Developing Effective Vegetation

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Developing effective vegetation

bioshield for tsunami protectionN. Tanaka

a, N. A.K. Nandasena

a, K. B.S.N. Jinadasa

a, Y. Sasaki

a , K. Tanimoto a & M. I.M. Mowjood ba

Graduate School of Science and Engineering, Saitama University,

Saitama, Japanb

Faculty of Agriculture, University of Peradeniya, Sri Lanka

Published online: 23 Apr 2009.

To cite this article: N. Tanaka , N. A.K. Nandasena , K. B.S.N. Jinadasa , Y. Sasaki , K. Tanimoto

& M. I.M. Mowjood (2009) Developing effective vegetation bioshield for tsunami protection, Civil

Engineering and Environmental Systems, 26:2, 163-180, DOI: 10.1080/10286600802435850

To link to this article: http://dx.doi.org/10.1080/10286600802435850

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Civil Engineering and Environmental Systems

Vol. 26, No. 2, June 2009, 163180

Developing effective vegetation bioshield for tsunami protection

N. Tanakaa*, N.A.K. Nandasenaa, K.B.S.N. Jinadasaa, Y. Sasakia, K. Tanimotoa and

M.I.M. Mowjoodb

a Graduate School of Science and Engineering, Saitama University, Saitama, Japan; bFaculty ofAgriculture, University of Peradeniya, Sri Lanka

(Received 1 August 2007)

To elucidate the effectiveness and limitations of coastal vegetation for tsunami protection, the impact ofvegetationstructure on dragforces wasanalysed using the observed characteristics of reference treespecies.The drag coefficient, including the vertical stand structures of trees, Cdall , and thevegetationthickness perunitarea, dNu (d, reference diameterof trees; Nu, number of trees per unitarea),variesgreatly with differentspecies.Based on dataanalyses, dense Casuarina equisetifolia and Pandanus odoratissimus grown in beachsand were found to be especially effective in providing protection from tsunami damage dueto their densityand complex aerial root structure. The breaking moment of trees was investigated as a function of treediameter. The breaking moment equation of P. odoratissimus explains well the damage caused to trees bythe 2004 Indian Ocean tsunami and the 2006 Java tsunami. Numerical simulation indicates that inertia isthe dominant force (99.1%) in comparison with the drag force when a wave front collides with a vegetation

face, but while the water depth is very shallow and the total force is 6% of the maximum. Drag resistanceis the dominant force in reducing both water depth and current velocity, but inertia resistance is active inreducing current velocity only in front of the vegetation. The breaking condition of trees can be discussedby the drag-force moment alone because when the total moment reaches the maximum, the contribution ofthe inertia moment is in the range of 0.10.3%. Considering the limitations of P. odoratissimus in reducingtsunami water depth and the other roles that coastal vegetation can play in mitigating tsunami-relateddamage, a forest with two layers in the vertical direction of P. odoratissimus and dense C. equisetifoliawas found to be effective for increasing drag and trapping floating debris.

Keywords: Pandanus odoratissimus; Casuarina equisetifolia; tsunami protection; coastal vegetation;numerical simulation

1. Introduction

The recent Indian Ocean tsunami not only caused destruction of life and property but also massive

damage to the coastal ecosystem as well as itseconomic bases.This damage has brought to light the

urgent need to develop tools to mitigate tsunami and other natural disasters in the coastal regions.

This is especially felt by countries like Sri Lanka that had never experienced damage on such a

scale. In this context, various organisations and researchers are currently involved in developing

appropriate technologies for tsunami mitigation for developing countries like Sri Lanka.

Coastal vegetation provides a range of protection options and economic revenue sources for

coastal communities. The potential benefits of vegetation are mainly the capacity to mitigate

*Corresponding author. Email: [email protected]

ISSN 1028-6608 print/ISSN 1029-0249 online 2009 Taylor & FrancisDOI: 10.1080/10286600802435850http://www.informaworld.com


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164 N. Tanaka et al.

the adverse impacts of natural disasters like tsunamis, storms, and cyclones, to control coastal

erosion, and to enhance fishery potentials of the adjacent coastal waters by providing organic

and inorganic nutrients. To realise the potential benefits of coastal vegetation, a holistic coastal

resource management approach incorporating coastal vegetation has to be implemented with due

consideration to the socio-economic and scientific aspects of such a strategy.

The bioshield is a concept that enhances the ability of the natural ecosystem to protect people and

their livelihoods by conserving, managing, and restoring coastal vegetation, wetlands, mangroves,

spawning areas, sand dunes, seagrass beds, coral reefs, and other coastal environments. It is of

utmost importance to conduct scientific analyses before the bioshield concept is implemented.

