ORIGINAL ARTICLE
Numerical modeling of pollutant load accumulation in the Musaestuary, Persian Gulf
Alireza Payandeh • Nasser Hadjizadeh Zaker •
Mohammad Hossien Niksokhan
Received: 20 October 2013 / Accepted: 30 May 2014
� Springer-Verlag Berlin Heidelberg 2014
Abstract Musa estuary is a predominantly tide-driven
embayment located in the northwestern part of the Persian
Gulf. This estuary is bordered by dense population and
industrial development that add significantly to the water’s
pollution load. The eastern part of the estuary opens into
the small estuaries which are not similar in terms of pol-
lutant load accumulation. The present study investigates
the relationships between pollutant load accumulation and
some physical and hydrodynamic characteristics of the
Musa estuary. Tidal regime, bottom topography, persis-
tency of currents and pollutant sources were analyzed
numerically in relation to pollutant load accumulation.
Residence time was calculated using the MIKE 3 model
and this concept was used as a metric of pollutant load
accumulation. It was found that the assimilative capacity of
Musa estuary is not the same during the month so that the
capacity to absorb pollution in spring tide is more than at
any other time. Based on the results, the present study
suggests that in all estuarine ecosystems, the persistency of
currents can be used as an indicator of areas which are
faced with pollutant load accumulation.
Keywords Musa estuary � Residence time � Pollutant
load accumulation � Persistency of current � Tidal regime
Introduction
In recent decades, considerable amounts of pollutants are
entering into the estuarine environment due to large
deployment of utilities, industrial and port activities. Wo-
lanski (2007) noted some of the risks that threaten such
environments such as marine eutrophication because of
additional concentrations of nutrients in wastewater, heavy
metal pollution, polychlorinated biphenyls, radionuclide
and hydrocarbons. Proportional to the acceleration of
industrialization and urban development in coastal areas,
the environmental research should address the influence of
the developmental activities on environment in order to
mitigate the adverse environmental effects. Numerical
modeling is a useful way to study water environment and
has long been used to study estuaries (e.g. Chen et al. 2013;
Sentenac et al. 2013; Shi et al. 2010; Liu et al. 2012; Nouri
et al. 2010).
Indiscriminate industrialization and urbanization threa-
ten the Musa estuary. Musa estuary is a long and deep
channel in the northwest of Persian Gulf between 30� to
30�450N and 48�200 to 49�510E (Fig. 1). The span width of
Musa estuary is 37–40 km and its length from the span to
Mahshahr port is about 120 km. The estuary is important
for the local fisheries activities in Khuzestan Province and
fish from this aqua resource serve as the main source of
animal protein for the population surrounding the estuary
(Mortazavi and Sharifian 2011). There are some other
estuaries driven from Musa estuary, some of which are
Ghazale, DoraQ, Ghanam, Zangi, Jafari and Ahmadi
estuaries. Musa estuary is a tree-shaped and predominantly
tide-driven embayment where tidal currents are considered
as the major currents of the estuary (Sabagh-Yazdi and
Sadeghi-Gooya 2010). The development of petrochemical
industries, aquaculture activities, the expansion of two
cities of Mahshahr and Sarbandar and development of
Imam Khomeini and Mahshahr ports, are considered as
significant threats to the estuary (Malmasi et al. 2010; Jozi
et al. 2010; Jafarian Moghadam et al. 2011). For
A. Payandeh � N. H. Zaker (&) � M. H. Niksokhan
Graduate Faculty of Environment, University of Tehran,
Tehran, Iran
e-mail: [email protected]
123
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DOI 10.1007/s12665-014-3409-0
Author's personal copy
environmental management of this region and to reduce the
possible effects of expanding industries, it is necessary to
exactly identify the vulnerability of the estuary against
pollution load accumulation.
