Marine Pollution Bulletin 144 (2019) 265–274

Contents lists available at ScienceDirect

Marine Pollution Bulletinjournal homepage: www.elsevier.com/locate/marpolbul

On relaxation of the inﬂuences of treated sewage eﬄuent on an adjacent
seaweed farm in a tidal straitT⁎

Xu Zhanga, , Yusuke Uchiyamaa,b, Akihiko NakayamacaDepartment of Civil Engineering, Kobe University, Kobe, Japan
Coastal and Estuarine Environmental Department, Port and Airport Research Institute, Yokosuka, Japanc
Department of Environmental Engineering, Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysiab

A R T I C LE I N FO

A B S T R A C T

Keywords:
Treated wastewater eﬄuent
Alternative operation
Coastal dispersal
Transient eﬄuent ﬂux
Tidal strait
ROMS

An Eulerian passive tracer model coupled with a quadruple-nested 3D circulation model was used to assess thecoastal dispersal of treated wastewater eﬄuent from a sewage treatment plant and the associated impacts on an
adjacent seaweed farm using three diﬀerent operational scenarios. When the discharged volume and source
eﬄuent ﬂuxes were decreased by ~16.7%, the accumulated eﬄuent in the farm was reduced by ~25.4%. A
tracer ﬂux budget analysis revealed the apparent predominance of the transient component that accounts for the
nonlinear interactions primarily from tidal currents and eddies. The transient ﬂux promoted the eﬄuent inﬂux toimpede eﬄuent accumulation in the farm, whereas the mean ﬂux contributed to the outgoing ﬂux. A source ﬂux
reduction caused a remarkable decrease in the transient ﬂux and thus an even greater eﬄuent accumulation
reduction. In turn, a modiﬁed source density scenario without total eﬄuent volume change did not work as
expected.

1. Introduction
Osaka Bay is located in the northeastern area of the Seto Inland Sea(SIS), Japan, that is the largest estuary in the nation and forms a typical‘basin-strait’ system. Osaka Bay consists of a shallow inner bay and a
deep channel that is connected with the neighboring two sub-basins,
Harima Sea and Kii Channel, by the narrow Akashi and Kitan straits(Fig. 1). The subtidal residual circulations in the SIS and Osaka Bay
primarily occur in the clockwise direction under substantial remoteinﬂuences from the Kuroshio drifting eastward oﬀ the Kii Channel andits occasional intrusions into the SIS (Takeoka et al., 1993; Tada et al.,2018) and meandering of the Kuroshio path (e.g., Kawabe, 1987,
1995). Concurrently, strong tidal currents bring water back and forth to
Osaka Bay through the straits at a maximum speed of 3 m s−1 throughthe Akashi Strait (Fujiwara et al., 1994). In this type of basin-strait
system, the water is well mixed near the straits, while it is stratiﬁed in
the inner basins (e.g., Guo et al., 2004; Chang et al., 2009). ‘Red tides’
are an indicator of harmful algal blooms followed by hypoxia. Historically, these have occurred quite frequently in Osaka Bay mostly
during the boreal summer and fall, resulting in serious water quality
deteriorations that damage the aquaculture and marine ecosystem (e.g.,
Imai et al., 2006; Terawaki et al., 2003). Accordingly, several ecologicalshifts have been reported to occur in this densely populated region⁎(Irizuki et al., 2018). A series of environmental preservation policies
and laws have been enacted to limit the total amount of nutrients intreated wastewater eﬄuents. These measures have adequately succeeded in improving the water quality in recent years in the SIS (Tomita
et al., 2016). However, Osaka Bay still suﬀers from severe water pollution due to a vast amount of sewage from the densely populated
hinterland.
The Tarumi Sewage Treatment Plant (TSTP) is one of the largest
wastewater treatment plants in Osaka Bay, collocated with the second
largest productive seaweed farm in the nation. The local farmers association continually claims that the treated wastewater eﬄuent derived from the TSTP may result in severe reductions in the quality andproduction of the seaweed farm located next to the TSTP. To alleviatepossible undesirable TSTP inﬂuences on the local aquaculture, the Cityof Kobe Sanitation Bureau (hereafter KSB), the local government, hasconstructed an alternative western diversion outfall (Fig. 1c; indicatedby “W”) 500 m away from the original TSTP central outfall (Fig. 1c,“C”). The TSTP has thereby conducted seasonal diversions from October
to December when the seaweed spores are the most sensitive to theambient marine environment.
In our previous study (Uchiyama et al., 2018a), we conducted aquantitative assessment of the impacts of the western diversion discharge relative to the hypothetical central outfall discharge in the fall

Corresponding author.
E-mail address: 167t142t@stu.kobe-u.ac.jp (X. Zhang).

https://doi.org/10.1016/j.marpolbul.2019.04.050
Received 19 February 2019; Received in revised form 11 April 2019; Accepted 19 April 2019
Available online 16 May 20190025-326X/ © 2019 Elsevier Ltd. All rights reserved.

