HYDROLOGICAL PROCESSES
Hydrol. Process. 22, 3829– 3843 (2008)
Published online 11 March 2008 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/hyp.6993
A spatial assessment of hydrologic alteration caused by dam
construction in the middle and lower Yellow River, China
Tao Yang,1,5 Qiang Zhang,1,2 * Yongqin David Chen,1 Xin Tao,3 Chong-yu Xu,4 and Xi Chen5
1 Department of Geography and Resources Management, The Chinese University of Hong Kong, Hong Kong, China
Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, 100081, China
3 Hydrology Bureau, Yellow River Conservancy Commission, Zhengzhou, 450004, China
4 Department of Geosciences, University of Oslo, Norway
State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, Hohai University, Nanjing 210098, China
2
5
Abstract:
The ‘range of variability approach’ (RVA) and mapping technique are used to investigate the spatial variability of hydrologic
alterations (HA) due to dam construction along the middle and lower Yellow River, China, over the past five decades. The
impacts of climate variability on hydrological process have been removed during wet and dry periods and the focus is on
the impacts of human activities, such as dam construction, on hydrological processes. Results indicate the following: (1) The
impacts of the Sanmenxia reservoir on the hydrologic alteration are relatively slight with a mean HA value of 0Ð48, ranking
in the last place among the four large reservoirs. (2) Xiaolangdi reservoir has significantly changed the natural flow regime
downstream with mean HA value of 0Ð56, ranking it in first place among the large reservoirs. (3) The results of ranked
median degrees of 33 hydrologic alteration indicators for 10 stations in the Yellow River show that the hydrologic alteration of
Huayuankou ranks the highest among 10 stream gauges. (4) Impacts of reservoirs on hydrological processes downstream of the
dams are closely associated with the regulating activities of the reservoirs. At the same time, alterations of streamflow regimes
resulting from climatic changes (e.g. precipitation variability) make the situation more complicated and more hydrological
observations will be necessary for further analysis. The results of the current study will be greatly beneficial to the regional
water resources management and restoration of eco-environmental systems in the middle and lower Yellow River characterized
by intensified dam construction under a changing environment. Copyright  2008 John Wiley & Sons, Ltd.
KEY WORDS
spatial assessment; range of variability approach (RVA); indicators of hydrologic alteration (iha); dam
construction; eco-environmental system; the Yellow River
Received 17 December 2006; Accepted 15 December 2007
INTRODUCTION
The growing municipal, industrial and agricultural
demands for water have raised the need for further understanding of the impacts of hydraulic structures, such as
impoundments, dams and reservoirs, on hydrological processes over the past five decades in China (MWR, 2002).
These structures facilitate water and electric-power supplies but also alter the natural hydrologic regimes of
rivers (Cardwell et al., 1996; Benjamin and VanKrik,
1999; Flug et al., 2000; Smith et al., 2000; Cowell and
Scoudt, 2002; Ren et al., 2002; Sung-UK et al., 2005;
Timme et al., 2005; Armando et al., 2006; Zhang et al.,
2006a, 2006b; Wouter et al., 2006; He et al., 2007). The
structure and persistence of aquatic communities have
been strongly affected by both spatial and temporal variation within hydrologic regimes (Poff et al., 1997; SungUK et al., 2005; Timme et al., 2005). Several instream
flow methods based on historic flow regime, hydraulics
and habitat have been reviewed comparatively and evaluated by Jowett (1997) after application to ecosystemoriented water allocation planning. Pegg et al. (2003)
* Correspondence to: Qiang Zhang, Department of Geography and
Resource Management, The Chinese University of Hong Kong, Shatin,
NT, Hong Kong. E-mail: zhangqiang@nju.org.cn
Copyright  2008 John Wiley & Sons, Ltd.
analysed daily mean flow data from locations along the
mainstem Missouri River and described human impacts
on the natural flow regime of the Missouri River, particularly the middle Missouri River, which was strongly
affected by impoundments and channelization. Sung et al.
(2005) investigated the effect of flow regime changes on
the fluvial morphology and vegetation cover downstream
of the dam, suggesting that construction of the dams
resulted in a stream length of approximately 25 km in the
river reach downstream of the dams. Song et al. (2007)
estimated the ecological and environmental instream flow
requirements for improvement of the ecological and environmental condition of Wei River, the largest tributary
of the Yellow River, the results indicating that the Ecological and environmental instream flow requirements
(EEIFR) for the Wei River include instream flow requirements for self-purification and sediment transportation in
each typical year.
Many researchers have developed indices to quantify the flow characteristics that are believed to be
sensitive to various human perturbations. Early studies
focused on individual indices, e.g. the average flow, mean
daily flow variability, predictability of streamflow, skewness of streamflow and peak discharge, flood frequency,
slope of flood–frequency curves, seasonal distribution
3830
T. YANG ET AL.
of monthly streamflow, flow and flood frequency duration curves, and annual discharge series analysis. More
recent investigations have tended to use a multivariable
approach to quantify hydrologic alterations (Hughes and
James, 1989; Richter et al., 1996, 1997, 1998; Clausen
and Biggs, 2000; Puckridge et al., 1998; Extence et al.,
1999; Pettit et al., 2001) The multivariable approach
enables one to investigate the multi-impacts of hydrological changes on the structuring of biotic diversity
within the river channel, the floodplain, and hyporheic
(stream-influenced ground water) ecosystems concerning
measures of availability, suitability, life-cycle and stranding of habitat, which are difficult using a single variable
approach (Richter et al., 1996; 1998; Shiau et al., 2004).
Improved quantitative evaluations of human-induced
hydrological changes were adopted to describe biotic
implications of hydrologic alteration and to support
ecosystem management. Richter et al. (1996) developed a
method to assess the degree to which human disturbance
impacts the hydrologic regimes within an ecosystem.
This method, referred to as the ‘Indicators of Hydrologic
Alteration’, is based on either hydrologic data available within an ecosystem or on model-generated data.
Extensive research results indicated that the range of the
streamflow regime is a major driving force for the river
ecosystem (Stanford and Ward, 1996; Poff et al., 1997)
and is one of the key factors sustaining aquatic environments (NRC, 1992). Richter et al. (1997) proposed the
Range of Variability Approach (RVA) as the river management eco-targets, in which 33 hydrologic parameters
(IHA, Richter et al., 1995, 1996) were used to assess
hydrologic alterations in terms of streamflow magnitude,
timing, frequency, duration and rate of change. The application of RVA in assessing and mapping hydrologic alteration from a river basin perspective is demonstrated by
evaluating the impacts of dam construction on hydrologic variability of two major rivers in the upper Colorado
River Basin in Colorado and Utah, USA (Richter et al.,
1998). Galat and Lipkin (2000) studied the hydrological
alterations of the Missouri River flows using the Index of
Hydrological Alteration (IHA), indicating that the river
flows were heavily influenced by the reservoirs. Shiau
et al. (2004) applied the Range of Variability Approach
(RVA) to investigate the hydrologic conditions before and
after the construction of a diversion weir on Chou-Shui
Creek, Taiwan, suggesting that restoration of the natural
flow is expected to promote the natural stream biota.
The RVA has proved to be a practical and effective
approach facilitating river restoration planning. However,
there are some defects in previous reports on hydrologic alteration assessment. (1) The validity of hydrologic
alteration assessment must be carefully considered when
flow records for pre- or post-impact periods or both are
insufficient. (2) Since there is usually more than one dam
on a river, it is hard to distinguish which dam plays
the major role in influencing the degree of hydrologic
alteration downstream. The Yellow River basin is characterized by serious water deficit. Increasingly intensified
human activities, e.g. construction of water reservoirs
Copyright  2008 John Wiley & Sons, Ltd.
along the mainstem Yellow River, further altered the spatial and temporal distribution of water resource across the
Yellow River basin. To a certain degree, the impacts of
human activities on hydrological processes are even more
serious than the impacts of climatic change in the lower
Yellow River. Exploring the extent to which human interventions affected the hydrological regimes and related
hydrological alterations is crucial for better understanding of human-induced hydrological alterations, and will
aid water resources management within the Yellow River
basin. Unfortunately, however, few reports addressing
this scientific problem are available in the literature. The
objectives of this work were: (1) to identify and evaluate
the impacts of dams (e.g. Sanmenxia, Xiaolangdi, Guxian and Luhun reservoirs) on the hydrologic regimes of
the river networks in the middle and lower Yellow River,
China after excluding the impacts of climate variability
and change during wet and dry periods; (2) to quantify
and characterize flow variations in the mainstream and
tributaries of the Yellow River before and after dam construction; (3) to map the degree of hydrologic alteration
at and between stream gauge stations to assess flow variations. The implications of spatio-temporal hydrologic
alteration for the downstream environment and ecosystem
are addressed as an important part of this investigation,
which will contribute to regional eco-hydrological system
management and planning.