Different water time scales, such as residence time and
water age, are criteria that link the physical and biological
features of water and are appropriate indicators to compare
the behavior of each part of estuary in dealing with pol-
lution. Estuaries with a short residence time will export
pollutants from upstream sources more rapidly then estu-
aries with longer residence time The development of pri-
mary definitions of water residence time and water age can
be viewed in works of researchers such as Bolin and Rhode
(1973), Zimmerman (1976), Takeoka (1984). Also, using
the concept of residence time, Brooks et al. (1999) inves-
tigated the condition of dispersion and flushing of Cobs-
cook Bay which is a macrotidal estuary near the entrance to
Bay of Fundy. They attempted a three-dimensional mod-
eling of water circulation which is affected by semi-diurnal
tide and runoff from rivers. Using a two-dimensional par-
ticle tracking modeling, Patgaonkar et al. (2012) calculated
the residence time of pollutant discharge in Kachchh bay
which is in northeast coast of the Arabian Sea and
concluded that tidal currents have a strong component in
the east–west direction that prevents the transmission of
pollutants between its north and south. Longer residence
time of anthropogenic nutrients has been reported as the
main cause of eutrophication and hypoxia conditions in
Chesapeake Bay (Cerco and Cole 1993).
The most important point in previous studies about
residence time in estuaries especially the Musa estuary is
lack of a comprehensive study on the factors that increase
or decrease the residence time. In the present study, the
residence time in Musa estuary is studied as an effect and
attempt to provide a comprehensive study on relationships
between residence time and tidal regime, persistency of
currents and bottom topography. In addition to these fac-
tors, pollutant sources has strong effect on the amount of
pollution, therefore another part of the research deals with
effects of pollutant sources position on the pollutant load
accumulations in various estuaries of Musa. Results of the
current study can be used in Environmental management of
the study area. Also they can be used for identifying the
suitable locations for sewer outlets, suitable sites for
aquaculture activities, finding locations of spawning areas
used by marine fishes and calculations related to TMDL
(total maximum daily load).
Materials and methods
Model setup
MIKE 3 FM hydrodynamic model was used to calculate
the residence time. MIKE 3 FM is based on the numerical
solution of the three-dimensional incompressible Rey-
nolds-averaged Navier–Stokes equations, subject to the
assumption of Boussinesq and of hydrostatic pressure. The
spatial discretization of the primitive equations is per-
formed using finite volume method. In the horizontal plane
an unstructured grid is used while in the vertical domain a
structured discretization is used (DHI 2007). Model grids
were generated by MIKE Mesh Generator, which uses
hydrography data and user defined grid limits. Hydrogra-
phy of the region was carried out by Iranian Port and
Maritime Organization (PMO) in 2004. Recorded surface
elevations of tide gauge located at 30�120900N and
48�5705900E employed to provide the boundary condition of
the hydrodynamic model. Analysis of wind data in Mah-
shahr synoptic station (30�330E, 40�490N) for 5 years
showed that the prevailing wind in the area is Shamal wind.
This result agrees with previous studies (e.g. Thoppil and
Hoganb 2010) indicating that Shamal wind is a north-
westerly wind blowing over Iraq and the Persian Gulf
states including Saudi Arabia and Kuwait, often strong
during the day, but decreasing at night. Measured wind at
Fig. 1 Landsat TM image showing the tree-shaped study area and
geographic features cited in text. The inset map (upper right) shows
the Khor-Musa (in the red quadrangle) along the NW Persian Gulf
margin
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Mahshahr synoptic station was uniformly applied over the
entire domain. Table 1 contains parameters specified in the
MIKE 3 FM model. As the model is located in an area
where flooding and drying occur, we have specified a
drying water depth, a flooding water depth and a wetting
depth. When the water depth is less than the wetting depth
the problem is reformulated and only if the water depth is
less than the drying depth the element/cell is removed from
the simulation. The flooding depth is used to determine
when an element is flooded (i.e. reentered into the calcu-
lation). The reformulation is made by setting the
momentum fluxes to zero and only taking the mass fluxes
into consideration. Figure 2 shows all permanent water
areas and areas that can become dry in low tides.
Sensitivity analysis and calibration
Various sensitivity tests were carried out to analyze the
effect of variations of different model parameters on the
results including bed resistance, mesh resolution, eddy
viscosity, and boundary conditions. This analysis revealed
that the modeling was sensitive to some parameters. Model
outputs were sensitive to mesh resolution. After increasing
the resolution a few times, the outputs became insensitive
to mesh resolution. Sensitivity analysis indicated that the
modelling is very sensitive to bed resistance. It can be
calculated either through the roughness height or quadratic
roughness coefficient. Examining the roughness heights
between 0.001 and 0.3 m, a value of 0.01 m was chosen.