Marine Pollution Bulletin 144 (2019) 265–274

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Fig. 1. Quadruple-nested JCOPE2-ROMS model domains and bathymetry (color: m). (a) The ROMS-L1, L2 (white boxes), L3, and L4 domains (red boxes) embeddedin the JCOPE2 domain (outside of the perimeter of the L1). The gray contours are the isobaths with 1000 m intervals, while the red contours indicate the approximate
Kuroshio region with the surface velocity magnitudes > 0.5 m s−1 at 0.2 m s−1 intervals. (b) The enlarged region around Osaka Bay including the ROMS-L3 and L4
domains (red boxes). (c) The entire L4 domain with isobaths at 15 m intervals. The blue box is the approximate extent of the seaweed farm area of interest; TFP is the
Tarumi Fishery Port; the red star shows the location of the Tarumi Sewage Treatment Plant (TSTP); the red dots are the two outfalls (W: western diversion outfall, C:
central original outfall). (d) Aerial photo around the TSTP from Google map. The seaweed farm (red box), TSTP, and TFP are indicated on the ﬁgure. The local ﬁshingpier (FP) construction is shown by the red circle. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of thisarticle.)asymmetrically with a westward-stretched, coastally trapped shape,leading to the reduction of eﬀective accumulation in the farm. The
high-resolution numerical model used in Uchiyama et al. (2018a)
provided solid explanations for the mechanism behind such nonGaussian distributions and has been validated comprehensively against
in-situ measurements and the observations of Bricker et al. (2006) andcondition based on a 3D numerical ocean circulation model. Uchiyama
et al. (2018a) concluded that the diversion operation successfully decreased the accumulation of the TSTP eﬄuents in the adjacent farm byon average ~28%, while the instantaneous eﬄuent concentration was
reduced to ~50%. The time-averaged horizontal eﬄuent concentration
derived either from the central or western outfall was distributed

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System (ROMS; Shchepetkin and McWilliams, 2005, 2008). The lateralboundary conditions for the outermost ROMS-L1 model were acquired
from the assimilative Japan Coastal Ocean Predictability Experiments(JCOPE2) oceanic reanalysis (Miyazawa et al., 2009). The one-way
oﬄine nesting technique (e.g., Mason et al., 2010; Buijsman et al.,2012; Romero et al., 2013; Uchiyama et al., 2010, 2017a, 2017b,
2017c, 2018b; Kamidaira et al., 2017, 2018) was utilized to successively convey the parent model results into the child models with gridsize reﬁnements (i.e., JCOPE2 at a lateral grid resolution of ~10 km →L1 at 2 km → L2 at 600 m → L3 at 100 m → L4 at 20 m). Thus, the innermost ROMS-L4 model domain was discretized horizontally at 20 m
lateral grid spacing, and vertically into stretched 32 s-layers. The ROMS
conﬁgurations were the same as those in Uchiyama et al. (2018a). For
instance, the L4 model was forced using the surface wind stress datafrom the Japan Meteorological Agency (JMA) Grid-Point Values–MesoScale Model (GPV-MSM; Isoguchi et al., 2010) and the surface heat/
freshwater ﬂuxes from the Comprehensive Ocean-Atmosphere Data Set(COADS; Woodruﬀ et al., 1987). Along the L2 model open boundaries,
the barotropic tides were synthesized from ten constituents acquired
from the TPXO7.0 global reanalysis (Egbert et al., 1994; Egbert andErofeeva, 2002) that spontaneously generated the intrinsic barotropic
and baroclinic tides that were transmitted through the open boundaries
into the L3 and L4 models. Because the seaweed spores are sensitive toboth salinity and nitrate, the impacts of freshwater from the local rivers
are worth considering. Therefore, freshwater discharge from all the
major rivers located in the model domains was also taken into accountas monthly-averaged freshwater volume ﬂuxes. The ROMS-L4 model
was run for approximately 50 days to include October 2015 when theseaweed spores were the most sensitive to the eﬄuent. Table 1 summarizes the detailed numerical conﬁgurations for the ROMS-L1-L4
models. Further details of the model design can be found in Uchiyama
et al. (2018a).

