WATER RESOURCES RESEARCH, VOL. 43, W06434, doi:10.1029/2006WR005705, 2007
Streamflow variations of the Yellow River over the past 593 years
in western China reconstructed from tree rings
Xiaohua Gou,1,2 Fahu Chen,1 Edward Cook,2 Gordon Jacoby,2 Meixue Yang,3
and Jinbao Li2
Received 2 November 2006; revised 28 February 2007; accepted 14 March 2007; published 30 June 2007.
[1] Annual streamflow of the Yellow River has decreased in recent years (1980 to 2000)
because of climate change and human activity. This decrease affects the environment
and the lives of the people in the drainage area. Tree ring width chronologies from six sites
in the headwaters of the Yellow River were developed to provide estimates of past
Yellow River streamflow in order to place the recent flow reduction in a long-term
context. The ring width indices of the six local Juniperus przewalski chronologies
correlate significantly with the observed streamflow of the Yellow River recorded at the
Tangnaihai hydrological station. Principal components analysis shows that the first
principal component (PC) of the tree ring indices explains 49% of the streamflow
variance. On the basis of this result, Yellow River streamflow was reconstructed for the
past 593 years. Several severe droughts and low-flow events are recognized in the decades
1920–1930, 1820–1830, 1700–1710, 1590–1600, and 1480–1490. The most severe
droughts in 1480–1490 were also recorded in other studies on the Tibetan Plateau.
Regional historical climate archives further support the validity of our streamflow
reconstruction. The reconstructed increase in streamflow during much of the twentieth
century also coincides with generally wetter conditions in the Tienshan and Qilianshan
Mountains of China, as well as in northern Pakistan and Mongolia. After the 1980s, our
reconstruction indicates a decreasing trend in streamflow, which is cause for concern.
Presently, Yellow River streamflow is relatively low but not yet outside the range of
streamflow fluctuations that occurred during the past six centuries.
Citation: Gou, X., F. Chen, E. Cook, G. Jacoby, M. Yang, and J. Li (2007), Streamflow variations of the Yellow River over the past
593 years in western China reconstructed from tree rings, Water Resour. Res., 43, W06434, doi:10.1029/2006WR005705.
1. Introduction
[2] Most of northern China has experienced severe and
prolonged dry periods since the late 1990s. In some of the
areas, the extreme drought situations were unprecedented in
the latter half of the twentieth century [Zou et al., 2005].
During 1972 – 1997, there were 20 years when the Yellow
River experienced drying-up (zero streamflow) episodes.
The earlier seasonal beginning and longer periods of
drying-up have become more frequent since the early
1990s. The severe drought of 1997 in northern China resulted
in a period of 226 days with no streamflow in the Yellow
River, which is the longest drying-up duration on record [Zou
et al., 2005]. Most of the Yellow River drainage is located in
1
Center for Arid Environment and Paleoclimate Research, Key
Laboratory of Western China’s Environmental Systems, Ministry of
Education, Lanzhou University, Lanzhou, China.
2
Tree-ring Laboratory of Lamont-Doherty Earth Observatory, Columbia
University, Palisades, New York, USA.
3
Key Laboratory of Cyrosphere and Environment, Cold and Arid
Regions Environmental and Engineering Research Institute, Chinese
Academy of Sciences, Lanzhou, China.
Copyright 2007 by the American Geophysical Union.
0043-1397/07/2006WR005705
arid and semi-arid areas of China where water shortage is a
major environmental and social concern. Frequent drought
stress in recent decades has become more serious [Zou et al.,
2005], and the severe droughts in 1997 and 1999 to 2002 in
many areas of northern China caused large economic and
societal losses [Zhang, 2003].
