Continental Shelf Research 31 (2011) 685–694

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Continental Shelf Research
journal homepage: www.elsevier.com/locate/csr

Research papers

Response of salinity distribution around the Yellow River mouth to abruptchanges in river discharge
Yucheng Wang a,1, Zhe Liu a,b,n, Huiwang Gao a, Lian Ju c,d, Xinyu Guo ea

Key Laboratory of Marine Environment and Ecology (Ocean University of China), Ministry of Education, Qingdao 266100, China
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, ChinacLaboratory of Marine Spill Oil Identiﬁcation and Damage Assessment Technology, the State Oceanic Administration, Qingdao 266033, Chinad
The Organization of North China Sea Monitoring Center, North China Sea Branch of the State Oceanic Administration, Qingdao 266033, ChinaeCenter for Marine Environmental Studies, Ehime University, 2-5 Bunkyo-Cho, Matsuyama 790-8577, Japanba r t i c l e i n f oabstract

Article history:
Received 7 May 2010
Received in revised form
9 January 2011
Accepted 12 January 2011
Available online 19 January 2011

To investigate how salinity changes with abrupt increases and decreases in river discharge, threesurveys were conducted along six sections around the Yellow River mouth before, during and after awater regulation event during which the river discharge was increased from  200 to 4 3000 m3 s  1
for the ﬁrst 3 days, was maintained at 43000 m3 s  1 for the next 9 days and was decreased too 1000 m3 s  1 for the ﬁnal 4 days. The mean salinity in the Yellow River estuary area during the event
varied  1.21, which is much larger than its seasonal variation ( 0.50) and interannual variation(  0.05). Before the event, a small plume was observed near the river mouth. During the event, theplume extended over 24 km offshore in the surface layer in the direction of river water outﬂow. Afterthe event, the plume diminished in size but remained larger than before the event. The downstream
propagation of the plume (as in a Kelvin wave sense) was apparent in the bottom layer during thesecond survey and in both the surface and bottom layers during the third survey. The plume sizes
predicted by the formulas from theoretical studies are larger than those we observed, indicating thatfactors neglected by theoretical studies such as the temporal variation in river discharge and verticalmixing in the sea could be very important for plume evolution. In addition to the horizontal variation of
the plume, we also observed the penetration of freshwater from the surface layer into the bottom layer.
A comparison of two vertical processes, wind mixing and tidal mixing, suggests that the impact of wind
mixing may be comparable with that of tidal mixing in the area close to the river mouth and may be
dominant over offshore areas. The change in Kelvin number indicates an alteration of plume dynamics
due to the abrupt change in river discharge during the water regulation event.
& 2011 Elsevier Ltd. All rights reserved.

Keywords:
River plume
Discharge variation
Salinity distribution
Tidal mixing
Yellow River

1. Introduction
River plumes are a general phenomenon in coastal water. They
are affected by many factors, including the inertial effect at theriver mouth, Coriolis force, winds (Fong, 1998; Garcı́a Berdeal
et al., 2002; Choi and Wilkin, 2007), ambient currents (Fong andGeyer, 2002; Xing and Davies, 2002), tidal currents (Isobe, 2005;
Guo and Valle-Levinson, 2007), local topography (Kourafalou,
2001; Xing and Davies, 2002), stratiﬁcation (Kourafalou, 1999;
Wang et al., 2008) and river discharge (Pullen and Allen, 2000;
Kourafalou, 2001; Yankovsky et al., 2001; Choi and Wilkin, 2007).

n
Corresponding author at: Key Laboratory of Marine Environment and Ecology(Ocean University of China), Ministry of Education, Qingdao 266100, China.
Tel.: + 86 532 66786568; fax: +86 532 66782810.
E-mail address: zliu@ouc.edu.cn (Z. Liu).
1
Present address: Center for Marine Environmental Studies, Ehime University, 2-5 Bunkyo-Cho, Matsuyama 790-8577, Japan.

0278-4343/$ - see front matter & 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.csr.2011.01.005

The competition of these factors results in a variety of behaviors
and time scales in river plumes.
Among the factors affecting river plumes, the river discharge
and its temporal variation are particularly important. River
discharge varies over many time scales. The longer time scales
can be interannual or seasonal, whereas shorter time scales canlast only several days, such as during a ﬂood. Hereafter, we referthese short time scales as abrupt changes in river discharge.
Compared to the interannual or seasonal variations in riverdischarge, it is difﬁcult to understand the inﬂuence of abruptchanges in river discharge on salinity distributions from ﬁeld
observations. Interannual and seasonal variation in salinity can bemonitored by monthly or seasonal routine hydrographic surveys.
However, the variation in salinity with an abrupt change in riverdischarge is difﬁcult to capture with such routine surveys. In
addition, an abrupt change in river discharge is often caused by aheavy precipitation event accompanied by bad weather conditions. The strong winds that coincide with bad weather conditions

