DECISION ANALYSIS FOR BANGLADESH COASTAL AFFOliESTATION

GIAS UDDIN AHMED

A thesis submitted in conformity with the requirements for the Degree of Master of Science in Forestry

University of Toronto

0 Copyright by Gias Udclin Ahmed

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FACULTY OF FORESTRY University of Toronto

DEPARTMENTAL ORAL EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN FORESTRY

Examination of Mr. Gias Uddin AHMED

Examination Chair's Signature:

We approve this thesis and affirm that it rneets the departmental oral examination requirements set down for the degree of Master of Science in Forestry.

Examination Cornmittee:

Bangladesh is known as a country of natural disasters. Disasters have become a regular

phenornenon and have caused s u f f e ~ g to millions of people for many decades. The coastai areas

fiequently experience cyclones and water surges. The imporiance of sustainable forest management

in relation to Bangladesh is discussed. The role of coastal afforestation in protecting the country

from natural hazards like floods is ernphasised. Equations for the estimation of flooded area in terrns

of the altitude of the area, the wind speed, the maximum surge height and width of the forest of that

area. Models that relate flooded area to wind speed, sea level and maximum surge height were

developed for dams, and protective forests. It was observed that a coastal afforestation program

could significantly reduce the flooded area by creating a drag force. But this will depend on the

width of the forest, the number of stems per unit area and the size of the trees. Effect of branches

or the roughness of the land were not considered. Finally, a decision analysis was camed out for

coastal &orestation in Bangladesh. The analysis based the information available suggested that the

govenunent should support coastal afforestation. In addition to protecting against natural calamities

like surges, coastal aorestation has the potential to improve the socio- econornic condition of the

people, especially the coastal people. It was recommended that the Government of Bangladesh

should proceed with both coastai florestation and dams. If there is budget constraint then the

govenunent should proceed with coastal afforestation aione.

Acknowledgments

I wish to extend my sincere gratitude to Dr. David L. Martel1 for his continiious

guidance, support and encouragement. 1 am also thankful to the members of my thesis examination

cornmittee: Professor D.N. Roy, Dr. S. Kant and Professor Sandy Smith of the Faculty of Forestry,

University of Toronto.

Also 1 would like to express my appreciation to the faculty members of the Institute of

Forestry and Environmental Studies, University of Chittagong, Bangladesh for allowing me to stay

in Canada.

My study program was fùnded by the Forest Resource Management Project, Institute of

Forestry and Environmental Studies component, financed by the World Bank, Credit No 2397 BD.