[3] As the main water resource for large parts of China,
the Yellow River streamflow contributes 2% of the total
water resource of China and supplies 15% of the water used
for agricultural production and 12% of the water used by the
population of the country [Zhu and Li, 2003]. Nearly 40%
of the streamflow of the Yellow River comes from headwater areas above the Tangnaihai hydrological station in the
northeast Tibetan Plateau [Mu et al., 2003]. Variations in
streamflow from this part of the overall drainage area
therefore greatly affect downstream discharge and available
water supply [Wang et al., 2002]. Understanding the longterm variability of Yellow River streamflow is very important in a practical sense because it enables the recent
observed changes to be put into a longer-term perspective.
Otherwise this is difficult to do because meteorological and
hydrological records are very short.
[4] Annual tree ring records from long-lived trees are
among the most important archives of paleoclimatic information available. Among other applications, tree ring
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Figure 1. Map of the sample sites (MQB, MQD, MQF, MQDQ, YYAH, and TDC), weather stations
Maqin, Maduo, Tongde, and Xinhai, and hydrological station Tangnaihai in the study area.
chronologies have been successfully used to reconstruct
long records of seasonal or annual streamflow of rivers
[Cook and Jacoby, 1983; Woodhouse, 2000; Pederson et
al., 2001]. Reconstruction of hydrologic variability from
tree rings, known as dendrohydrology, also has a great
potential in China [Kang et al., 2002]. To demonstrate this,
we have used long tree ring records to reconstruct streamflow from the headwaters of the Yellow River over the past ca.
Figure 2. Monthly average precipitation and temperature (1971 – 2000) of four meteorological stations
(Maduo, Maqin, Tongde, and Xinhai) in the research area. The elevation, location, and the observation
time span of each station have been marked in the figure.
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Figure 3. Annual precipitation at the four meteorological stations (Maqin, Maduo, Tongde, and Xinhai)
and the streamflow at Tangnaihai hydrological station.
600 years to examine recent trends in streamflow in a longterm perspective.
2. Data and Methods
2.1. Study Area
[5] The headwater area of the Yellow River is located in
the northeastern Tibetan Plateau (Figure 1). The Animaqin
and Xiqin Mountains, where the trees for this study were
sampled, have peaks up to 6282 meters a.s.l. and have
glaciers in their highest parts. Annual precipitation in this
area ranges from 300 to 500 mm, and annual mean
temperature ranges from 3° to 3°C. The dominant vegetation type is subalpine meadow with scattered tree cover.
The tree species used in our study is cypress (Juniperus
przewalski), a long-lived conifer. It typically occupies xeric
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Figure 4. Comparison of the monthly Yellow River
streamflow and the regional precipitation. The curve with
the square ticks is the Yellow River streamflow (mean of
1956 – 2001), and the curve with circle ticks is the average
precipitation of the four meteorology stations (Xinhai,
Tongde, Maqin, and Maduo) from 1960 –2002.
sites with shallow, rocky soil and limited moisture-holding
capacity. Shrubs, grasses, and herbs are scattered in the
understory of the forests. Most are subalpine species, such
as Dasiphora fruticosa, Potentilla chinensis, Polygonum
viviparum, and Leontopodium leontopodioides [Zhou et al.,
1987].
2.2. Hydrometeorological Characteristics
[6] The headwater area of the Yellow River in western
China is located on the northeastern fringe of the Tibetan
Plateau. Meteorological and hydrological observations began
there in the late 1950s and early 1960s. Figure 2 shows the
monthly distribution of the average temperature and precipitation at four meteorological stations (see Figure 1 for their
locations). The precipitation distribution with a clear summer
maximum reflects the effect of the Asian summer monsoon.
[7] There are no dams upstream of the Tangnaihai hydrological station (Figure 1); neither is there any industry or
farming in the research area. There is only a small human
population living in the surrounding mountain areas, and the
effect of grazing on runoff is negligible. The effect of human
activity on the streamflow record at the gauging location is
very limited. Climate fluctuation is the main factor in the
variation of the Yellow River streamflow in this area.
Therefore variations in the Yellow River streamflow record
can be expected to reflect natural hydrologic variability.