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Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

not only limit a ﬁeld survey but also strongly affect the evolutionof a plume.
The Yellow River (see Fig. 1 for the position) is one of largest
rivers in the eastern Asian marginal seas. During the past several
decades, its annual discharge has decreased gradually, partly due
to climate change and partly due to human use (Wang et al.,2006), resulting in an unbalanced relationship between water andsediment inside the river and an increase in the salinity of theBohai Sea (Wu et al., 2004). During 2002–2004, the Yellow River
Conservancy Commission (YRCC) carried out a series of water
regulation experiments to reshape the coordinative relationshipbetween water and sediment by artiﬁcially releasing a large
amount of water in a short time. Usually, a water regulation
event last for only two weeks but the river discharge during theevent accounted for greater than 20% of the annual discharge.
Since 2005, water regulation events have been conducted regularly at the beginning of every ﬂood season.
The salinity around the Yellow River mouth is expected tochange dramatically with a large river discharge during a water
regulation event, but the changes have not been well documented. With an interest in sediment transport, Wang et al. (2005)
have reported that the plume near the river mouth containing
high sediment moved rapidly during the water regulation eventin 2005. Using a numerical model, Mao et al. (2008) havesuggested that the variations in Yellow River runoff, including
runoff during water regulation events, are important to thesalinity not only in the area around the river mouth but also in
the entire Bohai Sea. Based on a box model, Zhao et al. (2010)
have examined the effects of water regulation events on the meansalinity of the Laizhou Bay, a semi-enclosed bay located southwest of the river mouth (see Fig. 1 for its position).
Treating the water regulation event as an opportunity toobserve the response of a plume to an abrupt increase anddecrease in river discharge, we carried out three surveys andmeasured the salinity and temperature around the Yellow River

39

Latitude (N)

38.8

40
Bohai
Sea

38.6

38

38.4

36

38.2

Yellow Sea
118

120

122

124

Bohai Sea
126

A

B

mouth before, during and after the water regulation event in2009. After describing our observations in Section 2, we report thesalinity distributions from our three surveys in Section 3 anddiscuss them in Section 4. Our conclusions are presented
in Section 5.

2. Field observations
For the water regulation event of the Yellow River in summer of2009, the river runoff recorded at Station Lijin (see Fig. 1b for
its position), the nearest hydrological station to the river mouth( 100 km away), increased from 230 m3 s  1 on June 22 to
3170 m3 s  1 on June 24. After a runoff larger than 3000 m3 s  1
was maintained for 9 days, the runoff decreased from 3135 m3 s  1
on July 3 to less than 1000 m3 s  1 on July 7 (Fig. 2). Corresponding
with the variation in river discharge, we carried out three surveys on
June 19, July 1 and July 19, which were before, during and after thewater regulation event, respectively (Fig. 2). The distance between
Lijin Station and the Yellow River mouth may have caused a time lagof  10 h between the record of river discharge and its arrival timeat the Yellow River mouth during the water regulation event.
Because our goal was to observe the subtidal movement of theplume, this time lag was neglected.
Six sections were arranged over a semicircle centered at theriver mouth. Each section consisted of eight stations (Fig. 1) thatwere relatively denser near the river mouth. Three ﬁshing boats
were employed, with each covering two sections. The boats
started at the same time and ﬁnished all the sections within 10 h. The water temperature and salinity were measured byconductivity–temperature–depth proﬁlers (CTDs).
A large amount of river sediment always ﬂows into the sea
during a regulation event and causes a change in bathymetryaround the river mouth (Wang et al., 2005). We also found slightchanges in water depth at some stations during our survey period.
However, such changes in bathymetry had essentially no inﬂuence on the plume observations because the maximum differencein water depth was less than 10% of the whole depth.
In addition to the in-situ hydrographic data, daily satellite
wind data from QuikSCAT Level 3 Daily, Gridded Ocean wind
Vectors (see Fig. 1 for data positions; data were available fromhttp://podaac.jpl.nasa.gov/DATA_PRODUCT/OVW/index.
html#quikscat) and daily precipitation data observed at the
Hekou weather station (see Fig. 1b for its position), which is thenearest weather station to the study area, were also used inthis study.

C

3. Results

38
D

3.1. Variability in the horizontal distribution of salinity

Hekou

37.8

E

37.6
37.4

Yellow River

F

Lijin
Laizhou Bay

37.2
10 km

37
118.2 118.4 118.6 118.8

119 119.2 119.4 119.6 119.8
Longitude (E)120Fig. 1. (a) Location of the survey area and (b) the positions of the six sections,represented by characters A–F. The arrow denotes the outﬂow direction of the
Yellow River water. Squares denote stations for salinity and water temperature
measurements. Stars denote grid points for wind data from QuikSCAT.

The ﬁrst survey was carried out on June 19, 2009, when theriver discharge was low (173 m3 s  1). Before the water regulation
event, low salinity water was concentrated in the northern regionof the Yellow River mouth in only the surface layer (Fig. 3a).
Because the salinity was relatively high, water with salinity lower
than 26, which will be used to deﬁne the plume front in thesecond and third surveys, was rarely identiﬁed in the results of
the ﬁrst survey.
The second survey was on July 1, 2009, when the riverdischarge was high (3600 m3 s  1) and a high river discharge
had been maintained for several days (Fig. 2). During the water
regulation event, the surface salinity at most of the stations
decreased dramatically, and low salinity water spread offshore
far from the river mouth (Fig. 3d). The low salinity water in the

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

Discharge (m3s−1)

First survey

Second survey

687

Third survey

4000

2000

0

5 m s−1(mm day−1)

100

50

0
7−Jun

13−Jun 19−Jun 25−Jun

1−Jul

7−Jul

13−Jul19−Jul25−JulFig. 2. (a) Daily discharge of the Yellow River, (b) daily sea surface winds and (c) daily precipitation rate from June 7 to July 30, 2009. The three vertical bars indicate thedates of the three surveys. The daily discharge was recorded at Station Lijin; the wind data is the average of the four QuikSCAT grid points; daily precipitation was observedat the Hekou weather station. The positions of Station Lijin, the four QuikSCAT grid points and the Hekou weather station are given in Fig. 1.