STUDY REGION
The Yellow River is the second longest river in China
(Ren and Walker, 1998; Ongley et al., 2000; YRCC,
2001, 2002; MWR, 2002; Figure 1). Frequent floods
and droughts have devastated the economy and caused
much loss of human lives in the Yellow River basin.
The construction of large dams along the mainstream
and major tributaries has very significantly changed
the natural flow regime of the river. In recent years,
zero flow conditions have occurred in the lower Yellow
River because of rapidly increasing water consumption.
The Sanhuajian area (the area between Sanmenxia Dam
and Huayuankou, Figure 1) is located in the middle
and lower Yellow River, and with a drainage area of
41 615 km2 , plays a vital role in flood control as well
as reduction of sediment deposition in the downstream
area (YRCC, 2001; 2002). Large numbers of dams and
reservoirs were built in the Sanhuajian region between
1950 and 2000 aiming to control floods and to reduce
sediment deposition downstream. The major dams and
reservoirs in the middle and lower Yellow River are
the Sanmenxia, Xiaolangdi, Guxian and Luhun reservoirs
(Figure 1 and Table II). Outflow from the Sanmenxia
and Xiaolangdi dam and the confluence of the three
downstream tributaries, Qin, Yi and Luo River, form the
streamflow for the Huayuankou.
Sanmenxia dam, located about 60 km downstream of
Tongguan, was finished in April,1957 to control floods
in the downstream part of the Yellow River, and is the
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3831
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
Longtitude°(E)
37°
00’
110°00’
80 E
50 N
110°30’
111°00’
111°30’
112°00’
112°30’
113°00’
113°30’
114°00’
114°30’
120 E
100 E
36°
40’
36°
40’
36°
20’
30 N
36°
00’
36°
00’
35°
40’
35°
40’
Xia
Re olang
ser
d
vio i
r
35°
00’
Tonggu
an
34°
40’
34°
20’
Xinxiang
W
ul
i
on
zh
gk
Huayuankou
Wu
ou
Xiaolangdi
R
Qin River
ashi River
Baim
Sa
nlu
pin
g
35°
20’
n xxiaia
x i a Saa nnm
meen
en
S
Yellow
nm vior
a
S ser
Re
n
een
Sanmenxia
zzhh
eenn
ui
m
r
h
ggm
Rive
gs
o nn
Luo
an
LLo
Ch
er
r
n
n or Riv
ia vio
hu rvi Yi
u
ux er
e
L es
G es
R
R
He
ish
ig
ua
n
Latitude°(N)
36°
20’
37°
00’
Low alternation
35°
Medium alternation
00’
High alternation
Kaifeng
34°
Streamflow gauges
Zhengzhou
40’
Cities
N
Rivers
W
34°
00’
E
34°
20’
Middle reserviors
34°
Large reserviors 00’
S
0
33°
40’
35°
20’
110°00’
110°30’
111°00’
111°30’
112°00’
112°30’
5
113°00’
10
15
113°30’
20
Basin boundary
114°00’
114°30’
33°
40’
Figure 1. Location map of Sanhuajian area on the middle and lower Yellow River
major multifunctional hydro-project on the mainstem Yellow River. Owing to the tremendous sediment deposition,
the reservoir has lost much of its capacity and associated operational function. Hence, the recent operational
scheme of Sanmenxia is to store clear water in the nonflood season from November until June of the next year
for the sake of various water usages downstream. Water is
released during the flood season and the large amounts of
sediment deposited during the non-flood period is taken
away by the excess water.
The Xiaolangdi project, located 130 km downstream
from Sanmenxia dam and 128 km upstream from
Huayuankou, is an important dam project in the Yellow River basin and was constructed during the period
1991–1997. It aims to reduce the flood risk, decrease
sediment deposition in downstream river channels and is
also used for irrigation and electricity generation.
The main tributaries between Xiaolangdi and
Huayuankou are the Yi, Luo and Qin rivers (Figure 1).
The tributaries have a maximum streamflow of
200–300 m3 s1 and do not significantly influence the
peak flood discharge. The discharge of these tributaries
during the year is very uneven. Most of the year, the discharge is less than 200 m3 s1 . During July and August
the discharge can increase to 3500 m3 s1 and even
higher. The Guxian and Luhun reservoirs were built in
the 1950s and completed in 1992 on the Luohe and the
Yihe River to control flooding from tributaries and to
provide water for agricultural irrigation (YRCC, 2001,
2002). Other mid-size and small reservoirs were built,
mostly in the 1950s, along the Qinhe River to mitigate
Copyright  2008 John Wiley & Sons, Ltd.
flood hazards and for hydropower and irrigation (more
detailed information on the above-mentioned dams and
reservoirs can be found in Tables II and IV).
The Yellow River is an important source ofr water
supply in north-western and northern China; however,
it is also characterized by shortage of water (Wang
et al., 2001). Since 1986, owing to climate change
and human activities, runoff from the lower Yellow
River has significantly decreased (Xu, 2002). Annual
precipitation over the Yellow River basin has exhibited a
decreasing tendency since the 1970s, which, together with
increasing human withdrawal of water from the Yellow
River, has led to frequent desiccation (dry up) events
(Xu, 2001). Climatic changes and human activities have
combined to reduce runoff over the Yellow River basin.
Different driving forces and consequent impacts have
been observed in different parts of the Yellow River.
The hydrological regime in the source region of the
Yellow River is dominated by natural forces, whereas,
human interference, including dams, reservoirs, water
and soil conservation measures, water withdrawal and
diversion, are identified as the primary driving forces
on the hydrological processes of the middle and low
Yellow River (Wang et al., 2004). The runoff processes
in the Yellow River basin have suffered tremendous
hydrological changes. With the river’s unique natural
heavy sediment load, a large quantity of river water is
required to flush the sediments (YRCC 2001; 2002). In
the more traditional sense of ecological use, hydrologists
usually recognize the value of maintaining dry-season
flows for bio-diversity protection and sustenance of
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3832
T. YANG ET AL.
grass, wetlands, and fisheries in the Yellow River delta.
However, with the current rapid industrial development,
thriving urbanization and agriculture, increasing human
demand for water resource is further intensifying the
dilemma that the Yellow River basin needs enough water
to maintain the ecological environment. Therefore, it
is important to detect the spatio-temporal hydrologic
alterations and associated impacts on water resources and
eco-environmental systems.
It is well identified that human activities in the study
region, Sanhuajian area, include intensive dam or reservoir construction (Gao et al., 2004; Liu and Zhang,
2003; Ye et al., 2006), thus it is of importance scientifically and of tremendous practical significance to investigate and evaluate the hydrologic alterations induced
by dam construction, which is in close association with
water resource management. This work thus aims to:
(1) assess the impacts of reservoirs on the hydrological
regime and related impacts on environment and ecosystem; (2) determine and map the degree of hydrological
alterations in different river reaches. The current study
will be helpful for water resources management in the
middle and lower Yellow River basin under the changing
environment.
DATA
Daily streamflow and precipitation data from 10 gauging
stations in the middle and lower Yellow River basin
were analysed in the current study (Figure 1, Table I).
These records were provided by the Hydrology Bureau,
Yellow River Conservancy Commission (YRCC), China,
and were divided into pre- and post-alteration periods
based on the timing of the water reservoir construction.
The length of the daily mean streamflow record of the
pre- and post-dam period varied among gauging stations.
For the convenience of comparison, most series are
processed as similar data lengths. Detailed information
about the data is given in Table I, and the location of the
gauging stations are detailed in Figure 1. The primary
design indexes of the dam projects in the study region
are listed in Table II.