[8] The interannual variability in precipitation at the
four meteorological stations (Maqin, Maduo, Tongde, and
Xinhai) and the streamflow at Tangnaihai hydrological
station are quite similar (Figure 3). Correlation analysis
indicates that annual streamflow of the Yellow River at
Tangnaihai correlates well with annual precipitation at each
of the four meteorological stations (Maqin, Maduo, Tongde,
and Xinhai). The correlation coefficients are 0.68, 0.51, 0.71,
and 0.62, respectively. These results show that Yellow River
streamflow is closely related to local precipitation in its
headwater region.
[9] The seasonal distributions of precipitation and streamflow do differ somewhat, but both increase rapidly from
May to July because of the influence of the Asian summer
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monsoon (Figure 4). However, there is only one peak (in
July) in the monthly distribution of precipitation, while
there are two peaks (in July and September) in streamflow.
The first streamflow peak is directly related to the monsoonal May– July precipitation in the research area (Figure 2).
There are glaciers and permafrost in upstream area of
Tangnaihai hydrological station. July – August is the warmest
period in the research area. The second peak is probably due
to meltwater input from glaciers and shallow permafrost in
the higher elevations of the watershed during the warm
summer months. In combination, the warm and wet summer season is the principal flood season of the Yellow River
with the majority of the runoff coming from monsoon
precipitation.
[10] The streamflows of Yellow River at Tangnaihai and
Shanxian Hydrological stations (see Figure 1 for their
locations) are also compared in Figure 5. Shanxian hydrological station is one of the important stations, located in the
transition zone from the middle to lower reaches of Yellow
River. Its contributing area is 680,000 km2. The distance
from Shanxian station up to the highest tributaries is about
4400 km and down to the estuary is about 1000 km. The
streamflow variations at Tangnaihai and Shanxian hydrological stations are quite similar. The correlation coefficient
of the streamflow between these two stations is 0.72 from
1956 to 1989. However, since the late 1960s, several large
dams were constructed for waterpower along the Yellow
River, and most of them are located between these two
stations. Liujiaxia and Qingtongxia Reservoirs began to
retain water in later 1960s [Li, 1998]. The reservoirs should
affect the streamflow record at the lower reaches (such as
Shanxian station). The correlation coefficient of streamflow
between Tangnaihai and Shanxian hydrological stations
from 1956 to 1970, prior to the dam’s major effects, is
0.80. The high correlation indicates that the variation of the
streamflow at Tangnaihai could explain 64% of the streamflow at Shanxian hydrological station, which is located at
the end of middle reaches of Yellow River and far from
Tangnaihai, even though the streamflow at Tangnaihai is
only about 40% of the streamflow at Shanxian.
2.3. Development of the Tree Ring Chronologies
[11] Tree ring increment cores were collected from six
sites on the Animaqin and Xiqin Mountains in the central
Figure 5. Annual streamflow variations of Yellow River at
Shanxian (a) and Tangnaihai (b) hydrological stations.
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Table 1. General Information About the Sample Sites, Samples, and the Chronologies
Sample Site
Location
Elevation,
m.a.s.l.
Sample Depth,
Cores/Trees
Mean Correlation
Coefficient
Mean
Sensitivity
Locally Absent
Ring, %
Chronology
Time Span
MQB
MQD
MQF
MQDQ
YYAH
TDC
99°4702100E, 34°4700800N
99°4000100E, 34°4302500N
99°4102900E, 34°4501500N
100°0102900E, 34°4800500N
100°2002100E, 34°4701300N
100°2005700E, 35°0305600N
3550 – 3650
3600 – 3700
3650 – 3700
3560 – 3700
3440 – 3480
3400 – 3420
53/38
34/22
52/37
46/31
23/13
64/34
0.741
0.645
0.662
0.744
0.694
0.696
0.543
0.400
0.365
0.434
0.435
0.459
2.597
1.074
1.068
0.998
2.201
1.075
470 – 2002
1163 – 2001
1230 – 2002
1291 – 2003
1385 – 2003
1130 – 2003
region of the headwater area of the Yellow River (Figure 1).
Detailed information about the sample sites and the tree ring
samples are given in Table 1.