32

Latitude (N)38.2

Surface layer
June 19 2009

Bottom layer
June 19 2009

Bottom−Surface
June 19 2009

18

30

38

15

37.8

28

37.6

26
12

Latitude (N)38.2

Surface layer
July 1 2009

Bottom layer
July 1 200924

Bottom−Surface
July 1 2009

38
22

9

37.8
20

37.6

6

Latitude (N)38.2

Surface layer
July 19 2009

Bottom layer
July 19 200938

18

Bottom−Surface
July 19 2009

16
3

37.8

14

37.6
0

12

119 119.2 119.4 119.6 119.8
Longitude (E)119 119.2 119.4 119.6 119.8
Longitude (E)119 119.2 119.4 119.6 119.8
Longitude (E)Fig. 3. Horizontal distribution of salinity in the surface layer (0–1 m below the sea surface), in the bottom layer (1 m above the sea bottom) and their difference (bottom
layer – surface layer) in the ﬁrst survey ((a)–(c)), second survey ((d)–(f)) and third survey ((g)–(i)). Black bold lines denote the 28-isohaline in the ﬁrst survey and the
26-isohalines in the second and third surveys. Arrows denote the outﬂow direction of the Yellow River water. Squares denote CTD stations. The green bold line in eachpanel denotes the position of the maximum magnitude of the horizontal gradient in salinity.

688

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

surface layer was distributed symmetrically to the direction ofriver water outﬂow, while that in the bottom layer was mainly
concentrated in the southern area of the river mouth (Fig. 3e), thedownstream direction, in a Kelvin wave sense. Accordingly, alarge vertical difference in salinity was found in the northeasternarea of the river mouth (Fig. 3f). The minimum salinity in thesecond survey was 8.90 in the surface layer in the vicinity of
the river mouth, and the largest salinity difference between thebottom and surface layers was 17.50 at the same station. Because
the depth of this station was only 2.5 m, the outﬂow of freshwaterfrom the river mouth was driven across a very thin surface layer.
The third survey was conducted on July 19, 2009, when theriver discharge had decreased to 478 m3 s  1. After the water
regulation event, the plume diminished in size (Fig. 3g and h) andthe low salinity water in the surface layer had veered southward(Fig. 3g). This result indicated that the extension of the river
plume depended strongly on the river discharge and the mixing of
low salinity water within the plume with ambient water. In
addition, the upwelling favorable winds before the second survey
and the downwelling favorable winds before the third survey may
also have contributed to the differences in the distribution of low
salinity water (Fig. 3g).
The vertical salinity difference was small in the ﬁrst survey(Fig. 3c), increased to its largest value during the second survey(Fig. 3f) and decreased rapidly in the third survey (Fig. 3i). The
rapid reduction in vertical salinity difference between the second
survey and the third survey reﬂects the inﬂuence of verticalmixing.
Practically, a plume front can be deﬁned as a place withmaximum horizontal gradient of a variable such as salinity or
turbidity. Here, we calculated the horizontal gradient of salinity ineach survey and the position of its maximum magnitude is shownin Fig. 3. The position of the maximum magnitude of the salinity
gradient generally coincided with the 28-isohaline during the ﬁrst
survey and the 26-isohaline during the second and third surveys.
For a clear image of the plume front movement, we present
the distribution of the 28-isohalines for the ﬁrst survey and the
26-isohalines for the second and third surveys in the surface andbottom layers from three surveys in one ﬁgure (Fig. 4). According

38.3
38.2

Black lines for first survey
Red lines for second survey
Blue lines for third survey

to the results, the plume front was barely identiﬁable before thewater regulation event, spread out in the direction of river wateroutﬂow when the river discharge increased to a high value during
the event and returned to the river mouth as the river discharge
decreased after the event. During the evolution of the plume, thediluted water gradually ﬂowed in the downstream direction in a
Kelvin wave sense.
The factors affecting the movement of a plume competed witheach other during the water regulation event. As a buoyancydriven current, the Yellow River plume tends to move southward,
a downstream direction in a Kelvin wave sense. According
to Wang et al. (2008), the inherent northward tidally induced
residual current in our study area tends to prevent the plumefrom extending southward. When the river discharge was small
as in the ﬁrst survey, the buoyancy-driven current was weak andthe low salinity water was limited to the upstream area by thetidally induced residual current. With input of a large amount offreshwater, as before and during the second survey, the inﬂuenceof the tidally induced residual current became relatively small
and the inertial effect of river water led the low salinity water to
distribute itself in a quasi-symmetric structure in the direction ofriver water outﬂow. In addition, the upwelling favorable winds
between the ﬁrst and second surveys helped the plume spreadoffshore. The development of the buoyancy-driven current
between the second and third surveys and the downwellingfavorable winds prior to the third survey may have been responsible for the low salinity water observed in the downstream areain the third survey.
In order to quantitatively examine the temporal change ofsalinity, the daily rate of variation of salinity in the surface andbottom layers was calculated from the results of three surveys(Fig. 5). During the period from the ﬁrst survey to the second
survey, the mean reduction rate of salinity was maximal near theriver mouth (  1 day  1) in the surface layer and decreased with
distance from the river mouth (Fig. 5a). It was much lower in thebottom layer than in the surface layer (Fig. 5b). During the period
from the second survey to the third survey, the surface salinity
increased with a maximum rate of 0.5 day  1 in the northern areaof the river mouth (Fig. 5c). The bottom salinity increased on thedownstream side but decreased on the upstream side (Fig. 5d).
The surface salinity at the northwestern corner of the survey area
increased during the period from the ﬁrst survey to the second
survey (Fig. 5a), but decreased during the period from the second
survey to the third survey (Fig. 5c), indicating a time lag in the
spread of freshwater toward the upstream area.

