DSpace at VNU: Modelling the Impacts of Mangrove Vegetation Structure on Wave Dissipation in Ben Tre Province, Vietnam, under Different Climate Change Scenarios

Journal of Coastal Research

00

0

000–000

Coconut Creek, Florida

Month 0000

Modelling the Impacts of Mangrove Vegetation Structure on
Wave Dissipation in Ben Tre Province, Vietnam, under
Different Climate Change Scenarios
Nguyen Thi Kim Cuc†‡, Tomohiro Suzuki§††‡‡, Erik D. de Ruyter van Steveninck§§,
Hoang Hai†††

†

Department of Natural Resources
Management
Faculty of Water Resources Engineering
Water Resources University
175 Tay Son
Dong Da, Hanoi, Vietnam


‡
Mangrove Ecosystem Research Division
Centre for Natural Resources and

Environmental Studies
Vietnam National University
Hanoi, Vietnam

§
Flanders Hydraulics Research
Berchemlei 115
B-2140 Antwerp, Belgium

††

‡‡

§§

Department of Civil Engineering
Ghent University
Technologiepark 904
B-9052 Ghent, Belgium

Environmental Fluid Mechanics Section
Faculty of Civil Engineering and Geosciences
Delft University of Technology
P.O. Box 2600 GA Delft
The Netherlands

Water Science and Engineering
Department
UNESCO-IHE Institute for
Water Education,

Delft, The Netherlands

†††

Faculty of Environment
Da Nang University of Technology,
Da Nang, Vietnam

Abstract
Cuc, N.T.K.; Suzuki, T.; Ruyter van Steveninck, E.D. de, and Hai, H., 0000. Modelling the impacts of mangrove
vegetation structure on wave dissipation in Ben Tre Province, Vietnam, under different climate change scenarios.
Journal of Coastal Research, 00(0), 000–000. Coconut Creek (Florida), ISSN 0749-0208.
Mangroves are widely distributed along the coastline of Vietnam, where they provide protection against sea waves
caused by extreme weather. Impacts of climate change, together with population growth and economic development, are
expected to exert pressure on these vulnerable systems. In this study the numerical wave-propagation model SWANVEG (Simulating Waves Nearshore–Vegetation) was used to simulate the possible impacts of climate change on the
wave-dissipation capacity of different types of mangrove vegetation. Vegetation characteristics were assessed in planted
plots (Rhizophora apiculata and a mix of R. mucronata, Sonneratia caseolaris, Avicennia alba, and Nypa fructicans) and
in natural regenerated areas (A. alba and S. caseolaris) in Thanh Phu Natural Reserve, Mekong Delta, Vietnam; these
assessments were used as model input. Different sea levels and mangrove vegetation characteristics were used to
simulate the potential impacts of climate change. Planted plots with a cover of 70% reduced the height of incoming waves
by 60%, compared with 40% for natural regenerated forest. Reducing the vegetation cover in planted plots from 70% to
50%, 35%, and 0% resulted in wave-height reductions of 51%, 42%, and À4%, respectively. A sea level rise (SLR) up to
0.96 m did not change the wave-dissipation potential of R. apiculata planted in the plots. However, an assumed decline in
the width of vegetation from 1.5 km to 0.5 km, e.g. as a consequence of coastal erosion, reduced the height of incoming
waves 21% (no SLR) and 29% (0.96 m SLR), as compared to 60% and 59%, respectively, without erosion.

ADDITIONAL INDEX WORDS: Mangrove, wave, climate change, SWAN-VEG, Thanh Phu.

INTRODUCTION
Tropical coastlines are under great pressure due to a rapid

increase in population, changes in land use, and infrastructural developments. Large-scale mismanagement of these
DOI: 10.2112/JCOASTRES-D-12-00271.1 received 27 December 2012;
accepted in revision 16 April 2013; corrected proofs received 10 June
2013.
Published Pre-print online 15 July 2013.
Ó Coastal Education & Research Foundation 2013

coastlines and the inability to cope with events such as cyclones
can have devastating long- and short-term effects, especially in
developing countries. Densely vegetated mangrove forests
contribute to the protection of coasts against severe sea waves
caused by storms or tsunamis, which can affect local people
living in tropical coastal areas (Alongi, 2008; Kathiresan and
Rajendran, 2005). Thus many efforts to plant mangroves have
been made based on qualitative observations (Hong and San,
1993). As argued by Lewis and Streever (2000), however, the
function of the ecosystem and the hydrology at individual sites


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Cuc et al.

need to be understood quantitatively in order to determine
what is needed in terms of vegetation density and width to
provide the required level of protection.
Unfortunately, very little knowledge has been accumulated
in this regard. Studies on the wave-dissipation capacity of
mangrove vegetation are limited compared to those on salt
marshes (e.g. Knutson, 1988) or sea grass beds (e.g. Fonseca

