Acta Oceanologica Sinica 2009, Vol.28, No.5, p.66-75
http://www.hyxb.org.cn
E-mail: hyxbe@263.net

The vertical attenuation of irradiance as a function of
turbidity: a case of the Huanghai (Yellow) Sea in spring
LIN Shaoying1 , ZOU Tao1 , GAO Huiwang1∗ , GUO Xinyu2
1

Key Laboratory of Marine Environment and Ecology, Ministry of Education of China, Ocean
University of China, Qingdao 266100, China

2Center for Marine Environmental Studies, Ehime University, 2-5 Bunkyo-Cho, Matsuyama
790-8577, Japan

Received 31 March 2009; accepted 6 September 2009

Abstract
The planar photosynthetically available radiation (PAR), turbidity and concentration of chlorophylla (chl a), were measured at 26 stations in the Huanghai (Yellow) Sea during a cruise of China
SOLAS from 19 to 27 March 2005. Due to low chl a (<0.35 mg·m−3 ) in upper layers (above 5 m),
suspended particulate matter became the major factor that influenced the turbidity in early spring.
The calculated vertical diffuse attenuation coefficient of PAR, KPAR , varied with water depths witha maximum value in the upper 5 m layer. The mean KPAR in survey area was 0.277±0.07 m−1that is considerably higher than most of the other case 2 waters. Within the survey area, K PAR
also showed distinct regional characteristics, corresponding to the distribution of turbidity. Basedon measurements, the relationship between KPAR and turbidity as well as chl a was established.
It was suggested that suspended particulate matter plays an important role in light attenuation in
the Huanghai (Yellow) Sea in spring.
Key words: Photosynthetically available radiation, Diffuse attenuation coefficient, Turbidity,
Chlorophyll a, the Huanghai (Yellow) Sea

1 Introduction
Light is essential for photosynthetic plants andaquatic algae. Besides nutrients, temperature andsalinity, due to the rapid attenuation in water, lightis often a limiting factor to the primary production inaquatic environment (Fisher et al., 1999). Light availability also influences species composition (Rijstenbil,
1987; Jones and Gowen, 1990) and many other biological and chemical processes, such as behavior of organisms (e.g., Graham et al., 2001; Dieguez and Gilbert,
2003), phytoplankton physiological response (Cullen
and Lewis, 1988) and photochemical degradation (Anning et al., 2000).
In the visible part of light spectrum, the light withwavelengths between 400 and 700 nm, termed PAR(Photosynthetically Avaliable Radiation) is utilizedby phytoplankton for photosynthesis (Falkowski andRaven, 1997). The light attenuation underwater occurs mainly due to four factors: water molecule, phytoplankton, colored dissolved organic material (CDOM)
and suspended particulate matter (SPM). The last fac-

tor, i.e., SPM, has a close relationship with turbidity(Jones and Wills, 1965). Through light, these factors
are related to the rates of primary production. Therefore, correct representation of underwater light field isa key issue in modeling the biogeochemical processes
and primary production in aquatic ecosystems.
Because the incident PAR at air-water interface
can be measured or calculated quite accurately (Fisher
et al., 2003), the main difficulty in calculating underwater light field is to correctly estimate vertical lightattenuation coefficient (K). The vertical light attenuation coefficient can be decomposed to a set of partial
attenuation coefficients, each characterizing absorption and scattering by a different waterborne material.
Attenuation depends on wavelength of light andan accurate underwater model for attenuation coefficient must consider light spectrum. Recently, spectral
bio-optical models have been developed and applied tovarious kinds of water bodies (Platt et al., 1988; Gallegos et al., 1990; Arrigo et al., 1994; Lee et al., 2005).
On the other hand, because of its simple principle andeasy measurement, non-spectral bio-optical models

Foundation item: The National Natural Science Foundation of China for supporting this work financially under Contracts No.
40490262. Guo Xinyu thanks the support from JSPS KAKENHI(21310012).
∗ Corresponding author, E-mail: hwgao@ouc.edu.cn