Latitude (N)

38.1
3.2. Variability in the vertical distribution of salinity

38
37.9
37.8
37.7
10 km
37.6
37.5
118.9 119 119.1 119.2 119.3 119.4 119.5 119.6 119.7 119.8
Longitude (E)Fig. 4. Positions of the plume fronts in the surface layer and bottom layer
observed during the three surveys. The plume front was deﬁned as the locationof the 28-isohaline in the ﬁrst survey and the location of the 26-isohaline in thesecond and third surveys. Dashed lines represent the plume fronts in the surface
layers, while solid lines are the plume fronts in the bottom layers.

The salinity observed in the ﬁrst survey was relatively uniform
vertically (left panels in Fig. 6). Low salinity (o28) appeared onlyin the surface layer of Section C. Some stations near the rivermouth along Section B that were also expected to have low
salinity were not observed due to the bad weather conditions.
The salinity decreased in the second survey at all sections, but
the thickness of the low salinity water layer was different amongsections (middle panels in Fig. 6). With the input of a large amountof freshwater, low salinity water was observed in the surface layer.
Accordingly, the position of the 30-isohaline became deeper at all
sections except for Section A, indicating the possibility of onshore
movement of high salinity water there. The low salinity water was
separated from the bottom water at Sections A–D but remained incontact with the bottom water at Sections E and F.
After the reduction in river discharge, in the third survey, thediluted water stayed close to the river mouth and remained in thesurface layer (right panels in Fig. 6). The salinity of the bottom

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

689

1.5

38.2

Surface layer

0

+

38

0

−0.5

38

0

+

1
−

−

−0.5

37.8

37.8

0.5

0

37.6

37.6
119.2

119.4

38.2

119.6

119.8

−

119.2

119.4

38.2

Surface layer

38

119

119.6

119.8

0

Bottom layer
−0.5

0

38
0.5

37.8

0

37.8

−

+

0.5

119

Latitude (N)Bottom layer−1

Latitude (N)

38.2

0

−1
+

37.6

37.6

0

−1.5

119

119.2

119.4

119.6

119.8

Longitude (E)

119

119.2

119.4

119.6

119.8

Longitude (E)Fig. 5. Rates of temporal variation of (a) surface salinity between the second and ﬁrst surveys, (b) bottom salinity between the second and ﬁrst surveys, (c) surface salinity
between the third and second surveys and (d) bottom salinity between the third and second surveys. The symbol ‘+ ’ denotes an increase in salinity, while that of ‘  ’ adecrease in salinity. The unit is day  1.

water decreased at Sections A–D but increased at Sections E and F.
Because horizontal mixing with ambient salty water may increase
the salinity of bottom water and the horizontal spreading of low
salinity bottom water could be limited by strong tidal currents,
the decrease in bottom water salinity can be explained by freshwater supply via vertical mixing from the surface layer during theperiod between the second survey and the third survey. On theother hand, the increase in bottom water salinity was likely
caused by the onshore intrusion of high salinity ambient waterfrom outside the survey area because the increase occurred along
only two sections.
Until now, we have presented how the abrupt increase or
decrease in river discharge affected the salinity distribution in thehorizontal and vertical directions. We have not shown any resultson variations in water temperature because river discharge has
little inﬂuence on water temperature. However, it has beenreported that the offshore movement of a plume depends onthe density stratiﬁcation due to water temperature (Wang et al.,2008). It is, therefore, necessary to examine how the density
stratiﬁcation depends on water temperature and salinity andwhether this relationship changes with river discharge.
We adopted the following method to examine the contributionof water temperature and salinity to stratiﬁcation deﬁned by thedensity difference (D) between the surface layer and the bottom
layer. The temperature was ﬁxed to that of the bottom layer and
we used the observed salinity to calculate the density difference(DS) between the surface layer and the bottom layer. We also
ﬁxed salinity to that of the bottom layer and used the observed
temperature to calculate the density difference (DT) between thesurface layer and the bottom layers. As ﬁrst-order approximations, DS/D and DT/D are considered to be the density stratiﬁcation due to salinity and temperature, respectively.
In general, both temperature and salinity contributed to
stratiﬁcation (Fig. 7a and b). The contribution from salinity
decreased apparently with distance from the river mouth. For
example, the salinity contributed 70% to the density stratiﬁcation

at onshore stations (Fig. 7a), but less than 50% at offshore stations.
Furthermore, the linear regressions of DS/D and DT/D to the
distance from the river mouth indicate that the contribution ofsalinity to stratiﬁcation is proportional to the river discharge(Fig. 7a), whereas that of temperature to stratiﬁcation is inversely
proportional to the river discharge (Fig. 7b).
Because the river plume tends to turn right after entering the sea,
the inﬂuence of salinity on density stratiﬁcation probably depends
on the relative position of the measurement station in relation to theplume. In order to examine this possibility, the study area wasdivided into three subregions: an upstream region (Sections A andB), an outﬂow region (Sections C and D) and a downstream region(Sections E and F). The proportional relationship between thecontribution of salinity to density stratiﬁcation and the riverdischarge was generally kept in the three subregions, except for in
the upstream region during the ﬁrst and third surveys (Fig. 7c).
Among the possible causes for this exception (that the contributionof salinity to density stratiﬁcation is larger in the ﬁrst survey than in
the third survey), the fast movement of the river plume from the
upstream and outﬂow regions to the downstream region after thelarge river discharge before and during the second survey andsubsequent intrusion of ambient water into the upstream region
must be an important process.