and Cahalan, 1992). Based on field observations, Mazda,
Wolanski, et al. (1997) have shown the quantitative effects of
two mangrove species, Rhizophora stylosa and Kandelia
candel, on reduction of the impact of sea waves. Massel,
Furukawa, and Brinkman (1999) have discussed the wavedissipation capacity of Rhizophora spp. and Sonneratia spp.
based on a mathematical model. A predictive model of wave
propagation through a nonuniform forest in water of changing
depth in the mangrove forest of Can Gio, Vietnam, has been
developed by Vo-Luong and Massel (2008). Recently, Mendez
and Losada (2004) and Suzuki et al. (2011) have incorporated a
full frequency-direction wave spectrum in the numerical wave
model SWAN (Simulating Waves Nearshore) and additionally
included a layer-wise implementation of vegetation characteristics. Their results, however, cannot be applied directly to
other regions or species, as each mangrove species has a unique
configuration of trunks, prop roots, and pneumatophores that
produces a different drag force (Wolanski et al., 2001) and
therefore results in a different reduction rate of sea waves. For
example, with regard to Bruguiera spp., Sonneratia spp.,
Avicennia spp., and Nypa fruticans, no information on their
wave-dissipation capacity exists, either on their quantitative
hydrological functions or on their physical impact. Accordingly,
for useful and effective mangrove planting, there is a need for
quantitative knowledge of the physical impact of individual
mangrove species in relation to their wave-dissipation capacity.
Vietnam is located in the tropical region of Asia. With its long
coastlines and high concentration of population and economic
activities in coastal areas, its coastal ecosystems and communities could potentially be dramatically impacted by a rise in
sea level (CCFSC, 2001). According to Bates et al. (2008),
changes in the hydrological cycle are expected to be the most
significant aspect of climate change to affect the Mekong Delta.

These include changes in sea level, precipitation patterns, and
monsoon cycles, both frequency and magnitude of these
climatic events. Climate change could also increase the
frequency and severity of typhoons (Byrnes et al., 2011).
Coastal erosion and accretion (sedimentation) are both part of
the natural, dynamic interaction between shorelines and the
sea. Erosion along the East Sea coast of the Mekong Delta
appears to be mainly structural erosion caused by waves and
longshore sediment transport, which strips sediment from the
coast and deposits it at the confluence of the East sea current
and the circular pattern of water flow from upper streams.
Changes in sediment inflow to the coastal zone from rivers in
the Mekong Delta could also be involved (Fabrice and Claudia,
2012). Any rise in sea level or increase in the frequency and
intensity of coastal storms is likely to accelerate the rate of
coastal erosion and could lead to changes in its spatial pattern.
Sections of the coastline that are now eroding could become
areas of accretion; conversely, sections that are now accreting

may become areas of erosion in the future. Coastlines of the
Mekong Delta and Thanh Phu Natural Reserve are facing
serious erosion and accretion in different areas.
Mangroves have been a key element in reducing the rate of
erosion and provide a protective barrier along the shoreline.
Mangroves alone cannot provide complete protection against
erosion in all situations, as illustrated by the current situation
on the Thanh Phu coastline, where there are reasonably welldeveloped mangrove stands. Arguably, however, the rate of
erosion would have been much faster without them (Clough
and Phan, 2010). Mangroves are widely distributed in coastal
areas in Vietnam, particularly in the south (Maurand, 1943).

However, deforestation due to war activities and conversion to
agricultural land and (more recently) shrimp ponds (Hong,
1999) has resulted in a decline from 408,500 ha in 1943
(Maurand, 1943) to 290,000 ha in 1962 (Rollet, 1981), 252,000
ha in 1982 (FIPI, 1982), 156,608 ha in 2001 (FIPI, 2001),
209,741 ha in 2006 (FIPI, 2007), and 139,955 ha in 2010
(MARD, 2011).
In this paper, the SWAN model has been used to analyze the
impact of different mangrove species and densities on wavedissipation capacity and wave-energy dissipation characteristics in Thanh Phu Natural Reserve, Mekong Delta. The SWAN
model is a third-generation wave model developed at Delft
University of Technology, the Netherlands (TU Delft, 2011).
The SWAN model computes the processes of wave generation
by wind, quadruplet wave-wave interactions, white-capping,
bottom friction, depth-induced breaking interactions, and triad
wave-wave interactions; it is thus capable of estimating wave
propagation from offshore to nearshore. In addition to the
fundamental features of waves, the effects of vegetation have
been recently incorporated into the model. Using data about
the present mangrove vegetation in Thanh Phu Natural
Reserve, a comparison has been made between a planted area
dominated by Rhizophora sp. and a naturally regenerated area
dominated by Avicennia sp. To analyse the impacts of tree
density, sea level rise (SLR) associated with climate change,
and coastal erosion, only data about the planted forest have
been used.

MATERIALS AND METHODS
Study Area
The study was carried out in Thanh Phu Natural Reserve,
Ben Tre Province, Vietnam (Figure 1). Ben Tre is a coastal

province in the Mekong Delta. The area is characterised by a
tropical monsoon climate (Vu, 1994); average air temperature
is about 268CÀ288C. In the channels inside Thanh Phu Natural
Reserve, the average water temperature is about 288C.
Normally the rainy season extends from May to November,
with maximum monthly rainfall from June to August. Monthly
maximum river flows occur from August to October. About 9%
of the delta area is occupied by channels 20–30 m long. The
tidal regime is semidiurnal with a tidal amplitude of 1.5–3.75
m. Tides can propagate 50–100 km inland with velocities of
0.75–1.80 m sÀ1. Salinity in the estuaries varies from 0%–12%
(June–November) to 12%–30% (November–May) (Sub-FIPI II,
2003).