Table of Contents

Abstract

Acknowledgment s

List of Tables

List of Figures

1 -0. Introduction

1 . 1 . Impact of climate change

1.2. Sea level change

1.3. Coastal populations

1.4. Coastd erosion

1.5. Cyclones and stonn surges

1.6. Location

L .7. Monthiy surges

1.8. Coastal florestation in Bangladesh

1.9. Objective of the present study

2.0. Literature Review

2.1. Sustainable forest management and future generations

2.2. Past forest management in Bangladesh

2.3. Uncertaint y in forest management planning

2.4. Deforestation

2.5. Sustainability

Page .. II

viii

2.6. Objectives of coastal aorestation in Bangladesh

2.7. Property damage

2.8. Reduction of darnage

2.8.1. Different measures for flood control

2.9. Types of decision making situations

2.9.1. Cntet-ia for decision making under uncertainty

2.9.2. Stochasticity

2.9.3. Nature and sources of uncertainties

2.10. Influence diagram and decision tree

3. 0. Deterministic Phase of a Decision Analysis for the Establishment of a

Coastai morestation Program in Bangladesh

3.1. Introduction

3.2. Decision anaiysis process

3.3. Storm surges

3.4. Different alternatives for flood control in Bangladesh

3 S. Description of the deterministic model

3 -6. Other benefits of different alternatives

3.7. Choice and size of alternatives

3.8. Organization of the deterministic model

3.8.1. Structural equations

3.8.2. Dam

3.8.3. The effect of a forest on water surge

3.8.4. Dynarnic model

3.9. Numencal example

4.0. Detenninistic Sensitivity Andy sis

5 .O. Probabilistic Phase

5.1 . Influence diagram

5.2. Estimation of the cost of each type of calamity

5.3. Determination of the cost of protective measures

5.3.1. Cost of a dam

5.3.2. The cost of coastai florestation

5.4. Benefits

5.5. Total cost of different calamities with protective measure

5.6. Decision tree

5.7. Cornparison of the cost and retum from decision tree

6.0. Discussion

6.1. Detednistic model

6.2. Probabilistic analysis

6.3. Future research

7.0. References

List of Tables

1.1 The fiequency of disasters in ditferent penods in south east Asia

1.2. Mean and variance of the number of severe storms fomiing over the

Bay and the number of severe storms striking the coast in each year

1.3 Number of cyclonic stoms which formed over the Bay, the number

which intensified into severe stonns and the number which struck

the coast as severe storms in different 13-years period 18

1.4. Maximum sustained wind speed, stom surge height, flooded area,

crop damage and death reported due to severe cyclones dunng 1960- 199 1 20

1 S. Classification of cyclones on the basis of pressure drop and

maximum sustained wind speed 22

1.6. Month and area wise number of surges during year 1960- 199 1 23

1 -7. Chisquare test for the surge arrivai in Bangladesh 25

1.8. Chisquare test for surge amval rate during the month of May 27

2.1. Cost and performance of different programs 45

3.1. Strategic objectives for flood control in Bangladesh 63

5.1. Probabilities of different calamities 98

5.2. Model input for determination of the present net wonh of future costs for 100 km dam 106

5.3. Model input for the determination of present net worth of future costs for

100 sq. Km coastal florestation

5.4. Total cost of dEerent calamities with protective measures

vii

List of Figures

1.1. The frequency of disasters in diEerent penods in south east Asia 7

1.2. Number of stoms surges in Bangladesh during 1600- 199 1 (1 0 year intervals) 16

1.3. Number of stoms formed over the Bay of Bengal and number

which stmck the Coast during dif3erent 13-years period 17

1.4. Nurnber of water surges in Bangladesh during 1960- 199 1 24

1 S. Average probability per month of water surge in Bangladesh for the period 1960- 199 1 26

2.1. Organizationai structure for decision making concerning coastal

florestation in Bangladesh 57

3.1. The decision analysis cycle and prior information 61

3.2. Flood control strategies and their benefits 67

3.3. Organization of the deterrninistic mode1 72

3.4. Surge resistance phenornenon for flooded area estimation 75

4.1. Sensitivity anaiysis of wind speed ( using Equation 3.6) 90

4.2. Sensitivity anaiysis of wind speed with a forest (using Equation 3.1 1) 91

4.3. Sensitivity analysis of surge height (using equation 3.8) 92

4.4. Sensitivity analysis of sea level of the area 93

4.5. Sensitivity analysis of the number of stems per unit area (using equation 3.1 1) 94

4.6. Sensitivity analysis of the width of the coastal fiorestation (using equation 3.11) 95

4.7. Sensitivity analysis of the wind speed without a dam or a forest (using Equation 3.6) 96

5.1. Influence diagram for the coastal florestation program in Bangladesh 1 O0

5.2. Decision tree showing net cost ( $ Million) of the protective measure and resulting storm 109

1.0. Introduction

Bangladesh is a srnall country in Asia with a total area of 144,400 km ; almost all of which

lies in the active delta of three of the world's major rivers, the Padma, Jamuna and Meghna. There

are hilly areas in the Sylhet, Mymensingh, Chittagong and Chittagong Hill Tract regions. Bangladesh

is aimost rectangular in shape, extending from 20 "45' N to 26' 40 'N latitude and fiom 88" 05 'E to

92 40' E longitude (Pant and Kurnar, 1997). South of the country is the Bay of Bengal. The Coast-

tine consists of the estuanes of the Padma, Jamuna and Meghna rivers that form a network which

discharges large arnounts of fresh water and silt into the Bay of Bengal. These nvers onginate in the

hilly zones of India and Nepal. The country is prone to severe fiooding during the monsoon season

and when cyclones strike. Although the land elevation ranges from mean sea level to 30 m above

sea level, more than half of the land has an elevation less than 8 m above sea level (Begum, 1996).