3.3. Variability of water exchange capability
To determine the variation in the water exchange capability of
the waters around the Yellow River mouth during our survey
period, we computed the ﬂushing time (t), which is deﬁned as theratio of the volume (VOL) of the target region and the inﬂow ﬂux(Vin) of seawater from outside the target region (Sheldon andAlber, 2006). The target region here was set as the survey area,
which had a volume of 1.65  1010 m3.
In order to obtain the inﬂow ﬂux Vin, a simple box model was
conﬁgured based on the conservation of volume and salt within

690

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

Fig. 6. Vertical distributions of salinity observed for three surveys along Section A (a–c), Section B (d–f), Section C (g–i), Section D (g–l), Section E (m–o) and Section F (p–r).
The white lines denote the 26-isohaline, 28-isohaline and 30-isohaline.

the box (Gordon et al., 1996):
Vout ¼ VQ þ Vin þPE

ð1ÞdS
¼ Vin S0 Vout S
dt

ð2Þ

VOL

Here, Vout is the outﬂow ﬂux from the survey area, VQ is theriver discharge, P and E are the precipitation and evaporation overthe survey area, respectively, S is the spatially averaged salinity
within the survey area and S0 is the salinity outside the survey
area. From Eqs. (1) and (2), Vin is obtained as follows:


1
dS
ð3Þ
ðVQ þPEÞS þ VOL
Vin ¼
ðS0 SÞ
dt

We applied Eq. (3) to every two consecutive surveys. The valueof S0 was set to 31.60, the largest salinity observed during thethree surveys. Denoting the survey times as T1, T2 and T3 thespatially averaged salinity within the survey area as S1, S2 and S3,
respectively, we obtained S as 0.5(S1 + S2) and 0.5(S2 +S3), dS/dt as(S2  S1)/(T2 T1) and (S3  S2)/(T3  T2) for the period from the ﬁrst
survey to the second survey and that from the second survey tothe third survey, respectively. The other variables VQ, P and E weretreated as the mean values between two subsequent surveys andcalculated from observed daily data.
Before analyzing the box model results, we examined the relativerole of surface freshwater ﬂux in the river discharge. The average
precipitation rate (6.02 mm day  1) during the entire survey period

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

100

Percentage

100

DT/D
50

50
DS/D

0
100

Percentage

0
100

DT/D
50

50
DS/D

Percentage

0
100

0
100
DT/D

50

50
DS/D

0
100
Percentage

691

0
100
DT/D
50

50
DS/D

0

0
0

10

20
30
Distance (km)

0

40

10

20
30
Distance (km)40

Fig. 7. Contributions of vertical variations in salinty (left panel) and water temperature (right panel) to density stratiﬁcation at the stations where the density difference
between the surface and bottom layers was larger than 1 kg m  3. The dots were caculated from data observed for each survey, and the lines are based on ﬁrst-order linear
regressions. The black, red and blue colors for the dots and lines are for the ﬁrst, second and third surveys, respectively. Panels (a) and (b) present data from all stations;(c) and (d) present data from Sections A and B; (e) and (f) present data from Sections C and D; and (g) and (f) present data from Sections E and F.

Table 1
Calculation of ﬂushing time. See Eq. (3) for meaning of each term. dS/dt is in day  1; VQ, P, E, Vin, Vout are in 108 m3 day  1 and t is in days.
Period

S

S0

dS/dt

VQ

P

E

Vin

Vout

t

First survey to second survey
Second survey to third survey

30.11
28.90

31.60
31.60

 0.11
0.05

1.96
0.95

0.12
0.07

0.18
0.13

26.21
12.58

28.11
13.48

6.3
13.1

was obtained from the daily observation data at the Hekou weather
station. According to Yan (1999), the evaporation rate in our study
area in the summer is less than 0.56 mm day  1. Given the net
surface freshwater ﬂux (6.02–0.56¼5.46 mm day  1) and the surface area of the box (1.55  109 m2), the surface freshwater ﬂux was
8.5  106 m3 day  1, which is smaller than the Yellow River meandischarge (1.38  108 m3 day  1) from June 19 to July 19 by almost
two orders of magnitude. Therefore, the surface freshwater ﬂux
contributed extremely little to the water volume budget and salt
budget during the period of the water regulation event, although it
could be important for the long-term variations in salinity in the
study area (Wu et al., 2004). It must be noted that a direct
estimation of evaporation rate using a bulk formula gave a different
value from that of Yan (1999). However, using the direct estimate
did not change the fact that the surface freshwater ﬂux played anegligible role in the water volume budget. The calculated ﬂushingtime was 6.3 days for the period from the ﬁrst survey to the second
survey and 13.1 days for the period from the second survey to thethird survey (Table 1). The difference in ﬂushing time results fromthe difference in the inﬂow ﬂux of seawater from outside the box,
which was generally proportional to the river discharge with a ratio
approximately 15. Therefore, increasing the river discharge generally promotes the water exchange of our target region.
An alternative method to calculate the variability in waterexchange capability is to examine the freshwater budget inside
the survey area. The volume of freshwater can be calculated by

the following equation (Choi and Wilkin, 2007):
FP ¼

Z Z h2h1

ðS0 SA Þ
dzdA
S0

ð4Þ

Here, SA denotes the observed salinity at each station, S0 is the
background salinity of 31.6, A is the surface area of the target
region and h1 and h2 denote water depths. Because most low
salinity water was observed in the surface layer, we separated thewater column into two layers. The upper layer is from the surface
to a depth of 5 m, while the lower layer extends from the 5 m
depth to the sea bottom.
The calculated freshwater volumes in the upper layer were
4.12  108, 9.98  108 and 5.19  108 m3, in the ﬁrst, second andthird surveys, respectively. The increase and decrease in the
freshwater volume of the upper layer is consistent with thechanges in river discharge. The calculated freshwater volumes
in the lower layer were 3.64  108, 4.10  108 and 4.70  108 m3,
respectively. The increase in the freshwater volume of the lower
layer between the second and third survey is not consistent withthe change in river discharge, indicating the downward transportof freshwater via vertical mixing.
During the period between the ﬁrst survey and the second survey,
the freshwater volume within entire water column increased by
6.32  108 m3, the majority of which (5.86  108 m3) entered theupper layer, while the rest (0.46  108 m3) entered the lower layer.