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Modelling the Impacts of Mangrove Vegetation Structure on Wave Dissipation

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Figure 1. Study area in Thanh Phu Natural Reserve

Mangroves concentrated in the districts of Binh Dai, Ba Tri,
and Thanh Phu covered 13,153 ha, or 33%, of the province in
1994 (Sub-FIPI II, 1995). In 2000 and 2007, coverage was
estimated at 3413 and 3520 ha, respectively (Ben Tre DARD,
2010; Ngo, 2004).
The coastal landscape at Thanh Phu consists of sandy belts,
tidal mudflats, saline tidal swamps, and toxic acid-sulphate

swamps. Thanh Phu Natural Reserve contains a narrow strip
(about 0.8–5.0 km) of mangroves along the coastline between
two of the mouths of the Mekong River: the Co Chien and Ham
Luong estuaries (Figure 1). As is the case with other sites on
the eastern coastline of the Mekong Delta, Thanh Phu Natural
Reserve is strongly affected by both erosion as well as accretion
(Sub-FIPI II, 1998, 2003).
In 2009, Thanh Phu had a population of 127,574 inhabitants.
The district covers an area of 44,350 ha, of which 17,300 ha is
used for aquaculture and 15,000 ha as paddy fields. Another
2000–3000 ha is used for industrial crops, fruit farming, etc.
(Ben Tre Statistics Office, 2010).

Mangrove Vegetation Structure
In the study area, planted Rhizophora apiculata is the
predominant species, representing more than 80% of the
mangrove vegetation. Three transects perpendicular to the
coastline were laid out with a length of 1–2 km, depending on
width of the vegetation. In each transect three 10 3 10 m plots
were established—one close to the shore, one in the middle, and
one at the end of the transect—according to accessibility. In
each plot all trees were counted, while a separate 1 3 1 m
subplot was established within each plot to count seedlings
(less than 1.0 m in height) and saplings (1.0–4 m in height).
Trees taller than 4 m were identified to the species level, and for
these the following parameters were measured as described by
English et al. (1994):
(1)
(2)
(3)

(4)

Tree and still root densities
Root diameter and height
Tree diameter at a height of 1.3 m
Height from stratum to height of the first branch (h
branch)

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Cuc et al.

(5) Height from stratum to height of the first leaf (h leaf)
(6) Height from stratum to the top of the tree (h top).
One similar transect with three plots was set up within the
section of natural regenerated vegetation in the study area and
was analysed in the same way.
For the model input, possible zonation patterns were
neglected, and the mean values of the measured parameters
per vegetation type, i.e. planted and natural regenerated, were
used.

¯ and the total wave
mean frequency r,
¯ the mean wave number k,
energy Etot are defined as follows (Wamdi Group, 1988):


r¯ ¼

k¯ ¼

EÀ1
tot ¼

SWAN-VEG Model
The SWAN-VEG model consists of the original SWAN model
with a vegetation module added. This module consists of a
variable for energy dissipation due to vegetation. The dissipated energy is subtracted from the incoming wave energy, which
results in less wave energy behind the vegetation field and thus
a lower wave height. Vegetation is modelled as cylindrical
obstacles; vegetation characteristics such as height, width,
density, and drag coefficient are used to determine the
magnitude of the dissipation term. In addition, wave characteristics like significant wave height and peak period influence
the energy-dissipation term (de Oude et al., 2010). The SWANVEG module for wave dissipation by vegetation (Suzuki et al.,
2011) is based on Mendez and Losada (2004) and de Oude et al.
(2010). The model assumes a group of cylinders as representation of vegetation. It includes vertical-layer schematization,
making it possible to calculate multilayer structures such as
mangroves. The energy dissipation term in SWAN-VEG is
described by Suzuki et al. (2011):
Sds;veg ¼

n
X

Sds;veg;i ;

ð1Þ

i¼1

where Sds,veg is the total energy dissipation due to vegetation, n
is the number of vegetation layers, i is the layer under
consideration, and Sds,veg, i is the energy dissipation for layer i.
The energy dissipation term for a given layer i therefore becomes
rffiffiffi
 ¯ 3
2 2
k
Sds;veg;i ¼ À
g CD bv Nv
p
2r
¯ i h À sinh3 ka
¯ iÀ1 hÞ þ 3ðsinh3 ka
¯ i h À sinh3 ka
¯ iÀ1 hÞ
ðsinh3 ka
3
¯
3k¯ cosh kh
pffiffiffiffiffiffiffiffi
3 Etot Eðr; hÞ;
ð2Þ
3

where g is gravitational acceleration, CD is the bulk drag
coefficient, bv the cylinder diameter, Nv is the cylinder density,

aih is the plant height, and E(r,h) is the wave-energy density.
The bulk drag coefficient value 1.0 is used for simplicity in this
study as per de Oude et al. (2010) and Narayan et al. (2010). As
far as we are concerned, the bulk drag coefficient value of
mangrove forest has not been very clear up to now due to the
complexity of the vortex effect around cylindrical structures (e.g.
stems and roots) under wave motion. For instance, different
cylinder densities and arrays, which generate different vortex
patterns, give different bulk drag coefficient values under
waves. Furthermore, even drag coefficient values of a single
cylinder range from 0.5 to 2.5 (Sarpkaya and Michael, 1981) with
changes in Keulegan–Carpenter (KC) value and beta value. The