1Lin Shaoying et al. Acta Oceanologica Sinica 2009, Vol. 28, No.5, P.66-75

have had a long history and have also been broadly
used (Morel, 1988; Varela et al., 1992; Radach et al.,
1993; Mcgillicuddy et al., 1995; Wong et al., 1995;
Loukos et al., 1997). However, most of them, no matter spectral or non-spectral models, did not include
the effects of SPM. In the open ocean, this assumptionis acceptable where the concentration of SPM is very
low. However, in coastal waters, the concentration of
SPM is relatively high and it is therefore necessary toconsider the influence of SPM on the light attenuation
underwater. This is particularly true in the Huanghai(Yellow) Sea, where SPM and turbidity is high (Suand Yuan, 2005).
The Huanghai Sea is semi-enclosed water surrounded by China, DPR Korea and RO Korea. The
average water depth of Huanghai Sea is nearly 44
m and the maximum depth is above 140 m. The
connection line between Cheng Shanjiao, China andChangsangot, DPR Korea divides the Huanghai Sea
into two parts, north Huanghai Sea and south Huanghai Sea (Su and Yuan, 2005). The Huanghai Sea receives Yellow River diluted water from west (Wanget al., 2008) and Changjiang (Yangtze River) diluted
water from south (Zhu et al., 1998; Pu et al., 2002),
and consequently large amounts of sediment was sent
to the sea (Pang et al., 2003). In addition, the resuspension of sediment offshore the old Yellow Rivermouth and the terrestrial input from Huai, Han, andYalv rivers also contribute to the SPM distribution in
the Huanghai Sea. The Huanghai Sea therefore has
been considered as one of the most turbid water inthe world (Sun et al., 2000).
There is still no a simple model or a function tolink with turbidity and chl a for the Huanghai Sea.
However, such a function is expected to give a morereasonable estimation of underwater light field than aconstant light attenuation coefficient, which is important to the ecological modeling study. In this study,
based on the field data in the Huanghai Sea, a linear
function was established and the effects of SPM andchl-a on light attenuation were discussed.
2 Materials and methods
2.1 Observations
The survey in spring was carried out in an areafrom 121◦ E to 124◦ E and 33◦ N to 39◦ N as the firstcruise of China SOLAS (Surface Ocean-Lower Atmosphere Study) project from 19 to 27 March, 2005 (Fig.
1) on board R/V Dongfanghong II. Observations were67

conducted at 26 stations, among which A1 and A2
were anchor stations and measurements were carriedout every two hours during the 25-hour anchored period. At all stations, CTD measurements were performed down to 2 m above the bottom with XR620CTD probe (RBR Ltd., Canada), which measuresconductivity, temperature and pressure with a maximum sampling rate of 6Hz. The LICOR PAR sensors(LI-192SA) were placed on the CTD probe to measure downwelling planar irradiance profiles in the water. Chlorophyll a and turbidity were measured using
Seapoint sensors attached to the CTD probe. During
each CTD casting, the ship was oriented to minimize
the influence of ship shadow and all the instruments
were lowered from a crane which stretched out 2 mfrom the ship’s side. Dark values were measured at
the beginning of each casting and subtracted from all
the readings.
Compared with traditional fluorescence analysis(chl aFLUO ), the values measured by CTD probe (chlaCTD ) were lower, but they have similar spatial pattern. The linear regression between them is expressedas equation (1) (with a credible degree of 95%). The
good linear regression relation between CchlaCTD and
CchaFLUO indicates that the use of CchlaCTD is acceptable.
chl aCTD = 0.174chl aFLUO × 0.087
R2 = 0.68(1)

In the survey, 17 CTD castings were carried out
during daytime and table 1 shows the measurement
time and dates of these castings.
2.2 Data processing
Light intensity decreases approximately exponentially with depth in water (Kirk, 1994),
Ed (z) = Ed (0) × exp(−KPAR·z )(2)

where Ed (z) is downward irradiance at depth z, Ed (0)is downward irradiance just beneath air-water interface, KPAR is the average value of vertical attenuation coefficient over the distance from surface to water
depth z. Equation (2) can be rearranged to calculate
KPAR :
1
KPAR = − ln(Ed (z)/Ed (0))z(3)

