, B., 2007. Guidelines for planning and
implementing drought mitigation measures. In: Rossi, G., Vega, T.,
Bonaccorso, B. (Eds.), Methods and Tools for Drought Analysis and
Management. Water Science and Technology Library, Springer, Netherlands,
pp. 325–347.
Shankman, D., Heim, B.D., Song, J., 2006. Flood frequency in China’s Poyang Lake
region: trends and teleconnections. Int. J. Climatol. 26, 1255–1266.
Tsakiris, G., Vangelis, H., 2005. Establishing a drought index incorporating
evapotranspiration. Eur. Water 9–10, 3–11.
Van Loon, A.F., Van Lanen, H.A.J., 2013. Making the distinction between water
scarcity and drought using an observation-modeling framework. Water Resour.
Res. 49 (3), 1483–1502.
von Storch, H., 1995. Spatial patterns: EOFs and CCA. In: von Storch, H., Navarra, A.
(Eds.), Analysis of Climate Variability: Application of Statistical Techniques.
Springer Verlag, Berlin, pp. 227–257.
von Storch, H., 1999. Spatial patterns: EOFs and CCA. In: von Storch, H., Navarra, A.
(Eds.), Analysis of Climate Variability. Springer, Berlin Heidelberg, pp. 231–263.
Wilks, D.S., 2006. Statistical Methods in the Atmospheric Sciences, 2nd edn.
Academic Press, Amsterdam.
Zhang, Q., Liu, Y., Yang, G., Zhang, Z., 2011a. Precipitation and hydrological
variations and related associations with large-scale circulation in the Poyang
Lake basin. China. Hydrol. Process. 25 (5), 740–751.
Zhang, Z.X., Zhang, Q., Chen, X., Zhang, J., Zhou, J., 2011b. Statistical properties of
moisture transport in East Asia and their impacts on wetness/dryness variations
in North China. Theoret. Appl. Climatol. 104 (3), 337–347.
Zhang, Z.X., Xu, C-Y., Ying, B., Hu, J.J., Sun, Z.H., 2012. Understanding the changing
characteristics of droughts in Sudan and the corresponding components of the
hydrologic cycle. J. Hydrometeorol. 13, 1520–1535, 0.1175/JHM-D-11-0109.1.
Zhang, Q., Ye, X.C., Werner, A.D., Li, Y.L., Yao, J., Li, X.H., Xu, C.-Y., 2014. An
investigation of enhanced recessions in Poyang Lake: comparison of Yangtze
River and local catchment impacts. J. Hydrol. 517, 425–434.
Zhao, G., Hörmann, G., Fohrer, N., Zhang, Z., Zhai, J., 2010. Streamflow trends and
climate variability impacts in Poyang Lake Basin. China. Water Res. Manag. 24
(4), 689–706.
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