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RESEARCH ARTICLE
Water level variation characteristics under the impacts of
extreme drought and the operation of the Three Gorges Dam
Yuanfang CHAI
1
, Yitian LI (✉)
1
, Yunping YANG
2
, Sixuan LI
1
, Wei ZHANG
1
, Jinqiu REN
1
, Haibin XIONG
1
1 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
2 Key Laboratory of Engineering Sediment, Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300000, China
© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract Under the influence of a climate of extreme
drought and the Three Gorges Dam (TGD) operation, the
water levels in the middle and lower reaches of the Yangtze
River in 2006 and 2011 changed significantly compared
with those in the extreme drought years of 1978 and 1986.
To quantitatively analyze the characteristics of water level
variations in 2006 and 2011, a new calculation method was
proposed, and the daily water level and discharge from
1955–2016 were collected in this study. The findings are as
follows: in 2006 and 2011, the water level in the dry season
significantly increased, but that in the flood season
obviously decreased compared with the levels in 1978
and 1986. Here, we described this phenomenon as “no
low-water-level in dry season, no high-water-level in flood
season”. Based on the calculation method, the contribu-
tions of climate variability and the Three Gorges Dam
operation to water level variations in the middle and lower
reaches of the Yangtze River were calculated, and the
contributions indicated that climate variability was the
main reason for the phenomenon of “no low-water-level in
dry season, no high-water-level in flood season”instead of
flood peak reduction in the flood season and drought runoff
implementation in the dry season, which are both induced
by TGD.
Keywords water level, extreme drought climate, the
Three Gorges Dam, the Yangtze River Basin
1 Introduction
Water level variations are closely related to navigation
conditions, the location of water intakes, the stability of
slopes and the growth of aquatic vegetation and animals.
Many scholars have studied the patterns of water levels (Li
et al., 2017; Lin et al., 2017) and its causes (Lin et al.,
2011; Mei et al., 2018) and impacts (Fischer and Öhl,
2005). Some researchers have concentrated on the
response of water level variations to climate variability
(Gibson et al., 2006; Bian et al., 2010). For instance,
Milano (Milano, 2012) predicted the influence of pre-
cipitation variations on water levels in the Des Prairies
River based on Hec-Geo HMS, Hec-Geo RAS and
River2D software. Xiao et al. (2018) analyzed evaporation
and its effects on present, past, and future water levels in
White Bear Lake. Wu et al. (2014) studied the effects of
glacial melting on water levels, and the results show that
glacial meltwater in a catchment contributes to the water
level rise in Nam Co Lake. Some scholars have also
focused on the effects of human activities on water level
changes. Wu (2008) analyzed the effects of dredging
activities and the Three Gorges Dam (TGD) on the water
level of Poyang Lake. The influence of the Shuikou
Reservoir on water level changes in the Minjiang River
was analyzed by using a mathematical model (Yang et al.,
2013). Wang et al. (2013, 2017) used the hydrological
model PCR-GLOBWB and the stage-discharge rating
curves to assess the influence of the TGD operation on the
water level downstream the dam by comparatively
quantifying the impacts of two major outcomes of TGD
operation: (i) regulated Yangtze flow and (ii) concurrent
channel erosion due to reduced sediment discharge.
Particularly in Wang et al. (2017), the authors also
considered the impacts of human water consumption.
However, water level variations are affected by both
climate variability and human activities, and because of
this, the influence of these two factors on water levels have
also been analyzed by many researchers (Hu and Wang,
2009). Lai et al. (2014) reconstructed the water level at
Luoshan, Hankou, and Datong under the condition of non-
TGD operation using a newly developed hydrodynamic
model and suggested that the TGD operation significantly
Received February 26, 2018; accepted September 25, 2018
E-mail: 15871435411@163.com
Front. Earth Sci. 2019, 13(3): 510–522
https://doi.org/10.1007/s11707-018-0739-3
decreased the water level in late September to November
because of water impoundment and increased water level
from April to early June due to the drawdown of the TGD
water level, but the influence of riverbed scouring on water
levels needs more detailed studies. However, under the
combined influence of a climate of extreme drought and
reservoir operation, fewer studies have focused on the
hydrological processes in these conditions (Dai et al.,
2008a). Some researchers have concentrated on the
variability characteristics of organic carbon transport
process (Yu et al., 2011), sediment (Yan et al., 2008; Dai
et al., 2011), baseflow (Dai et al., 2010a), groundwater
(Dai et al., 2010b), salinity (Dai et al., 2008b), and river-
lake interactions (Dai et al., 2010c). Few studies are about
the water level variation characteristics with the impacts of
both extreme drought and reservoir operation. Dai et al.