Eddy viscosity coefficient is another important parameter
defining the turbulence mixing in the water. Turbulence
mixing is generally larger in places where the velocity
gradient is large. There are two available options provided
in MIKE 3 FM model for eddy viscosity, i.e. constant eddy
viscosity and Smagorinsky eddy viscosity, which is a
function of velocity gradients. The Smagorinsky eddy
viscosity (Smagorinsky 1963) with the coefficient of 0.28
was adopted for the simulation. Figure 3 shows the com-
parisons of measured and simulated tidal elevations and
current velocity time series at a point with coordinates of
30�2504000N and 49�405900E. It is observed that the pre-
dicted tidal elevations show a very good agreement with
field measurements. Similar good agreements were
observed in current speed.
Fig. 2 Permanent water areas
(yellow areas) and areas that
can become dry at low tides (red
areas)
Table 1 Overview of parameters specified in the MIKE 3 model
Parameters Values
Time step interval 7 s
Time integration Higher order
Critical CFL number 1
Drying depth 0.005 m
Flooding depth 0.05 m
Wetting depth 0.1 m
Interpolation method Natural neighbour
Number of scatter points 80,976
Number of elements 6,453
Mesh nodes 4,728
Eddy viscosity Smagorinsky eddy viscosity
with the coefficient of 0.28
Bed resistance Roughness height = 0.01 m
Wind Mahshahr synoptic station data
with a time step of 15 min
Boundary condition The recorded surface elevations
of tide gauge Located at
30�120900N and 48�5705900E
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Calculation of residence time
Several definitions and methods have been proposed to
calculate the residence time which most of them are dif-
ferent from each other in terms of concept and calculation
methods and procedures (Bolin and Rhode 1973; Zimmer-
man 1976; Dettmann 2001; Monsen et al. 2002; Delhez
et al. 2004; Sandery and Kampf 2005; Patgaonkar et al.
2012). For example, Zimmerman (1976) and Shen and Haas
(2004) have used flushing time, Monsen et al. (2002) has
used the residence time and some other researchers (Dett-
mann 2001; Delhez et al. 2004) have used e-folding time.
In the present study, two concepts of point residence
time and regional residence time have been used to which
are developed based on Thomann and Mueller (1987).
According to Thomann and Mueller (1987) definition, if a
certain amount of a substance in time of t0 and initial
concentration of c0 which is released in homogeneous mass
of water and no further amount of the substance is added to
the water and the density of water and fluxes in boundaries
remain constant, the concentration of water in time of t is:
Cðt�t0Þ ¼ C0e�Q=V � ðt � t0Þ ¼ C0eð�ðt � t0Þ=h ð1Þ
where Q is the flux of substance, V is the density of control
volume, t stands for time and O– is the residence time.
Residence time is the e-folding time, i.e., the time
required to reduce the total mass of the tracer in the estu-
ary, or a segment of it, to a factor of e-1 of its original
Fig. 3 Comparisons between
the calculated and measured
time series at 30�250400 0N and
49�40590 0E. a and b water
surface elevations for 10 and
15 days, c current velocities for
6 days
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value. This time scale has been termed residence time
(Thomann and Mueller 1987). For example if the initial
mass of the tracer is X and after a time T the current value
is observed Y = X/e then T is the residence time.
This definition is selected as a measure of control vol-
ume and cannot be an index of point to point comparison.
Therefore, in the present study the following definitions are
developed.
Point residence time: Point residence time is the required
time for the absolute reduction of grid mesh concentration by
a factor of 1/e. Considering that the concentration time series
has the minimum and maximum points on different time-
scales, our understanding of the term ‘‘absolute’’ is the first
time that the concentration drops to 1/e & 0.37 and after that
the concentrations don’t increase from this value. Point
Residence Time makes it possible to show the distribution of
residence time in area with enough resolution.