Land and life in this country are closely entwined. Over 80% ofthe country's population lives in mral

areas. Land is fiequently fiooded by heavy rains, over-flooding river channels and sea surges

associated with cyclones. Natural disasters like floods, cyclones, humcanes and tomadoes are

relatively comrnon. Changes in climate therefore have serious implications for local economic and

human welfare.

Climate also influences vegetation, soi1 and animai resources upon which the people of

Bangladesh depend for food and other necessities and climate plays an important role in the

sustenance of large ecological diversity in Bangladesh and south Asian region as a whole. Sea level

rise is also higher in the Bay of Bengal (Wamck and Ahmad, 1996). It is important to note that the

1

forest area in this region is decreasing at a high rate so many plants and animals are becoming extinct

(Pant and Kumar, 1 997).

1.1. Impact o f climate change

The Intergovernmental Panel on Climate Change ( IPCC) (1995) indicated that the impact of

clirnate change on forests is uncertain. It may be beneficial for some regions and species and

detrimental for others. The IPCC (1998) noted that the composition and geographic distribution of

many ecosystems will shifl as individual species respond to changes in climate and there will likely

be reductions in biological diversity and in the goods and services that nonforest terrestrial

ecosystems provide to society. The clirnate ofBangladesh is tropical and monsoon rainfall varies from

1200- 3500 mm per year. There has been no discemible trend in average rainfall but rainfall variability

appears to have increased in recent decades (IPCC, 1998). Over the past 100 years, Bangladesh has

wamed by about 0.5 O C and this warming trend is consistent with that of the northem Hemisphere

as a whole (Warrick and Ahmad, 1996). Based on global climate change, the P C C estimated that

Bangladesh will be OS°C to 2'C warmer than today in the year 2030 and average monsoon rainfall

wiii increase by 10 to 15 % (Warrick and Ahmad, 1996). This may cause frequent cyclone and other

natural calarnities with higher intensity in the Bay ofBenga1.

13. Sea Ievel change

Sea level rise and possible changes in the frequency and / or intensity of extrerne events such

as temperature and precipitation extremeq cyclones and storm surges, constitute the components of

climate change that are of most concern to coastal zones and small islands (IPCC, 1995). The

possibility of a future rise in sea levei is of therefore great concern to Bangladesh which has a low

lying and densely populated deltaic Coast, especially in coastal and nearby areas. It may cause more

soi1 erosion than the past, inundation of land, salinisation of soi1 and water and flooding fiom storm

surges. But the occurrence of such calamities is uncertain.

The best estimate based on recent analysis is that the sea level has risen about 18 cm over the

last 100 years with a range of uncertainty of 10 - 25 cm (IPCC, 1995). Pant and Kumar (1997)

estimated the annual average precipitation in the Chittagong region is 2730 mm which is the highest

in South Asia The sea-level rise that has been observed over the last century poses a significant threat

to coastal zones throughout the world (Wigley and Raper, 1992) but the effect of sea level nse is

dangerous to Bangladesh for several reasons. Human activities can reduce sea IeveI rise and

ultimately can reduce the frequency and intensity of natural calamities like floods and cyclones. It has

recently been estimated that a combination of ground water withdrawal, a surface water diversion,

and land use change (such as deforestation) may have contributed at least 0.54 mm each year since

1960 to the observed sea level rise (Sahagian et al. 1994).