EÀ1
tot



EÀ1
tot

Z
0

2P

Z

2P
0

Z

‘

0

2P

0

Z

Z

Z

‘
0

1
Eðr; hÞdrdh
r

À1

1
pffiffiffi Eðr; hÞdrdh
k

ð3Þ
À2
ð4Þ

‘

Eðr; hÞdrdh

ð5Þ

0

The wave-dissipation term associated with vegetation,
Sds,veg, is implemented in the source term Stot, as shown in
Equation (6):
Stot ¼ Sin þ Snl3 þ Snl4 þ Sds;b þ Sds;wc þ Sds;br

ð6Þ

where Sds,b is bottom friction, Sds,wc is white-capping, Sds,br is
depth-induced breaking, Sin is wave growth due to wind input,
Snl4 and (Snl3) are energy transfer within the spectrum due to
nonlinear wave-wave interactions such as quadruplets (Snl4)
and triads (Snl3). These six processes contribute to the source
term Stot. The evolution of the wave spectrum is described by
the spectral action balance equation, which for Cartesian
coordinates is given by (e.g. Hasselmann et al., 1973)
d
d
d

d
d
Stot
N þ cx N þ cy N þ
cr N þ
ch N ¼
;
dt
dx
dy
dr
dh
r

ð7Þ

where the first term represents the local rate of change in N
over time and the second and third terms represent propagation along the x and y directions with velocities cx and cy. Thus
the model is capable of calculating wave dissipation associated
with vegetation along with other source terms. As shown in
Equation (7), not only one-dimensional but also two-dimensional calculations are feasible by distributing the vegetation
factors in space.

Model Inputs
Table 1 summarises the parameters used as input data in the
SWAN-VEG model to analyse the impacts of (1) vegetation type
and coverage, (2) water level as a consequence of SLR, and (3)
the width of vegetation on the wave-dissipation capacity of
mangroves.

Water Level, Wave Height and Wave Peak Period
According to the Centre for Meteorology Forecast in Ben Tre
and the Vietnam Institute of Meteorology, Hydrology, and
Environment, the maximum recorded value of significant wave
height on the coast of Ben Tre during the past 100 years was 0.9
m at a point 2.5 km from the shoreline with a depth ofÀ1 m. The
shoreline refers to the line behind the 1.5 km wide mangrove
vegetation (see Figure 2). The peak periods range from 7 s to 10
s. This value occurred when the water level was at 4.1 m (total
depth at À1 m is 5.1 m). This value was used as the extremeevent condition in the simulation.

Vegetation Type and Density
The local forest management system allows households to
harvest or convert up to 30% of mangrove areas that are
managed by them to water surface for aquaculture activities.

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Table 1. Summary of data used as input for the SWAN-VEG model to analyse the impact of mangrove type (planted vs. natural regenerated) and coverage,
SLR, and coastal erosion with and without SLR.
Vegetation

Vegetation type and density

SLR

Erosion and SLR

Code

Type

% Coverage

Width (km)

A1, A3
A4
A5
A6
B1
B2
B3
C1
C2
C3
C4

P, N
P
P
P
P
P
P

P
P
P
P

70
0
50
35
70

1.5
1.5

70

1.0
0.5
1.0
0.5

70

WL (m)

Hs (m)

Tp (s)

4.1

4.1

0.9
0.9

9.0
9.0

0.39
0.65
0.96
0

4.49
4.75
5.06
4.1

0.9

9.0

0.9

9.0

0.96

5.06

0.9

9.0

SLR (m)
0
0

1.5

Abbreviations: Width ¼ width of mangrove forest, SLR ¼ possible sea level–rise scenarios based on MONRE (2010), WL ¼ water level, Hs ¼ significant wave
height, Tp ¼ wave peak period, P ¼ planted mangrove type, N ¼ natural regenerated mangrove type. The simulation codes are also used in Figures 3–6.
Note: mangroves coverage(0–70% cover); sea level rise (0.39-0.96 m) and coastal erosion (from 1.5-0.5 km width) with/without sea level rise (0.96 m).

Thus coverage of 70% of the actual measured figures was used
to compare the impact of planted forests with naturally
regenerated forests (codes A1 and A3, respectively; see Table
1). The impact of vegetation density was analysed by reducing
the coverage in the planted forest from 70% (A1) to 50% (A5),
35% (A6), and 0% (A4) (Table 1).

caseolaris and A. alba were mainly found on the alluvial coastal
and river mud flats, while N. fruticans was planted in the
inland brackish aquaculture ponds. In the planted area, the
tree density was 0.16 trees mÀ2, with a mean tree height of 12.7

Sea Level Rise
Sea level rise scenarios for Vietnam have been developed
based on different emission scenarios: low (B1), medium (B2),
and high (A1F1) (MONRE, 2009). MONRE (2010) recalculated

the expected water levels for several specific coastal locations in
Vietnam. This resulted in predicted increases in water levels of
0.39 m (scenario B1), 0.65 m (B2), and 0.96 m (A1F1) in Ham
Luong (Ben Tre) in the year 2050, 2075, and 2100, respectively.
In this study, these values have been added on top of the
extreme water level of 4.1 m (comparisons A1, B1, B2, and B3;
see Table 1).