(2008a) analyzed the water level variation characteristics
under the influence of extreme drought and the TGD
operation in great detail, but the reasons for the variation
characteristics needs to be further investigated.
Under the impacts of climate variability and human
activities, river hydrology and morphology have changed,
which further changed the relationship between runoff and
water level (Dai et al., 1998; Mei et al., 2016). There is a
general rule that riverbed erosion will occur and the
elevation of a thalweg will decline after reservoir
operations, and this phenomenon is quite normal in
many rivers, including the Nile, Danube, Ebro, and
Mississippi rivers (Dai and Liu, 2013) and 21 rivers in
North America (Williams and Wolman, 1984). In 2003,
TGD, the largest reservoir in the world, was constructed in
the Yangtze River, which obviously reduced the river
sediment load downstream of the dam and thus signifi-
cantly changed the water level variation characteristics.
During the period from October 2002 to October 2014, the
incision of the thalweg downstream of the TGD within
410 km was up to 1.5 m due to the TGD operation (Yang
et al., 2017a), which significantly reduced the water level
under the same discharge. In addition, the variations in the
runoff caused by the TGD can also have a significant
impact on the water level variations. From January 1 to
June 10, 2011, the total water volume supplemented by the
TGD was up to 2.1510
10
m
3
to satisfy the needs of the
ecological environment and to combat drought, which
distinctly increased the water level downstream of the
TGD. Thus, the water level variation characteristics
become more complex under the effects of the riverbed
evolution and discharge variations caused by the TGD
operation. Apart from the influence of the TGD operation,
the Yangtze River Basin suffered from extreme drought in
2006 and 2011. The annual average discharges at Datong
Station (the control station of the mouth of the Yangtze
River) were the lowest and the third lowest in history
(1955–2017), respectively, which further changed the
water level processes in the middle and lower reaches of
the Yangtze River (MLRYR). Furthermore, based on the
PRECIS climate model system, Zhang et al. (2006)
concluded that extreme climate events, especially extreme
precipitation events, will be more and more frequent in the
Yangtze River Basin because of the warming environment.
The obvious fluctuation in water levels can significantly
impact the ecological environment, shipping, and irriga-
tion. Thus, based on insufficient research and the research
significance, the purposes of this paper are as follows:
(i) analyzing the changes in water level characteristics and
their causes in 2006 and 2011, under the influence of the
TGD operation and the climate of extreme drought;
(ii) estimating the contributions of the TGD operation
and climate variability on the water level variations
downstream of the TGD. This research will be meaningful
for optimizing reservoir operation rules and the distribu-
tion and management of water resources.
2 Study area and data collection
2.1 Study area
The Yangtze River originates from the Qinghai-Tibetan
Plateau and flows into the East China Sea at a downstream
distance of approximately 6300 km (Liu et al., 2007) and is
divided by Yichang and Hukou into the upper reach, the
middle reach and the lower reach (Han et al., 2017a)
(Fig. 1(a)). The river is the largest in Asia in terms of
discharge, and its runoff accounts for 35.1%of the total
runoff in China (Cao et al., 2011). Owing to its abundant
water resources, more than 45,694 reservoirs have been
constructed since 1950, with a total capacity of up to
1.5910
11
m
3
(Li et al., 2011). In 2003, TGD, the largest
reservoir in the world, was constructed in the upper reach
of the Yangtze River, posing landmark impacts on riverbed
evolution and the spatiotemporal distribution of water
resources. In addition, there are two lakes (Dongting Lake
and Poyang Lake) and a main tributary (Hanjiang River) in
the middle and lower reaches. Six main hydrological
stations on the mainstream of the Yangtze are involved in
this study, including Yichang, Jianli, Chenglingji,
Luoshan, Hankou, and Datong stations (as shown in
Fig. 1(b)). Yichang and Datong are the control stations of
the TGD outflow and the mouth of the Yangtze River,
respectively. The supplement of runoff and sediment from
Dongting Lake and Poyang Lake into the Yangtze River
are gauged at the Chenglingji and Hukou stations,
respectively.