Regional residence time: Regional residence time can be
calculated for any desired area. In this case, the average
concentration of all the elements within each time step is
calculated and the time required for absolute reduction of
average concentration by a factor of 1/e of its initial con-
centration is considered Regional Residence Time. This
index can be used to compare different areas with each
other or the same area in different conditions.
Calculation of pollution age and pollution influx rate
Residence time can be used as an indicator of pollutant load
accumulation in different parts of the Musa estuary, but this
concept does not consider pollutant sources effect. As
defined in previous section, uniform concentration of the
tracer was used to calculate the residence time. Therefore
pollutant sources effect is eliminated deliberately in order to
study other factors. In the present study, two concepts of
pollution age and pollution influx rate were developed for
assessing the sensitivity of different parts to pollutant sour-
ces. Pollution age index was defined based on the concept of
age. Zimmerman (1988) defined age as the time which a
water parcel has elapsed since its entrance to the estuary from
one of its boundaries. Delhez et al. (1999) used another
definition which is: the time elapsed since the parcel under
consideration left the region where its age is assumed to be
zero (Fig. 4a). Delhez et al. (2003) developed a method to
calculate the age of water using two tracers: one conservative
and one decaying with decay constant k. If these two tracers
release with the same concentration and the same rate then
water age could be calculated as below:
T ¼ �k�1 lnðCdecay=CconservativeÞ ð2Þ
Here, T is the age of water particle (day), K is the decay
coefficient (1/day), Cdecay is the Concentration of the
decaying tracer (kg/m3), and Cconservative is the concentra-
tion of the conservative tracer (kg/m3). Water age in Del-
hez et al. (2003) definition is always dependent on the
discharge point of the tracers.
The present study is looking for an index which shows
time travel of pollutant to reach to different parts of the
estuary. To achieve this goal, the discharge point of the two
tracers is replaced with existing pollutant sources (Fig. 4b).
Calculating age under this condition represents the time
travel of pollutants to different parts. Therfore in the
present study pollution age is used instead of water age.
Pollution influx rate was defined as bellow:
Pollution Influx Rateg
ðm3 dayÞ
� �
¼Cdecay
gm3
� �� �ðpollution age ð30 daysÞ½day])
ð3Þ
This index represents the arrival rate of the pollution in an
individual point. This index was used to compare sensitivity
of different parts of the estuary to existing pollutant sources.
Calculation of persistency
Persistency is a concept that expresses the stability of cur-
rent vectors (Witting 1912; Palmen 1930). When the current
is unidirectional in time, the persistency is 100 % and the
more variable the direction, leads to smaller persistency.
Witting (1912) and Palmen (1930) defined the persistency
as the ratio between vector and scalar mean speeds:
R ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1=N
Pn un
� �2þ 1=NP
n v2n
� �q1=N
Pn
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiu2
n þ v2n
p ð4Þ
where R is the persistency and is given as a percentage,
N is the number of time steps, un is the velocity in
x direction and vn is the speed in y direction.
Results and discussion
Results are categorized and presented in individual
sections.
Hydrodynamic results
Hydrodynamic modeling was conducted for a period of
4 months between August and November 2000. This is the
time period that current velocity and sea surface elevation
data were measured in the study area. Figure 5 shows two
snapshots of surface velocity vectors at rising tide (flood)
and lowering tide (ebb), respectively.
The results of simulations showed no significant dif-
ferences in the pattern of currents in the study area during
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different months. The results also indicated that tides are
the major forcing factor in the Musa estuary and wind
forcing does not have significant effect on the current. The
simulations showed that tidal range increases from 3 m
near the mouth of the Musa estuary to a maximum of 6 m
at the head of the creek. The magnification of the tidal
range can be attributed to the geometrical shape of the
creek. The maximum current velocity ranged between 1.25
and 2.5 ms-1 with the highest velocities at the western end
of the main channel. Currents were mainly in the long-
shore direction with little cross-shore component. Hydro-
dynamic results are in line with previous studies (Sabagh-
Yazdi and Sadeghi-Gooya 2010).