Bricker and Nakayama (2007), as brieﬂy described below. Overall, theeﬄuent is transported due to tidal and subtidal residual currents thatare largely dominant in the coastal area around the TSTP and the adjacent seaweed farm. The tidal currents occur more intensively near theoutfall (the western area of the farm) causing both cross-shore andalong-shore eﬄuent transports, although the subtidal currents are moreinﬂuential leaving westward from the Akashi Strait where the energetic
tidal currents occur. The cross-shore currents are pronouncedly developed more by the tidal oscillations with noticeable inﬂuences from lowfrequency wind stress variations than from the alongshore currents. The
key inﬂuencer on the anisotropic eﬄuent distribution is the subtidal
counterclockwise circulation that brings eﬄuents westward and thensouthward 2–3 km west of the outfall to the oﬀshore.
Even though the diversion operation was numerically assessed suchthat it would function properly in terms of reducing eﬄuent accumulations in the seaweed farm, the farmers are still demanding that the
KSB should further diminish the TSTP inﬂuence with minimal additional costs. Hence, the KSB has proposed two possible alternative operational scenarios using the diversion outfall. The ﬁrst option is simply
to lower the freshwater eﬄuent discharge volume without the nutrient
concentration adjustments (discharged total nutrient load is also lowered proportionally with the eﬄuent volume). The second is to increase
the eﬄuent density by mixing the treated fresh wastewater with theambient saline seawater while retaining the nutrient total mass. Bothoperational scenarios are not only practically plausible, but also scientiﬁcally intriguing to pursue. According to Uchiyama et al. (2018a), it
is presumed that the anisotropic subtidal circulation may invoke nonlinear proportionality between the eﬄuent volume and the resultant
accumulation in the farm during the ﬁrst scenario. By contrast, thesecond scenario is expected to weaken the near-ﬁeld vertical buoyant
plume from the bottom-mounted diﬀusers of the diversion outfall, andthis would presumably alter the vertical distribution of the nutrients atthe source location and subsequent far-ﬁeld lateral dispersal.
Therefore, this study aimed to provide scientiﬁc insights and qualitative guidelines on the alternative discharge operations for reducing
the TSTP inﬂuence on the farm. To this end, we conducted a detailed
numerical assessment based on the high-resolution 3D model developedin Uchiyama et al. (2018a) using the two proposed scenarios. Our 3Dmodel accounts for the driving mechanisms responsible for the present
assessment as realistically as possible. For instance, the model considers
large-scale eﬀects including the remote inﬂuences from the Kuroshiothat determines the eastward residual current in the SIS (so-called the
SIS throughﬂow; Tada et al., 2018), spatiotemporally varying atmospheric forcing (sea surface wind stress, radiation, and heat ﬂuxes),
high-frequency intrinsic variabilities such as barotropic and baroclinic
tides, and freshwater inputs from both precipitation and rivers. The
remainder of the paper is organized as follows. The model design andconﬁgurations for constructing the proposed operational scenarios are
brieﬂy described in Section 2. Section 3 illustrates the near-surface
horizontal hydrodynamic and eﬄuent concentration ﬁelds formed
around the TSTP and the seaweed farm, and a quantitative assessmentof the TSTP inﬂuences on the seaweed farm in the two scenarios isconducted in this section based on an eﬄuent ﬂux budget analysis, withcomparisons to the standard discharge operation with the western diversion outfall. The conclusions are provided in Section 4.

Table 1Model conﬁgurations.
Models

L1

L2

Computational period
3/1/2006–11/31/2015
9/1/2006–11/9/2015
Grid cells
320 × 320 (×32 layers)
800 × 480 (×32 layers)
Horizontal grid
2 km
600 m
resolution
Baroclinic time step
120 s
30 s
Surface wind stress
JMA-MSM (hourly)
JMA-MSM (hourly)
Surface ﬂux
COAMPS bulk formula
COAMPS bulk formula
Boundary/Initial
JCOPE2 (daily)
ROMS-L1 (daily)
condition
T-S nudging
JCOPE2 (10-day averaged)
None
Topography
SRTM30 + JEGG500
SRTM30 + JEGG500
COAMPS: Coupled Ocean/Atmosphere Mesoscale Prediction System (Hodur, 1997)
STRM30: SRTM30_PLUS (Rodriguez et al., 2005; Rodriguez et al., 2006; Becker
et al., 2009)
J-EGG500 (http://www.jodc.go.jp/data_set/jodc/jegg_intro.html)

2. Methods
2.1. The ocean circulation model
We employed a 3D Eulerian passive tracer model with a near-ﬁeld
dilution sub-model (Uchiyama et al., 2014) to compute a 3D dispersalof the buoyant plume representing the eﬄuent derived from the TSTP
western diversion outfall (see Sec. 2.2). The tracer model was driven by
the 3D velocity and eddy diﬀusivity estimated using the innermost childmodel of the quadruple-nested downscaling Regional Oceanic Modeling

Models

L3

L4

Computational period
Grid cells
Horizontal grid resolution
Baroclinic time step
Surface wind stress
Surface ﬂux

9/1/2015–11/9/2015
400 × 400 (×32 layers)
100 m
8.0 s
JMA-MSM (hourly)
COADS (monthly
climatology)
ROMS-L2 (hourly)

9/21/2015–11/9/2015
696 × 400 (×32 layers)
20 m
1.0 s
JMA-MSM (hourly)
COADS (monthly
climatology)
ROMS-L3 (hourly)

None
CDPC

None
CDPC

Boundary/Initialcondition
T-S nudging
Topography

CDPC: Central Disaster Prevention Council, Japan (50 m resolution).
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Table 2
Diﬀerent discharge operations scenarios.

Case 1: baseline
Case 2
Case 3

Sewage volume (m3/d)

Mixing seawater (m3/d)

Salinity (psu)

Density (kg/m3)

1.8 × 105
1.5 × 105
1.8 × 105

None
None
8 × 10400
10.46

997.55997.551005.43

Note: the mean temperature was as that of ambient seawater at 23 °C. The surface salinity and density of the seawater were 34.4 psu and 1023.48 kg m−3, respectively.