METHOD
Range of variability approach
The ‘range of vriability approach’ (RVA) uses 33
hydrological parameters to evaluate the hydrologic alterations (Richter et al., 1997), which are categorized into
five groups addressing the magnitude, timing, frequency,
duration, and rate of change (Table III).
Group 1. 12-monthly mean flows describe the normal
flow condition. The magnitude of monthly water conditions at any given time is a measure of availability or
suitability of habitat and defines such habitat attributes
as wetted area or habitat volume, or the position of the
water table relative to wetland or riparian plant rooting
zones.
Group 2. 10 parameters describe the magnitude and
duration of annual extreme flows, including 1-, 3-, 7-, 30, and 90-day annual maxima and minima encompassing
the daily, weekly, monthly and seasonal cycles. The
mean magnitudes of high and low water extremes of
various durations provide measures of environmental
stress and disturbance during the year; conversely, such
extremes may be necessary precursors or triggers for the
reproduction of certain species. The inter-annual variation
in the magnitude of these extremes provides another
expression of contingency.
Table I. Detailed information on the stream flow and precipitation gauging stations
No.
Stations
Location
1
2
3
4
5
6
7
8
9
10
Sanmenxia
Xiaolangdi
Huayuankou
Changshui
Baimashi
Longmenzhen
Heishiguan
Wulongkou
Sanlupin
Wuzhi
111° 220 E
112° 300 E
113° 400 E
111° 260 E
112° 350 E
112° 280 E
112° 560 E
112° 410 E
112° 590 E
113° 160 E
34° 490 N
34° 530 N
34° 540 N
34° 190 N
34° 430 N
34° 330 N
34° 430 N
35° 090 N
35° 140 N
35° 040 N
River
Drainage area(km2 )
Sequences length
Yellow River
Yellow River
Yellow River
Luo River
Luo River
Yi River
Yiluo River
Qin River
Qin River
Qin River
688,421
694,155
730,036
6,244
11,891
5,318
18,563
9,245
3,049
12,880
1952–2001
1955–2006
1957–2006
1951–2001
1952–2001
1952–2001
1950–2003
1954–2002
1954–2002
1954–2002
Table II. Primary design indexes of dam projects on the middle and lower Yellow River
Dam
project
Sanmenxia
Xiaolangdi
Luhun
Guxian
Max. Height
(m)
Normal level
(m)
Storage capacity
(million m3 )
Regulation storage
(million m3 )
Installed capacity
(million KWh)
106
173
55
125
335
275
319Ð5
534Ð8
964
1265
132
117Ð5
570
405
57Ð6
70Ð8
0Ð4
1Ð8
0Ð001045
0Ð06
Copyright  2008 John Wiley & Sons, Ltd.
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
3833
Table III. Summary of hydrologic parameters used in the RVA, and their features
General group
Group 1: Magnitude of monthly water
conditions
Group 2: Magnitude and duration of
annual extreme conditions
Group 3: Timing of annual extreme
water conditions
Group 4: Frequency and duration of
high and low pulses
Group 5: Rate and frequency of water
condition changes
Regime features
Magnitude, timing
Mean value for each calendar month
Magnitude, duration
Annual minimum 1-day means
Timing
Magnitude, frequency duration
Frequency, rate of change
Group 3. Julian dates for 1-day annual maximum
and minimum indicate the timing of annual extreme
flows. The timing of these occurrences of particular
water conditions can determine whether certain life-cycle
requirements are met or can influence the degree of stress
or mortality associated with extreme water conditions,
such as floods or droughts.
Group 4. Four parameters refer to the frequency and
duration of the high and low pulses. The high pulses
are periods within a year when the daily flows are
above the 75th percentile of the pre-dam period. The
low pulses are periods within a year when the daily
flows are below the 25th percentile of the pre-dam
period. The frequency of specific water conditions, such
as droughts or floods, may be tied to reproduction or
mortality events for various species, thereby influencing
population dynamics. The duration of time over which a
specific water condition exists may determine whether
a particular life-cycle phase can be completed or the
degree to which stressful effects such as inundation or
desiccation can accumulate.
Group 5. Four parameters (fall rate, rise rate, fall count,
rise count) indicate the numbers and mean rates of both
positive and negative changes of flow on two consecutive
days. The rate of change in water condition may be tied to
the stranding of certain organisms along the water edge
or in pond depressions, or the ability of plant roots to
maintain contact with phreatic water supplies.
The mean, standard deviation, and range of these
parameters are computed with the pre-dam daily flows.
The RVA target range of each hydrologic parameter is
decided by selected percentile thresholds or a simple
Copyright  2008 John Wiley & Sons, Ltd.
Streamflow parameters used in the RVA
Annual maximum 1-day means
Annual minimum 3-day means
Annual maximum 3-day means
Annual minimum 7-day means
Annual maximum 7-day means
Annual minimum 30-day means
Annual maximum 30-day means
Annual minimum 90-day means
Annual maximum 90-day means
Julian date of each annual 1-day maximum
Julian date of each annual 1-day minimum
Number of high pulses each year
Number of low pulses each year
Mean duration of high pulses within each year
Mean duration of low pulses within each year
Means of all positive differences between consecutive
daily values
Means of all negative differences between consecutive
daily values
Number of rises
Number of falls
multiple of the parameter standard derivations for the
natural or pre-dam streamflow regime. The management
objective is not to have the river attain the target range
every year; rather, it is to attain the range at the same
frequency as occurred in the natural or pre-development
flow regime. For example, attainment of RVA target
range defined by the 25th and 75th percentile values of
a particular parameter would be expected in only 50%
of years. The degree to which the RVA target range
is not attained is a measure of hydrologic alteration.
This measure of hydrologic alteration, expressed as a
percentage, can be calculated as:
Observed frequency Expected frequency/
Expected frequency ð 100
1
Hydrologic alteration is equal to zero when the
observed frequency of post-development annual values
falling within the RVA target range equals the expected
frequency. A positive deviation indicates that annual
parameter values fell inside the RVA target window more
often than expected; negative values indicate that annual
values fell within the RVA target window less often than
expected.
Removal of potential impacts of climate varibility on
hydrological process
It is essential to address the problem that the two periods separated by the dam construction period may be
characterized by different hydro-climatological properties. Therefore, potential impacts of climate variability on
hydrological series in the study region should be removed
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
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T. YANG ET AL.
before RVA analysis. Generally, the wet and dry years
characterized by high and low flow can be regarded as the
main consequence of climate variability and can be considered. Chulsang (2006) recommended that the proper
periods in which annual basin precipitation is more than
PmeanC0Ð75stdv (P ½ PmeanC0Ð75stdv ) can be decided as the
wet years, whereas, periods with annual basin precipitation less than Pmean0Ð75stdv are decided as the dry years
(P ½ Pmean0Ð75stdv ). Periods with annual basin precipitation more than Pmean0Ð75stdv but less than PmeanC0Ð75stdv
can be considered as the normal years (Pmean0Ð75stdv P PmeanC0Ð75stdv ). Thus, only the streamflow records
corresponding to the normal years, i.e. Pmean0Ð75stdv P PmeanC0Ð75stdv are considered in the RVA hydrological
alteration assessment. Figure 2 demonstrates streamflow
time-series corresponding to the water years such as wet,
normal and dry years for the Sanhuajian area in the middle and Lower Yellow River. The normal water year and
associated time of dam construction used in the current
study are listed in Tables IV and V.
Evaluation of hydrologic alteration with different lengths
for pre- and post-dam period
Generally, evaluation of hydrologic alteration requires
adequate streamflow records representing natural conditions. In many situations, it is hard to obtain adequate
or relatively equivalent lengths of hydro-data record for
both post- and pre-impact periods in hydrologic alteration
assessment. Initially, ‘observed’ is the count of years in
which the observed value of the hydrologic parameter
fell within the targeted range; ‘expected’ is the count of
the years for which the value is expected to fall within
the targeted range. Hydrological alteration is equal to
zero when the observed frequency of post-development
annual values falling within the RVA target range equals
the expected frequency (The Nature Conservancy, 2001).