Following proper scientific analysis, the implementation of findings has to be matched to real

ground conditions. This might be the most difficult part because it has to incorporate the socio-

economic conditions of coastal communities and will need the extensive cooperation of local

government authorities, non-government organisations, and other stakeholders. The bioshield

concept has been found to be promising for developing countries due to limitations of funds for

capital investment. A hard-structure solution could also severely affect the tourism industries ofthese countries because it would limit the aesthetic attraction of waterfronts.A bioshieldcombining

coastal vegetation, sand dunes, coral reefs, mangroves, and other natural coastal ecosystems can

be an environmentally friendly and sustainable management strategy to mitigate tsunami and

other coast-related natural disasters in developing country contexts (Fernando et al. 2005).

Previous studies have revealed that coastal vegetation can play a significant role in reducing the

energy of tsunami waves and could reduce the damage to humans and coastal ecosystems (Shuto

1987, Mazda et al. 1997a, Kandasamy and Narayanasamy 2005, Dahdouh-Guebas et al. 2005,

Danielsen et al. 2005). Shuto (1987) also identified the potential of coastal vegetation to mitigate

tsunami waves by statistically analysing the physical damage suffered by pine trees in Japan.

Additionally, Tanaka et al. (2007) investigated damaged sites, classified coastal vegetation, andidentified effective tree species in Sri Lanka and Thailand. Although previous studies researched

coastal vegetation andother individual ecosystems separately to identify their potential for tsunami

protection, there has not been a systematic investigation into the combined effects of individual

unit ecosystems. The present study explores the effectiveness and limitation of coastal vegetation

combined with sand slopes as a protective bioshield tool for mitigating tsunami damage.

2. Field survey and analysis

2.1. Analysis of drag coefficient using representative species

Field investigations were conducted and damage to the southern coast of Sri Lanka and the

Andaman coast of Thailand by the 2004 Indian Ocean tsunami was described by Tanaka

et al. (2007). A similar study was carried out on the southern coast of Java Island for the 2006

Java tsunami by Tanaka and Sasaki (2007).

To analyse the physical characteristics of coastal vegetation, we considered the drag force, D,

due to vegetation (Mazda et al. 1997b, Nepf 1999) in the forest length, L (m), in the tsunami

direction with unit width (cross-stream direction) as:

D = n

h

0

1

2Cd(z)u(z) |u(z)| b(z)dz = n

1

2CdrefbrefU |U|

h

0

b(z)

bref

Cd(z)

Cdrefdz, (1)

n = L 1l1 l2

= Ll2

, (2)


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Civil Engineering and Environmental Systems 165

where z (m) is the height above the ground surface, h (m) is the tsunami water depth, Cd(z) is the

drag coefficient at height z, Cdref is the drag coefficient of a circular cylinder (=1 in this study),u(z) (m/s) is the stream-wise velocity at height z, U (m/s) is the depth-averaged velocity, b(z)

is the cumulative width of tree trunks and branches at height z, bref is the reference diameter at

1.2 m height, n is the number of trees per L (m) vegetation length to the tsunami current direction

and 1 m width (unit: trunks/(vegetation length (L) m 1 m)) defined by Shuto (1987), (kg/m3)is the density of the sea water, l1, l2 (m) are the spaces between the trees in shore and cross-shore

directions, respectively, and l (m) is the average space between the trees. In this research, the

difference in the stream-wise velocity at each height z, u(z), was not considered, and the average

velocity in depth, U (m/s), was used. (For details of the definition, refer Tanaka et al. 2007.)

Drag coefficients, including the vertical stand structure, Cdall, are defined as:

D = n 12

CdallU |U| brefh, (3)

Cdall = Cdref 1h

h0

b(z)bref

Cd(z)Cdref

dz = Cdref 1h

h0

(z) (z)dz, (4)

(z) = b(z)bref

, (5)

(z) = Cd(z)Cdref

, (6)

= 1h

h0

(z) (z)dz, (7)

where (z) is an additional coefficient that expresses the effect of cumulative width in each heightb(z) on the drag, (z) is an additional coefficient representing the effect of leaves or aerial roots

on the drag, and is the averaged value of (z)(z), in depth.

Shuto (1987) defined vegetation thickness as dn (cm/(vegetation length (L) m 1 m)), whered (cm) is a reference diameter at the height of 1.2 m from the ground. d was taken as cm for

comparison with Shuto (1987). Including vegetation stand structure and vegetation thickness per

unit area, dNu (cm/(unit vegetation area (m2))) was defined from Equations (4) to (7) as:

dNu = dn

L= dn

l2n= d

l2. (8)

Equations (4) and (8) are all related to the drag force in Equation (1). Cd

all is the characteristic

of the tree itself, and dNu is the characteristic of a unit vegetation area.