Coastal Erosion
The expected SLR will affect the hydrodynamic regime of the
Vietnam East Sea through general circulation, tidal amplitude,
and tidal coastal flooding. In addition, factors affecting
hydrodynamic regimes such as wind, storms, and air temperature will be impacted by climate change. Changes in these
parameters are expected to lead to changes in erosion and
accretion in the region (Ben Tre DARD, 2010). Therefore, in
this study, future erosion scenarios simulation a reduction in
the width of mangrove forests to 0.5 and 1.0 km have been
included (comparison of A1 with C1 and C2; comparison of B3
with C3 and C4; see Table 1). Although a simplification, it was
assumed that erosion did not change the shore topography, and
thus a narrower mangrove forest resulted in the ocean floor
rising less steeply.

RESULTS
Mangrove Vegetation Structure
Vegetation in the planted site consisted of Rhizophora
apiculata (.90%) and a mix of R. mucronata, Sonneratia
caseolaris, Avicennia alba and Nypa fruticans. Sonneratia

Figure 2. Spatial variation of significant wave height for simulations A1,

A3, A4, A5, and A6: vegetation type and density (see Table 1 footnote for
explanation of simulation codes). Wave: Hs denotes significant wave
height; Tp denotes wave peak period; WL denotes water level. The dotted
arrow shows an SLR of 0.96 m (scenario 3); the dashed arrow shows an SLR
of 0.65 m (senario 2); the dotted and dashed arrow shows an SLR of 0.39 m
(senario 1).

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Cuc et al.

Table 2. Mean values (significant difference) of mangrove vegetation
characteristics in both planted Rhizophora (n ¼ 9) and natural
regenerated (n ¼ 3) plots in Thanh Phu Natural Reserve.
Parameter
À2

Tree density (m )
Diameter at 1.3 m (m)
Height branch (m)
Height leaf (m)
Height top (m)
Stilt roots
Density (mÀ2)
Diameter (m)
Height root (m)

Planted Rhizophora
0.16
0.12
6.67
7.20
12.73

(0.07)
(0.04)
(1.83)
(2.04)
(1.77)

3.2 (0.4)
0.04 (0.01)
1.42 (0.64)

Natural Regenerated
0.24
0.11
1.90
4.13
7.63

(0.10)
(0.08)
(1.63)
(1.92)
(2.04)
—

—
—

m and a diameter (measured at a height of 1.3 m) of 0.12 m
(Table 2).
Vegetation in the naturally regenerated site consisted
mainly of A. alba and S. caseolaris. Avicennia alba grows
naturally on mud flats with average tidal levels of 1.0 m to 1.5
m and is directly exposed to waves and wind from the sea. In
some areas, A. officinalis appears landwards from the A. alba
zone, protected from the direct impact of waves and wind.
Sonneratia caseolaris develops on soft mud at depths of 1.0–1.5
m, affected by tides, waves and wind, and a mixture of seawater
and freshwater from rivers. Although tree density in these
plots was higher than in the planted plots (0.24 trees mÀ2), their
average size was smaller (3.9 m high and a diameter of 0.11 m).
Besides these differences, another major difference between
the planted and naturally regenerated sites that could affect
wave-dissipation capacity is caused by the different root
structures for the various tree species, i.e. stilt roots for
Rhizophora and pneumatophores for Avicennia (Figure 3).
Based on the characteristics of the planted Rhizophora trees
(h top, 12.73 m; h leaf, 7.20 m; h branch, 6.67 m) and the
maximum water level (5.06 m), it was assumed that the stems
and roots of the trees will play a major role in wave dissipation;
therefore the influence of the canopy was not considered.

Figure 3. Root structures for the different tree species: stilt roots for
Rhizophora sp. and pneumatophores for Avicennia sp. and Sonneratia sp.
(Hong and San, 1993).

same, i.e. a 59% reduction, which is comparable to the 60%
observed in case A1 (Table 3).

Coastal Erosion
The impacts of coastal erosion, in combination with a more
gradually increasing ocean floor (C1 and C2) and an SLR of 0.96
m (C3 and C4), are illustrated in Figure 5. The impact of wave
dissipation by vegetation (planted forest with 70% cover) shifts
landwards when the width of the mangrove forest is diminished to 1.0 km and 0.5 km. This resulted in a clear impact on
the reduction of wave height: 46% and 21% reduction by the 1.0
km and 0.5 km forests, respectively (compared to 60% by the
1.5 km forest with the sea level at 4.1 m); and 46% and 29%
reduction by the 1.0 km and 0.5 km forests, respectively
(compared to 59% by the 1.5 km forest with the sea level at 5.06
m; see Table 3).
Table 3. Summarised output of the SWAN-VEG model showing percent
reduction of the incoming wave height after passage through the mangrove
vegetation (see Table 1 footnote for explanation of simulation codes).

Model Analyses
Vegetation Type and Density
The wave-simulation model started 2.5 km seaward from the
shoreline with a wave of 0.9 m high. After passing the 1.5 km
wide mangrove forest, the wave height was reduced by 60% in
the planted forest dominated by R. apiculata with stilt roots
(70% coverage, A1) compared to 40% by the natural regenerated forest (A3), which is characterised by A. alba and S.
caseolaris and their associated numerous, but small (10–15
cm), pneumatophores (Figure 2, Table 3). Decreasing the
mangrove cover in the planted Rhizophora forest to 50% and

35% resulted in a reduction of wave height of 51% and 42%,
respectively (A5 and A6; see Figure 2, Table 3). When the
vegetation was removed completely (A4), the wave height even
slightly increased after passing the 1.5 km of no forest (now
cleared) (Figure 2, Table 3).