For our calculations to examine the vertical of KPAR ,z is the distance between the upper and lower levels

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Lin Shaoying et al. Acta Oceanologica Sinica 2009, Vol. 28, No. 5, P.66-75

Fig.1. Area and stations of the first China SOLAS cruise. The dot with a name denotes the stations from 19
to 27 March, 2005. The broken line between Cheng Shanjiao, China and Changsangot, DPR korea separates
the Huanghai Sea into north Huanghai Sea and south Huanghai Sea.

of PAR measurement, Ed (z) is the lower PAR measurement, and E0 (z) is the upper PAR measurement.
It is commonly assumed that the average KPAR
can be decomposed as a set of partial attenuation coefficients. In addition to the contribution of water itself,
KPAR is often modeled as a linear function of anotherthree substances’ concentration (Smith, 1982) including phytoplankton (and, if any, macrophytes), SPM
and CDOM (Kirk, 1994). Consequently, KPAR can beapproximated as
KPAR = Kw + Kcchl a +KSPM + KCDOM ,(4)

Where Kw is the attenuation due to water, andKcchl a , KSPM and KCDOM are the specific attenuation coefficients for phytoplankton, SPM and CDOM,
respectively. Theoretically, the estimation of Kchl a ,KSPM and KCDOM is quite challenging in the Huanghai Sea because the temporal and spatial variations ofphytoplankton, SPM and CDOM are large.
The above empirical, non-spectral approach (Eq.
4) has been widely used to study the relation be-

tween light attenuation and water component concentrations in many different marine systems (Smith,
1982; McMahon et al., 1992; Wang et al., 1996, Gallegos and Moore, 2000). It is indicated that if one cansimultaneously measure both KPAR and water component concentrations, the values of specific attenuation coefficients can be obtained by multiple linear
regression method. In this study, we also used such
multiple linear regression method to obtain the relation between KPAR and water component concentrations including those of chlorophyll a and SPM. The
CDOM is not included in our analysis for lack of thedata. With the calculation using field survey data,
we compare the influence of chlorophyll a with that of
SPM on the attenuation of PAR to find out which one
is the major factor affecting the light attenuation in
the Huanghai Sea.
3 Results
3.1 Horizontal and vertical distributions ofchlorophyll a and turbidity
The chlorophyll a concentration chl a was gener-

Lin Shaoying et al. Acta Oceanologica Sinica 2009, Vol. 28, No.5, P.66-75

ally lower than 0.35 mg·m−3 in the surface layer (Fig.
2). Such low chl a was kept in the middle and bottom
layers at most stations except for stations G23, A2-13,
G17, and A1-12, where the chl a increased with depth.
In north Huanghai Sea, chl a varied largely among stations. The chl a was higher at inshore stations (A2,
G23) than those at offshore stations (G22, G21) (Fig.

693a). In south Huanghai Sea, all the stations except for
station A1 presented a similar low level of chl a in thevertical (Fig. 3b). At station A1-12, an inshore station, the chl a was low in the surface layer, but rapidly
increased with depth and reached a maximum of 3.18
mg·m−3 down to about 37 m (data not shown due torange used in figure).

Fig.2. Horizontal distribution of chlorophyll a concentration (mg·m−3 ) (a) in the surface layer and (b) in
the bottom layer.

The vertical profiles of turbidity in north andsouth Huanghai Seas were shown in Fig. 3c and Fig.
3d. There were essentially two types of turbidity profiles in the water column. One was that turbidity
shows a uniform value in the vertical, such as stations
G10, G14, G17, and Gp in south Huanghai Sea andstations G21 and G23 in north Huanghai Sea. The
other was that turbidity is uniform in the upper few
meters and increased with depth in the bottom layer,such as stations G12 and A1-12 in south Huanghai Sea
and stations A2-13 and G22 in north Huanghai Sea.
The horizontal distribution of turbidity was
shown in Fig. 4. In the surface layer, G23, a station in north Huanghai Sea, showed the most turbid
water. The maximal turbidity appeared in the areaeast of Cheng Shanjiao, China. The clearest water inthe study area in south Huanghai Sea located at stations G17 and Gp. In the bottom layer, there were
two maximum turbid areas: one was corresponding tothat in the surface layer, the other appeared in the
middle area of south Huanghai Sea.
Station G12 presents the largest vertical change
in turbidity whose value varied from about 0.8 to 7.9
NTU. In the horizontal, turbidity ranged from about