Tidal regime and residence time
Musa estuary has a mixed semidiurnal tidal cycle as it
experiences two unequal high tides and two unequal low
Fig. 4 a The concept of water
age based on Delhez et al.
(1999) definition, b the concept
of pollution age
Fig. 5 Velocity-magnitude
vectors of the flow field at
a rising tide (flood), b lowering
tide (ebb). Black arrows
indicate the direction of current
vectors
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tides every lunar day. Most od areas in Persian Gulf
experience these tidal cycles. Musa estuary exhibits a much
greater tidal range around the time of the full moon and
new moon which is named spring tide. In this period high
tides are very high and low tides are very low. In Neap tide
periods there is a smaller difference between high and low
tides. Two scenarios were simulated to evaluate the effect
of tidal regimes on residence time. In the first scenario
simulation period was mainly in neap tide period and the
second scenario mainly contains spring tide period. Max-
imum point residence Times were calculated 11.5 and
11.2 days respectively in scenario 1 and 2. Figure 6 shows
the distribution of point residence time under scenarios 1
and 2.
As can be seen in Fig. 6 point residence time during
spring tide is less than neap tide in most of areas. For better
comparison of results, regional residence time of the Musa
estuary was calculated in both scenarios (Table 2).
The regional residence time of Musa estuary during
neap tide is 25.46 h more than spring tide. Since during
spring tide there are two strong high tides and low tides,
tidal currents are greater which cause lower residence time
during spring tide. It shows that the assimilative capacity of
the estuary is not the same during the month and during
spring tide currents have more power to clean the water
from pollutants. This result can be considered in the studies
related to pollutant load allocations in estuaries. Varying
regimes of pollutant loads during the mounth should be
Fig. 6 The time averaged point
residence time in a scenario 1
(Neap tide), b scenario 2
(Spring tide)
Table 2 Comparisons between regional residence time in different
scenarios
Scenario Regional residence time (h)
1 246.66
2 221.2
Difference of two scenarios 25.46
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allocated in order to use full assimilative capacity of Musa
estury.
Residence time of deeper parts especially the main
channel are more affected by tidal regimes. It was found
that the difference between point residence time in neap
tide and spring tide is 36 h in some deep areas. Shallow
areas of Musa estuary are mostly located at the end of
estuary and are less affected by main tidal currents therfore
their residence time is less sensitive to monthly tidal
regimes.
Persistency of current and bottom topography
Figure 7 shows the persistency of currents in Musa estuary.
According to the bottom topography, residence time
(Fig. 6) and Fig. 7, following results are striking:
• Figure 8a shows the relationship between the persis-
tency and bottom depth while Fig. 8b shows the
relation between persistency and mean flow velocities.
According to these plots, more stable flows occur in
shallower areas that have lower current speeds. As
shallow areas are less affected by tidal currents.
Direction of currents in the Musa estuary vary four
times a day but shallower areas and sub estuaries of the
region are not coordinated with the mainstream.
Therefore, they are also more stable.
• Figure 8c shows the relationship between the persis-
tency and Point residence time. This figure indicates
that residence time is higher in areas with more
persistence currents. Figure 8d shows the relationship
between mean flow velocities and residence time.
According to these plots, higher persistency coupled
with lower speed of current coause higher residence
time and pollutant accumulation.
• Figure 8e shows the relationship between the bottom
topography and point residence time. This figure
indicates that the residence time increases in shallow
areas that leads to faster dilution of pollutants in deep
areas of Musa estuary.
Pollutant sources and pollutant load accumulation
in sub estuaries of Musa estuary
MIKE 3 Transport Module was used in order to simulate
pollution concentration within Musa estuary. The main
sources of pollution in the Musa estuary generally consist
of urban sewage and petrochemical sewage (Shakouri et al.
2006; Kianersi et al. 2009). Figure 9 shows the location of
the pollutant sources that were applied in the model. The
discharge rate of these sources is based on the first phase of
the Musa estuaries monitoring program which was con-
ducted in 2001. Thus, all pollutant sources start releasing
two tracers with the same concentration of 1 kg/m3
according to their own discharge rate.