Table IV. The middle-flow years in Sanhuajian area of the middle
and lower Yellow River
NO. Year
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
1952
1953
1955
1956
1957
1959
1960
1961
1962
1963
1966
1968
1970
1971
1974
1975
1976
1977
1978
Mean
NO. Year
Mean
precipitation (mm)
precipitation (mm)
547Ð1
626Ð3
576Ð5
753Ð2
626Ð8
527Ð7
523Ð4
720Ð6
655Ð1
707Ð7
567Ð7
591Ð9
579Ð0
653Ð9
685Ð0
681Ð4
553Ð1
586Ð3
525Ð1
15Ð
16Ð
17Ð
18Ð
19Ð
20Ð
21Ð
22Ð
23Ð
24Ð
25Ð
26Ð
27Ð
28Ð
29Ð
30Ð
31Ð
32Ð
33Ð
1979
1980
1982
1985
1987
1988
1989
1990
1992
1993
1994
1996
1998
1999
2000
2002
2004
2005
2006
618Ð7
640Ð6
757Ð5
633Ð3
608Ð7
650Ð8
591Ð7
641Ð3
597Ð3
621Ð3
610Ð1
750Ð1
718Ð7
527Ð4
663Ð3
521Ð4
626Ð0
682Ð1
580Ð8
Threshold: PmeanC0Ð75stdv D 759Ð2 mm, Pmean0Ð75stdv D 492Ð0 mm
The measure of Hydrologic Alteration Factor, kept as
the same calculation method, will be more practicable in
hydrologic alteration assessment after taking into account
the ratio of sufficient or deficient records of both preimpact and post-impact period.
IHA factors used in the yellow river
Considering the influences of most IHA indicators contributing to the total degree of hydrologic alterations with
percentile value <67% in the basin, it is not necessary
to determine the degree of hydrological changes for all
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
1100
Average basin precipitation(mm)
1000
900
Wet year
Wet year threshold: Pmean+0.75stdv =759.2(mm)
800
700
Normal year
600
500
400
300
Dry year
Dry year threshold: Pmean-0.75stdv =492.0(mm)
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Water year
Figure 2. Water year separation of the streamflow time-series for Sanhuajian area in the middle and lower Yellow River (in terms of the results and
recommendation for threshold of wet/dry year by Chulsang, 2006)
Copyright  2008 John Wiley & Sons, Ltd.
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3835
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
Table V. The middle flow water year (Table IV) of stream flow records which are excluded the high-flow year (P Pmean0Ð75stdv ,
492Ð0 mm) and the low-flow year (P ½ PmeanC0Ð75stdv , 759Ð2 mm) to remove the impact of climate variability and changes.
Cross-hatched bars represent the pre-dam period, shades bars represent the post-dam period. The total number of years of record
available for these pre- and post-impact periods are specified in parentheses within each bar. The construction dates for each reservoir
are identified within each interlude between pre- and post-dam periods
No.
Dam or reservoir
River
Construction period
1.
Sanmenxia Dam
Mainstem of Yellow River
2.
Xiaolangdi Dam
Mainstem of Yellow River
3.
Guxian Dam
Luo River, tributary of Yellow River
1952-58
5 years
4.
Luhun Dam
Yi River, tributary of Yellow River
1952-59
6 years
1960-64
5.
5 Middle reservoirs
Qin River, tributary of Yellow River
1954-59
4 years
1959-63
5 years
1952-57
1956-91
2.5
2.0
1961-2001
1992-97
24 years
1959-91
1965-01
27 years
1998-2006
7 years
1992-2001 7 years
24 years
1964-2002
25 years
Evaluating flow alteration at a stream network scale
The RVA is based on hydrologic data collected at
a point (stream gauge), and therefore only measures
hydrologic alteration in a temporal (rather than a spatial)
dimension at that point. However, such point-based data
and evaluations usually reflect hydrologic conditions over
a wider area of the river. For instance, hydrologic conditions evaluated at a gauge station should strongly reflect
conditions in the lateral (river-floodplain) dimension as
well as in the channel-hyporheric dimension, unless barriers to natural hydrologic connectivity, such as levees or
drainage ditches, have been constructed. Stream gauge
data also provide information on hydrologic conditions
extending upstream and downstream of the gauge location. Using point-based data to assess hydrological conditions upstream and downstream of gauge stations requires
Jan
Fe uary
b
Ma ruary
Ap rch
Maril
Juny
Jul e
y
Au
g
Se ust
p
Oc temb
t
No ober er
De vemb
cem er
ber
1-d
3-day m
i
7-day m nimu
i
m
30 ay m nimu
i
m
90 day mnimu
1-dday minimm
3-day m inimum
a
7-day m ximuum
a
30 ay m ximum
a
90 day mximum
Nu day maximm
Ba mber aximum
se of um
flo ze
w i ro
Da
nd day
te o
ex s
Da f m
te o in
f m imu
axi m
Lo
mu
w
Lo pul
m
w p se
Hi ul cou
gh se nt
Hi pul dur
gh se ati
pu cou on
lse nt
Ris
du
rat
Fa e rate
ion
ll r
a
Nu te
mb
er
of
rev
ers
als
33 IHA indicators. Herein, the ranked median absolutedegrees and percentile value of 33 indicators of hydrologic alteration for 10 stream gauges in the study region
(Figure 3) are provided to detect statistically significant
contributions to IHA factors. Thereafter, the hydrologic
alteration factors are singled out according to the mean
value of the IHA factors exceeding the 67th percentile
(IHA D 0Ð52), which are different from those factors used
by Richter (1998) in the Upper Colorado river basin,
USA, wherein, six IHA factors (i.e. annual maxima,
30-day low flows, high pulse durations, date of annual
maximum and minimum and number of reversals) were
accepted to decide hydrological alterations in that investigation. The factors used in the current study are fall rate,
June, number of reversals, April, March, February, 7-day
minimum, July, September and October (Figure 4).
1958-60
Degree of IHA
1.5
1.0
0.5
0.0
-0.5
-1.0
Figure 3. Degree of indicators of hydrologic alteration at Huayuankou gauge in the middle and lower Yellow River
Copyright  2008 John Wiley & Sons, Ltd.
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3836
T. YANG ET AL.
rules to determine the distance upstream or downstream
where the applicability of the stream gauge based data or
measure of alteration is guaranteed.
Once point-based data have been analysed and their
spatial applicability determined, mapping of hydrologic
alteration can provide a visual portrayal of the spatial
extent of hydrologic alteration. A number of different
strategies for mapping hydrologic alteration could be
employed using the results of the RVA analysis at each
stream gauge station. One strategy is to categorize the
numerical measures of hydrologic alteration into a few
qualitative classes, assigning a different mapping pattern
to each alteration class and displaying each mapped
river segment with appropriate pattern based on the
level of hydrologic alteration detected within that river
segment.
Ideally, the definitions of qualitative classes, e.g.
highly or moderately altered, should correspond to differing degrees of ecological impact associated with hydrologic alterations. For example, if the dependence or tolerance of a particular species relative to specific values
of each hydrologic parameter were known, the classes
of hydrologic alteration could be scaled and defined
accordingly. However, such tolerances or dependencies
are seldom known for more than one species within
an ecosystem, and for these species such knowledge is
nearly always limited to just a few hydrologic parameters (Richter et al., 1996, 1997). Without compelling
ecological justification, and unless policy or regulatory constraints dictate a narrow focus, it is recommended that qualitative classes of hydrologic alteration
are not based on the needs of one or a small set
of individual species. Rather, simply sub-dividing the
range of possible alteration values into a small set of
arbitrarily-defined classes may adequately describe relative degrees of hydrologic alteration at certain river
network scales.