0.03 to 5.8 NTU in the surface layer and from about
0.9 to 7.9 NTU in the bottom layer. Therefore, turbidity looks like changed at the same order in the verticaland in the horizontal.
The mean values of turbidity and chl a in the surface layer averaged are presented in Table 2, and fromwhich, an interesting trend can be found. The averaged turbidity decreased from north Huanghai Sea
to south Huanghai Sea. In contrast, the averaged chl
a was higher in south Huanghai Sea than in north
Huanghai Sea.
In the Huanghai Sea, the inshore water had distinct optical properties from the offshore water (Table
2). All of KPAR , turbidity and chl a were higher at inshore stations than at offshore stations. The influenceof bathymetry on currents or sediment transport looks
like partly response for the optical difference between
inshore and offshore waters.
3.2 Vertical profile of KPAR
Generally, the value of KPAR can be considered
as a constant in the entire euphotic zone if the watercomponent concentrations do not change significantlyin the vertical water column. To examine this in the

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Fig.3. Vertical profiles of (a, c) chlorophyll a concentration (mg·m−3 ) and turbidity (NTU) at the stations
in north Huanghai Sea and (b, d) south Huanghai Sea (see Fig.1 for their locations).

Fig.4. Horizontal distribution of turbidity (NTU) (a) in the surface layer and (b) in the bottom layer.

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Table 1. Observation time and geographic location of the stations with PAR measurements in the first China SOLAS
cruise on March 2005 in the Huanghai Sea. Four measurements at different time were performed at stations A1 and A2,
respectively. Among total 11 stations, stations A2, G23, G22 and G21 are located in north Huanghai Sea; stations Gp,
G14, G17, A1, G5, G10 and G12 in south Huanghai Sea.
Number
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17

StationLongitude (◦ E)

Latitude (◦ N)

Local Time

Date (March 2005)

A2-11
A2-12
A2-13
A2-14
G23
G22
G21
Gp
G14
G17
A1-10
A1-11
A1-12
A1-13
G5
G10
G12

122◦ 59’008

38◦ 29’009
38◦ 29’009
38◦ 29’009
38◦ 29’009
37◦ 47’008
37◦ 29’930
36◦ 59’008
36◦ 30’002
35◦ 29’819
35◦ 59’932
35◦ 54’062
35◦ 54’062
35◦ 54’062
35◦ 54’062
33◦ 59’890
33◦ 59’890
34◦ 59’846

09:26
11:45
13:33
15:13
09:44
07:34
11:38
15:45
07:34
11:54
09:18
11:23
13:17
15:10
16:09
08:30
16:48

21
21
21
21
20
22
22
22
23
23
27
27
27
27
25
26
23

122◦ 59’008
122◦ 59’008
122◦ 59’008
122◦ 30’002
124◦ 00’099
123◦ 30’000
123◦ 59’009
122◦ 59’896122◦ 30’035
121◦ 34’849
121◦ 34’849
121◦ 34’849
121◦ 34’849
122◦ 30’101
121◦ 00’154122◦ 30’082

Table 2. Mean concentrations of turbidity and chlorophyll a, and mean values of KPAR in the surface layer ofthe Huanghai Sea.
North
South
Inshore Offshore
Huanghai Sea Huanghai Sea stations stations
Turbidity (NTU)
cchl a (mg·m−3 )KPAR (m−1 )

1.699
0.158
0.259

0.692
0.262
0.241

1.481
0.260
0.333

0.906
0.210
0.244

Huanghai Sea, we calculated the value of KPAR every
0.5 meters using measured downwelling planar PAR.
The calculation shows a relatively large KPAR in theupper layer and low KPAR in the lower layer (Fig.5),
which can be confirmed in both inshore stations (Fig.