2.2 Data collection
In this paper, daily water level and discharge data at the
main hydrological stations in the Yangtze River Basin
(Fig. 1(b)) were collected over the period from 1955 to
Yuanfang CHAI et al. Water level variation characteristics 511
2016, referring to the CWRC (Ministry of Water
Conservancy of China). The daily inflow discharge data
of the TGD in 2006 and 2011 were obtained from China
Three Gorges Corporation (http://www.ctg.hk/sxjt/sqqk/
index.html). To study the water level variation patterns of
the Yangtze River in 2006 and 2011, the hydrological data
of 2006 and 2011 are compared with typical years, the
extremely dry years of 1978 and 1986 (pre-TGD) (it is
quite clear that the annual average discharge of these four
extremely dry years at Datong were the lowest during the
period from 1975‒2012 (Fig. 2(b)), and the average annual
precipitation in the Yangtze River Basin in 1978, 1986, and
2011 was also lowest during this period (Fig. 2(a))), the
mean over the decade from 1955 to 2002 (pre-TGD), and
the mean over the decade from 2003 to 2016 (post-TGD).
2.3 Method
Water level variations are affected by many factors,
including climate variability, reservoir operation, back-
water effect, irrigation and living water, human sand
excavation and so on. It is obvious that it is almost
impossible to calculate the contribution of each factor on
water level variations. Thus, we only consider the impact
of climate variability and TGD operation. Assuming that
the annual average discharge and water level of the year N
are QAand HA, then the values of the year M(M>N) are
QBand HBafter the effects of climate variability and
human activity. We also assume that the influences of
discharge changes and riverbed evolution changes on the
water level are independent of each other, and thus the
water level variation of the year Mcompared with the year
N, namely ΔH, can be separated according to Fig. 3(a),
and then the contributions of climate variability (RN) and
human activity (RH) on water level changes can be
calculated with Eqs. (1) and (2), respectively:
Fig. 1 (a) The geographical location of the Yangtze River Basin; (b) the location of the hydrological stations.
Fig. 2 Long-term variations in average annual precipitation in
the Yangtze River Basin (a) (Dai et al., 2016a) and the annual
average discharge at Datong station (b).
512 Front. Earth Sci. 2019, 13(3): 510–522
RN¼jΔHDN jþjΔHQN j
jΔHDN jþjΔHDH jþjΔHQH jþjΔHQN j, (1)
RH¼jΔHDH jþjΔHQH j
jΔHDN jþjΔHDH jþjΔHQH jþjΔHQN j, (2)
where ΔHQdenotes the water level changes caused by
discharge variations, ΔHDrepresents the water level
changes induced by riverbed evolution, ΔHQH is the
water level variation caused by discharge changes resulting
from human activity, ΔHQN denotes the water level
variation caused by discharge changes resulting from
climate variability, ΔHDH represents the water level
variation caused by riverbed evolution resulting from
human activity, and ΔHDN is the water level variation
caused by riverbed evolution resulting from climate
variability.
However, it is difficult to separate ΔHDN ,ΔHDH ,ΔHQH ,
and ΔHQN from ΔH, which is the main reason why it is
hard to quantify the individual impact of the human
activity and climate variability on the water level variation.
To solve this problem, a new calculation is proposed as
follows:
Step 1 (Fig. 3(b)): calculation of water level variation
(ΔHQ, namely, ①) caused by discharge changes (ΔQ):
ΔQ¼QB–QA, (3)
ΔHQ¼HCT –HAT , (4)
where HAT and HCT denote the water level under the
condition of QAand QB, respectively (Fig. 2(b)), which can
be calculated using the fitting curves of Nyears.
Step 2 (Fig. 3(c)): calculation of water level variation
(ΔHD, namely, ②) under the same discharge (QB). Note:
the water level variation under the same discharge, namely,
ΔHD, is caused by the riverbed evolution. If the measured
water level variation of year Mcompared with that of year
N, namely, ΔH, is approximately equal to the theoretical
water level variation (ΔHT, Eqs. (6) and (7)), then it
suggests that the results of this calculation method show
good agreement with the actual situation, following:
ΔHD¼HBT –HCT , (5)
ΔHT¼ΔHQþΔHD, (6)
ΔHΔHT, (7)
where HBT denotes the water level under the condition of
QB(Fig. 2(b)), which can be calculated with the fitting
curves of Myears.
Step 3 (Fig. 3(d)): the discharge variation (ðΔQÞ) can be
divided into two different aspects: ΔQH(induced by
human activity, such as reservoir operation) and ΔQN
(caused by climate variability). Therefore, the correspond-
ing ΔHQcan also be split into ΔHQH (③) and ΔHQN (④)
based on Eqs. (8) and (9), respectively:
ΔHQH ¼ΔQH
ΔQ
⋅ΔHQ, (8)
Fig. 3 Flow diagram of the calculation method. Note: M,N, and Pare the fitting curves in the years M,N, and P, respectively.