the resultant mean density was 1023.48 kg m−3, while the freshwater
density was 997.55 kg m−3.
The two alternative operations proposed by the KSB (Section 1)
were then conﬁgured on the basis of the Case 1 experimental set-up.
The ﬁrst alternative was simply a reduced Qp discharge volume from
1.8 × 105 m3 d−1 to 1.5 × 105 m3 d−1 with the other conditions retained (Case 2: the reduced Qp case). Hence, the Fp source tracer ﬂux
was also lowered at the same reduction rate as the Qp with cs = 1. In thesecond scenario, the eﬄuent density was increased by mixing with
0.8 × 105 m3 d−1 of the ambient seawater to suppress the buoyant
plume from surfacing during the initial dilution (Case 3: the increased
density case). As a consequence, the total Qp discharge rate, the densityof the mixed eﬄuent ρ′, and its salinity S′ were modiﬁed in Case 3 to
Qp = 2.6 × 105 m3 d−1, ρ′ = 1005.43 kg m−3, and S′ = 10.46 psu, respectively. We further modiﬁed the source tracer ﬂux
cs = (1.8 × 105) / (2.6 × 105) ~ 0.69 such that the total tracer loadfrom the TSTP for Case 3 was equal to Case 1, even with the seawater
addition and density alteration. The vertical shape function H was notaltered in all three cases as deﬁned in Section 2.2. The model conﬁgurations for the three cases are summarized in Table 2.

2.2. The sewage eﬄuent model
The 3D sewage eﬄuent oceanic dispersal in the L4 domain wasmodeled as a conservation equation of the non-dimensional Eulerianpassive tracer concentration c with the near-ﬁeld dilution sub-model(Uchiyama et al., 2014, 2018a):∂c+ ∇∙uc = D + P∂t(1)

where the near-ﬁeld dilution is represented as the non-dimensionalsource term, P :P (x , y, z; t ) = Ps (t ) A (x , y ) H (z )(2)where u is the 3D velocity of the ambient ﬂow, D is the diﬀusion term,∇ is the 3D gradient operator, Ps is the tracer ﬂux from the outfall, and
A and H are the non-dimensional spatial plume shape functions above
the bottom-mounted diﬀusers. The shape functions A and H were utilized to represent the source region spatial distribution as shown in thefollowing integral relations:∬ Adxdy = As , ∫ Hdz = Hs

(3)

where As is the horizontal area, Hs is the vertical size, and Vs = As Hs isthe sewage plume volume. Hence, Ps(t) = Qp(t)/Vs, where Qp (t)[m3 s−1] is the volume ﬂux. The dimensional pollutant concentrations
were retrieved using cCp, where Cp is the input pollutant concentration
at the outfall. Note that a similar source term is added to the 3D mass,
momentum, salinity, and temperature conservation equations to account for the near-ﬁeld dilution eﬀects.
The shape functions A and H are described also according to
Uchiyama et al. (2014). A Gaussian distribution model,

3. Results and discussion
3.1. Residual currents
In basin-strait systems, tides are known to be the most inﬂuential
factors to aﬀect currents particularly near straits with intensive ﬂuctuations at relatively small spatiotemporal scales (e.g., Imasato, 1983;
Imasato et al., 1994; Li et al., 2015). The present study area is in alocation where strong tidal currents are generated in the narrow Akashi
Strait that could aﬀect the transport and dispersal of sewage eﬄuentsfrom the TSTP. Strong tidal currents are repeatedly generated at thenarrow Akashi Strait. Fig. 2a shows the surface residual currents in Case
1 estimated for the entire experimental period from September 21st to
October 31st, 2015. Overall, the strong southeastward residual currents
occur and intrude into Osaka Bay through the Akashi Strait. These residual currents involve three major circulations. The largest is aclockwise circulation formed as a part of the well-known ‘Okinose
Circulation’ (e.g., Nakatsuji et al., 1994; Mishima et al., 1999) thatappears as a semi-circle with the origin at approximately (x, y) = (4 km,
0 km). Consistent with the ﬁndings in Imasato (1983), the intermediate
counterclockwise circulation (hereafter termed the ‘Tarumi Recirculation’) develops with the prominent westward alongshore current near
the TSTP. The smallest local recirculation is instigated oﬀ the northerncoast of the Akashi Strait. The two counter-rotating larger circulations
converge at around (x, y) = (4 km, 4 km) and develop into the intensive
southeastward current. In turn, the strongest northwestward current
occurs along the northern coast of Awaji Island and then veers clockwise at two locations in the Akashi Strait to form two clockwise circulations including the Okinose Circulation. As was reported in
Uchiyama et al. (2018a), the Tarumi Recirculation is substantially important for promoting the mean westward transport of eﬄuent from the
TSTP that is ultimately responsible for reducing eﬄuent accumulationsin the seaweed farm using the diversion operation.
It is worth mentioning that the velocity vectors in Fig. 2a are2(z − z s ) ⎤H (z ) = exp ⎡−
⎥
⎢
ds2
⎦
⎣

(4)