5a) and offshore stations (Fig. 5b). More specifically,
KPAR has a maximum value of 0.5–0.7 m−1 in thesurface, decreases sharply to a value of 0.3 m−1 in theupper few meters between 1 and 5 m. Under the depthof 5 m, it decreases gradually to a low value of 0.2 m−1 .
The mean vertical profile of KPAR (Fig. 6), which
was obtained by averaging the KPAR shown in Fig. 5
at the same depth over all the stations, can be approximately expressed by an exponential function between
KPAR and depth (D) as equation (5).
KPAR = 0.352exp(0.026 × D),

R2 = 0.95

Fig.5. The diffuse attenuation coefficients KPAR (m−1 ) versus depth (m) at (a) inshore stations and (b)offshore stations in the Huanghai Sea.

(5)

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that is determined by the calculated depth-dependent
KPAR at each station.
According to Fig. 7, depth-averaged KPAR has
good positive correlation with turbidity with a credible degree of 95% and the correlation coefficient R2 is
0.68. The linear relationship is expressed as,
KPAR = 0.142 × T + 0.07

Fig.6. The averaged diffuse attenuation coefficients KPAR as a function of depth for theentire area. (dot represents measured value;line represents regressive value).

3.3 Depth-averaged KPAR versus depth averaged cchl a and turbidity
Although we can not obtained a correlation between depth-dependent KPAR and Cchl a or turbidity, we find a really good correlation between depthaveraged KPAR and depth-averaged turbidity (Fig. 7).
The values were averaged in the whole euphotic zone

R2 = 0.68(6)(6)

Where T is the value of turbidity, ranging from 0.48
to 2.5 NTU.
According to the measurements, there were essentially two types of turbidity profiles in the watercolumn. The first was that turbidity showed a uniform value in the vertical, such as at stations G17,
G21, G23 and Gp, and the second was that turbidity
was uniform in the upper few meters and increased
with depth to the bottom layer, such as at stations
A112, A213 and G12. We made liner regression between KPAR and turbidity in the two different areas.
The results were that:
KPAR = 0.11 × T + 0.07

R2 = 0.83(7)which applied to the first area. And
KPAR = 4.31 × T + 0.11

R2 = 0.8(8)which applied to the second area.

Fig.7. The linear relationship (a) between KPAR and chl-a (mg·m−3 ) and (b) between KPAR and turbidity(NTU).

The two correlation coefficients R2 were both
higher than that in equation (6), which implied that it
is more precise to divide the Huanghai sea according

to the turbidity profiles in the water column.
Usually, phytoplankton is also an important factor affecting light attenuation. In Fig. 7, however,

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Lin Shaoying et al. Acta Oceanologica Sinica 2009, Vol. 28, No.5, P.66-75

there is no apparent correlation between KPAR andchl a, indicating that phytoplankton was not the major factor affecting light attenuation during our cruise
period.
To consider the contribution of both chl a andturbidity to light attenuation with one equation, we
conducted a multiple regression of KPAR with chl aand turbidity. The depth-averaged KPAR is expressed
as,

KPAR = Kw + Kcchl a × [Cchl a ] + Kt × T(9)where Kw is the attenuation part due to water plus
CDOM. Based on all the measurements of our survey,
the regression of depth-averaged KPAR against depthaveraged chlorophyll a and depth-averaged turbidity

yields (with a credible degree of 95%),
KPAR = 0.03 + 0.13C chl a [Cchl a ] + 0.23T
R2 = 0.89(10)Where chl a and T have the units of mg·m−3 and NTU,
respectively.
According to equation (10), the specific coefficientof turbidity is much larger than that of chlorophylla, suggesting a possibility that the light attenuation
effect of SPM is more important than that of phytoplankton in the Huanghai Sea. To examine this possibility, we substituted depth-averaged turbidity anddepth-averaged chl a observed at all the stations into
equation (10). The ratio of KPAR due to chl a is among
0.05-0.21 while the ratio of KPAR due to turbidity is
0.62-0.86 (Fig. 8). Clearly, the attenuation of light
was influenced more by SPM than by chlorophyll a.