Additional drag by leaves was taken as the constant (z) = 1.25 (in leaf-bearing layers) or(z) = 1 (in leafless layers), referring to previous research (Fukuoka and Fujita 1990) for a thin-leaved tree, Casuarina equisetifolia. Pandanus odoratissimus has complex aerial root structures

that affect the drag coefficient (Tanaka et al. 2006). (z) at each height varied from 1.5 to 1

according to the spacing of the aerial roots (Furukawa et al. 1997, Nepf 1999, Tanaka et al. 2005).

For the leaf layer ofP. odoratissimus, there was no previous information on the additional drag due

to leaves, (z), so we conducted sensitivity analysis of this parameter by numerical simulation,

changing (z) from 1.25 to 2. This analysis revealed that leaf drag does not affect the total

drag force because P. odoratissimus has many aerial roots, and the drag produced by the aerial

roots is dominant. Therefore, the same constant, (z) = 1.25, was used for leaf layers of bothP. odoratissimus and C. equisetifolia. The height divided vertically, dz, was taken as 0.5 m.

Additional areas of the projecting aerial roots or branches were calculated by analysing the digital

photographs. The values ofd, b(z), n, L, l1, l2, and h in Equations (1) to (8) were obtained in the

field survey.


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The breaking strength was measured by a force gauge (Aikoh RX-100). The breaking moment

of a tree trunk or a first-order branch was calculated by the force and the length of the arm from

the node to the forcing point. Each experiment was conducted more than thrice for each species

as a principle, and the data was analysed using a video recorder. The threshold breaking moment

of a tree can be expressed by:

Mbc =maxI

R= max R

4/4

R=

4maxR

3 = 32

maxd3ref (9)

considering a circular cylinders shape, where R is the radius (m), dref is the reference diameter

(m), I is the second moment of the area, and max is the threshold bending shear stress (N/m2).

2.2. Numerical simulation analysis

2.2.1. Governing equations

To analyse the flow through the vegetation, modified one-dimensional depth-averaged equations

are used. Two-dimensional depth-averaged equations, including the Morrison force correction and

porosity enhancement, from which the volumetric effect of vegetation was rectified were devel-

oped (Nandasena et al. 2007). Here two-dimensional equations are reduced to one-dimensional

equations to simplify the problem. One-dimensional equations are written as follows.

Modified continuity equation:

hh

t+ Qx

x= 0. (10)

Modified momentum equation:

hQx

t+ (Q

2x / h)

x+ hgh

h

x+ 3/2h gh

z

x+ b

h

x

+

3/2

h

ki=1

fxi = 0, (11)

where h is the depth-averaged aerial porosity at water depth h, b is the bed aerial porosity due to

vegetation, Qx is the depth-integrated discharge, z is the bed elevation with respect to the selected

datum, x is the bed resistance, fxi is the total resistance generated by the vegetation (in this study,

drag and inertia are to be considered), g is the gravitational acceleration, and is the density of sea

water (taken as 1024 kg/m3). Assuming that vegetation can be modelled as cylindrical structures

in shape, porosity can be written as:

h = 1 m b2h

4, b = 1 m

b2b

4,

where bh is the depth-averaged tree width at water depth h, bb is the equivalent tree width on the

ground (because P. odoratissimus has many aerial roots on the ground), and m is the number of

trees per unit area.

Bed friction, drag, and inertia forces are modified to be compatible with the governing

equations as:

x = gn20Q2x /(hh7/3), Fdx =1

2 CdAQ2x / h2h and Fix = CM

d(Qx / h

h)

dt , (12)

where n0 = 0.025, Mannings roughness coefficient (Harada and Imamura 2006), Cd is the dragcoefficient, A is the drag area, CM is the inertia coefficient, and is the volume subjected to inertiaresistance (volume submerged in water).


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2.2.2. Numerical model validation

The existing data are not accurate enough for model validation. Thus, the following laboratory

experiment was conducted to validate the numerical model.