was used for the vertical function H, where zs is the plume center
height, and ds is the vertical scale of the plume. We deﬁned zs = 0 m
and ds = 7 m as the buoyant eﬄuent was released from the bottommounted diﬀusers of the TSTP diversion outfall at a mean depth of 7 m.
This depth is shallower than the local mixed layer depth, and thus thereleased buoyant eﬄuent immediately reaches the surface, regardlessof choice of the shape functions and model parameters. The outfall was
represented by two grid points with a footprint of 20 m × 40 m, whereA = 0.5, centered 40 m oﬀshore from the TSTP sea wall, approximately
corresponding to the actual diversion outfall design.
2.3. The standard and two alternative operation scenarios
The sewage eﬄuent was applied to the coastal area near the TSTP as
a bottom-released freshwater plume at the volume rate of Qp with aprescribed concentration of c = cs, yielding a source tracer ﬂux at theoutfall of Fp = csQp. The discharged hypothetical passive tracer was set
to unity (cs = 1) with the temperature of the ambient seawater, unlessotherwise stated. For the standard diversion operation (Case 1: thebaseline case), a constant volume rate Qp = 1.8 × 105 m3 d−1 and zerosalinity were imposed. The mean seawater surface temperature andsalinity near the outfall were 23.0 °C and 34.4 psu. Hence, at 23.0 °C,
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Fig. 3. (a) Time-averaged passive tracer concentration, c (color, non-dimensional) at the surface for the baseline case (Case 1). The black contours denotethe sea surface density at 0.02 kg m−3 intervals. (b) The diﬀerences in c (color,
non-dimensional) and density (contours) between Case 2 and Case 1 (Case2 − Case 1). The red and blue contours are positive and negative values (intervals: 0.001 kg m−3). (c) Same as (b), but for Case 3 − Case 1. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to
the web version of this article.)

Fig. 2. (a) Time-averaged surface velocity vectors (white arrows) on their own
magnitude (color). (b) Same as (a) but for the enlarged region shown by the red
dotted box (z1) in Fig. 2a. The location of the ﬁshing pier (FP) construction isshown by the red circle. (c) Same as (a) but for the enlarged region shown by
the red dotted box (z2) in Fig. 2a. The red solid box shows the seaweed farmarea. (For interpretation of the references to color in this ﬁgure legend, thereader is referred to the web version of this article.)

3.2. Time-averaged density and eﬄuent concentrations
subsampled every 20 grids, resulting in lack of the detailed ﬂow
structures that should be observable in the ROMS-L4 model outcome
with a lateral grid resolution of 20 m. Two selected enlarged regions
shown in Fig. 2b-c demonstrate the inﬂuences of man-made marine
constructions in the red dotted boxes labeled with z1 and z2 in Fig. 2a,
where the velocity vectors were then subsampled every 5 grids. We now
see the complex residual current ﬁeld around the foundation of aﬁshing pier (indicated as “FP” in Fig. 1d) in Fig. 2b. The pier has signiﬁcant eﬀects on the local residual currents, where zonal divergenceoccurs with obvious opposing eastward ﬂows in the downstream region. The southward transport is formed locally near the pier crossing
the northern perimeter of the seaweed farm depicted by the red line. On
the western area of the TSTP, the Tarumi Fishery Port (“TFP” in Fig. 1d)breakwater provokes a bifurcation of the westward coastal residual
current with noticeable velocity weakening, southward veering, and atiny local clockwise recirculation along the southern side (Fig. 2c).

As the seaweed is cultivated near the surface for adequate photosynthesis conditions (Abowei and Ezekiel, 2013), we primarily investigated the eﬄuent transport in the upper ocean, albeit its substantial 3D behavior crucial to its accumulation in the seaweed farm
(Section 3.4). Fig. 3 shows the time-averaged non-dimensional tracer(eﬄuent) concentration c (color) and the seawater density (contours) at
the surface from September 21st to October 31st, 2015. The top panel
corresponds to Case 1 (the baseline case with Qp = 1.8 × 105 m3 d−1),while the other two panels represent the deviations for Case 2 (reduced
Qp = 1.5 × 105 m3 d−1, middle) and Case 3 (increased density,
bottom), where the deviations are deﬁned as (Case 2 − Case 1) and(Case 3 − Case 1), respectively. Consistent with the residual current
ﬁeld (Fig. 2a), for the baseline case shown in Fig. 3a, the mean eﬄuent
concentration c is mostly distributed in the alongshore direction near
the TSTP with a pronounced westward bias and suppressed cross-shore
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X. Zhang, et al.

transport. Similar to the c distribution, slight decreases in the surface
density occur because of the fresh eﬄuent discharge from the diversion
outfall. Another density decrease is observed in the northeastern area ofthe seaweed farm, and is attributed to both the fresh eﬄuent and toremote inﬂuences from major river mouths located in the inner Osaka
Bay ~30 km east of the study area (see also Uchiyama et al., 2018a).
The eﬄuent concentration and density surface deviations observedfor Case 2 are generally consistent although with opposite signs(Fig. 3b). The surface density ρ slightly increases around the TSTP due
to the reduced fresh eﬄuent, while c is diminished. Noticeable modiﬁcations in ρ and c are observed only within ~2 km from shore,
whereas they extend to the western area of the seaweed farm. Density
deviations could dynamically alter the local ﬂow ﬁeld due to buoyancy
eﬀects that may further aﬀect the tracer transport, in addition to the
reduced tracer ﬂux at the outfall. In Section 4, the tracer budget analysis to quantify the eﬀects of the reduced tracer ﬂux Fp at the outfall on
the seaweed farm is presented. By contrast, the adjusted eﬄuent density with the unchanged total tracer ﬂux (Case 3) does not result in
obvious changes in ρ and c, particularly at the seaweed farm, except forthe source area (Fig. 3c). We expected for Case 3 that the suppressedsurface c from the density change could cause a decrease in the nearsurface c transport to the farm, whereas this may not be the case in thepresent situation where the outfall is located in a very shallow area at
7 m deep. Section 4 also quantiﬁes the eﬀects of the adjusted densitychanges in the eﬄuent accumulation in the farm.