Fig.8. The relative contributions of chlorophyll a (a) and turbidity (b) to KPAR .

In order to further verify equation (10), we applied it to the data in the Huanghai Sea from anothercruise in spring, the third cruise of China SOLAS from17 to 30 on April 2006 (Table 3). The survey was

Table 3. Diffuse attenuation coefficients KOPAR and KTPAR at 10 stations in the Huanghai Sea, computed by theobserved data and equation (10), respectively. The Turbidity and chl a data were obtained from the third cruise of China
SOLAS from 17 to 30 April 2006.
Station
A1
A2
G10
G25
G26
G27
G28
G34
G37
G40

chl a
(mg·m−3 )
1.181
0.318
0.438
0.515
0.604
0.375
0.689
0.251
0.256
0.304

Turbidity
(NTU)
0.789
0.913
0.531
0.93
0.499
1.346
0.281
0.835
1.289
0.651

KOPAR
(m−1 )
0.341
0.285
0.214
0.271
0.25
0.375
0.221
0.289
0.333
0.253

KTPAR
(m−1 )
0.359
0.278
0.206
0.306
0.219
0.383
0.181
0.251
0.355
0.216

∆
0.053
0.025
0.037
0.129
0.124
0.021
0.181
0.131
0.066
0.146

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carried out in an area from 121◦ E to 124◦ E and 32.5◦ N
to 39◦ N and observations were conducted at 45 stations (locations were not shown here). At all the stations, CTD measurements were similarly performed
with those in the first cruise, including conductivity,
temperature, pressure, downwelling planar irradance,
chlorophyll a concentration and turbidity. The relative error ∆ is calculated by equation (11), in which
KOPAR denotes the values calculated from observed
PAR data on April 2006 and KTPAR calculated byequation (10) with the simultaneously observed dataof turbidity and chl a.
∆ = |KOPAR − KTPAR |/KOPAR(11)

As shown in Table 3, the value of ∆ was within
20% at most stations. Therefore, we conclude that
equation (10) is able to estimate reasonably the vertical attenuation of irradiance in the turbid HuanghaiSea, at least works well for spring.
4 Summary and conclusion
Up to now, KPAR used in many marine ecosystem models is usually expressed as a linear functionof the concentration of chlorophyll a (Megard et al.,
1980; Morel, 1988; Radach et al., 1993) or phytoplankton biomass and detritus (Mcgillicuddy, 1995; Wong etal., 1995). Varela et al. (1992) has proposed an equation of KPAR for a study of deep-chlorophyll maximum
and suggested that the extinction of light is not only
affected by pure water and chlorophyll a but also byother factors that could be related to the chlorophylla or other particles, but still not explicitly include theeffects of SPM. In most Chinese coastal waters suchas the Bohai Sea, Huanghai Sea and East China Sea,in addition to the large amount of terrestrial input of
sediments from Yellow River and Changjiang, the resuspension of sediments due to strong tidal currents
and strong winds in shallow shelf also maintain thehigh concentrations of SPM. However, SPM concentration is not easily measured by normal marine observational instruments, turbidity is though to be areasonable alternate parameter which can be easily
obtained by multi functional CTD or water quality
monitor, and it also has good correlation with SPM incoastal waters (Jones and Wills, 1965; Su et al., 2001).
Based on the observations in early spring in the
Huanghai Sea, we presented a function for the attenuation of PAR by turbidity and chl a. The results
suggested that SPM affects more on light attenuation
than phytoplankton. The direct cause for this conclusion is that the concentration of suspended particles