Experimental study: Figure 1a shows the details of the model bed that is fixed in a flume. The

flume was 18 m long, 0.4 m wide, and 0.75 m in height. The model bed consisted of two relatively

steep slopes, starting from 1:4.7 spanning 0.76 m and then connected to a 1:20.5 slope, which

has a length of 7.01 m. The effective horizontal length of the model bed was 14.27 m of the total

flume length of 18 m. Vegetation (trees) was represented by cylindrical rods whose diameter was

5 mm; the tree density was 2183 rods per unit area, and the porosity was 0.957. The vegetation

model was 1 m long in the wave propagation direction. Figure 1b depicts a plan view of the

arrangement of cylindrical rods in the bed. Six wave gauges (G1 to G6) were deployed to measure

the temporal water surface elevation. The vegetation model was placed between G5 (in front

of the vegetation model) and G6 (behind the vegetation model). The wave-generating system

(electric motor type) was capable of synthesising sinusoidal small-amplitude long wave profiles.The wave period was 20 s. Data were collected at a frequency of 5 Hz. The numerical model

was validated by experimental data with and without the vegetation model. Figure 2a shows the

wave height distribution calculated by the numerical model and experimental results at six wave

gauges without vegetation, while Figure 2b illustrates the results with vegetation. Good agreement

between experimental and numerical results is shown.

2.2.3. Parameter selection

Field investigations carried out post-tsunami demonstrated that densely grown coastal vegetation

can impose a considerable buffer against extreme oceanographic events (Tanaka et al. 2006, 2007).

Figure 1. Wave channel experiment: (a) experimental set-up and (b) details of vegetation model.


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Figure 2. Numerical model validation: (a) wave height distribution for model without vegetation, and (b) wave heightdistribution for model with vegetation. Nu, numerical; Ex, experimental.


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P. odoratissimus, a densely growing vegetation on sandy beaches, with a complex aerial root

structure that provides additional value to the drag coefficient, and young C. equisetifolia, a

species that grows densely on sandy beaches and provides a trapping effect, were selected for

simulations. The drag coefficient, Cd(z), ofP. odoratissimus varies from 1.5 to 1 at the root section

(Furukawa et al. 1997, Nepf 1999, Takemura and Tanaka 2007), and additional drag generated by

the leaves was taken as 1.25, based on previous research (Fukuoka and Fujita 1990). The average

tree height is 6 m, aerial root height is 2 m, reference diameter of the tree trunk, bref, at 1.2 m

from the ground level is 0.16 m, and density, the number of trees per unit area, m, =0.35. ForC. equisetifolia, Cd(z) = 1.0, the additional drag by leaves was taken as 1.25, the average treeheight is 10 m, the reference diameter of the tree trunk, bref, is 0.15 m, and the density, m = 0.44,were determined and calculated based on the respective field investigations (Tanaka et al. 2006,

2007). The general drag and inertia components were modified to represent vegetation resistance

as follows:

Fdx = m 12

Cdallbrefh Q2

xh2h

, (13)

Fix = mCMd.a.d(Qx / h

h)

dt, (14)

where CM = 2.0 (assuming a cylindrical shape) and d.a. is the the depth-averaged submergedtree volume subject to inertia forces.

Case 1 (100 m wide green belt of P. odoratissimus) and case 2 (200 m wide green belt of

P. odoratissimus) were selected to understand how effective it is to widen the green belt, and case

3 (100 m, two layers of vegetation, P. odoratissimus and young C. equisetifolia, in the vertical

direction) was selected to demonstrate the effectiveness of two layers of vegetation in comparison

with case 1. Cases 1 and 2 were divided into two parts. One part with drag ( D) vegetation

(resistance model) and another with drag + inertia (D + I model) served to demonstrate thevegetation resistance of each force component; bare land without vegetation (WV) served as

the control for comparison. In addition, tsunami characteristics at the start boundary of period,

20 min, and wave height, 3 m, were assumed. Figure 3 shows a schematic sketch of the topography

and plantation area. Water depth, current velocity, draginertia force, and draginertia moment

changes in the time scale were obtained in front of, in the middle of, and behind the vegetation

for cases 1, 2, and 3, respectively.

Figure 3. Schematic sketch of simulation topography selected for analysis. WD, deep-sea water depth, is 200 m; HL,horizontal length, is 5000 m; SL, slope length, is 20,000 m; 1:S, slope, is 1:100 (neither too gentle nor too steep); C,distance from shoreline to vegetation front, is 20 m; VW, vegetation width, for case 1 is 100 m (P. odoratissimus), case 2 is2 0 0 m (P. odoratissimus), and case 3 is 100 m with two layers of vegetation (starts with a 5 m thick belt ofP. odoratissimus,followed by a 5 m thick belt ofC. equisetifolia, and continues the same pattern up to 100 m).