In Bangladesh, run-off, sediment flow, and deposition rates have been attributed to changes

in the flood defense systems as well as deforestation in the head-waters of the Ganges-Brahmaputra-

Meghna river system and these changes have contributed to detrimental effects on coastlines and

fisheries and have played a part in the increased frequency and severity of island flooding (Turner

et al. 1996).

Coastal wetlands are likely to be severely affected by sea level nse and have already

experienced significant cumulative losses (Turner and Jones, 199 1). Cyclones pose multiple threats

fiom severe wind, storm surge, and heavy raidal1 that produce flooding especially dong the 7 10 km

long strip coastal belt area (Wanick and Ahmad, 1996).

Changes in global average sea level are caused by three main processes: changes in ice mass

on land, changes in the temperature of ocean water and changes in liquid water stored on land in

ground water aquifers or surface reservoirs (Meier, 1990).

Sea level rise (SLR) over a specific time penod is also influenced by anthropogenic effects.

Its effect over a specified time penod may be estimated as (Gomtiq 1995):

S L R = ( G k D + W ) - ( R + I ) ,

where G = SLR due to ground water mining;

D = SLR due to deforestation (combustion, oxidization, * runoff);

W = SLR due to drainage of wetlands;

R = SLR reduction from reservoir impoundment, infiltration, and water vapor storage; and

I = SLR reduction due to imgation (infiltration and water vapor storage).

It was estimated there has been a net positive addition of 0.54 d y e a r to sea level nse over

the last 60 years fiom such activities as ground water mining, deforestation, and wetland loss and the

irnpounding of water in reservoirs (Sahagian et al. 1994). ShuWa et al. (1990) observed that

precipitation has decreased significantly in the deforested environment.

Over the past 50 years, sea level has been rising at an average rate of 2.4 * 0.9 mm/ year,

a value obtained by correcting tide gauge data for the continuing glacial isostatic adjustment (Meier,

1990). Mangroves rnay be aEected by climate change and increases in temperature and sea level rise.

Although the effect of temperature on plant growth and species diversity is unknown, sea level nse

may pose a S ~ ~ O U S threat to the ecosystems. For instance, in Bangladesh, there are threats in three

district ecological zones that mzke up the Sunderbans, the largest continuous mangrove area in the

world (PCC, 1998). If the saline water mixes with the inland water, many species could be

threatened. Anglo et al. (1996) noted that changes in average climatic conditions and climatic

variability will have significant effects on agiculture in many parts of Asia and increasing population

also could place stress on agricultural production. In addition, trends in extreme sea levels such as

those produced by storm surges and waves are of great concem because of the potential flood

damage in low lying coastal areas. Rising sea level will lead to a decrease in the retum penod of a

storm surge of given elevation because the surge is supenmposed on a higher base level. For this

reason, the frequency of disasters in the South- East Asian region has increased at an alarming rate

during the last 30 years (Table 1.1). Bangladesh has been identified as one of the areas especially

vulnerable to natural calamities and this is problematic because extreme options of retreat and full

protection highlight the negative effects and overestimate the potential costs and losses fiom climate

change and sea level nse P C C , 1995). This is clear from Figure 1.1. Even without clirnate change

and sea level nse, Bangladesh will continue to experience rapidly increasing wlnerability to natural

coastal hazards due to high rates of population growth, increased demand for land and forest

products, continued unsustainable exploitation of resources in the coastai zone, and the development

of upstream catchment areas (IPCC, 1995).

TABLE 1.1. The fiequency of disasters in different penods in south east Asia

Country 1960- 1969 19790- 1979 1980-1989

Bangladesh 18

India 34

Indonesia 20

Myanmar 10

Nepal 7

Sri Lanka 5

Thailand 4

Source: Begum, 1996.