is high during the observations. Since our equation
has been verified by independent data from anothercruise in the Huanghai Sea, the conclusion that SPM
plays an important role in light attenuation in spring
looks reasonable. An extension of this conclusion isthat any ecosystem model for the Huanghai Sea needs
to consider the influence of SPM on light attenuation.
Like any studies based on field measurements, thedata used in this study was unavoidably limited interms of time and space. For example, our stations
are biased to Chinese side of the Huanghai Sea and it
could be therefore to obtain a little different result for
the Korea side of the Huanghai Sea. In addition, theturbidity and chl a in the Huanghai Sea vary significantly from season to season (Qin et al., 1989; Sun etal., 2000). Finally, KPAR has a close relation with thesolar zenith angle (Gordon, 1989; Kirk, 1991) that we
did not consider. All of these factors suggest the necessity of further efforts to parameterize the relation of
KPAR with turbidity, chl a and other water properties
in the turbid Huanghai Sea.
Acknowledgements
We wish to thank the scientists and staff on board
R/V Dongfanghong II for their assistance on observation campaign. We thank two anonymous reviewers
whose comments and suggestions resulted in substantial improvement to this paper.
References
Anning T, MacIntyre H L, Pratt S M, et al. 2000. Photoacclimation in the marine diatom skeletonema
costatum. Limnol Oceanogr, 45: 1807–1817
Arrigo K R, Sullivan C W. 1994. A high resolution
bio-optical model of microalgal growth: Tests using
sea ice algal community time series data. Limnol
Oceanogr, 39: 609–631
Cullen J J, Lewis M R. 1988. The kinetics of algal photoadaptation in the context of vertical mixing. J
Plankton Res, 10: 1039–1063
Dieguez M C, Gilbert J J. 2003. Predation by Buenoa
macrotibialis (Insecta, Hemiptera) on zooplankton:
effect of light on selection and consumption of prey.
J Plankton Res, 7: 759–769
Falkowski P G, Raven J A. 1997. Aquatic Photosynthesis. Blackwell Science, Massachusetts, 500
Fisher T R, Gustafson A B, Radcliffe G M, et al. 2003.
A long-term record of photosynthetically available
radiation (PAR) and total solar energy at 38.60
degrees N, 78.2 degrees W. Estuaries, 26 (6): 1450–
1460
Fisher T R, Gustafson A B, Sellner K, et al. 1999. Spatial and temproral variation of resource limitation in
Chesapeake Bay. Mar Biol, 133 (4): 763–778

Lin Shaoying et al. Acta Oceanologica Sinica 2009, Vol. 28, No.5, P.66-75

Gallegos C L, Correll D L, Pierce J W. 1990. Modeling spectral diffuse attenuation, absorption andscattering coefficients in a turbid estuary. Limnol
Oceanogr, 35: 1486–1582
Gallegos C L, Moore K A. 2000. Factors contributing to water-column light attenuation, pp.16-27. In
Batiuk, R A et al. [eds.], Chesapeake Bay submerged
aquatic vegetation water quality and habitat-based
requirements and restoration targets:A second technical synthesis.US EPA, Chesapeake Bay Program,
Annapolis, MD. 106
Gordon H R. 1989. Can the Lambert-Beer law be applied
to the diffuse attenuation coefficient of ocean water?
Limnol Oceanogr, 34: 1389–1409
Graham B P, Wong A Y C, Forsythe I D. 2001. A computational model of synaptic transmission at thecalyx of Held. Neurocomputing, 38: 37–42
Jones D, Wills M S. 1965. The attenuation of light in sea
and estuarine waters in relation to the concentrationof suspended solid matter. J Mar Biol Assoc U K,
35: 431–444
Jones K J, Gowen R J. 1990. Influence of stratificationand irradiance regime on summer phytoplankton
composition in coastal and shelf seas of the British
Isles. Estuar Coast Shelf Sci, 30: 557–567
Kirk J T O. 1991. Volume scattering function, average cosine, and the underwater light field. Limnol
Oceangr, 36: 455–467
Kirk J T O. 1994. Light and Photosynthesis in Aquatic
Ecosystems. Cambridge University Press, Cambridge, 400
Lee Z P, Du K P, Arnone R. 2005.
A modelfor the diffuse attenuation coefficient of downwelling irradiance. J Geophys Res,110, C02016,
doi:10.1029/2004JC002275
Loukos H, Frost B, Harrison D E, et al. 1997. An ecosystem model with iron limitation of primary production in the equatorial Pacific at 140◦ W. Deep-Sea
Res. II, 44: 2221–2249
McGillicuddy D J. 1995. One dimensional numericalsimulation of new primary production:Lagrangianand Eulerian formulations. J Plankton Res, 17(2):405–412McMahon T G, Raine R C T, Fast T, et al. 1992. Phytoplankton biomass, light attenuation and mixing in
the Shannon Estuary, Ireland. J Mar Biol Assoc U
K, 72 (3): 709–720
Megard R O, Seles J C, Boyer H A, et al. 1980. Light,
Secchi disks, and trophic states. Limnol Oceanogr,
25: 373–377
Morel A. 1988. Optical modeling of the upper ocean
in relation to its biogenous matter content (case 1
waters). J Geophys Res, 93:10749–10768
Pang C G, Wang F, Bai X Z, et al. 2003. Distribution
features of suspended matter and amount of sediment at the changing estuary and adjacent area.
Mar Sci, 12: 31–35.