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3. Results and discussion

3.1. Drag characteristics and validation by breaking conditions of representative trees

Figure 4a shows the variations of Cdall calculated with an average tree diameter for differenttsunami water depths. The value of Cdall was close to the value obtained for mangrove trees(Wolanski et al. 1980). The difference becomes clearer if we include the density difference,

because trees that have aerial roots, P. odoratissimus andRhizophora apiculata, or young C. equi-

setifolia, can grow densely. Figure 4b shows the variations of dNu calculated with the average

diameter for different tsunami heights. If we expect a forest to provide protection against a tsunami

more than 10 m in height, young C. equisetifolia (e.g. d= 15 cm) is effective because it growsdensely and is not broken by the tsunami. Because it is a self-thinning tree, the dNu of large-

diameter C. equisetifolia is quite small, almost the same as that of Cocos nucifera (coconut tree).

Age had a quite important effect in the case of C. equisetifolia.

Figure 5 shows the breaking moment curve of representative tree species classified into threeparts by elasticity and habitat. GP1 is the curve for coastal vegetation (including P. odoratissimus),

Figure 4. Physical characteristics of representative vegetation: (a) relationship between Cdall and tsunami water depth,and (b) relationship between dNu and tsunami water depth.


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Figure 5. Breaking moment of representative coastal vegetation as a function of tree diameter. B, broken; NB, notbroken.

GP2 is the curve for elastic trees, and GP3 is the curve for trees with hard trunks (including

C. equisetifolia).

The breaking moment equations for GP1, GP2, and GP3, MGP1, MGP2, and MGP3 (Nm),

respectively, are:

MGP1 = 4.45 dbh2.62, (15)MGP2 = 6.30 dbh2.86, (16)MGP3 = 20.52 dbh2.83, (17)

where dbh is the diameter (cm) of a tree at breast height. The decision coefficient for each equation

is shown in Figure 5.

The max in Equation (9) is assumed to change, especially while the trees are young. In addition,

we want to apply the function not to each species but to each representative group. Therefore,

the power is slightly changed from a dbh3

function. Although the breaking test was conducted inSri Lanka before the 2006 Java tsunami, the breaking condition in Equation (15) for GP1 trees

expressed well the damage situation at the sites of the Java tsunami (Batuhue and Pangandaran

in Figure 6a). However, the breaking condition for C. equisetifolia (GP3 group) was not satisfied

(Figure 6b). C. equisetifolia does not have aerial roots, but its diameter is greater at the ground

level than at breast height with increasing age. Thus, its trunks were rarely broken. Most of the

damage to C. equisetifolia was uprooting. Therefore, the breaking moment is assumed to be larger

than the shear stress between the roots and soil. This indicates that the breaking condition is not

well expressed by the breaking test. Further study of the breaking or uprooting conditions for

C. equisetifolia is required with a real-scale breaking or uprooting test. Meanwhile, an empirical

curve for C. equisetifolia is proposed as:

MGP3R = 4.9 (1.5dbh)3. (18)

Tanaka and Sasaki (2007) showed the height at which P. odoratissimus and C. nucifera trees

were broken, and the threshold tsunami water depth for tree trunk breaking was about 80% of


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Figure 6. Validation of breaking moment as a function of tree diameter. Plot data were calculated with Cdall andtsunami water depth from the 2004 Indian Ocean tsunami or the 2006 Java tsunami. Dashed lines were obtained by apulling test. (a) P. odoratissimus and (b) C. equisetifolia.

the tree height for P. odoratissimus in the two tsunamis. C. nucifera was seldom damaged except

for small trees, and the critical tsunami height was 80%, the same as P. odoratissimus. Because

the breaking point of P. odoratissimus is 12 m high, the moment by drag at that point is smaller

than that of a tree without aerial roots. Although the threshold tsunami water depth for breaking

P. odoratissimus is similar to that for C. nucifera, its trunk strength is not great because it receives

a large drag force and reduces tsunami energy at a certain tsunami water depth.

Therefore, we need to combine different trees in the forest. P. odoratissimus was observed to

grow under the shade of the taller C. nucifera and C. equisetifolia. In field observations, two layers

of vegetation, P. odoratissimus and C. equisetifolia, in the vertical direction exhibited a strongpotential to decrease the damage behind the vegetation cover (Kalutara), but a combination of

P. odoratissimus and C. nucifera had little additional effect (Hikkaduwa, Habaraduwa) because

they have a wide gap in the vertical direction. Considering this and the drag characteristics shown

in Figure 4, C. equisetifolia is appropriate for mixed vegetation. If it does not break, it traps


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debris. Considering the other roles (trapping debris and providing something to climb or a soft-

landing place for people) that coastal vegetation plays (Tanaka et al. 2006), a two-layer forest of

P. odoratissimus and dense C. equisetifolia should be planted or preserved near the coast, and

other broad-leaved trees should be grown behind the forest (landward side).