Table 3Cumulative non-dimensional tracer ﬂuxes in the seaweed farm, Qfarm (m3).
Up to Oct. 3rd

where un is the velocity perpendicular to the cross-section, and τ is time.
Because c is a non-dimensional concentration, F has the unit of m3 s−1.
Then, we integrate F over a given time period to evaluate the cumulative tracer ﬂux Q (m3) for the duration from τ = 0 to t as follows:

Q (t ) =t∫0 F (τ ) dτ

(6)3

cumulative tracer (m )where the incoming cumulative tracer ﬂuxes into the farm are deﬁned
as positive at each of the four sections surrounding the farm as represented by blue lines in Fig. 1c. Hence, the sum of Q at the four
vertical cross-sections identiﬁes the net tracer (eﬄuent) ﬂux Qfarm accumulated in the seaweed farm, i.e., Qfarm = Qw + Qn + Qe + Qs, where
Qw, Qn, Qe, and Qs are the cumulative ﬂuxes Q (t) through the western,northern, eastern, and southern sections, respectively. To distinguish
Qfarm for the three cases, we denote the net ﬂux as Q1, Q2, and Q3 for
Qfarm for Cases 1, 2, and 3.
Fig. 4a shows the net cumulative tracer temporal variability in theseaweed farm for the three cases. As time progressed from the initial

8

x 10

(a)

4

Q

6

1

Q

2

Q

1

x 10

2

(b)
ΔQ

21

ΔQ

31

-1

0

-2
21/Sep1/Oct

11/Oct21/Oct-2
31/Oct 21/Sep

1/Oct

4

5.49 × 10
4.15 × 104
5.22 × 104−1.34 × 104−0.27 × 104

Average
2.01 × 104
1.50 × 104
1.98 × 104−0.51 × 104−0.03 × 104

The counterclockwise residual Tarumi Recirculation formed oﬀ the
TSTP (Fig. 2a) is anticipated to contribute to a 25.4% reduction in theeﬄuent accumulation in the farm due to the 16.7% decrease in the
input ﬂux. However, as long as the residual current ﬁeld is not alteredby the reduced fresh eﬄuent ﬂux from the outfall, the nonlinear

04

3.67 × 10
2.78 × 104
3.66 × 104−0.89 × 104−0.01 × 104

Up to Oct. 31th

3.4. Eﬀects of the mean and transient ﬂow components on the tracer ﬂuxes

4

3

4

state with no eﬄuent, the released eﬄuent from the TSTP gradually
accumulates in the farm, with apparent tidal and subtidal variabilities
in all three cases. Q1 and Q3 have similar ﬂuctuations, although Q2
deviates from the others later in the experiments. The result is consistent with the time-averaged surface tracer concentrations shown in
Fig. 3, whereas c is signiﬁcantly reduced in Case 2. Nevertheless, theincreased eﬄuent density in Case 3 does not appreciably inﬂuence the
eﬄuent accumulation in the farm. Fig. 4b shows the Qfarm diﬀerences ofCases 2 and 3 from Q1, in which we denote ΔQ21 = Q2 − Q1 and
ΔQ31 = Q3 − Q1. The diﬀerences clearly indicate that the net tracer
accumulation is signiﬁcantly diminished in Case 2 (ΔQ21 < 0), while
the reduction in Case 3 is subtle (ΔQ31 ~ 0). The results are quantitatively summarized in Table 3 for three selected durations from Sept. 21
and their time averages over the experimental period. The averaged net
cumulative tracers are determined to be 2.01 × 104 m3, 1.50 × 104 m3,
and 1.98 × 104 m3 for Cases 1–3, respectively. The density change inCase 3 is again conﬁrmed to scarcely alter the eﬄuent accumulation.
However, the released ﬂux reduction of 16.7% (1.8 × 105
m3d−1→ 1.5 × 105 m3d−1) at the diversion outfall in Case 2 results in a
25.4% reduction (2.01 × 104 m3→ 1.50 × 104 m3) in the eﬄuent accumulation in the farm relative to Case 1. These results ﬁrmly indicatethat the complicated currents and associated dispersal near the TSTP
have nonlinear inﬂuences on total tracers released at the outfall. As
shown in Fig. 4a, the Qfarm (Q1, Q2, and Q3) variability is dominated by
low-frequency subtidal ﬂuctuations that yield Qfarm peaks on October 3,
17, and 21, thus occurs at a period of ~14 days. This periodic behavior
indicates that intrusion of the sewage eﬄuent into the seaweed farmoccurs mainly at a spring–neap tidal cycle. Consistent with the mean
accumulations, Table 3 shows that the Qfarm peaks for these three days
are 1.84 × 104 m3, 3.67 × 104 m3, and 5.49 × 104 m3 for Case 1,
1.60 × 104 m3, 2.78 × 104 m3, and 4.15 × 104 m3 for Case 2, and1.85 × 104 m3, 3.66 × 104 m3, and 5.22 × 104 m3 for Case 3. In summary, the decreased source ﬂux in Case 2 is more eﬃcient than expected for reducing the eﬄuent in the farm, whereas the densitychanges in Case 3 are not very eﬃcient in the present conﬁguration.

(5)cUp to Oct. 17th

Note: ΔQ21 = Q2 − Q1, ΔQ31 = Q3 − Q1.