Yuanfang CHAI et al. Water level variation characteristics 513
ΔHQN ¼ΔQN
ΔQ
⋅ΔHQ:(9)
Step 4 (Figs. 3(e) and 3(f)): ΔHDcan also be separated
into ΔHDH (⑤) and ΔHDN (⑥) by adopting the time series
prediction method or the restoration method:
Time series prediction method (Fig. 3(e)): based on the
varying tendency of a variable over time, an effective
prediction method, such as the arithmetic average method,
moving average method, or trend extrapolation method,
will be selected to build a mathematical model to predict
the developing trend of the variable (Simon et al., 2004).
This method is widely applied to hydrological forecasts
(Deng et al., 2015), but it is only applied to the variable that
has an obvious change rule with time. The basic
mathematical model is as follows:
Htþh¼fðHt–i,Ht–iþ1,:::,Ht–1,HtÞþh⋅etþh, (10)
where Htþhdenotes the predicted value of the prediction
period of t+h;fðHt–i,Ht–iþ1,:::,Ht–1,HtÞrepresents the
estimated function; his the prediction step; and etþh
denotes the random noise.
The application of this method to this study: based on
the fitting curves of water level and discharge during
different years, the water levels under the same discharge
(QB), namely, ðHt–i,Ht–iþ1,:::,HCT,:::,Ht–1,HtÞ, are calcu-
lated. Then, according to the variation characteristics of the
values over time, the suitable prediction method (in this
study, the arithmetic average method and the calculation
formula Eq. (11) is chosen to predict the water level (HDT )
under the condition of QBin the year P(assuming that the
human activity did not happen during the year M, and thus
here we describe this year as the year P). Therefore, ΔHDN
and ΔHDH can be calculated by Eqs. (12) and (13):
HDT ¼Ht–iþHt–iþ1þ::: þHt
tþ1, (11)
ΔHDN ¼HDT –HCT , (12)
ΔHDH ¼ΔHD–ΔHDN :(13)
Restoration method (Fig. 3(f)): if the values ðHt–i,
Ht–iþ1,:::,HCT ,:::,Ht–1,HtÞdo not have significant varia-
tion characteristics with time, we can choose the restora-
tion method. Based on hydrological and topographic data,
the discharge and water level in the year Pcan be restored
by adopting a one-dimensional unsteady flow and sedi-
ment transport model, which allows us to draw the fitting
curve of P. Thus, based on the fitting curves of M,N, and
P,ΔHDcan be divided into ΔHDN and ΔHDH .
3 Results
3.1 Effects of the TGD operation on runoff and sediment
The operation rules of the TGD are flood peak reduction in
the flood season (FPRF) and drought runoff implementa-
tion in the dry season (DRID) (Figs. 4(a) and 4(b)). In the
flood season, the upstream flood peak is decreased to
alleviate the pressure of downstream flood prevention, and
the runoff is supplemented to dramatically relieve down-
stream drought conditions in the dry season (Han et al.,
2017b; Yang et al., 2017b). Because of this, the maximum
discharge shows a distinct downward trend, and the
minimum discharge shows a significant increasing trend
relative to the predam period (Fig. 4(c)). According to Fig.
4(d), it is clear that the sediment discharge at Yichang saw
a significant decline after the opening of the TGD, which
caused riverbed erosion downstream of the TGD (Han et
al., 2017c). Because of this, the water level at the same
discharge showed a significant decline, especially during
the dry season (Zhu et al., 2017).
3.2 Water level variation characteristics
Flow regulations at the TGD implement flood peak
reduction in the flood season and drought runoff
implementation in dry season (DRID), which has a
leveling effect on the water level in the MLRYR (Dai
et al., 2016b; Kuang et al., 2017). As shown in Fig. 5, the
C
v
and Rvalues from 2003 to 2016 (post-TGD) are
significantly smaller than that of the period from 1955 to
2002 (pre-TGD), which may suggest that the discrete level
of the water level in the downstream reservoir decreased
due to the TGD operation. Before the TGD construction,
the C
v
and Rin the extremely dry years of 1978 and 1986
are slightly smaller than that from 1955 to 2002 as a whole.
Under the effects of both the TGD operation and extreme
drought, C
v
and Rare smallest compared with those in
typical years, implying that the water level variation in
2006 and 2011 was the smoothest. This obvious and
special phenomenon can be described as “no low-water-
level in dry season, no high-water-level in flood season”
(NLD-NHF).
3.2.1 Water level during the dry season
In the dry season, the monthly average water levels in the
MLRYR in 2006 and 2011 all showed a notable upward
trend compared to the extreme drought years of 1978 and
1986 (the brown oval in Fig. 6). As shown in Table 1, it is
noticeable that the average water level of the six
hydrological stations in the dry season in 1978 and 1986
showed a remarkable decline in comparison to 1954–2002
(pre-TGD), with the maximum reduction being up to
1.4 m, while the values in 2006 and 2011 did not change
substantially compared with 2003–2016 (post-TGD), and
the variations were between –0.5 m and 0.4 m. In
conclusion, the distinct and special phenomenon of “no
low-water-level in dry season”(NLD) occurred in 2006
and 2011.