To map hydrologic alteration, Richter et al. (1998)
divided the ranges of hydrologic alteration (0–100%) into
three classes of equal range and assigned each class a
distinct pattern: (1) 0–33% (light grey) represents little
or no alteration; (2) 34–67% (medium grey) represents
moderate alteration; (3) 68–100% (dark grey) represents
a high degree of alteration. Because the measurement of
hydrologic alteration is point based, i.e. measured at the
stream gauge station, mapping conventions are necessary
for characterizing whole stream reaches based on point
source data. When the measure of hydrologic alteration
at a particular stream gauge site is greater than 67%,
it is assumed that the high level of alteration should
extend upstream to the location of the first upstream
dam. The highly altered zone is also extended downstream from the stream gauge to the first confluence
with a major tributary. Minimally or moderately altered
zones (hydrologic alteration of 0–33% and 34–67%,
respectively) are handled in a similar fashion to highly
altered zones downstream of stream gauges, but may
extend upstream to either the location of the first dam,
to the location of the first dammed major tributary, or
Copyright  2008 John Wiley & Sons, Ltd.
to a contact with a highly altered zone. The method
was applied to spatial mapping the degree of hydrologic alteration for river reaches at and between stream
gauge sites on two major rivers in the upper Colorado
River Basin in Colorado and Utah, USA by Richter
(1998).
RESULTS
Hydrologic Impacts Of Sanmenxia Dam
The medians, coefficients of dispersion, RVA targets
and hydrologic alteration factors for pre- and post-impact
periods are listed in Table VI, and can be summarized as
follows:
1) Median of monthly flow throughout the post-impact
period indicates a decreasing trend compared with that
in the pre-impact period. The dispersion coefficients
for the post-impact period (ranging from 0Ð42 to 1Ð33)
are mostly lower than those for the pre-impact period
(ranging form 0Ð40 to 1Ð16), indicating the lower
monthly flow fluctuations in the post-impact period
due to the regulation of reservoir operation.
2) The medians of annual 1-, 3-, 7-, 30-, 90-day minimum
and 1-, 3-, 7-, 30- and 90-day maximum for the postimpact period decrease significantly. Results indicate
that the daily, weekly, monthly and quarterly maximum/minimum flow cycles are negatively influenced
by reservoir regulation.
3) The median Julian dates of each annual 1-day minimum move forward from the 41st day in the preimpact period to the 28th day in the post-impact
period; the median Julian dates of each annual 1-day
maximum move forward from the 244th day in the
pre-impact period to the 205th day in the post-impact
period.
4) The medians of low and high pulse counts in the postimpact period are higher than those in the pre-impact
period, which may be a result of inadequate records in
the pre-impact period. The medians of low and high
pulse durations in the post-impact period are almost
the same as those in the pre-impact period, which
indicates only a small hydrologic alteration of low and
high pulse durations because of the rapidly shrinking
storage capacity of Sanmenxia reservoir.
5) The medians of rise rate and fall rate decreased
except for the number of reversals. The coefficients of
dispersion of rise rate, fall rate and number of reversals
are higher than in the earlier period.
6) The highest hydrologic alteration factors of Sanmenxia
reservoir are low pulse count (0Ð79), high pulse duration (0Ð73), fall rate (0Ð69), March (0Ð69), September
(0Ð69), and 1-, 3-, 30-, 90-day minimum (0Ð69) when
considering all 33 parameters.
Generally, results indicate that the impacts of Sanmenxia reservoir on the hydrologic alteration are relatively small because of the decreasing storage capacity
caused by sediment deposition.
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3837
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
Table VI. IHA non-parametric RVA scorecard results for Sanmenxia gauge
5 group
IHA Group 1
January
February
March
April
May
June
July
August
September
October
November
December
IHA Group 2
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Number of zero days
Base flow index
IHA Group 3
Date of minimum
Date of maximum
IHA Group 4
Low pulse count
Low pulse duration
High pulse count
High pulse duration
IHA Group 5
Rise rate
Fall rate
Number of reversals
Pre-impact period:
1952–1957 (5 years)
Post-impact period:
1961–2001 (27 years)
RVA targets
Hydrologic
Alteration Factor
Medians
Coeff. Of Dispersion
Medians
Coeff. Of Dispersion
Lower
Upper
1145Ð0
794Ð0
580Ð0
484Ð5
474Ð6
832Ð5
846Ð5
742Ð5
670Ð0
976Ð0
1590Ð0
1390Ð0
1Ð17
0Ð67
0Ð46
0Ð40
0Ð56
0Ð62
0Ð47
0Ð63
0Ð69
0Ð92
1Ð06
1Ð02
352Ð0
305Ð0
424Ð0
328Ð0
424Ð5
765Ð0
708Ð0
450Ð0
612Ð5
732Ð0
641Ð0
462Ð5
0Ð89
1Ð33
0Ð69
0Ð72
0Ð42
0Ð45
0Ð40
0Ð56
0Ð45
0Ð72
0Ð76
0Ð82
724Ð8
655Ð4
487Ð5
446Ð3
403Ð5
599Ð8
691Ð4
681Ð5
519Ð3
660Ð2
820Ð0
820Ð3
2013Ð0
941Ð0
714Ð8
538Ð8
513Ð3
984Ð5
931Ð1
868Ð9
818Ð9
1409Ð0
2205Ð0
2316Ð0
0Ð37
0Ð37
0Ð69
—
0Ð26
0Ð57
0Ð26
0Ð37
0Ð69
0Ð57
0Ð26
0Ð37
237Ð0
265Ð2
301Ð1
380Ð2
485Ð4
4730Ð0
4160Ð0
3961Ð0
2921Ð0
1868Ð0
—
0Ð3
0Ð86
0Ð78
0Ð77
0Ð43
0Ð37
0Ð53
0Ð55
0Ð51
0Ð48
0Ð58
—
1Ð31
157Ð0
169Ð0
182Ð4
214Ð7
305Ð2
2580Ð0
2347Ð0
2257Ð0
1306Ð0
977Ð8
—
0Ð3
0Ð83
0Ð78
0Ð74
0Ð63
0Ð57
0Ð84
0Ð82
0Ð80
0Ð84
0Ð51
—
0Ð55
154Ð0
160Ð8
184Ð7
338Ð1
433Ð9
3669Ð0
3297Ð0
3222Ð0
2525Ð0
1508Ð0
—
0Ð2
285Ð5
303Ð8
341Ð4
426Ð8
549Ð9
5272Ð0
4935Ð0
4337Ð0
3172Ð0
2123Ð0
—
0Ð4
0Ð26
0Ð26
0Ð26
0Ð69
0Ð69
0Ð69
0Ð69
—
—
—
—
0Ð06
41
244
0Ð46
0Ð18
28
205
0Ð35
0Ð27
48Ð6
216Ð7
234Ð1
271Ð2
0Ð37
0Ð69
5Ð0
5Ð5
5Ð0
4Ð0
1Ð00
2Ð34
1Ð65
0Ð91
8Ð0
5Ð6
6Ð0
4Ð2
0Ð63
2Ð00
1Ð17
0Ð71
2Ð0
3Ð9
4Ð0
3Ð0
6Ð5
12Ð1
8Ð5
5Ð1
0Ð79
0Ð57
0Ð50
0Ð73
54Ð5
58Ð8
103Ð0
0Ð68
0Ð55
0Ð88
30Ð0
28Ð0
146Ð0
0Ð86
0Ð99
0Ð76
41Ð3
67Ð3
66Ð1
60Ð5
40Ð3
131Ð5
0Ð37
0Ð69
—
Hydrologic Impacts Of Xiaolangdi Dam
Xiaolangdi dam significantly altered the natural flow
regime of the downstream river reach after its construction in 1997. The medians, coefficients of dispersion,
RVA targets and hydrologic alteration factors for pre- and
post-impact periods of the Xiaolangdi dam are listed in
Table VII. The results can be summarized as follows:
1) The median of monthly flow of Xiaolangdi reservoir
in the post-impact period decreases due to the reservoir flood mitigation operation, irrigation and electricity generation. The median of October flow decreased
from 2495Ð0 m3 s1 to 728Ð5 m3 s1 to guarantee the
security of the downstream area. The dispersion coefficients of monthly flow in the post-impact period (ranging from 0Ð55 to 2Ð08) are generally higher than those
in the pre-impact period (ranging form 0Ð23 to 1Ð74),
indicating the higher fluctuation of monthly flow of the
post-impact period due to regulation by the reservoir.
Copyright  2008 John Wiley & Sons, Ltd.
2) The medians of annual 1-, 3-, 7-, 30-, 90-day minimum and 1-, 3-, 7-, 30- and 90-day maximum for
the post-impact period decreases significantly. The
results indicate that the daily, weekly, monthly and
quarterly maximal/minimal flow cycles are negatively
influenced by reservoir regulation.