A quantitative eﬄuent tracer budget analysis is carried out toevaluate the direct impacts of the TSTP on the seaweed farm for thethree cases. Considering a vertical section surrounding the farm with anarbitrary cross-sectional area of Ac, the instantaneous tracer ﬂux F
crossing the section is calculated with

∫A cun dAc

1.84 × 10
1.60 × 104
1.85 × 104−0.24 × 104
0.1 × 104

Q1
Q2
Q3
ΔQ21
ΔQ31

3.3. Eﬄuent ﬂux budget analysis

F (τ ) =4

11/Oct270

21/Oct31/OctFig. 4. (a) Time series of the temporally cumulative net tracer ﬂuxes stored in the seaweedfarm area, Qfarm (m3). The black, red and green
curves show Q1, Q2 and Q3 for Cases 1, 2, and 3,
respectively. Note that Q1 nearly coincides with
Q3. (b) The temporal changes in the Qfarm (m3)
diﬀerences for each case. The black curve ΔQ21
is for Case 2 − Case 1, while the red curve ΔQ31
is for Case 3 − Case 1. (For interpretation of thereferences to color in this ﬁgure legend, thereader is referred to the web version of this article.)Marine Pollution Bulletin 144 (2019) 265–274

X. Zhang, et al.

Fig. 5. Cross-sectional distributions of (a) the time-averaged ﬂux cun (m3 h−1), (c) the mean linear component c un (m3 h−1), and (e) the transient ﬂow component
c′un′ (m3 h−1) at the northern boundary of the seaweed farm for Case 2, (b), (d) and (f) show the diﬀerence of cun c un and c′un′ between Case 2 and Case 1 (Case2 − Case 1). The black contours denote 0.

principally depicts the cross-shore tracer transport, where the positiveﬂux denotes the incoming ﬂux into the farm. The total ﬂux cun isgenerally positive, indicating an overall southward intrusion of the
TSTP-derived eﬄuent into the farm. In particular, this occurs in thewestern area ~3 km from the northwestern corner of the farm (Fig. 5a,warm color), even though the westward residual current is formed as apart of the counter-clockwise circulation in this location (Fig. 2a). An
observable opposing outgoing ﬂux occurs locally around the middle
part of the northern section (cold color) that is most likely caused by theinﬂuences from the ﬁshing pier (Fig. 2b). The reduced source tracer ﬂux
in Case 2 successfully causes an overall reduction in the incoming ﬂux
cun (Fig. 5b). The decomposed ﬂux components (Fig. 5c, e) and theirdiﬀerences from those in Case 1 (Fig. 5d, f) demonstrate the striking
predominance of the transient component c′un′ over the mean component c un . The mean component is slightly negative because of theoutgoing northward residual currents formed along the northern section (e.g., Fig. 2b). Nevertheless, the nonlinear transient ﬂux plays adominant role in the overall incoming ﬂux and its reduction associatedwith the decreased source ﬂux in Case 2 (Fig. 5e, f). The superiority ofthe transient component over the mean component is also observed in
the southern cross-section of the farm, albeit with an outﬂux dominancein that location (not shown). It should be noted that Uchiyama et al.
(2018a) showed that a net eﬄuent accumulation occurs in the alongshore direction with persistent incoming eﬄuent ﬂuxes both along thewestern and eastern sections, while a net reduction occurs in the cross-inﬂuence observed in Case 2 may rarely occur. To examine the possible
mechanism behind the nonlinearity, we introduce a Reynolds decomposition to the prognostic variables for the mean and transient components, in which c = c + c′ and un = un + un′. Therefore, the timeaveraged tracer ﬂux cun is decomposed as

cun = c un + c′ un + cun′ + c′un′ = c un + c′un′(7)

where the overbar denotes an ensemble (time) averaging operator, andthe prime represents the transient component that is the deviation fromthe ensemble mean and explains ﬂuctuations associated mostly witheddies and tides. The ﬁrst term c un on the right hand side represents
the linear interaction of the mean tracer concentration c and residual
currents un , whereas the second term c′un′ denotes the tracer ﬂux associated with the nonlinear interaction of the transient currents un′ with
the instantaneous tracer concentration c′. Note that the high-frequency
turbulent components are included in the transient component, although they are subtle as compared to tidal and subtidal eddy components (Uchiyama et al., 2018a).
Fig. 5 illustrates the cross-sectional distributions of the time-averaged ﬂux cun (m3 h−1, top panels), the mean linear component c un
(middle panels), and the nonlinear transient component c′un′ (bottom
panels) along the northern boundary of the seaweed farm from September 21st to October 31st, 2015. For Case 2 (left column) and thedeviations from those for Case 1 (Case 2 − Case 1, right column). As un
is the velocity component normal to the northern section, Fig. 5
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Fig. 6. Same as Fig. 5, but for the western cross-section of the seaweed farm.