[12] In order to collect samples that contain a consistent
climate signal, the sampling elevations were restricted to the
lowest 140 meters above the local river level. The microenvironments of the living trees were also carefully selected
for homogeneity. Trees disturbed by any obvious nonclimatic factors, like rockfall, were not sampled. Most tree
cores were also taken from isolated trees or trees in small
Figure 6. Standardized (STD) tree ring width chronologies and corresponding sample depth (grey
shaded areas, number of cores used) for the individual study sites (for explanations and locations, see
Table 1 and Figure 1).
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Table 2. Correlation Coefficients Between the Six STD
Chronologies: MQB, MQD, MQF, MQDQ, YYAH, and TDC
MQB
MQD
MQDQ
MQF
YYAH
TDC
MQB
MQD
MQDQ
MQF
YYAH
TDC
1.00
0.79
0.86
0.77
0.66
0.68
1.00
0.80
0.87
0.58
0.60
1.00
0.81
0.68
0.79
1.00
0.64
0.60
1.00
0.65
1.00
groves to reduce the effects of competition on tree growth
by neighboring trees. Because of many missing annual
rings, increment core samples were also taken from younger
trees or from the trees grown near the riverbank to aid in
cross-dating.
[13] Standard techniques of dendrochronology were used
to process the sampled tree cores [Fritts, 1976; Cook and
Kairiukstis, 1990]. The samples were cross-dated with three
methods: skeleton-plot cross-dating, visual cross-dating of
the ring width measurement series, and testing of crossdating using the computer program COFECHA [Stokes and
Smiley, 1968; Holmes, 1983]. With as many as seven
missing rings occurring in a century, the ring width series
plots were essential for correct dating. The increment core
samples taken from younger trees or the trees grown near
the riverbank were used to aid in cross-dating. There are
very few missing rings in those samples. Therefore the
missing ring in other samples could be determined by
comparing the skeleton-plotting and ring width series plotting with the samples from younger trees or growth near the
Table 3. Correlation Coefficients Between Tree-Ring Chronologies
and Monthly Yellow River Streamflow Data (1956 – 2001)a
P-Jan
P-Feb
P-Mar
P-Apr
P-May
P-Jun
P-Jul
P-Aug
P-Sep
P-Oct
P-Nov
P-Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A-J
a
MQB
MQD
0.11
0.17
0.15
0.12
0.10
0.05
0.16
0.25
0.50c
0.47c
0.42c
0.59c
0.41c
0.39c
0.45c
0.21
0.39c
0.57c
0.51c
0.30b
0.14
0.15
0.22
0.17
0.67c
0.13
0.14
0.16
0.14
0.16
0.03
0.17
0.24
0.47c
0.52c
0.47c
0.57c
0.49c
0.48c
0.49c
0.18
0.38c
0.47c
0.44c
0.19
0.15
0.16
0.22
0.24
0.60c
MQDQ
0.06
0.13
0.09
0.15
0.05
0.03
0.09
0.22
0.48c
0.46c
0.40c
0.57c
0.41c
0.38b
0.45c
0.26
0.45c
0.49c
0.34b
0.17
0.10
0.15
0.20
0.14
0.59c
MQF
TDC
0.03
0.07
0.03
0.19
0.19
0.14
0.16
0.20
0.40c
0.50c
0.45c
0.54c
0.43c
0.42c
0.44c
0.20
0.39b
0.53c
0.53c
0.28
0.06
0.13
0.22
0.21
0.60c
0.08
0.16
0.22
0.10
0.16
0.20
0.19
0.32b
0.35b
0.33b
0.35b
0.54c
0.39c
0.41c
0.49c
0.35b
0.48c
0.50c
0.29b
0.06
0.00
0.06
0.01
0.04
0.53c
YYAH
0.21
0.21
0.20
0.05
0.09
0.07
0.24
0.34b
0.51c
0.50c
0.46c
0.58c
0.46c
0.42c
0.47c
0.24
0.40c
0.33b
0.34b
0.13
0.14
0.14
0.21
0.18
0.58c
P denotes the previous months, and therefore P-Jan refers to the
previous January, and Jan refers to the current January in first column. A-J
refers to the average streamflow from previous August to current July.
b
Significant at p < 0.05.
c
Significant at p < 0.01.