514 Front. Earth Sci. 2019, 13(3): 510–522
3.2.2 Water level during the flood season
In the flood season, compared with 1978 and 1986, the
monthly average water level in the MLRYR in 2006 and
2011 showed a significant decrease (the pink oval in
Fig. 6). Furthermore, the average water levels during the
flood season at Yichang and Jianli in 2006 both dropped to
the lowest point on record (1955–2016), and the four other
stations in 2011 also dropped to the lowest on record
(Table 1). It is noteworthy that the decreasing values of the
average water level in 2006 and 2011 were between 1.8 m
and 2.7 m, compared to 2003–2016. More importantly, the
maximum reduction of the average water level in 2006 and
2011 was up to 3.6 m, in contrast to the extreme drought
years of 1978 and 1986. Therefore, the phenomenon of “no
high-water-level in flood season”(NHF) is an obvious
variation in the water level characteristics in the MLRYR
in 2006 and 2011.
Fig. 5 Statistical parameters of C
v
(a) and R(b) at each hydrological station. Note: C
v
is the coefficient of variation of the monthly
average water level; Ris the ratio of the maximum monthly average water level to the minimum; the values of Rand C
v
stand for the
degree of dispersion of the water level.
Fig. 4 Variations in discharge and sediment before and after the operation of the TGD. (a) and (b) The inflow and outflow of TGD in
2006 and 2011, respectively; (c) the maximum and minimum discharges at Yichang during the period from 1955‒2016; (d) the sediment
discharge at Yichang from 1955 to 2016.
Yuanfang CHAI et al. Water level variation characteristics 515
4 Discussion
Datong is situated at the mouth of the Yangtze River,
which means that its annual runoff represents the total
water resources of the Yangtze River Basin. Interestingly,
although the annual runoff values at Datong in the extreme
drought years of 1978, 1986, 2006, and 2011 were almost
the same (6.7610
11
m
3
, 7.1410
11
m
3
, 6.6710
11
m
3
,
6.8810
11
m
3
, respectively), the distinct and peculiar
phenomenon of “NLD-NHF”in the MLRYR occurred in
2006 and 2011, under the effects of the TGD operation and
extreme drought, instead of taking place in 1978 and 1986.
Fig. 6 The monthly average water level at six hydrological stations. (a) Yichang; (b) Jianli; (c) Chenglingji; (d) Luoshan; (e) Hankou;
and (f) Datong.
Table 1 Average water level (m) during the dry and flood seasons
City 1978 1986 1955‒2002 2006 2011 2003‒2016
Flood
season
Dry
season
Flood
season
Dry
season
Flood
season
Dry
season
Flood
season
Dry
season
Flood
season
Dry
season
Flood
season
Dry
season
Yichang 46.40 40.30 45.70 40.00 46.70 40.70 42.80 40.00 43.10 40.30 44.90 39.90
Jianli 29.89 24.90 30.10 25.10 31.10 25.80 28.76 25.60 28.80 26.00 30.70 25.80
Chenglingji 26.45 20.68 26.80 21.30 27.90 21.50 25.54 22.21 25.10 22.10 27.70 22.30
Luoshan 25.22 19.18 25.70 19.90 26.90 20.20 24.32 20.83 24.00 20.90 26.70 21.00
Hankou 20.30 14.30 20.70 14.90 22.20 15.70 19.30 15.90 19.00 15.60 21.50 15.90
Datong 9.30 5.20 9.60 5.50 11.10 6.20 8.60 6.10 8.40 5.70 10.40 6.20
516 Front. Earth Sci. 2019, 13(3): 510–522
The water level at Yichang is more seriously affected by
the TGD operation than the other five stations, because
Yichang is the control station of the TGD outflow and has
the smallest distance to the TGD. In contrast, the water
level at Datong is most seriously affected by climate
variability because Datong is the control station of the
mouth of the Yangtze River and is the farthest from the
TGD. In addition, the annual runoff at Datong in 2006 and
2011 are the most similar to the value in 1978. Thus, based
on the proposed calculation method, the water level and
discharge data in 1978, 2006, and 2011 at Yichang and
Datong were chosen to analyze the main reasons for the
phenomenon, which are highly typical and representative.