Sea Level Rise
Figure 4 shows the transmitted wave heights in the planted
forest for three different sea levels (B1, 4.49 m; B2, 4.75 m; and
B3, 5.06 m). Although the water levels increased, the impact of
the mangrove forest on the incoming wave height was the

Parameter
Vegetation type
A1
A3
Density
A1
A5
A6
A4
SLR
A1
B1
B2
B3
Erosion
A1
C1
C2

Erosion and SLR
B3
C3
C4

Journal of Coastal Research, Vol. 00, No. 0, 0000

% Reduction
60
40
60
51
42
À4
60
59
59
59
60
46
21
59
46
29


Modelling the Impacts of Mangrove Vegetation Structure on Wave Dissipation

0

Figure 4. Spatial variation of significant wave height for simulations B1, B2,
and B3 according to SLR (see Table 1 footnote for explanation of simulation
codes).

Figure 5. Spatial variation of significant wave height in erosion simulations
C1/C3 and C2/C4 (see Table 1 footnote for explanation of simulation codes).

DISCUSSION AND CONCLUSIONS

the planted Rhizophora forest. The resulting wave height of
almost 0.4 m is not different in the four tested water depths.
This probably could be explained by the high density of stems
and aboveground roots distributed throughout the whole water
depth, even with a rise in sea level.
The width of the vegetation, however, seems to have more
impact on the wave-dissipation capacity of the planted
mangrove forest. Although a reduction from 1.5 km to 1.0 km
resulted in a slight increase in wave height from 0.4 m to 0.5 m,
further reducing the forest width to 0.5 km resulted in a wave
height of 0.7 m. The actual sea level (present level and an
increase of 0.96 m) did not affect these results. In addition to
vegetation density, the width of the area to be planted is an
important factor in wave attenuation for protecting tropical
coastlines.
Quartel et al. (2007) found that wave heights were depth
limited. Small water depths corresponded with small wave
heights and large water depths with higher incident waves.
With the expected SLR as a consequence of climate change,
coastal areas will face the impact of higher wave height. The
existence of mangrove forests in coastal areas in general, and in

the study area in particular, will thus be very important in
terms of protecting the coastline from the impacts of sea waves.
Further investigations are needed to quantify the function of
mangroves in wind-driven and tidal currents in protecting the
coastal zone.

An analysis of the output of the SWAN-VEG model confirms
the potential role of mangroves in dissipating incoming wave
energy. A simulated reduction in mangrove vegetation in
planted R. apiculata–dominated forests from 70% to 0%
resulted in an increase in wave height from about 0.4 m to
more than 0.9 m. Similar conclusions were made by Mazda,
Magi, et al. (1997), Mazda, Wolanski, et al. (1997), and Quartel
et al. (2007) in the field when measuring surface wave
propagation in mangrove forests of Kandelia candel (in the
Tong King Delta, Vietnam) and Bruguiera gymnorrhiza (in
Nakama-Gawa in Iriomote Island, Japan) and R. stylosa and K.
candel (in the Red River Delta, Vietnam), respectively.
Comparable results were also described by Massel, Furukawa,
and Brinkman (1999) in a study combining theoretical analysis
and a field experiment with Rhizophora sp.
Rhizophora apiculata is characterized by very dense aboveground stilt roots. This probably explains the difference in
wave dissipation capacity between the planted Rhizophora
forest and the naturally regenerated plot (0.4 and 0.5 m,
respectively). The latter consists mainly of Avicennia sp. and
Sonneratia sp., both species with pneumatophores. A similar
difference in wave-energy reduction between species has also
been observed by Mazda, Magi, et al. (1997) and Mazda et al.
(2006) when comparing vegetation dominated by Sonneratia
sp. and K. candel, respectively.

Besides reducing the height of incoming waves, mangrove
forests probably also reduce wind-driven and tidal currents due
to their dense network of stems, branches, and aboveground
roots (Quartel et al., 2007). The mangrove trees in the study
area rise quite high above the water level (12.7 m on average)
and might efficiently reduce wind energy. Further studies on
this role of mangroves should be carried out, especially in the
Mekong Delta area, where the windy season has a strong
influence on the coastline. Increasing the sea level in the model
up to 0.96 m, thus anticipating a possible SLR due to climate
change, did not reduce the wave-energy dissipation potential of

ACKNOWLEDGMENTS
We thank the Department of Agriculture and Rural
Development of Ben Tre Province and the Management
Board of Thanh Phu Natural Reserve for their unstinting
support for data collection and field survey. The work
reported here was undertaken as part of the research
programme ‘‘PRoACC—Postdoctoral Research Programme
on Climate Change Adaptation in the Mekong River Basin’’.
The project is funded by the Netherlands Ministry of
Development Cooperation (DGIS) through the UNESCOIHE Partnership Research Fund. This research project is a

Journal of Coastal Research, Vol. 00, No. 0, 0000


0

Cuc et al.

joint initiative of UNESCO-IHE Institute for Water Education and many partner institutions in the Lower Mekong
countries and China.