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Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

During the period from the second survey to the third survey,
the freshwater volume within entire water column decreased by
4.19  108 m3. The lower layer kept receiving freshwater(0.60  108 m3), but the upper layer lost much more freshwater(4.79  108 m3).
The freshwater input from the Yellow River into the box was
25.51  108 m3 during the period between the ﬁrst survey and thesecond survey and 17.14  108 m3 during the period between thesecond survey and the third survey. Excluding the change in freshwater volume within the box, we know that 19.19  108 and21.33  108 m3 of freshwater ﬂowed out of the box through its
lateral boundary during the two periods mentioned above. Accordingly, the daily freshwater ﬂuxes through the lateral boundary of thebox were 1.48  108 and 1.19  108 m3 day  1 during the two
periods. The result that the ﬁrst period had a larger freshwater ﬂux
through lateral boundary than the second period is consistent withthe difference in ﬂushing time. Therefore, the exchange rate
between the area at the mouth of the Yellow River and the outside
region becomes large with the abrupt increase in river discharge andbecomes small with the abrupt decrease in river discharge.

4. Discussion

reasonable if we consider the spatial scales of wind velocities andtidal currents.
The above calculation has a large uncertainty because the data fortidal currents was not directly measured in our surveys. In addition,
the mixing efﬁciency parameters e and d were also from otherstudies. If we use the mixing efﬁciency parameters e ¼ 4  10  3 andd ¼2.3  10  2 from Simpson and Bowers (1981), Pt and Pw become
4.2  10  4 and 7.2  10  5 W m  3, respectively, in onshore areas and1.7  10  5 and 2.4  10  5 W m  3 in offshore areas. In this case, tidal
mixing is dominant over onshore areas and is comparable with wind
mixing over offshore areas. Therefore, we need to keep in mind theuncertainty of our conclusion based on the parameters given by
Zhao et al. (1994) although those parameters are more suitable toour survey area than the parameters given by Simpson and Bowers(1981).
To conﬁrm the effects of tidal mixing on the plume, we also needto compare the tidally induced bottom water boundary layer heightwith the water depth because low salinity water was usually only
distributed in the surface layer, where tidal mixing may not reach.
The bottom boundary layer thickness caused by the clockwise
component (B  ) and anticlockwise component (B + ) of tidal currents
were calculated by the following equations (Prandle, 1982):

2Nz 1=2
ð7Þ
B ¼
ðof Þ

4.1. Tidal mixing and wind mixing
As presented in Section 3, vertical mixing is likely to beimportant to the salinity distribution. Both tidal mixing and wind
mixing contribute to vertical mixing. Here, we compare theircontributions.
We computed the stirring power of the tidal current (Pt) andthat of the surface wind stress (Pw) using an empirical formula
given by Simpson and Bowers (1981):
Pt ¼

4
U3
ekb r
3p
h

Pw ¼ dks ra

W
h

Bþ ¼

Nz ¼
ð6Þ

In these equations, U is the amplitude of tidal current near theseabed, h is the typical depth of the area, W is the wind speed, r is
the density of seawater (1020 kg m  3), ra is the density of air(1.3 kg m  3), e is the efﬁciency of tidal mixing (2  10  3, according to Zhao et al., 1994), d is the efﬁciency of wind mixing (0.11,
according to Zhao et al., 1994), kb is the effective drag coefﬁcientfor bottom stresses (1.2  10  3, according to Zhao et al., 2001)
and ks is the effective drag coefﬁcient for surface stresses(6.4  10  5, according to Simpson and Bowers, 1981).
The amplitude of the observed tidal ﬂow around the river mouth
was approximately 1 m s  1 at a station with a water depth of 5 m(Wang et al., 2005), which gives a Pt of 2.1  10  4 W m  3. Meanwhile, the daily Pw calculated based on the same water depth andthe daily satellite wind speed during the period from June 19 to July
19 results in an average value of 3.2  10  4 W m  3. Consequently,
the tidal mixing was comparable with the wind mixing in this area.
However, the magnitude of tidal currents and water depth change
rapidly in space. For example, at a station far away from theriver mouth, where the water depth is 15 m and the tidal ﬂow
was 0.5 m s  1 (station A5 in Qiao et al., 2006), Pt becomes
0.9  10  5 W m  3, which is smaller than the stirring power of wind(1.1  10  4 W m  3) by almost an order. Therefore, although thetidal mixing and wind mixing are similar in strength in the area
close to the Yellow River mouth, wind mixing is dominant overoffshore areas. The sharper decrease in tidal mixing compared towind mixing between onshore areas and offshore areas looks