3) The median Julian dates of each annual 1-day minimum move backward from the 14th day in the preimpact period to the 327th day in the post-impact
period. The median Julian dates of each annual 1-day
maximum move backward from the 232nd day in the
pre-impact period to the 242nd day in the post-impact
period.
4) The medians of the low pulse and high pulse count
in the post-impact period are higher than those in the
pre-impact period, which may be the result of the relatively short post-impact period hydrological records
(only 7 years).
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3838
T. YANG ET AL.
Table VII. IHA non-parametric RVA scorecard results for Xiaolangdi gauge
5 group
IHA Group 1
January
February
March
April
May
June
July
August
September
October
November
December
IHA Group 2
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Number of zero days
Base flow index
IHA Group 3
Date of minimum
Date of maximum
IHA Group 4
Low pulse count
Low pulse duration
High pulse count
High pulse duration
IHA Group 5
Rise rate
Fall rate
Number of reversals
Pre-impact period:
1956–1991 (24 years)
Post-impact period:
1998–2006 (7 years)
RVA targets
Hydrologic
Alteration Factor
Medians
Coeff. Of Dispersion
Medians
Coeff. Of Dispersion
Lower
Upper
1120Ð0
725Ð8
494Ð5
445Ð5
589Ð0
733Ð5
899Ð5
828Ð5
936Ð5
2495Ð0
2075Ð0
1383Ð0
1Ð74
1Ð22
0Ð45
0Ð23
0Ð47
0Ð54
0Ð42
0Ð62
0Ð65
0Ð69
1Ð08
1Ð70
740Ð0
683Ð8
555Ð5
487Ð5
468Ð8
864Ð5
773Ð5
709Ð5
558Ð5
728Ð5
1295Ð0
1193Ð0
2Ð08
0Ð70
0Ð56
0Ð42
0Ð41
0Ð65
0Ð55
0Ð60
0Ð73
0Ð85
1Ð09
1Ð48
877Ð6
641Ð4
440Ð6
420Ð0
472Ð4
602Ð4
727Ð8
595Ð9
711Ð5
1727Ð0
1077Ð0
1038c
1849
1086
591Ð9
494Ð2
696Ð0
824Ð1
912Ð1
982Ð1
1068Ð0
2599Ð0
2808Ð0
2146Ð0
0Ð63
0Ð37
0Ð53
0Ð68
0Ð26
0Ð63
0Ð63
0Ð21
0Ð53
0Ð84
0Ð16
0Ð42
277Ð0
298Ð8
345Ð5
447Ð3
481Ð9
6180Ð0
5365Ð0
4309Ð0
3078Ð0
2273Ð0
—
0Ð28
0Ð31
0Ð24
0Ð24
0Ð24
0Ð33
0Ð58
0Ð59
0Ð59
0Ð59
0Ð82
—
1Ð12
166Ð5
192Ð3
226Ð9
334Ð0
445Ð3
4080Ð0
3528Ð0
3269Ð0
2230Ð0
1513Ð0
—
0Ð25
0Ð96
0Ð93
0Ð85
0Ð53
0Ð55
0Ð46
0Ð51
0Ð61
0Ð76
0Ð72
—
1Ð32
237Ð9
266Ð6
312Ð1
397Ð1
430Ð2
4552Ð0
3970Ð0
3190Ð0
2310Ð0
1477Ð0
—
0Ð26
301Ð8
318Ð9
363Ð5
493Ð7
550Ð8
6286Ð0
5583Ð0
4653Ð0
3356Ð0
2834Ð0
—
0Ð41
0Ð79
0Ð79
0Ð84
0Ð53
0Ð42
0Ð32
0Ð42
0Ð16
0Ð32
0Ð11
—
0Ð63
0Ð41
0Ð18
14Ð0
193Ð0
136Ð4
268Ð0
0Ð61
0Ð11
14
232
3Ð5
6Ð25
4Ð0
4Ð5
58Ð5
59Ð0
123Ð5
0Ð05
0Ð25
327
242
1Ð79
0Ð98
2Ð44
1Ð33
5Ð0
4Ð0
5Ð5
3Ð5
1Ð05
2Ð43
1Ð27
0Ð86
2Ð3
4Ð0
2Ð6
2Ð8
5Ð8
8Ð7
7Ð2
6Ð9
0Ð37
0Ð53
0Ð11
0Ð68
0Ð61
0Ð33
0Ð79
54Ð0
58Ð3
114Ð0
0Ð40
0Ð57
0Ð97
41Ð4
62Ð4
77Ð3
69Ð2
51Ð1
149Ð1
0Ð22
0Ð53
0Ð32
5) The medians of fall rate, rise rate and number of reversals decrease, however, the dispersion coefficients of
fall rate and number of reversals are higher in the later
period than the earlier period, indicating higher fluctuations.
6) The highest hydrologic alteration factors of Xiaolangdi
reservoir are 7-day minimum (0Ð84), median October
(0Ð84), 1-day minimum (0Ð79), 3-day minimum (0Ð79),
April (0Ð68), High-pulse duration (0Ð68), June (0Ð63),
July (0Ð63), base-flow index (0Ð63), January (0Ð63),
Date of minimum (0Ð61), fall rate (0Ð53), March (0Ð53),
September (0Ð53) and 3-day minimum (0Ð53) considering all 33 parameters.
Causally, hydrological alterations downstream of the
Xiaolangdi reservoir have been seriously affected by
reservoir regulation activities, namely the flood-control
regulation, ice-run control regulation and pre-flooding
Copyright  2008 John Wiley & Sons, Ltd.
joint regulation of Sanmenxia and Xiaolangdi. Since the
closure of the Xialangdi dam in 1997, decreasing streamflow downstream of the Xiaolangdi makes the factors
influencing the hydrological alterations downstream of
the Xiaolangdi more complicated.
Non-Parametric Analysis Of Hydrologic Alteration
The 33 hydrologic alteration values for the 10 hydrological stations on the middle and lower Yellow River
(Table VIII and Figure 4) were analysed to investigate
the order of indicators of hydrologic alteration caused by
the reservoirs using a non-parametric statistical method.
The degree of indicators of hydrologic alteration at
Huayuankou stream gauge (Figure 3) is accepted as a
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
Copyright  2008 John Wiley & Sons, Ltd.
0Ð37
0Ð37
0Ð69
—
0Ð26
0Ð57
0Ð26
0Ð37
0Ð69
0Ð57
0Ð26
0Ð37
0Ð26
0Ð26
0Ð26
0Ð69
0Ð69
0Ð69
0Ð69
—
—
—
—
0Ð06
0Ð37
0Ð69
0Ð79
0Ð57
0Ð50
0Ð73
0Ð37
0Ð69
—
Sanmenxia
0Ð63
0Ð37
0Ð53
0Ð68
0Ð26
0Ð63
0Ð63
0Ð21
0Ð53
0Ð84
0Ð16
0Ð42
0Ð79
0Ð79
0Ð84
0Ð53
0Ð42
0Ð32
0Ð42
0Ð16
0Ð32
0Ð11
—
0Ð63
0Ð61
0Ð11
0Ð37
0Ð53
0Ð11
0Ð68
0Ð21
0Ð53
0Ð32
Xiaolangdi
0Ð11
0Ð41
0Ð70
0Ð41
0Ð78
0Ð78
0Ð48
0Ð41
0Ð70
0Ð48
0Ð19
0Ð41
0Ð78
0Ð48
1Ð07
0Ð41
—
0Ð70
0Ð70
—
—
—
—
1Ð07
0Ð11
0Ð70
0Ð41
0Ð70
0Ð11
0Ð11
0Ð73
—
0Ð70
Huayuankou
—
—
—
—
—
—
0Ð80
0Ð60
0Ð80
0Ð60
0Ð80
—
—
—
—
—
—
0Ð60
0Ð60
0Ð40
0Ð40
0Ð80
—
0Ð60
—
0Ð80
0Ð68
0Ð20
0Ð68
0Ð80
0Ð00
0Ð84
0Ð40
Changshui
0Ð60
0Ð80
—
—
—
0Ð80
0Ð60
0Ð60
0Ð20
0Ð20
0Ð00
0Ð20
0Ð80
0Ð80
0Ð80
—
0Ð60
0Ð20
0Ð20
0Ð40
0Ð60
0Ð80
—
0Ð40
0Ð60
0Ð20
0Ð60
0Ð60
0Ð80
0Ð80
0Ð80
0Ð80
0Ð40
Baimashi
0Ð76
0Ð88
0Ð94
0Ð88
0Ð71
0Ð94
0Ð82
0Ð65
0Ð59
0Ð47
0Ð41
0Ð71
0Ð00
0Ð59
0Ð65
0Ð65
—
0Ð18
0Ð18
0Ð24
0Ð29
0Ð00
—
0Ð59
—
0Ð53
0Ð15
0Ð12
0Ð65
0Ð29
0Ð47
0Ð59
0Ð71
Longmenzhen
0Ð50
0Ð75
0Ð75
0Ð75
0Ð75
0Ð75
0Ð50
0Ð25
0Ð50
0Ð12
0Ð25
0Ð50
0Ð75
0Ð50
0Ð50
0Ð50
0Ð75
0Ð25
0Ð25
0Ð25
0Ð50
0Ð00
—
0Ð25
0Ð75
0Ð40
0Ð25
0Ð50
0Ð25
0Ð75
0Ð75
0Ð25
0Ð75
Heishiguan
Note: Dashes denote that the expected or observed frequency of specific IHA item is zero, thus the calculation results of hydrologic alteration are invalid.