4.1 Factors of NLD
In the 2006 dry season, the average inflow discharge was
up to 5870 m
3
$s
–1
, and the outflow discharge (Yichang,
5611 m
3
$s
–1
) showed no obvious variation because of the
weak influence of DRID (in Fig. 4(a), the daily inflow and
outflow discharges in the 2006 dry season are approxi-
mately the same), which is approximately 506 m
3
$s
–1
larger than the value in 1978 (Fig. 9). Based on the
calculation method, the rising average water level induced
by the increasing average discharge at Yichang was 0.32 m
(Fig. 7). As shown in Fig. 8, it is quite clear that the reach
between Yichang and Zhicheng was under scouring
conditions (Fig. 8(b)), and the thalweg elevation in the
reach shows a significant decreasing trend after the
opening of the TGD (Fig. 8(c)). Based on the statistics,
the average elevations of the thalweg in this reach
decreased by 2.3 m and 2.05 m during the periods of
2002‒2008 and 2008‒2013, respectively. Because of this,
the water level at Yichang under the same discharge also
shows a downward trend (Fig. 8(a)). Compared with the
level in 1978, the reduction in the average water level at
Yichang in 2006 caused by riverbed erosion was up to
Fig. 7 The fitting curve of water level and discharge at Yichang
in the 1978 and 2006 dry season.
Fig. 8 (a) The time-series graph of the water level at Yichang under the same discharge; (b) the volume of scour after the TGD operation
(Yichang-Zhicheng); and (c) downstream thalweg elevation before and after the construction of the TGD (Yichang-Zhicheng).
Yuanfang CHAI et al. Water level variation characteristics 517
1.08 m (Fig. 7 and Fig. 10(a)). Thus, under the effects of
both discharge variation and riverbed evolution, the
theoretical average water level reduction (ΔHT) in 2006
was 0.76 m compared to 1978, which is the same as the
measured average water level variation (ΔH). In addition,
the same conclusion that the theoretical water level
variation was approximately equivalent to the measured
water level changes can also be drawn based on the data in
Table 2, which satisfies Eq. (7). This shows that the results
of the calculation method were in accordance with actual
facts. In conclusion, the decreasing average water level
caused by riverbed erosion was partly offset by the rising
average water level caused by the rising average inflow
discharge, which resulted in the phenomenon of “NLD”at
Yichang in 2006, and the effects of DRID were small. As
shown in Fig. 9, the confluence of tributaries and lakes
between Yichang and Datong in 2006 was increased by
2741 m
3
$s
–1
compared to 1978, which further led to a
significant increase in the average discharge at Datong
during the dry season. Thus, the rising average water level
at Datong caused by the increasing average discharge was
up to 0.81 m, while the decline of average water level
induced by riverbed erosion was only 0.14 m (Fig. 10(a)).
Therefore, the decline of water level induced by riverbed
erosion was totally offset by the increasing average water
level induced by the abundant inflow of the TGD and the
Fig. 9 The average discharge during the dry and flood seasons.
Fig. 10 The values of the average water level changes in 2006 and 2011 caused by each factor compared with 1978. Dry season (a) and
flood season (b) in 2006; dry season (c) and flood season (d) in 2011.
518 Front. Earth Sci. 2019, 13(3): 510–522
rich implement of tributaries and lakes, and thus the
average water level at Datong in 2006 shows an obvious
increase compared with that in 1978, which corresponds to
the phenomenon of “NLD”.
In the 2011 dry season, the average inflow discharge of
the TGD was also up to 6397 m
3
$s
–1
, combined with the
significant effects of DRID (see Fig. 4(b), wherein the
daily outflow discharge was obviously larger than the daily
inflow discharge in the 2011 dry season),and thus the
average outflow discharge (Yichang) further increased to
7475 m
3
$s
–1
, with approximately 2370 m
3
$s
–1
more than
the value in 1978 (Fig. 9). Therefore, the increasing
average water level at Yichang caused by the rising
average discharge was up to 1.5 m, and the falling average
water level induced by riverbed erosion was 1.6 m,
compared to 1978 (Fig. 10(c)). Thus, under the combined
effects of discharge variations and riverbed evolution, the
theoretical average water level reduction (ΔHT) in 2011
was only 0.1 m (the measured average water level variation
was 0 m). In conclusion, the reduction in the average water
level caused by riverbed erosion was offset by the
increasing average water level induced by the rising
average inflow discharge and DRID,which caused the
phenomenon of “NLD”at Yichang in 2011. Based on
Fig. 9, the confluence of tributaries and lakes in 2011 was
increased by 519 m
3
$s
–1
compared to 1978, which further
led to an increase of the average discharge at Datong. Thus,
the increasing average water level caused by the rising
average discharge was up to 0.72 m, while the decreasing
average water level induced by riverbed erosion was only
0.25 m. Therefore, the phenomenon of “NLD”occurred at
Datong in 2011.