Figure 7. Correlation coefficient between PC1 and
streamflow from 1956 to 2001. The dashed lines refer to
the significant levels.
riverbank. The cross-dated tree rings were next measured on
a Velmex tree ring width measuring system (±0.001 mm
precision). The computer program ARSTAN [Cook and
Holmes, 1986; Cook and Kairiukstis, 1990] was then used
to develop the site chronologies used for streamflow reconstruction. Those young and riparian samples used to aid in
cross-dating were not included in the final tree ring chronologies. To remove the growth trends, most of the tree ring
series were detrended with linear or negative exponential
curves that conform to the expected model of radial growth
as trees age [Fritts, 1976]. The few ring width series with
growth trends that did not conform to the negative exponential or linear models were detrended with more adaptive
smoothing splines [Cook and Peters, 1981].
[14] Figure 6 shows the tree ring chronologies developed
from the six sampled sites and the changing sample depth
through time. Because the quality of each chronology
weakens as the sample depth declines back in time, we
used a measure of common signal strength called the
expressed population signal (EPS) [Cook and Kairiukstis,
1990] to determine the year beyond which each chronology
weakens too much to use. An EPS cutoff of 0.85 (down
from a perfect maximum of 1.0) is commonly used in
dendrochronology [Cook and Kairiukstis, 1990] and will
be used here as well. This resulted in a common time span
of 1409 – 2001 (593 years) for the six chronologies with
EPS > 0.85. Figure 6 also demonstrates that the variations
of the six chronologies are highly similar to each other, a
result that is verified by the high correlations between the
chronologies (Table 2). The average correlation between
each chronology is 0.72 ( p < 0.001), with the highest (r =
0.87) between MQD and MQF and the lowest (r = 0.58)
between MQD and YYAH. These strong correlations indicate that tree growth at these six sites is limited by a similar
set of environmental factors, most likely related to climate.
3. Results and Discussions
3.1. Correlation Analysis
[15] Correlation analyses between the six tree ring chronologies and the monthly Yellow River streamflow data
were conducted for the period 1956 – 2001 (Table 3). The
tree ring indices significantly correlate with river streamflow in most months from previous August to current July
of the growth year and the total streamflow from previous
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Figure 8. Comparison of observed and reconstructed
streamflow of the Yellow River from 1956 to 2001.
August to current July. The correlation coefficient between
the first principal component (PC) of the six chronologies and
the streamflow from previous August to current July is 0.70
( p < 0.001) (Figure 7). The growth of the trees in this cold
and dry area is clearly restricted by the climate factors,
especially those related to precipitation [Gou et al., 2001;
Zhang et al., 2003]. Given the close correlation between
streamflow and precipitation at the four meteorological
stations (r ranges from 0.51 to 0.71, p < 0.01), it is not
surprising that tree growth is well correlated with streamflow.
3.2. Reconstruction of Yellow River Streamflow
[16] A simple linear regression model was used to reconstruct total annual (previous August to current July) Yellow
River streamflow at Tangnaihai from the first PC of the six
tree ring chronologies over the common period 1409– 2001.
During the time period common to tree rings and streamflow (1956 – 2001), the first PC explained 49% of the
recorded streamflow variance. Figure 8 shows the observed
and reconstructed streamflow. The reconstruction estimates
the observed changes in Yellow River streamflow very
well, including the evident low-frequency change. The dry
periods are particularly well estimated. In contrast, the
reconstructed flow during high streamflow years tends to
underestimate the observed values, which is a typical weakness of tree ring-based streamflow reconstructions [Fritts,
1976]. In the high streamflow period, the precipitation in the
research area is quite large. The trees get enough moisture
from the soil, and the precipitation is not the restricting
factor for the tree growth.