LITERATURE CITED
Alongi, D.M., 2008. Mangrove forests: resilience, protection from
tsunamis, and responses to global climate change. Estuarine
Coastal Shelf Science, 76(1), 1–13.
Bates, B.C. Kundzewicz, Z.W. Wu, S., and Palutikof, J.P. (eds.), 2008.
Climate Change and Water. Technical Paper of the Intergovernmental Panel on Climate Change. IPCC technical Paper Vi.
Geneva: IPCC Secretariat, 210p.
Ben Tre DARD (Department of Agriculture and Rural Development)
Staff, 2010. Results of Inventory and Planning Three Kinds of
Forests in Ben Tre Province. Ben Tre, Vietnam: Department of
Agriculture and Rural Development, 290p. [in Vietnamese].
Ben Tre Statistics Office Staff, 2010. Statistical Yearbook, 2010. Ben
Tre, Vietnam: Ben Tre Services of Culture and Information, 345p.
[in Vietnamese].
Byrnes, J.E. Reed, D.C. Cardinale, B.J. Cavanaugh, K.C. Holbrooks,
S.J., and Schmitts, R.J., 2011. Climate-driven increases in storm
frequency simplify kelp forest food webs. Global Change Biology,
17, 2513–2524.
CCFSC (Central Committee Flood and Storm Control) Staff, 2001.
Second National Strategy and Action Plan for Disaster Mitigation
and Management in Viet Nam—2001 to 2020. Hanoi: Central
Committee Flood and Storm Control, Ministry of Agriculture and
Rural Development, 58p.
Clough, B. and Phan, V.H., 2010. Mangroves and Coastal Erosion in
the Context of Resilience to Climate Change Impacts in the
Southern Mekong Delta, Viet Nam. Mekong Photo Contest. http://
mekong-photocontest.com.

de Oude, R. Augustijn, D. Dekker, F. Wijnberg, K. de Vries, M., and
Suzuki, T., 2010. Modelling wave attenuation by vegetation in
SWAN to determine a vegetation field for decreasing dike height in
the Noordwaard, the Netherlands. Environmental Hydraulics, 1,
253–258.
English, S. Wilkinson, C., and Baker, V., 1994. Survey Manual for
Tropical Marine Resources. Townsville, Queensland, Australia:
Australian Institute of Marine Science, 368p.
Fabrice, G.R. and Claudia, K. (eds.), 2012. The Mekong Delta System
Interdisciplinary Analyses of a River Delta. Dordrecht, The
Netherlands: Springer Environmental Science and Engineering,
463p.
FIPI (Forest Inventory and Planning Institute) Staff, 1982. Results of
Review and Planning of Coastal Protection Forests. Hanoi City,
Vietnam: Forest Inventory and Planning Institute, 50p. [in
Vietnamese].
FIPI Staff, 2001. Results of National Forest Survey Following
Decision No. 03/2001 QD/TTG of the Prime Minister, dated 5
January 2001. Hanoi, Vietnam: Forest Inventory and Planning
Institute, 48p. [in Vietnamese].
FIPI Staff, 2007. Results of National Forest Survey Following
Decision No 405/TTg-KTN of the Prime Minister, dated March
16, 2009. City, Vietnam: Forest Inventory and Planning Institute,
64p. [in Vietnamese].
Fonseca, M.S. and Cahalan, J.A., 1992. A preliminary evaluation of
wave attenuation by four species of seagrass. Estuarine Coastal
Shelf Science, 35, 565–576.
Hasselmann, K. Barnett, T. Bouws, E. Carlson, H. Cartwright, D.
Enke, K. Ewing, J. Gienapp, H. Hasselmann, D. Kruseman, P.
Meerburg, A. Muller, P. Olbers, D. Richter, K. Snell, W., and

Walden, H., 1973. Measurements of Wind-Wave Growth and Swell
Decay During the Joint North Sea Wave Project (JONSWAP).
Hamburg, Germany: German Hydrographic Institute, 95p.
Hong, P.N. (ed.), 1999. Mangroves of Viet Nam. Hanoi: Vietnam:
Agricultural Publishing House, 205p.
Hong, P.N. and San, H.T., 1993. Mangroves of Viet Nam. Bangkok:
International Union for the Conservation of Nature, 173p.

Kathiresan, K. and Rajendran, N., 2005. Coastal mangrove forests
mitigated tsunami. Estuarine Coastal Shelf Science, 65, 601–606.
Knutson, P.L., 1988. Role of coastal marshes in energy dissipation
and shore protection. In: Hook, D.D. McKee, W.H., Jr. Smith, H.K.
Gregory, J. Burrell, V.G., Jr. DeVoe, M.R. Sojka, R.E. Gilbert, S.
Banks, R. Stolzy, L.H. Brooks, C. Matthews, T.D., and Shear, T.H.
(eds.), The Ecology and Management of Wetlands, 1: Ecology of
Wetlands. Portland: Timber Press, pp. 161–174.
Lewis, R.R. and Streever, B., 2000. Restoration of Mangrove Habitat.
WRP Technical Notes Collection (ERDC TN-WRP-VN-RS-3.2).
Vicksburg, Mississippi: U.S. Army Engineer Research and
Development Center, 7p.
MARD (Ministry of Agriculture and Rural Development) Staff, 2011.
Decision 1828/QD-BNN-TCLN, dated August 11, 2011, on Status of
National Forest in the Year 2010. Hanoi, Vietnam, 65p.
Massel, S.R. Furukawa, K., and Brinkman R.M., 1999. Surface wave
propagation in mangrove forests. Fluid Dynamics Research, 24,
219–249.
Maurand, P., 1943. L’Indochine forestiere. Institut de Recherches
Agronomiques et Forestiers de l’Indochine, impr. d’ExtrˆemeOrient, 254p.
Mazda, Y. Magi, M. Kogo, M. and Hong P.N., 1997. Mangroves as a
coastal protection from waves in the Tong King delta, Viet Nam.