1. January
2. February
3. March
4. April
5. May
6. June
7. July
8. August
9. September
10. October
11. November
12. December
13. 1-day minimum
14. 3-day minimum
15. 7-day minimum
16. 30-day minimum
17. 90-day minimum
18. 1-day maximum
19. 3-day maximum
20. 7-day maximum
21. 30-day maximum
22. 90-day maximum
23. Number of zero days
24. Base flow index
25. Date of minimum
26. Date of maximum
27. Low pulse count
28. Low pulse duration
29. High pulse count
30. High pulse duration
31. Rise rate
32. Fall rate
33. Number of reversals
IHA factor
0Ð03
0Ð25
0Ð25
0Ð66
0Ð40
0Ð36
0Ð66
0Ð17
0Ð30
0Ð37
0Ð17
0Ð11
0Ð40
0Ð40
0Ð40
0Ð45
0Ð31
0Ð24
0Ð24
0Ð17
0Ð18
0Ð11
—
0Ð36
0Ð11
0Ð44
0Ð11
0Ð69
0Ð79
0Ð38
0Ð18
0Ð90
0Ð93
Wuzhi
0Ð16
0Ð50
0Ð46
0Ð50
0Ð58
0Ð54
0Ð29
0Ð71
0Ð79
0Ð83
0Ð92
0Ð96
0Ð19
0Ð19
0Ð19
0Ð19
0Ð13
0Ð67
0Ð83
0Ð83
0Ð79
0Ð96
0Ð25
0Ð19
0Ð44
0Ð25
0Ð75
—
0Ð83
0Ð29
0Ð75
0Ð81
0Ð96
Sanluping
Table VIII. Statistic for 33 indicators of hydrologic alteration for 10 stream gauges on the middle and lower Yellow River
0Ð67
0Ð65
0Ð58
0Ð51
0Ð79
0Ð79
0Ð26
0Ð02
0Ð16
0Ð58
0Ð51
0Ð79
0Ð30
0Ð23
0Ð23
0Ð05
0Ð65
0Ð37
0Ð44
0Ð30
0Ð30
0Ð23
0Ð40
0Ð53
0Ð63
0Ð23
0Ð72
0Ð74
0Ð40
0Ð23
0Ð86
0Ð77
—
Wulongkou
0Ð43
0Ð55
0Ð61
0Ð63
0Ð57
0Ð68
0Ð53
0Ð40
0Ð53
0Ð52
0Ð37
0Ð50
0Ð47
0Ð47
0Ð55
0Ð43
0Ð51
0Ð42
0Ð46
0Ð34
0Ð42
0Ð38
0Ð33
0Ð47
0Ð45
0Ð44
0Ð48
0Ð52
0Ð51
0Ð51
0Ð51
0Ð69
0Ð65
Mean
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
3839
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3840
T. YANG ET AL.
Figure 4. Ranked median absolute degrees and percentile value of 33 indicators of hydrologic alteration for 10 stream gauges on the Yellow River
paradigm to demonstrate the changes of each hydrological indicator at Huayunkou, which suffers the greatest
hydrological alteration among the 10 gauges across the
study region (Table VIII). The results show that fall rate
ranks first in all hydrologic alteration values followed by
June, number of reversals, April, March, May, February, 7-day minimum, July, September, October and low
pulse duration, all with IHA percentiles exceeding 67%
(½0Ð52). Similarly, 33rd and 67th percentiles were computed for all 33 hydrologic alteration indicators as the
lower and upper limits of the RVA target range for the
10 stations. Items higher than the 67th percentile (½0Ð52),
namely fall rate, June, number of reversals, April, March,
May, February, 7-day minimum, July, September, October and low pulse duration, are singled out for spatial
assessment of hydrologic alteration in the middle and
lower Yellow River. They are assumed to be strongly
affected by construction and operation of the reservoirs
located upstream.
Spatial Variation Mapping Of Hydrologic Alteration At
A Stream-Network Scale
Using the mapping method described by Richter et al.
(1998), the average hydrologic alteration in the ‘Sanhuajian’ area was determined, based on 10 average hydrologic alteration values (see Table IX and Figure 5).
The decreasing median of the monthly flow in flooding
seasons, e.g. July, August and October, is the result of
flood-control activity, which reduced the peak flood. The
30-day minimum and maximum identifies the lowest and
Table IX. Degrees of hydrologic alteration at eight stream gauges on the middle and lower stream network of the Yellow River.
Location of the stream gauges is shown on Figure 1
No.
Streamgauge
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Sanmenxia gauge
Xiaolangdi gauge
Huanyuankou gauge
Changshui gauge
Baimashi gauge
Longmenzhen gauge
Heishiguan gauge
Wuzhi gauge
Sanluping gauge
Wulongkou gauge
Fall June Number April March May February
7-day
July September October Mean
rate
of
minimum
absolute
reversals
value
0Ð69
0Ð53
—
0Ð84
0Ð80
0Ð59
0Ð25
0Ð90
0Ð81
0Ð77
0Ð57
0Ð63
0Ð78
—
0Ð80
0Ð94
0Ð75
0Ð36
0Ð54
0Ð79
—
0Ð32
0Ð70
0Ð40
0Ð40
0Ð71
0Ð75
0Ð93
0Ð96
—
—
0Ð68
0Ð41
—
—
0Ð88
0Ð75
0Ð66
0Ð50
0Ð51
0Ð69
0Ð53
0Ð70
—
—
0Ð94
0Ð75
0Ð25
0Ð46
0Ð58
0Ð26
0Ð26
0Ð78
—
—
0Ð71
0Ð75
0Ð40
0Ð58
0Ð79
0Ð37
0Ð37
0Ð41
—
0Ð80
0Ð88
0Ð75
0Ð25
0Ð50
0Ð65
0Ð26
0Ð84
1Ð07
—
0Ð80
0Ð65
0Ð50
0Ð40
0Ð19
0Ð23
0Ð26
0Ð63
0Ð48
0Ð80
0Ð60
0Ð82
0Ð50
0Ð66
0Ð29
0Ð26
0Ð69
0Ð53
0Ð70
0Ð80
0Ð20
0Ð59
0Ð50
0Ð30
0Ð79
0Ð16
0Ð57
0Ð84
0Ð48
0Ð60
0Ð20
0Ð47
0Ð12
0Ð37
0Ð81
0Ð58
0.48(L)
0.56(M)
0.65(H)
0.69(H)
0.58(M)
0.74(H)
0.58(M)
0.50(L)
0.58(M)
0.53(L)
Degrees of hydrologic alteration are assigned based on distinct patterns of equal range: (1)0–33% (L, low) represents little or no alteration; (2) 34–67%
(M, medium) represents moderate alteration; (3) 68–100% (H, high) represents a high degree of alteration.
Average values are based upon absolute values of each item.