3.2. Numerical simulation results

It is essential to define the ratio parameters to compare the results with resistance models and

the bare land model. The ratio that follows indicates the increment or decrement of hydraulic

properties for resistance models with respect to the bare land model:

Percentage change = Max value in with vegetation Max value in without vegetationMax value in without vegetation

%

Figure 7ac shows the water depth fluctuation; Figure 7df demonstrates the corresponding vari-

ation in current velocity at the time in front of, in the middle of, and behind the vegetation for

Figure 7. Temporal variation of water depth (a) at the front edge, (b) in the middle, and (c) behind. Current velocity(d) in front, (e) in the middle, and (f) behind the vegetation in case 1. WV, without vegetation; D, only drag resistance;D + I, drag and inertia resistances.


13/19


case 1. Tables 1, 2, and 3 show the percentages of maximum water depth change, maximum

current velocity change for both landward and offshore areas for D and D + I models withoutvegetation case at locations in front of, in the middle of, and behind the vegetation for cases 1,

2, and 3, respectively. Figure 8 shows temporal variations of the hydraulic force on a tree (on the

primary Y-axis) and water depth (on the secondary Y-axis) for case 1. The corresponding tables

in Figure 8 show the percentage contribution of force components (inertia and drag) to total force

when each force is maximum, and the percentage of total force in maximum total force and the

percentage of water depth in maximum water depth in the time cycle. Figure 9 shows the temporal

variation of moment on a tree (on the primary Y-axis) and water depth variation (on the secondary

Y-axis) for case 1. The corresponding tables in Figure 9 show the percentage of drag and inertia

moment in total moment, percentage of total moment in maximum total moment, and percentage

of water depth in maximum water depth when each moment is maximum and when maximum

water depth occurs. Tables 4 and 5 explain the assessment of vegetation damage and show the

percentage of maximum water depth in average tree height and the percentage of maximum total

moment in the breaking moment for cases 1 and 3, respectively.It is evident from Figure 7a that resistant model results can express well the wave reflection on

the vegetation front. The percentage of change in the maximum water depth is the same for both

D and D + I models. An increase in the green belt width can magnify the maximum water depthat the vegetation front. Figure 7d shows the corresponding current velocity variation at the point

in which the vegetation front is subjected to a suddenly approaching water current, followed by

a swift drop to generate the maximum inertia force, as shown in Figure 8a, which is 99.1% of

Table 1. Percentage change of maximum water depth (+, increment, , decrement); other notationsare defined in Figure 3.

Front Middle Behind

Water depth % D D + I D D + I D D + I

Case 1 1.9 1.9 11.5 11.5 17.3 17.2Case 2 1.0 1.0 10.4 10.4 29.7 29.6Case 3 3.2 3.2 10.3 10.3 13.8 13.8

Note: Case 1 = 100 m vegetation, case 2 = 200 m vegetation, and case 3 = 100 m, two vertical layers of vegetation.

Table 2. Percentage changeof maximum current velocity landward (+, increment,, decrement);other notations are defined in Figure 3.

Front Middle BehindCurrent velocity %

(direct to land) D D + I D D + I D D + I

Case 1 10.5 14.7 56.2 56.4 43.4 43.2Case 2 10.5 14.7 59.6 59.5 50.1 49.8Case 3 10.3 14.1 48.8 49.7 37.1 36.9

Table 3. Percentage change of maximum current velocity seaward (+, increment, , decrement);other notations are defined in Figure 3.

Front Middle Behind

Current velocity %(direct to offshore) D D + I D D + I D D + I

Case 1 26.9 26.7 59.2 59.1 63.7 63.6Case 2 32.9 32.7 69.7 69.5 72.4 72.2Case 3 22.1 21.9 51.2 51.1 57.5 57.4


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Figure 8. Temporal variation of hydraulic force on a tree (a) at the front edge, (b) in the middle, and (c) behind theedge of the vegetation on the primary Y-axis, and water depth variation on the secondary Y-axis, respectively, in case 1.Corresponding tables show when each force component (drag or inertia) becomes a maximum, the contribution of each(I%, D%) to total force, the percentage of total force to maximum total (Tf/Mtf)%, and the percentage of water depth tomaximum water depth (Wd/Mwd)%, respectively (ve denotes force directly opposite to water flow).