Depending on wind speed these calamities may be classified into low depressions, cyclonic

storms, and severe cyclonic storms and humcanes. Generally, low pressure depressions associated

with a wind speed of 30 - 60 km per hour are termed depressions. When the speed associated with

the system is 61-87 km per hour, the system is cailed a storm, and when it is 88- 116 km per hour,

the system is called a severe cyclonic stom. Finally, when the associated wind speed exceeds 1 16 km

per hour, the system is termed a humcane (Mooley, 198 1). Low pressure areas either develop over

the Bay or move into the Bay fiom the far east across Vietnam, Thailand, and Myanmar. Some

intensify h o depressions. 35 - 40 % of these depressions develop into cyclonic storms. About one

-third of these storms further UitensiS, into severe cyclonic storms. Only a small number of the severe

storms fùrther intensifL into humcanes in the Bay of Bengal (Mooley, 198 1).

The recent rise in sea level is consistent with the histoncal temperature record (PCC, 1992).

This thennai expansion of the upper layer of the ocems could account for 0.14 to 0.45 mm of the

observed sea level rise, depending on the equilibrium climate sensitivity for doubled CO, and difision

coefficients used in the one dimensional difision model (Gomtiz, 1995).

Assuming a global warming of 0.4 - 0.6 O C over the penod 1880- 1985 and using a box -up

w e h g difision energy balance climate model, the thermal expansion has been estimated to be 2.3 - 4.8 cm (Wigley and Raper, 1992). Melt water from mountain glaciers also adds to the observed sea

level rise. A sea level rise of around 28 mm between 1900 and 1962 was estimated using mass

balance data fiom glaciers with records exceeding 50 years (Meier, 198 4).

Hofian et ai. (1986) predicted that sea level may rise up to 3.5 m by the year 2 100. The

present trend in sea level rise is much higher than that of the last few thousand years (Grontiz, 1995a).

This potentid rise of sea level may have a great impact on world coastal populated zones where a

large proportion of the global population may be affected. Deelstra (1995) noted that due to sea level

rise and climate change, low-lying countries like Bangladesh and the Netherlands, have leamed to live

with risks. But richer countries will be able to cope with rising sea levels. He also noted that the

frequencies ofstorms, floods, cyclones, earthquakes, landslides, typhoons and humcanes are expected

to increase. According to Sobhan (1994), coastd populations will be more affected economically and

environmentally t han the past .

1.3. Coastd populations

During the 20 th century, coastal populations have increased because of the many economic

opportunities and environmentai amenities that coastal zones can provide, as well as the general

urbanization process. The mangrove forests ofBangladesh are critical to the people and the economy

because they supply fùelwood for domestic and industrial use, timber for industry and a range of other

products (Warrick and Ahmad, 1996). They also noted that the mangrove forests of the Sunderbans

and coastai florestation in the newly accreted lands can protect the impacts of cyclone. Moreover,

these forests an integral part of the life cycle of many fish and shrimp species.

The trend of an increasing coastal population is expected to continue globally with the most

dramatic increase forecast to be in Asia, Mica and South America (World Resources Institute,

1994). As of 1992, as much as 66% of the present population lived within 60 km of the shore and this

figure could rise to 70% by the year 2000 (Pemetta and Elder, 1992). The coastai population in

Bangladesh will continue to increase at a higher relative rate than the population in general because

poor people living on the island take shelter in the coastd areas d e r severe cyclone and tornados.

P C C (1995) mentioned that two thirds of the population of developing countries is expected to live

dong the Coast by the year 2000. Sixty- five percent of the cities with a population above 2.5 million

inhabitants are located dong the world's coasts, and several of these are already at or below the

present sea level (Turner et al. 1996).

The intensive pressure on the land and resources inland in Bangladesh forces people to rernain

in areas vulnerable to cyclones and storrn surges (Wmick and Ahmad, 1996). These pressures are

likely to continue in the future, exposing people again and again to the dangers of cyclones and

floodhg. On the basis of census data, Khan (1996) concluded that the population growth rate in

most of the 1991 cyclone affected areas in Bangladesh is higher than the national figures. This large

population suffers from natural calamities like coastal erosion, cyclones and storm surges dmost

every year.