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Figure 9. Reconstructed streamflow of the Yellow River
over the past 593 years. The thin grey line is the reconstructed annual streamflow, and the imposed bold black line
is the 11-year moving average. The average during the reconstruction period (1409– 2001) is also shown as straight
dashed line.
[17] Split-sample calibration-verification tests [Meko and
Graybill, 1995] were employed to evaluate the statistical
fidelity of our reconstruction model. The resulting statistics are shown in Table 4. There are 46 years observation
data; the calibration-verification period were split into 30
and 16 years. Thirty years data were used for calibration, and
16 years data were used for verification. The values of the
two most rigorous tests of model validation, the reduction
of error (RE) and the coefficient of efficiency (CE), are both
positive, which indicates significant skill in the tree ring
estimates. The results of the sign test, which describes how
well the predicted value tracks the direction of actual data,
exceed the 95% confidence level. These test results demonstrate the validity of our regression model. Therefore Yellow
River streamflow was reconstructed over the time period
AD 1409 –2001 (Figure 9).
3.3. Discussions
[18] The streamflow reconstruction contains considerable
low-frequency variability that is only hinted at from the very
short instrumental streamflow record (cf. Figures 8 and 9).
There are several particularly dry periods indicated during
the past 593 years, namely, 1480 – 1490s, 1590 – 1600s,
1700 – 1710s, 1820 – 1830s, and 1920 –1930s. Most of these
droughts are consistent with a precipitation reconstruction
in northeast Qinghai [Sheppard et al., 2004; Liu et al.,
Table 4. Statistics of Calibration and Verification Test Results for the Common Period of 1957 – 2001
R
R2
Reduction of Error
Coefficient of Efficiency
Sign Test
Calibration
(1957 – 1986)
Verification
(1987 – 2001)
Calibration
(1972 – 2001)
Verification
(1957 – 1971)
Full Calibration
(1957 – 2001)
0.730
0.533
/
/
25+/5b
0.644
0.415
0.443
0.190
10+/5a
0.764
0.584
/
/
23+/7b
0.503
0.253
0.240
0.206
11+/4a
0.697
0.485
0.462
/
/
a
Significant at p < 0.05.
Significant at p < 0.01.
b
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GOU ET AL.: STREAMFLOW VARIATIONS OF THE YELLOW RIVER
2006], especially that in the 1480 – 1490 period. The
droughts in 1700 – 1710s, 1820– 1830s, and 1920 – 1930s
are also present in tree ring reconstructions from Tienshan
in western China [Li et al., 2006], Huashan in north-central
China [Hughes et al., 1994], and Mongolia [Davi et al.,
2006]. The 1590– 1600s drought is also present in tree rings
from the Yangtze River headwaters region [Qin et al., 2003],
and Liang et al. [2004] found that there was a large-scale
drought in Northwest China in the 1920s – 1930s, which
was the most serious drought during the past 150 years.
The late 1920s to early 1930s was also a period of significant
drought in east-central Mongolia [Pederson et al., 2001].
[19] The reconstructed drought events also coincide well
with historical archives. There was a serious drought in
Beijing, Shandong, Shanxi, Henan, and Shannxi in 1484,
which is close to one of the worst drought periods in our
reconstruction (Figure 9). The Yellow River was also dry
in Gansu in 1602, and there was a multiyear drought centered on 1877 in the drainage area (Chinese Hydrology
Events Records, http://www.chinawater.net.cn/history-new/
contents.asp, 2006). Centered on 1879, multiyear drought
exists in the reconstructed streamflow, and streamflow on
1877 is also quite low (Figure 9). All these drought events
are reflected by our reconstructed streamflow series, which
supports the reliability of our reconstruction. A very severe
drought period during the 1920s is also mentioned in
historical records [Shi, 1991; Xu, 1997]. This drought is
recorded in the reconstructed Yellow River streamflow
series as well (Figure 9).