shore direction due to the prevailing outgoing eﬄuent ﬂuxes from thesouthern section.
Fig. 6 is the same as Fig. 5, except that it shows the western crosssection of the seaweed farm. Note that the depicted ﬂuxes are mainly
the alongshore tracer transport as un becomes the normal component in
the western section. The Case 2 time-averaged tracer ﬂux cun (Fig. 6a)shows that the ﬂux of the discharged eﬄuent is largely positive(ﬂowing into the farm represented by warm colors) and occurs more
intensively in the lower layer peaking at around z = −10 m in thenorthern part of the cross-section closer to the TSTP, while it is rather
outgoing near the surface (cold colors). As compared to the baseline
case, Case 2 results in an increased tracer inﬂux near the surface and areduction in the deep layer (Fig. 6b). The contributions from the mean
linear components c un and the transient nonlinear components c′un′(Fig. 6c, e) are completely diﬀerent from those along the northern
section shown in Fig. 5c, e. Both components are similar in magnitude,
but with opposite signs. Although c′un′ is generally positive for inducing
overall incoming tracer ﬂuxes into the farm, c un counteracts to extractthe eﬄuent from the farm. The negative c un is apparently attributed to
the westward residual current in front of the TSTP (Fig. 2a). However,as compared to Case 1, c un enhances the eﬄuent accumulation in thefarm (Fig. 6d), while c′un′ depresses eﬄuent intrusion into the farm(Fig. 6f). The resultant net eﬀects of the reduced source ﬂux at theoutfall (Case 2) are to overall reduce eﬄuent accumulation in the farm(Fig. 6b). By contrast, at the eastern transect, the mean c un leads to anincreased inﬂux, while the transient c′un′ reduces the accumulation inCase 2 relative to Case 1 (not shown). Nevertheless, the eastern section

is located farthest from the outfall and thus the eﬄuent inﬂux along thissection on the net tracer budget was subtle.
The present tracer budget analysis provides important insights into
the assessment of this type of treatment plant operations. Synchronous
observation of the transient currents and eﬄuent concentrations is
crucial for proper ﬂux estimations, yet such observations are laborious.
A simple multiplication of the residual currents and mean concentrations could yield an incorrect eﬄuent ﬂux, where nonlinear interactions
between the transient currents and concentrations generate predominant mean ﬂuxes through their interactions. Moreover, the signiﬁcance of c′un′ arises diﬀerently in the alongshore and cross-shore
eﬄuent transports. The residual counterclockwise circulation thattransports the eﬄuent away from the farm largely aﬀects the seaweedfarm near the TSTP, although the nonlinear transient ﬂux brings more
complexity to the mechanism.
4. Conclusions
A well-validated, multi-nested, high-resolution, synoptic ocean circulation model coupled with a 3D Eulerian passive tracer model(Uchiyama et al., 2014, 2018a) was utilized to assess the impacts ofwastewater eﬄuents in the standard diversion and two alternative
scenarios at the TSTP on an adjacent seaweed farm located near the
narrow Akashi Strait. We discovered that in the reduced ﬂux case (Case2), 16.7% of the wastewater discharge rate decreased from the standard
diversion operation (1.8 × 105 m3 d−1 → 1.5 × 105 m3 d−1) resulted inan overall 25.4% reduction in the sewage eﬄuent accumulating on
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average in the seaweed farm (2.01 × 104 m3 → 1.50 × 104 m3). The
eﬄuent reduction at the farm was more than expected and was not
linearly proportional to the reduced source ﬂux with this particularconﬁguration (Case 2). We need to conduct more model cases to ensure
it in future. In turn, the addition of ambient seawater to the freshwatereﬄuent to adjust the source density (Case 3) did not substantially alter
the eﬄuent accumulation and associated hydrodynamics at the farm
because of the shallow bottom-mounted outfall (~7 m depth). A Reynolds decomposition demonstrated that the transient ﬂux played adominant role over the mean component in the eﬄuent accumulationin the farm, more evidently in the cross-shore transport than thealongshore transport. When the source eﬄuent ﬂux was reduced, thetransient component remarkably depressed the southward inﬂux at thenorthern boundary of the seaweed farm. In contrast, in the along-shore
direction, the mean and transient components competed with eachother, leading to comparable eﬄuent outﬂuxes and inﬂuxes, respectively. As a result, the net inﬂux emerged along the western boundary of
the farm, that was also decreased by the reduced source eﬄuent ﬂux.
Evidently, a key inﬂuencer on the eﬄuent budget was the mean westward residual current developed oﬀ the TSTP as a part of the counterclockwise Tarumi Recirculation. In turn, the transient ﬂux counteracts the mean component to promote the incoming eﬄuent ﬂux andthus the accumulation in the farm. Nevertheless, its contribution becomes more prominent and acts to signiﬁcantly reduce the inﬂux when
the source eﬄuent ﬂux was reduced.

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Acknowledgements
This study was ﬁnancially supported by the City of Kobe and theJapan Society for the Promotion of Science (JSPS) Grants-in-Aid for
Scientiﬁc Research 15KK0207 and 18H03798 at Kobe University. We
also appreciate Yota Suzue (CTI Engineering Co., Ltd.), Taichi Kosako(Port and Airport Research Institute), and Yasumasa Miyazawa (Japan
Agency for Marine-Earth Science and Technology) for their help in thedevelopment of the quadruple nested ROMS model embedded in theassimilative Japan Coastal Ocean Predictability Experiments (JCOPE2)
oceanic reanalysis that was used in the analysis. The eﬄuent data andalternative discharge scenarios for the Tarumi Sewage Treatment Plant
were provided by the City of Kobe.
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