2Nzðo þ f Þ1=2ð8ÞHere, o is the frequency of the tidal constituent (M2 tide,
1.4  10  4 s  1), Nz is the eddy viscosity coefﬁcient, and f is
the Coriolis parameter (0.9  10  4 s  1). The eddy viscosity coefﬁcient is related to tidal current amplitude (U), water depth (h)and the effective bottom drag coefﬁcient (kb) by the following
equation (Prandle, 1982), which may be applied to all of the areas
where tidal currents are dominant:

ð5Þ

3



1
k Uh
2 b

ð9Þ

The tidal currents in our survey area are strong and thestratiﬁcation is weak as observed before the water regulation
event (Fig. 6). During or after the water regulation event, thestratiﬁcation was concentrated in the surface layer and the waterfrom the sea bottom was well mixed to a considerable height(Fig. 6). All these facts suggest that tidal mixing is an important
engine for vertical mixing in our study area and that the usage ofthe empirical formula given by Prandle (1982) for eddy viscosity
is a reasonable choice.
According to Liu (1989), the tidal currents around the Yellow
River mouth are generally rectilinear, suggesting the same amplitudeof the anticlockwise and clockwise components, which are the half of
the amplitude of the tidal current. At the station near the river mouth(Wang et al., 2005), Nz is estimated to be 1.5  10  3 m2 s  1, yielding
B + and B  values of 4 and 8 m, respectively. At the station a little
farther from the river mouth (Qiao et al., 2006), Nz is estimated to be
2.3  10  3 m2 s  1, yielding B + and B  values of 4 and 10 m,
respectively. Accordingly, tidal mixing can reach the sea surface inthe former case but can only reach the middle layer in the latter case.
Therefore, the combination of tidal mixing and wind mixing isimportant for the vertical transport of freshwater in the area far
from the river mouth.
4.2. Offshore distance of the river plumeAs depicted in Fig. 4, the offshore distance of the river plumechanged distinctly in the surface layer and the bottom layer during
the observation period. Before the water regulation event, the riverY. Wang et al. / Continental Shelf Research 31 (2011) 685–694

plume front deﬁned by the 28-isohaline was hardly identiﬁable.
During the water regulation event, the offshore distance of the river
plume front in the surface layer was largest (424 km) in the
direction of river water outﬂow, while that of the bottom layer
was largest (o10 km) in the downstream region. After the water
regulation event, the largest offshore distance was 15 km in thesurface layer and only 3 km in the bottom layer in the downstream region.
Yankovsky and Chapman (1997) classiﬁed plumes into three
types: surface-advected plumes, bottom-advected plumes andintermediate plumes. According to the vertical structure of theplume observed around the Yellow River mouth, we classiﬁed it
as a surface-advected plume.
The offshore distance of a surface-advected plume can be calculated by the following equation (Yankovsky and Chapman, 1997):
ys ¼

2ð3guhi þ v2i Þ

ð10Þ

ð2guhi þ vi 2 Þ1=2 f

where ys is the offshore distance of the plume, g0 is the reduced
gravity based on the inﬂow density anomaly, g0 ¼g(Dr/r) (g is thegravity acceleration, r is the density of ambient water and Dr is thedensity difference between the river plume and the ambient water at
the river mouth), hi is the inﬂow depth and vi is the inﬂow velocity.
Substituting the corresponding values from the three surveys
into Eq. (10), the offshore distances of the plume front were
calculated (Table 2). In general, the offshore distances of theobserved plumes were shorter than those predicted by Eq. (10).
For example, the observed plume fronts in the second and thirdsurveys were shorter than the theoretical values by 33%, and thatin the ﬁrst survey was shorter by 66%. Because Eq. (10) does notconsider vertical mixing due to tidal currents, which tends toprevent the offshore movement of a plume (Guo and ValleLevinson, 2007), the longer predicted distance is understandable.
Meanwhile, the difference between Eq. (10) and observations
could also be caused by temporal variations in river discharge
because Eq. (10) is based on a constant river discharge.

4.3. Dynamical examination on the variability of the plume withriver discharge
The box model calculations in Section 3.3 demonstrated thatthe water exchange between the survey area and the area outside
the sea is roughly proportional to the river discharge. For a
dynamical interpretation, we calculated the geostrophic transport
within the plume and the wind-driven transport across the lateralboundary of the survey area. The latter is considered as arepresentative ageostrophic transport.

Table 2
Calculation of offshore distance of the plume front based on the formula given
by Yankovsky and Chapman (1997). B denotes width of river mouth and Dr
denotes density difference between plume water and ambient water; see Eq. (10)for meaning of other terms.
B
hi
r0
vi
ys
Observed offshore
Dr(km) (m) (m s  1) (kg m  3) (kg m  3) (km) distance (km)First
surveySecondsurveyThird
survey
a

1

1

0.2

3.0

1019

9

3

1

2

1.8

12.0

1019

46

424a

1

2

0.2

9.0

1018

20

14

Because the plume front in the second survey was beyond survey region, thedistance was assumed to be larger than 24 km.

