45
differ considerably from other mangroves because of the dominant tree species —
Sonneratia apetala, Heritiera fomes, H. littoralis and several species of Avicennia.
In order to critically analyse the defensive role of mangroves three situations were
identified: (1) A village in the shadow of mangroves; (2) a village not in the shadow
of mangroves and with no embankment; and (3) a village not in the shadow of mangroves, but with an embankment on the seaward side. Bankual village was in the
shadow of a mangrove forest, Singidi village was neither in the shadow of mangroves nor protected by an embankment from storm surge and Bandhamal village
was not in the shadow of mangroves, but had a seaward side embankment. The
report indicated that the intensity of the impact of the 1999 cyclone on these villages should have been fairly uniform, as all the three selected villages were equidistant from the seashore and had similar aspects. The two villages outside mangrove
cover were located close to each other, but both were far from the mangrove forest
in order to eliminate any effect of mangrove forest presence.
It was documented after the study that the loss incurred per household was greatest (US$153.74) in the village that was not sheltered by mangroves but had an
embankment, followed by the village that was neither in the shadow of mangroves
or the embankment (US$44.02) and the village that was protected by mangrove
forests (US$33.31).
A number of studies indicate that the resistance offered by mangroves (in terms
of magnitude) to storm induced waves is a function of few important biotic and
abiotic variables. The biotic variables include the density of mangroves (relative
abundance), above ground biomass of the mangrove trees, both biomass and abundance of prop roots, knee roots, pneumatophores, age of the trees etc.
The relative abundance of mangroves or in other words the density of mangroves
played a crucial role in determining the magnitude of damages caused by 2009
AILA in Indian Sundarbans. An in-depth study conducted by the present author in
10 stations of Indian Sundarbans (Table 2.6 and Fig. 2.5) revealed that the damage
of embankments was more at stations 6, 7, 8 and 9 where the relative abundance of
mangroves were less (Fig. 2.6 and Tables 2.7, 2.8 and 2.9).
The ages of the mangrove trees are also important in determining their ability to
attenuate waves, mediated by their size/biomass, shape and the density of trunks,
branches and aerial roots. Seedlings or young mangroves offer least or almost no
resistance compared to their matured forms. The abiotic variables related to wave
attenuation include the wind duration, tidal/wave energy, span or expanse of the
mangroves through which the wave can pass (dimension of the mangrove patch/
belt), bottom topography of the substratum and water depth relative to structure of
mangrove trees.
Dr. Mourani Sinha, Associate Professor of Department of Mathematics, Techno
India University, West Bengal is the pioneer worker in the field of using model with
ground level mangrove vegetation data of Indian Sundarbans (Fig. 2.7).
She used the SWAN model with vegetation and mud input to calculate the wave
attenuation along the estuaries of Indian Sundarbans. The major inputs in running
SWAN model are wind speed, depth, mud layer, density of the tree, height of the
Types of Tropical Cyclones
differ considerably from other mangroves because of the dominant tree species —
Sonneratia apetala, Heritiera fomes, H. littoralis and several species of Avicennia.
In order to critically analyse the defensive role of mangroves three situations were
identified: (1) A village in the shadow of mangroves; (2) a village not in the shadow
of mangroves and with no embankment; and (3) a village not in the shadow of mangroves, but with an embankment on the seaward side. Bankual village was in the
shadow of a mangrove forest, Singidi village was neither in the shadow of mangroves nor protected by an embankment from storm surge and Bandhamal village
was not in the shadow of mangroves, but had a seaward side embankment. The
report indicated that the intensity of the impact of the 1999 cyclone on these villages should have been fairly uniform, as all the three selected villages were equidistant from the seashore and had similar aspects. The two villages outside mangrove
cover were located close to each other, but both were far from the mangrove forest
in order to eliminate any effect of mangrove forest presence.
It was documented after the study that the loss incurred per household was greatest (US$153.74) in the village that was not sheltered by mangroves but had an
embankment, followed by the village that was neither in the shadow of mangroves
or the embankment (US$44.02) and the village that was protected by mangrove
forests (US$33.31).
A number of studies indicate that the resistance offered by mangroves (in terms
of magnitude) to storm induced waves is a function of few important biotic and
abiotic variables. The biotic variables include the density of mangroves (relative
abundance), above ground biomass of the mangrove trees, both biomass and abundance of prop roots, knee roots, pneumatophores, age of the trees etc.
The relative abundance of mangroves or in other words the density of mangroves
played a crucial role in determining the magnitude of damages caused by 2009
AILA in Indian Sundarbans. An in-depth study conducted by the present author in
10 stations of Indian Sundarbans (Table 2.6 and Fig. 2.5) revealed that the damage
of embankments was more at stations 6, 7, 8 and 9 where the relative abundance of
mangroves were less (Fig. 2.6 and Tables 2.7, 2.8 and 2.9).
The ages of the mangrove trees are also important in determining their ability to
attenuate waves, mediated by their size/biomass, shape and the density of trunks,
branches and aerial roots. Seedlings or young mangroves offer least or almost no
resistance compared to their matured forms. The abiotic variables related to wave
attenuation include the wind duration, tidal/wave energy, span or expanse of the
mangroves through which the wave can pass (dimension of the mangrove patch/
belt), bottom topography of the substratum and water depth relative to structure of
mangrove trees.
Dr. Mourani Sinha, Associate Professor of Department of Mathematics, Techno
India University, West Bengal is the pioneer worker in the field of using model with
ground level mangrove vegetation data of Indian Sundarbans (Fig. 2.7).
She used the SWAN model with vegetation and mud input to calculate the wave
attenuation along the estuaries of Indian Sundarbans. The major inputs in running
SWAN model are wind speed, depth, mud layer, density of the tree, height of the
Types of Tropical Cyclones