Threshold: IHA67% D 0Ð59, IHA33% D 0Ð56.
Copyright  2008 John Wiley & Sons, Ltd.
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3841
HYDROLOGIC ALTERATION CAUSED BY DAM CONSTRUCTION
Longtitude°(E)
110°00’
80°E
50°N
110°30’
100°E
111°00’
111°30’
112°00’
112°30’
113°00’
113°30’
114°00’
114°30’
120°E
37°
00’
36°
40’
36°
40’
36°
20’ 30°N
36°
20’
36°
00’
36°
00’
35°
40’
35°
40’
34°
40’
nen
hzeh
nezn
i
err
me
hu
RRiivve onognmg
gs
o
n
u
L
a
LL
Ch
r
r
n ior ive
u
an vio
i
h erv i R
x
r
u
u e
Y
L s
34°
20’
G es
R
Qin River
Xiaolangdi
ashi
Baim
Low alternation
35°
Medium alternation
River
00’
High alternation
34°
Streamflow gauges
40’
Zhengzhou
Cities
N
Re
W
34°
00’
Rivers
E
34°
20’
Middle reserviors
34°
Large reserviors 00’
S
0
33°
40’
35°
20’
Huayuankou
n
Yellow
z
Wu
ua
an
a
a
nxi
me or S
Sanservi
e
R
Sanmenxia
nggk
okuo
u
Xinxiang
hi
ig
Tonggu
uul
olon
ish
35°
00’
W
W
Sa
nlu
pin
g
XXiaia
o
RReess olalannggd
eervrvi di i
ioor r
ia
x
n
nme
35°
20’
He
Latitude°(N)
37°
00’
110°00’
110°30’
111°00’
111°30’
112°00’
112°30’
5
113°00’
10
15
113°30’
20
114°00’
Basin boundary
114°30’
33°
40’
Figure 5. Spatial distribution of mean hydrologic alteration degree for Sanhuajian area in the middle and lower stream network of the Yellow River,
China. (1) Light grey zones represent little or no alteration, 0–33% (L, low); (2) medium grey zones represent moderate alteration, 34–67% (M,
medium); (3) dark grey zones represent a high degree of alteration 68–100% (H, high)
highest monthly median discharge of each year. The
number of reversals counts the frequency at which the
hydrograph switches from a rising to a falling period in
each year (Richter et al., 1998).
Regulation of Sanmenxia dam strongly affected the
low pulse count, high pulse duration, fall rate, March,
September, and 1-, 3-, 30-, 90-day minimum; the
Heishiguan gauge was influenced greatly by median
runoff in February, March, April, May, June, 1-, 90-day
minimum runoff, date of minimum, high pulse duration,
rise rate and number of reversals for runoff. Results for
Wuzhi gauge indicate the influences of dams on the number of reversals, fall rate, low pulse duration, high pulse
count and runoff of April, July. Xiaolangdi reservoir is
ranked in first place among the mainstem reservoirs in
influencing hydrological alterations in the middle and
lower Yellow River. The next most important reservoirs
altering the hydrologic regimes in branches of the Yellow River are the Guxian reservoir in the Luo River
and the Luhun reservoir in the Yi River (Table IX).
Relatively high hydrological alteration can be identified
at the Sanluping gauge when compared to that at the
Wulongkou gauge as s result of regulation by many
middle- and small-size reservoirs in the Qin River. Wuzhi
gauge accepts streamflow from Wulongkou and Sanluping, which makes the hydrological alteration at the Wuzhi
gauge less obvious. Dam constructions upstream of the
Huayuankou gauge collectively result in a remarkable
hydrological alteration detected at the Huayuankou gauge
Copyright  2008 John Wiley & Sons, Ltd.
(Table IX, Figure 5), at which the following components
are seriously influenced: 7-day minimum (1Ð07), baseflow index (1Ð07), median streamflow of May (0Ð78), 7day minimum (0Ð78), median streamflow of June (0Ð78),
rise rate (0Ð73), number of reversals (0Ð70), low pulse
duration (0Ð70), date of maximum (0Ð70), September
(0Ð70), March (0Ð70) and 1-, 3-day maximum (0Ð70).
CONCLUSIONS AND DISCUSSION
The influences of dam construction on hydrological
regimes in the middle and lower Yellow River were
systematically studied using a RVA method. Some interesting conclusions can be summarized as follows:
1) The impact of Sanmenxia Dam on the hydrological regime is relatively small, with a mean absolute
HA value of 0Ð48, ranking lowest among the four
large reservoirs (Sanmenxia, Xiaolangdi, Guxian and
Luhun), which might result from the enormous sediment deposition and shrinking storage capacity.
2) Xiaolangdi reservoir, a major hydro-project for flood
control, agricultural irrigation and sediment deposition in the middle and lower Yellow River basin,
significantly changed the natural flow regimes in the
downstream river reach after its enclosure in 1997.
The mean HA value is 0Ð56, ranking highest among
the large reservoirs in the middle and lower mainstem
Yellow River. The median of the monthly river flow
Hydrol. Process. 22, 3829– 3843 (2008)
DOI: 10.1002/hyp
3842
T. YANG ET AL.
of Xiaolangdi reservoir (in July, August and September of the post-impact period) has decreased due to
reservoir regulation for flood reduction, irrigation and
electricity generation. The high-pulse duration, medians of June, July and September for the post-impact
period have decreased significantly because of flood
prevention activities.
3) The results of ranked median degrees of the 33
hydrologic alteration indicators for the 10 stations on
the Yellow River indicate that the hydrologic alteration
of Huayuankou ranks highest position among the
10 stream gauges, as a result of intensified dam
construction in both mainstem and branches of the
upstream Yellow River.
Construction and operation of the reservoirs, aiming to
reduce flood disaster and sediment deposition, inevitably
induced high hydrologic alteration, which has severely
changed the natural balance of eco-flow regimes, with
substantial threats to wild species and consequently has
resulted in undesirable ecological effects, such as the
disturbances of the habitat of river aquatic organisms,
excessive sediment deposition in the rivers (Song et al.,
2007), alteration of fish migrating routes (Moog, 1993)
and drastic reduction of wild species (Zincone and Rulifson, 1991). The spatial patterns of the hydrologic alterations caused by dam construction in the middle and
lower Yellow River during the recent five decades were
assessed using RVA method. It should be noted here that
an attempt was made to remove possible impacts of climatic change on hydrological processes, with the aim
of focusing attention on the influence of dam regulation
on streamflow regimes. However, it is almost impossible to exactly differentiate individual roles of climatic
change and human activities in hydrological alterations,
therefore complicated climatic changes along with intensive human activities (e.g. water and soil conservation
measures, irrigation engineering, dam or reservoir construction, groundwater extraction, water withdraw and
diversion) have the potential to affect the hydrological
regimes, which introduces uncertainties into assessments
of hydrologic changes. Therefore, it is necessary to further quantify and address these uncertainties in ongoing research. The current research has shed light on the
impacts of reservoirs and dams on hydrological regimes,
and regional water resources management will greatly
benefit from the research results. Further investigations of
the negative responses of the eco-environmental system
to hydrological regimes alteration resulting from intensified dam construction in the middle and lower Yellow
River are warranted.
ACKNOWLEDGEMENTS
The work described in this paper was fully supported by
a grant from the Research Grants Council of the Hong
Kong Special Administrative Region, China (Project
No. CUHK4627/05H), a direct Grant from the Faculty of Social Science, The Chinese University of Hong
Copyright  2008 John Wiley & Sons, Ltd.
Kong (Project No. 4450183), the Laboratory for Climate
Studies, National Climate Center, China Meteorological Administration, China (Grant No.: CCSF2007-35),
the Outstanding Overseas Chinese Scholars Fund from
CAS (The Chinese Academy of Sciences) and by the
National Natural Science Foundation of China (Grant
No.: 40701015). Cordial thanks should be extended to the
Nature Conservancy, USA for the ‘Indicators of Hydrologic Alteration’ (IHA) software used in RVA computation and the Hydrology Bureau and also to Yellow River
Conservancy Commission for providing hydrologic data.
Thanks should be extended to two anonymous reviewers
for their crucial comments which greatly improved the
quality of this paper.
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