the total force generated during the time. However, the percentage of total force in the maximum

total force is about 6%, and the percentage of water depth to the maximum water depth is 0.5%

at the same time, which means that the inertia force is negligible in the presence of a drag force,

as shown in Figure 8a. The drag force is dominant in the time cycle except at the very beginning;

it is 94.3% of the total force (D + I ), which is 99.8% of the maximum total force when themaximum drag force occurs, where the percentage of water depth in the maximum water depth

is about 13.2%. However, when the maximum water depth occurs, the drag force becomes less

than that of the maximum drag due to current velocity decrement. The drag force reduces both

the maximum water depth and the current velocity, and the inertia effect is negligible in reducing

the maximum water depth at the vegetation front, but reduction of the maximum positive currentvelocity is remarkable, as shown in Table 2. The maximum back current velocity is reduced when

the vegetation belt widens. To discuss the assessment of vegetation damage, calculated moments

were compared with breaking moment relations derived by field tests. It is clear from the results

shown in Figure 9 and Table 4 that the vegetation front is at a high risk of being broken by the


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Figure 9. Temporal variation of hydraulic moment on a tree (a) at the front edge, (b) in the middle, and (c) behind thevegetationon the primary Y-axis, and water depth variation on the secondary Y-axis, respectively, in case1. Correspondingtables show when each moment component (drag or inertia) and water depth becomes a maximum, the contribution ofeach (I%, D%) to total moment, the percentage of total moment to maximum total (Tm/Mtm)%, and the percentage ofwater depth to maximum water depth (Wd/Mwd)%, respectively (ve denotes moment directly opposite to water flow).

tsunami flow. The moment when the drag force is dominant and maximum (99.9% out of the total,

almost drag moment) occurs just before the maximum water depth occurs. When the maximum

water depth occurs, the moment due to the drag is of 99.7% of the total moment. According to

field observations, when the water depth exceeds 80% of the height of P. odoratissimus, the tree

will break. However, as shown in Table 4, the percentage of maximum water depth in average tree

height is 83.1%, which confirms field observations of when damage occurs, but the percentage of

maximum moment to the breaking moment is 7.8%, which indicates that the vegetation is safe,

leading to a contradiction. This indicates that the breaking criteria are not only governed by the

water depth limitation, but that the current velocity is also pertinent.

It is clearly shown by Figure 7b that the water level drop is due to resistance provided by

vegetation. Table 1 indicates that the percentage reduction of maximum water depth is about11.5%, but the D and D + I difference is negligible in the middle of the vegetation because theinertia effect becomes negligible as the velocity profile is flattened due to resistance. The maximum

inertia force is 9.4% of the total force when the percentage of total force in the maximum total

force is 23.5% and the percentage of water depth in the maximum water depth is 5.5%. The


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Table 4. Percentage of maximum water depth to average tree height and percentage of maximum moment to breakingmoment in the front, middle and behind the edge of vegetation, respectively, in case 1.

(Maximum water depth/average tree height)% (Maximum moment/breaking moment)%

Damage assessment Front Middle Behind Front Middle Behind

Case 1 83.1 69 58.9 7.8 3.9 1

Table 5. Percentage of maximum water depth to average tree height and percentage of maximum moment to breakingmoment in the front of the vertical two layers (P. odoratissimus and C. equisetifolia) of vegetation.

Damage assessment Front

Species P. odoratissimus C. equisetifolia

Case 3 (Maximum water d epth/average tree height)%

(Maximum moment/breaking moment)%

(Maximum water depth/average tree height)%

(Maximum moment/breaking moment)%

82.1 9.5 48.5 2.2

maximum drag force is 99.4% in the total force when the percentage of water depth is 43.6% of

the maximum water depth. This demonstrates that the inertia force effect is negligible against the

drag force in the middle of the vegetation. According to Table 2, the maximum positive current

velocity decreases by more than 50% in the middle of the vegetation in comparison with bare

land, demonstrating that current velocity reduction is dominant compared with the water depth

reduction. Reduction of the maximum back current also shows a trend similar to reduction of the

forward current, but is a little higher. The moment (Figure 9b) follows a similar pattern at the

vegetation front, but the peak values are reduced due to both water depth and current velocityreduction.

A rather interesting location in this research study is the area behind the vegetation, where

water depth, current velocity, and hydraulic force are decreased by the green belt to form a

favourable environment for the protection of humans, animals, and the infrastructure in a tsunami

event. Figure 7c indicates the initial difference between the data curves, showing that the delay

in a tsunami arriving behind the vegetation is about 23 s for a 100 m belt and 60 s for a 200 m

belt. Table 1 shows that the reduction in maximum water depth behind the vegetation is high in

comparison with that in the front and middle due to the full vegetation belt resistance to water flow.