75

Platt T, Sathyendranath S. 1988. Oceanic primary production: estimation by remote sensing at local andregional scales. Science, 241: 1613–1620
Pu Yongxiu, Huang Weiliang, Xu JianPing. 2002. The
spreading direction change of the Changjiang River
diluted water in 710 days. Donghai Marine Science(in Chinese). 20:1–5
Qin Yunshan, Li Fan, Xu Shanmin. 1989. Suspended
matter in the South Huanghai Sea. Oceano. Et
Limno Sinica, 20:101–111
Radach G, Moll A. 1993. Estimation of the variabilityof production by simulating annual cycles of phytoplankton in the central North Sea. Prog Oceanogr,
31: 339–419
Rijstenbil, J W. 1987. Phytoplankton composition ofstagnant and tidal ecosystems in relation to salinity,
nutrients, light and turbulence. Neth J Sea Res, 21:
113–123
Smith W O. 1982. The relative importance of chlorophyll,
dissolved and particulate material, and seawater tothe vertical extinction of light. Estuar coast Shelf
Sci, 15: 459–465
Su Jian, Jiang Wensheng, Sun Wenxin. 2001. Analysis
of SPM data obtained in ocean investigation in the
Bohai Sea. Journal of Ocean University of Qingdao(in Chinese), 31(5): 647–652
Su Jilan, Yuan Yeli. 2005. Hydrography of China seas(inChinese). Beijing: Ocean Press, 367
Sun Xiaogong, Fang Ming, Huang Wei. 2000. Spatial andtemporal variations in suspended particulate mattertransport on the Yellow and East China Sea Shelf.
Oceanologia et Limnologia Sinica(in Chinese), 31:
581–587
Varela R A, Cruzado A, Tintore J. 1992. Modelingthe deep-chlorophyll maximum: A couple physicalbiological approach. J Mar Res, 50: 441–463
Wang M, Lyzenga D R, Klemas V V. 1996. Measurement of optical properties in the Delaware Estuary.
J Coast Res, 12 (1): 211–228
Wang Q, Guo X Y, Takeoka H. 2008. Seasonal variations of the Yellow River plume in the Bohai
Sea: A model study. J Geophys Res, 113, C08046,
doi:10.1029/2007JC004555
Wong C S, Whitney F A, Iseki K, et al. 1995. Analysis of trends in primary production and chlorophyll a over two decades at Ocean Station P (50◦ N,
145◦ W) in the subarctic North-east Pacific Ocean,
R.J. Beamish, Climate change and northern fish
populations, Can. Spec. Publ. Fish. Aquat. Sci,
121: 107–117
Zhang Yunlin, Qin Boqiang, Chen Weimin. 2003. Regression analysis of beam attenuation coefficient underwater in Lake Taihu. Oceanologia et Limnologia
Sinica (in Chinese), 34: 209–213
Zhu Jianrong, Xiao Chenyou, Shen Huanting. 1998. The
impact of Huanghai Sea cold water mass on the expansion of the Changjiang diluted water. Oceanologia et Limnologia Sinica(in Chinese), 29: 398–394