As regards to this fact that the pollution age in each
point depends on both its position and its time of calcula-
tion (Delhez et al. 2003), pollution age will be different in
different times. In the present study, pollution age was
calculated in 30 days after the start date of the simulation.
So that spring tide and neap tide have impacted on the
Fig. 7 Persistency of currents in Musa estuary
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pollutant distribution. Figure 10a shows the pollution age
distribution within Musa estuary in 30 days after the start
date of the simulation and Fig. 10b shows the Pollution
Influx Rate distribution.
In the present study different control boxes have been
defined in order to compare vulnerability of various estu-
aries relative to the pollutant sources. Each of these boxes
contains a part of the Musa estuary or one of the sub
estuaries (Fig. 11). Each control box cover specified
number of triangulate elements of the model grid. Regional
pollution influx rate is an index assigned to each control
box, and is defined as the average of Pollution influx rate of
all control box elements. Table 3 shows the results of these
calculations. Considering that more regional Pollution
influx rate means more vulnerability, different estuaries
were ranked based on their vulnerability.
Fig. 8 Relationships between
a persistency of currents and
bottom depth, b persistency of
currents and mean flow
velocities, c persistency of
currents and point residence
time, d mean flow velocities and
point residence time, e bottom
topography and point residence
time
Fig. 9 Position of pollutant sources in Musa estuary
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According to the Table 3 classification, Zangi and
Ja’afari estuary have the most vulnerability with the
regional pollution influx rate of 165 kg/m3 day, and the
estuary of Douragh has the least vulnerability with the
rate of 0.8 kg/m3 day. Zangi and Jafari estuaries are not a
good choice for disposal of petrochemical waste water
while Ahmady estuary has a safe position in despite of its
short distance to pollutant sources. Behruzi rad et al.
(Behruzi Rad and Nejad Bahadori 2010) measured the
water’s physico-chemical factors such as COD, BOD,
TSS, TDS, EC, NO3, NO2, SO4 in sub estuaries of Musa
and reported them higher in the Zangi estuary. Then,
counting the number of sea birds as bio indicators, they
found that their number in the Ahmadi estuary is tenfold
compared with the other one. They also reported that the
species diversity of birds was threefold in Ahmadi estu-
ary compared with Zangi estuary. According to Behruzi
Rad and Nejad Bahadori (2010) Ahmadi estuary is so
health which is in agreement with the results of the
present study. Similar good agreements were observed
between the present study results and Shakouri et al.
(2006) study.
Conclusion
Tidal regime, bottom topography, persistency of currents
and pollutant sources were analyzed numerically in relation
to pollutant load accumulation in Musa estuary. It was
found that the assimilative capacity of Musa estuary is in
deep relationship with mounthly tidal regimes and should
be considered in allocation of pollution permits. Most of
the. The peresent study investigated that the pollution has a
limited dilution in sub estuaries while in deeper parts is
diluted more and faster. Results of the study showed that,
Zangi and Jafari estuaries are not a good choice for dis-
posal of petrochemical waste water. Efforts should be done
to replace the sewer.
Fig. 10 a Pollution age
distribution within Musa estuary
in 30 days after the start date of
the simulation, b pollution
influx rate distribution within
Musa estuary
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The mothodology of the present study can be used in
related studies in the study area and even in other tidal
estuaries as effects of tidal regime, bottom topography and
persistency of currents are almost common in macro-tidal
estuaries. In an estuary with high diversity of water con-
dition a blend use of residence time, persistency of currents
and pollution age can be a good criteria for related envi-
ronmental studies.
Acknowledgments The authors would like to thank Mrs Ghazavi
for proof reading the manuscript during its preparation. Also we
appreciate the Iran Ports and Maritime Organisation (PMO), for their
invaluable efforts on providing necessary data.
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Fig. 11 Defined control boxes
to compare vulnerability of
various estuaries
Table 3 Estuaries rank according to their vulnerability
Control box Pollution influx
rate (kg/m3 day)
Vulnerability
rank
Zangi and Jafari Estuary 165 1
Qazale estuary 43.7 2
Ahmadi estuary 7.8 3
Central part 6 4
Qanam estuary 1.7 5
Doraq estuary 0.8 6
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