693

The geostrophic transport (Qg) within the plume follows theequation given by Fong and Geyer (2002) as follows:
Qg ¼

Drg
2rf

ðh0 Þ2

ð11Þ

where Dr is the difference in density between the plume andambient water, r is the density of ambient water (1020 kg m  3 forthree surveys), g is gravity acceleration and h0 is the plume thickness
at the coast. Values of Dr for the three surveys are shown in Table 3.
According to Fig. 6g–i, h0 was chosen to be 1.5, 5 and 2 m,
respectively, corresponding to the 28-isohaline for the ﬁrst survey
and the 26-isohalines for the second and third surveys. The
calculated Qg values were 263, 7500 and 1022 m3 s  1, respectively.
The ratios of Qg to the corresponding river discharge were 2 in all
three surveys. By assuming that this ratio was maintained throughout the survey periods and using the mean river discharge during
the period between the ﬁrst survey and the second survey andbetween the second survey and the third survey (Table 1), the meanvalues of Qg for the two periods mentioned above were calculated as
4.46  108 and 2.04  108 m3 day  1.
The wind-induced outﬂow transport volume (VE) across thelateral boundary of the survey area was calculated by
X ti
L
VE ¼
ð12Þ
rf i
i ¼ 1,5
where Li is the distance between the farthest points of twoneighbor sections and ti is the wind stress component parallelto L. The calculated VE was 2.63  108 m3 day  1 for the period
between the ﬁrst survey and the second survey and2.87  108 m3 day  1 for the period between the second survey
and the third survey.
Combining this information with Table 1, the sum of thegeostrophic transport and wind-driven transport can account for
only 25–36% of the outﬂow ﬂux from the survey area. Apparently,
other processes are also important to the water exchange
between the survey area and the area outside it. A full understanding of this problem requires the use of a numerical model.
Based on scaling analysis of the continuity and momentum
equations, Garvine (1995) suggested using the Kelvin number (K)to categorize river plumes. The Kelvin number represents theratio of the across-shore length of the plume to the baroclinic
Rossby radius and is expressed as
K

D
c=f

ð13Þ

where D is the across-shore length (i.e., the observed offshore
distance of the plume in Table 2), and c is the internal wave phasespeed based on the difference in density between the plume andthe ambient water.
Following Eq. (13), we obtained values of 0.6, 2.8 and 1.8 forthe Kelvin numbers for the three surveys (Table 3). According
to Garvine (1995), if the Kelvin number is less than 1, theadvection term in the momentum equation is relatively strong
while the Coriolis force is relatively weak, as in the small
K-limiting case. If the Kelvin number is larger than 1, theadvection term is weak and the Coriolis term strong, as in thelarge K-limiting case. Therefore, the values of the Kelvin numbers
Table 3Calculation of geostrophic transport (Qg) based on Eq. (11) and Kelvin number (K)based on Eq. (13). See Eqs. (11) and (13) for meaning of each term.

First survey
Second survey
Third survey

Dr (kg m  3)

h0 (m)Qg (m3 s  1)

K

2.2
5.6
4.8

1.5
5
2

263
7500
1022

0.56
2.8
1.8

694

Y. Wang et al. / Continental Shelf Research 31 (2011) 685–694

from three surveys (Table 3) indicate that the plume dynamics
were altered dramatically by the abrupt changes in Yellow River
discharge during the water regulation event. From the surface
salinity distribution (Fig. 3a, d and g), we can deduce that thebulge was weak or did not exist before the water regulation event,but became strong during and after the water regulation event.
Accordingly, the Kelvin number may be considered as an indicatorof the bulge state: the bulge is strong when the Kelvin number isrelatively large and is weak when the Kelvin number is small.

5. Conclusions
In the three ﬁeld surveys carried out before, during and after
the water regulation event that occurred in the Yellow River in
2009, we observed the responses of a plume to an abrupt change
in river discharge. The distribution of low salinity water wasdifferent between the surface layer and bottom layer. In thesurface layer, low salinity water concentrated around the rivermouth before the water regulation event. As a large amount ofriver water ﬂowed into the sea during the water regulation event,the plume spread offshore with a quasi-symmetrical distribution
in the direction of river water outﬂow. After the water regulation
event, most of the diluted water was identiﬁed close to the rivermouth and turned downstream in a Kelvin wave sense. Meanwhile, the plume in the bottom layer occupied a smaller area thanthat in the surface layer, and the diluted water was generally
distributed in the downstream direction.
Box model analysis indicated that the water exchange rate
between the water around the river mouth and the outside area
was proportional to the river discharge. The geostrophic transport
within the plume and the wind-driven transport across the lateralboundary of survey area can account for only 25–36% of theoutﬂow ﬂux from the survey area. A downward transport offreshwater through vertical mixing was evident during theobservation period. A comparison of the stirring power due totidal current and that due to surface winds suggested that the
impact of wind mixing was comparable with that of tidal mixing
in the area close to the river mouth and was dominant overoffshore areas. The difference between the offshore spreading
distance of the plume predicted by the equation based on atheoretical study and that observed in this study suggests that theinclusion of vertical mixing and the temporal variation in riverdischarge in future theoretical studies. The change in Kelvinnumber, from a value less than 1 before the water regulation
event to a value larger than 1 during and after the event, suggests
an alteration of the plume dynamics due to the abrupt change inriver discharge. Because some parameters such as the verticalviscosity and tidal current data used in above analysis were fromother studies, it is necessary to conﬁrm them by using numericalmodeling or direct observations in the future.

Acknowledgments
We are very grateful to all of the crews involved in the threesurveys. We also thank Prof. Jing Zhang of East China Normal
University and Prof. Wensheng Jiang of Ocean University of China
for their kind help. We appreciate two reviewers for their criticalcomments that are very helpful to improve the manuscript. This
study was funded by the Natural Science Foundation of China(No. 40706007), the Key Laboratory of Marine Environment andEcology (Ocean University of China), Ministry of Education, andthe State Key Laboratory of Estuarine and Coastal Research, East

China Normal University (No. 200813). Xinyu Guo was supported
by a Grant-in-Aid for the Global COE Program from the Ministryof Education, Culture, Sports, Science and Technology, Japan(MEXT) and the Japan Society for the Promotion of Science (JSPS)
and JSPS KAKENHI (21310012).
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