Mangroves Salt Marshes, 1, 127–135.
Mazda, Y. Magi, M. Ikeda, Y. Kurokawa, T., and Asano, T., 2006.
Wave reduction in a mangrove forest dominated by Sonneratia sp.
Wetlands Ecology and Management, 14, 365–378.
Mazda, Y. Wolanski, E. King, B. Sase, A. Ohtsuka, D., and Magi, M.,
1997. Drag force due to vegetation in mangrove swamps.
Mangroves Salt Marshes, 1, 193–199.
Mendez, F.M. and Losada, I.J., 2004. An empirical model to estimate
the propagation of random breaking and nonbreaking waves over
vegetation fields. Coastal Engineering, 51, 103–118.
MONRE (Ministry of Natural Resources and Environment), 2009.
Climate Change, Sea Level Rise Scenarios for Viet Nam. Hanoi:
Ministry of Natural Resources and Environment, Hanoi Press, 34p.
MONRE, 2010. Sea Level Rise Scenarios and Possible Disaster Risk
Reduction. Hanoi: Viet Nam Institute of Meteorology, Hydrology
and Environment, Ministry of Natural Resources and Environment, Hanoi Press, 80p.
Narayan, S. Suzuki, T. Stive, M. Verhagen, H. Ursem, W., and
Ranasinghe, R., 2010. The effectiveness of mangrove in attenuating
cyclone induced waves. In: Proceedings of the 32nd International
Conference on Coastal Engineering, Shanghai, China, (in press).
Ngo An, 2004. Contributing to the Research on Mangrove Land Use
Planning of Ben Tre Province on a Sustainable Development Basis.
Ho Chi Minh City, Vietnam: Ho Chi Minh Press, 38p. [in
Vietnamese].
Quartel, S. Kroon, A. Augustinus, P.G.E.F. van Santen, P., and Tri,
N.H., 2007. Wave attenuation in coastal mangroves in the Red
River Delta, Viet Nam. Journal of Asian Earth Sciences, 29, 576–
584.
Rollet, B., 1981. Bibliography on Mangrove Research 1600–1975.
UNESCO, Paris, France, 479p.

Sarpkaya, T. and Michael, I., 1981. Mechanics of Wave Forces on
Offshore Structures. Van Norstrand Reinhold Company Publisher,
New York, United States, 651p.
Sub-FIPI (Sub–Forest Inventory and Planning Institute) II Staff,
1995. Master Plan for the Forestry Economy Development in the
Pivotal Ecological Zone of the Mekong Coastal Delta, Ho Chi Minh
City: Sub–Forest Investigation and Planning Institute II Press,
53p. [in Vietnamese].
Sub-FIPI II Staff, 1998. Investment Plan for Thanh Phu Wetland
Natural Reserve, Thanh Phu District, Ben Tre Province, 1999–
2003. Ho Chi Minh City: Sub–Forest Investigation and Planning
Institute II Press, 48p. [in Vietnamese].
Sub-FIPI II Staff, 2003. Findings from Wetlands Classification and
Inventory of Wetlands/Aquatic Ecosystem in the Mekong Basin,
Viet Nam. Ho Chi Minh City: Mekong River commission—Viet
Nam National Mekong Committee—Environment programme,

Journal of Coastal Research, Vol. 00, No. 0, 0000


Modelling the Impacts of Mangrove Vegetation Structure on Wave Dissipation

Sub–Forest Investigation and Planning Institute II Press, 64p. [in
Vietnamese].
Suzuki, T.; Marcel, Z.; Bastiaan, B.; Martijn, C.M., and Siddharth, N.,
2011. Wave dissipation by vegetation with layer schematization in
SWAN. Coastal Engineering, 59, 64–71.
TU Delft (Delft University of Technology), 2011. SWAN. www.swan.
tudelft.nl.
Vo-Luong, P. and Massel, S., 2008. Energy dissipation in non-uniform

mangrove forests of arbitrary depth. Journal of Marine Systems,
74, 603–622.

0

Vu, T.T., 1994. Estuarine Ecosystems of Viet Nam. Hanoi, Vietnam:
Scientific and Technical Publishing House, 271p.
Wamdi Group, 1988. The WAM model—a third generation ocean
wave prediction model. Journal of Physical Oceanography, 18,
1775–1810.
Wolanski, E. Mazda, Y. Furukawa, K. Ridd, P. Kitheka, J. Spagnol,
S., and Stieglitz, T., 2001. Water circulation in mangroves, and its
implications for biodiversity. In: Wolanski, E. (ed.), Oceanographic
Processes of Coral Reefs. London: CRC, pp. 53–76.

Journal of Coastal Research, Vol. 00, No. 0, 0000