4.2 Factors of NHF
In the flood season, the average inflow discharge was only
12,945 m
3
$s
–1
and 14,916 m
3
$s
–1
in 2006 and 2011,
respectively, and the average outflow discharge (Yichang)
further decreased to 12,387 m
3
$s
–1
and 13,991 m
3
$s
–1
,
respectively, due to the influence of FPRF, and thus the
decreasing values were up to 7123 m
3
$s
–1
and 5519 m
3
$s
–1
,
respectively, compared to 1978 (Fig. 9). Therefore, the
reductions in the average water level caused by the decline
of the average discharge were up to 2.43 m and 1.83 m at
Yichang in 2006 and 2011, respectively. Furthermore, the
declines in the average water level induced by riverbed
erosion were also up to 1.33 m and 1.53 m, respectively
(Figs. 10(b) and 10(d)). In conclusion, the obvious
decreases in average inflow discharge, FPRF and riverbed
erosion caused the phenomenon of “NHF”at Yichang in
2006 and 2011.
Although the quantity of tributaries and lakes in 2006
and 2011 increased by 4669 m
3
$s
–1
and 2108 m
3
$s
–1
,
respectively, in contrast to 1978 (Fig. 9), the reductions in
the average discharge at Yichang were so large that the
average discharge at Datong also showed a significant
decline. As a result, the decreases in the average water
level induced by the decreases in average discharge were
up to 1.18 m and 0.69 m at Datong in 2006 and 2011,
respectively. In addition, the reductions in the average
water levels caused by riverbed erosion were 0.08 m and
0.2 m (Figs. 10(b) and 10(d)). In conclusion, the obvious
declines in the average discharge at Yichang and riverbed
erosion were the reasons for the phenomenon of “NHF”at
Datong in 2006 and 2011.
4.3 Estimating the contributions of the TGD operation and
climate variability
Based on these calculations, the average water level
changes during the dry season in 2006 caused by the
increase of average inflow discharge and DRID were
0.47 m (ΔHQN ) and ‒0.15 m (ΔHQH ), respectively (as
shown in Fig. 10(a)). Combined with the fitting curves of
water level and discharge during the 1978 and 2006 dry
seasons, the average water level under the same discharge
at Yichang decreased by 1.08 m (ΔHD) compared with that
in 1978. To separate ΔHDN and ΔHDH from ΔHD, the time
series prediction method was selected in step 4 of the
calculation method. Thus, the average water level under
the same discharge (Fig. 11(a)) was calculated based on the
fitting curves of each year during the period from 1976–
2002 (pre-TGD), which had a significant decline from
1976 to 1986 while remaining almost the same from 1987
to 2002. This result is consistent with the existing research:
from 1976 to 1986, the water level during the dry season
decreased significantly under the same discharge (Yang
et al., 2009), while the counterpart between 1987 and 2002
Table 2 Contributions of climate variability and TGD operation on water level changes
Item 2006 2011
Dry season Flood season Dry season Flood season
Yichang Datong Yichang Datong Yichang Datong Yichang Datong
ΔHT–0.76 0.67 –3.76 –0.55 –0.10 0.47 –3.33 –0.89
ΔH–0.76 0.68 –3.54 –0.56 0.00 0.50 –3.30 –0.90
RN71%93%82%78%56%62.5%66%72%
RH29%7%18%22%44%37.5%34%28%
Yuanfang CHAI et al. Water level variation characteristics 519
was basically unchanged due to the stable riverbed in the
Yichang reach (Xu, 2013; Dai et al., 2005). Therefore,
based on the water level variation characteristics under the
same discharge in the dry season from 1987–2002, the
arithmetic average method (one of the time series
prediction methods) was chosen to predict the water
level HDT under the condition of non-TGD in the 2006 dry
season (Eq. (11), Fig. 11(a)), and thus, ΔHDN and ΔHDH
were –0.74 m and –0.34 m, respectively based on Eqs.
(12) and (13) (Fig. 10(a)). Based on the calculated values
of ΔHQN ,ΔHQH ,ΔHDN , and ΔHDH , the contributions of
climate variability (RN) and DRID (RH) on the average
water level variation at Yichang in the 2006 dry season
were 71%and 29%, respectively (Table 2). Similarly, the
contributions of climate variability and DRID were 56%
and 44%at Yichang in the 2011 dry season, respectively.