The difference between the effects of D and D + I on water depth is minimal. Doubling the beltwidth does not halve the maximum water depth, but lowers it by about 17% for case 1 and 30%

for case 2 for selected slope and wave conditions. The percentage reduction of maximum positive

current velocity is slightly lower than in the case of behind the vegetation due to a slight increase

in velocity when the rear boundary passes, as shown in Table 2. The percentage reduction of the

maximum back current velocity is the highest due to blocking and resistance. This circuitously

demonstrates that the decrease in the water level behind a long vegetation strip takes considerably

longer in comparison with a vegetation patch, which is what is mostly available in reality. Moment

(Figure 9c) follows a similar trend both in front and in the middle of vegetation, but peak values

are greatly reduced due to total vegetation resistance, and the maximum total moment behind the

vegetation is decreased by approximately 17% in comparison with the maximum in front.

Finally, we compared P. odoratissimus, case 1, and two-layer vegetation in a vertical direction,

P. odoratissimus and C. equisetifolia, case 3, to propose a representative vegetation belt for the wetzone in Sri Lanka. Tables 1, 2, and 3 show that the reduction of water depth and current velocity

for case 3 is a little lower than in case 1, but not significant. Furthermore, the tsunami delay for

case 3 is 19 s, and for case 1, it is 23 s. Simulation results also suggest that C. equisetifolia has

more potential than P. odoratissimus against breaking as a percentage of maximum water depth to


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average tree height, and the maximum total moments to breaking moments are 48.5% and 2.2%,

respectively, as shown in Table 5.

3.3. Effective vegetation structure on ground slope

The drag characteristics of representative species are quite different, and they change the disaster

situation behind vegetation (Tanaka et al. 2007, Tanaka and Sasaki 2007). Figure 4 illustrates that

P. odoratissimus is obviously effective in a tsunami, but the breaking moment of its trunk is not

large compared with other species (Figures 5 and 6). P. odoratissimus is broken when the tsunami

water is deeper than 80% of the tree height (Tanaka and Sasaki 2007). However, a numerical

simulation suggests that not only water depth, but the current velocity also affects the breaking

criteria. P. odoratissimus is not tall compared with C. equisetifolia, and it is easily broken if the

tsunami water is deeper than 5 m. Young C. equisetifolia can grow densely (Tanaka et al. 2007),

and its drag is slightly larger than that of C. nucifera. Thus, we propose combined vegetation of

Figure 10. Effective vegetation structure and species on a sand dune.


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P. odoratissimus and C. equisetifolia. A numerical simulationshows that the reduction of hydraulic

properties, water depth, and current velocity of the aforesaid combination (case 3) is only slightly

lower than that of P. odoratissimus alone (case 1), but together they are not destroyed by high

water and have other effective roles in a tsunami event. Moreover, considering biodiversity and

the aesthetics of the beach front, we envisage that a representative vegetation type of the wet

zone of Sri Lanka would be as shown in Figure 10. In this figure, we have considered the other

roles (Tanaka et al. 2007) of coastal vegetation. Prior to implementation, a pilot study of a coastal

vegetation landscape project like that proposed here should be made on real ground, and further

explorations should be incorporated into enhanced two-dimensional numerical simulations.

4. Conclusions

The inertia effect is dominant in comparison with the drag effect for a short time when a wavefront collides with a vegetation face, while the water is comparatively shallow. Drag resistance

is responsible for reducing both water depth and current velocity, but inertia resistance is active

in reducing the current velocity only in front of the vegetation. The breaking condition of trees

can only be discussed in terms of the drag-force moment because when the moment becomes

a maximum, the contribution of the inertia moment is only 0.10.3%. The breaking criteria of

coastal vegetation cannot be discussed only in terms of tsunami water depth, but consideration

of a combination of both current velocity and water depth is necessary. If there is no limitation

of space, a coastal green belt should be as wide as possible; however, doubling the thickness of

vegetation belt will not halve the water depth behind the vegetation.

The data analysis identified appropriate coastal vegetation species for dissipating tsunamienergy. Considering the limitations of trees with increasing tsunami water depth and the other

roles that coastal vegetation plays, it was found that two layers of forest in the vertical direc-

tion with P. odoratissimus and dense C. equisetifolia are useful for increasing drag and trapping

floating objects and broken branches.

Constructing a green belt takes time and is sometimes prevented by the current land use.

However, the interval between tsunamis is considered to be longer than the period required for

forest development, and disasters will possibly occur in the future. Therefore, more consideration

of the planting and management of coastal vegetation from the viewpoint of landscape and urban

planning based on scientific studies is necessary.

Acknowledgements

This study was specially funded by the Heiwa Nakajima Foundation for research in Sri Lanka. Professor D.R.I.B.Werellagama of the University of Peradeniya, and Professor S. Samarawickrama and Professor J. Manatunge of theUniversity of Moratuwa are acknowledged for their useful suggestions during field investigations in Sri Lanka.

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