[20] Streamflow at Tangnaihai actually increased over
much of the twentieth century (Figure 9). A similar trend is
indicated in the Qilian Mountains [Shao et al., 2005],
Tienshan, western China [Li et al., 2006], Mongolia
[Pederson et al., 2001; Davi et al., 2006], and northern
Pakistan [Treydte et al., 2006]. However, since the 1980s,
Yellow River streamflow has decreased significantly,
although it is not yet out of the range of earlier streamflow
fluctuations reconstructed for the past several centuries.
Previous studies have indicated considerable environmental
change in the Animaqing Mountains, including glacial
retreat, degrading grasslands, desertification, and lake shrinkage [Ji, 1996; Liu and Wang, 1999; Yang et al., 2003; Liu et
al., 2002]. The recent dramatic ecological and environmental
deteriorations that have occurred in the headwater area since
the 1980s must therefore take into consideration this longterm perspective.
[21] The wavelet power spectrum analyses [Torrence and
Compo, 1998] showed that there are several significant
periodicities in the reconstruction runoff of the Yellow
River: 3.6, 22, 57, 115, 200, and 260 – 300 years, with the
115-year period being the most significant. The meaning of
these periodic components is unclear now, but similar ones
around 110 – 115 and 22 years have been detected in
drought records and reconstructions from North America
[Cook et al., 1997; Herweijer et al., 2007]. Quasi-solar
periodicities have been found in two Mongolian paleohydrologic studies [Pederson et al., 2001; Davi et al., 2006].
4. Conclusion Remarks
[22] Most of northern China has experienced severe and
prolonged dry periods in recent decades. The severe
droughts in recent years in many areas of northern China
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caused large economic and societal losses. The main drainage area of the Yellow River is located in arid and semiarid
climate zones. The multiyear very low streamflow events
can have severe effects on water resources, quality, and river
ecology downstream. The annual Yellow River streamflow
in the past 593 years at Tangnaihai hydrological station,
headwater of Yellow River, was reconstructed on the basis
of the tree ring width chronologies. The reconstruction demonstrated that 1480– 1490 is the driest decade. The streamflow at Tangnaihai increased during much of the twentieth
century. However, since the 1980s, Yellow River streamflow has decreased significantly. Nevertheless, it is not yet
out of the range of earlier streamflow fluctuations reconstructed for the past several centuries. Although the Tangnaihai station only records streamflow from the headwater area,
the high correlation between this station and the Shanxian
station (prior to the reservoirs) indicates that this reconstruction may be representative of a much larger region.
[23] In view of the well-recognized water supply issues
that China will probably face in the future, the development
of further streamflow reconstructions from long tree ring
records is highly valuable. They will provide much needed
and improved long-term estimates of water supply variability
that are not available from the short streamflow gage records.
Consequently, tree ring reconstructions of past streamflow
will provide water supply and natural resources managers
with valuable new information on the expected range of
natural hydrologic variability that is largely independent of
human influences. This new perspective will be an enormous
benefit in evaluating recent observed changes in drought and
wetness over China.
[24] Acknowledgments. Thanks to Paul Krusic’s kind help with the
study. Jianfeng Peng, Yongxiang Zhang, and Yong Zhang from Lanzhou
University took part in the fieldwork. This research was supported by
National Science Foundation of China (40671191 and 90502008), Chinese
111 Project (B06026), Chinese NSFC Innovation Team Project (40421101),
Program for New Century Excellent Talents in University (NCET-05-0888),
and by US National Science Foundation OCE0402474 support for
E.R.Cook and G.C. Jacoby.
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F. Chen and X. Gou, Center for Arid Environment and Paleoclimate
Research, Key Laboratory of Western China’s Environmental Systems,
Ministry of Education, Lanzhou University, Lanzhou 730000, China.
([email protected])
E. Cook, G. Jacoby, and J. Li, Tree-ring Laboratory of Lamont-Doherty
Earth Observatory, Columbia University, Palisades, NY 10964, USA.
M. Yang, Key Laboratory of Cyrosphere and Environment, Cold and
Arid Regions Environmental and Engineering Research Institute, Chinese
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