At Datong, the reductions in the average water level caused
by riverbed erosion were only 0.14 m and 0.25 m during
the 2006 and 2011 dry seasons, respectively, which can be
ignored. Therefore, the contributions of climate variability
and DRID were 93%and 7%, respectively, at Datong in
2006, and the values in 2011 were 62.5%and 37.5%,
respectively. Clearly, climate variability was the main
reason for the water level variation (namely, the phenom-
enon of “NLD”) in the MLRYR in dry season in 2006 and
2011 compared to 1978, instead of DRID induced by the
TGD operation.
In the flood season, the average water level under the
same discharge also did not change significantly at
Yichang during the period from 1987–2002 because of
the stable riverbed in the Yichang reach (Figs. 11(b) and
11(d)). Thus, the arithmetic average method was also
selected, and finally the contributions of climate variability
and FPRF at Yichang in the 2006 flood season were 82%
and 18%, and the figures in 2011 were 66%and 34%.At
Datong, the average water level changes caused by
riverbed erosion were only 0.1 m and 0.2 m in 2006 and
2011, respectively, and thus the effects of riverbed erosion
can also be neglected. Therefore, the contributions of
climate variability and FPRF at Datong in the 2006 flood
season were 78%and 22%, respectively, and the values in
2011 were 72%and 28%. In conclusion, climate variability
was still the dominant reason for water level changes
(namely, the phenomenon of “NHF”) in the MLRYR in the
2006 and 2011 flood seasons, in contrast to 1978, instead
of FPRF caused by the TGD operation. More importantly,
many researchers have predicted that the precipitation
during the dry season will increase in the Yangtze River
Basin and precipitation during the flood season will
decrease (Sun et al., 2013; Zeng et al., 2013; Gu et al.,
2015). Obviously, the special phenomenon of “NLD-
NHF”may become more and more frequent in the future.
Therefore, the calculated contributions will be practically
significant to optimize reservoir operation rules and water
resource management.
5 Conclusions
Under the impacts of both extreme drought and the TGD
Fig. 11 The average water level under the same discharge at Yichang during the period from 1976–2002. (a) The average discharge
during the dry season in 2006 (5617 m
3
$s
–1
) is regarded as the same discharge; (b) the average discharge during the flood season in 2006
(12,388 m
3
$s
–1
) is regarded as the same discharge; (c) the average discharge during the dry season in 2011 (7475 m
3
$s
–1
) is regarded as
the same discharge; and (d) the average discharge during the flood season in 2011 (13,991 m
3
$s
–1
) is regarded as the same discharge.
520 Front. Earth Sci. 2019, 13(3): 510–522
operation, the water level variation characteristics in the
MLRYR in 2006 and 2011 were significantly changed in
contrast with the extreme drought years of 1978 and 1986,
even if the total water resources of the Yangtze River Basin
in these four years were almost the same. Based on the
daily discharge data and water levels from 1955–2016, the
characteristics of water level changes in 2006 and 2011 can
be described as follows:
1) In the dry season, the average water level in the
MLRYR in 2006 and 2011 did not change significantly
compared with 2003–2016, but it had an obvious increase
relative to 1978 and 1986. Here, we call this phenomenon
“no low-water-level in dry season”. In the flood season, the
average water level at Yichang and Jianli in 2006 and at
Chenglingji, Luoshan, Hankou, and Datong in 2011 all
dropped to the lowest in recorded history (1955–2016).
This condition can be described as “no high-water-level in
flood season”.
2) During the dry season, the reduction of the average
water level caused by riverbed erosion in the MLRYR in
2006 and 2011 was offset by the rising average water level
from the higher inflow of the TGD and the higher
confluence of tributaries and lakes caused by climate
variability, which led to the phenomenon of “no low-water-
level in dry season”.
3) In the flood season, the significant decline of the
average water level induced by the scarce inflow of TGD
and FPRF in the MLRYR in 2006 and 2011, combined
with riverbed erosion, all led to the occurrence of “no high-
water-level in flood season”.
4) Based on the proposed new method, the contribu-
tions of climate variability and TGD operation on the water
level changes in the MLRYR in 2006 and 2011 were
calculated relative to 1978. The conclusion is that climate
variability was the main reason for the water level variation
in the MLRYR (namely, “no low-water-level in dry season,
no high-water-level in flood season”), instead of DRID and
FPRF, which are both induced by TGD.
Acknowledgements This research was supported by the National Science
and Technology Support Program of China (2012BAB04B04), the National
Basic Research Program of China (No. 2010CB429002), Open Research
Fund Program of State Key Laboratory of Water Resources and Hydropower
Engineering Science (2016HLG02), and National Key Research and
Development Program of China (2016YFC0402106). We also highly
appreciate the valuable insights from the reviewers.
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