1.4. Coastnl erosion

Coastal erosion is a major hazard which huge coastal population has had to learn to live

with. There are no reliable estimates of the number of people who have lost their homes to coastal

erosion, but it is said that every year at least one million are displaced (Wamck and Ahmad. 1996).

Many of these destitute people join the ranks of the floating population and most eventually drift to

nearby towns or industriai belts or end up in Dhaka in search of food, shelter, and employment (Khan,

1996). The people in the coastal area are increasing and they are the worst victims. They have to live

with disasters like cyclones and hazards like the intrusion of salt-water fiom the sea. Cyclones are

instant kiilers and their effects are also dreadfùl. The intrusion of salt-water fiom the sea is also a

major threat to agriculture, forestry, and fishing and is one of the biggest problems facing the

environment and economy of Bangladesh. Deforestation, along with the potential impacts of climate

change, also may have a negative impact on the sustainable nutrient security in south Asia.

Erosion and accretion are continuous processes along the coastd belt. Studies show that

prominent erosion occurs along the wider channels. Most of the erosion of the Bay of Bengal front

was due to stom surges and wave action. Accretion has taken place in certain places on the Bay side,

however, an overall seaward extension of the delta was observed. In some of the inhabited islands,

erosion is taking place at an alaming rate. The area of Sandwip Island, for example, was 1,080 sq

km in 1780, but now it has been reduced to only 238 sq km and Hatiya, the rnost densely populated

and one of the largest islands of the region, erosion is taking place at the rate of 400dyear (Manda],

1998).

The coastal ecosystems cany an estimated annual sediment load of 1.5- 1.8 billion tons while

flowing through Bangladesh on their way to the Bay of Bengal. These sediments are subjected to

coastal dynamic processes generated mainly by river flow, tide and wind actions, leading to accretion

and erosion in the coastal area.

Most of the Chakana Sunderbans mangrove forests formerly covered an area of over 8,000

ha have been cleared for shrimp ponds and other aquiculture projects. But this very destructive

activity threatens the sustainability of forestry projects.

Available data for different periods suggest there have been massive changes in the coastline

of this region over the past 200 years due to sediments. The net result of these and other factors is

an approximate yearly net accretion of 35.6 sq km ofland (Mandal, 1998). On the other hand, erosion

is taking place mostly in the expensive and fertile northeastem part of Bhola, the northern part of

Hatiya, and the northwestern part of Sandwip.

The western coastal region is a stable region and is mostly covered with the largest

mangroves, Sunderbans, which experiences less bank erosion so that scouring action is confined to

the river channels, which are in general deeper than those in other regions. Accretion does not occur

much in this region, being mostly concentrated at a few points. It is a general practice that as soon

as a new formation rises, ecological succession starts with grass coming up as the first colonizer. The

new land is then taken over by people and cattle start grazing thereby retarding the ecological

succession. ifthere had not been this retardation, grass would eventually be replaced by shnibs and

trees. Shailow-rooted grasses when replaced in succession by deeper-rooted shmbs and trees would

have consolidated the newly forrned land (Mandal, 1998). Without the development of deep-rooted

vegetation, new formations remain unstable and surface erosion is a continuous phenornenon. Thus,

new formations can't rise rnuch above the surface of water and become stable, but are subjected to

total surface wash dunng storm surges or monsoon high tides. Morestation and protection in certain

areas of new coastal formations have been attempted and stable formations are fast appearing around

the nucleus forest plantations. Realizing the importance of coastal affiorestation, the forest

department has underiaken extensive florestation projects in the coastal zone. The Ministry of

Enviromnent and Forests has started a multi-million dollar Coastal Green Belt Project d e r the

devastating cyclone and tidal surge of April 199 1.

1.5. Cyclones and storm surges

Tropical cyclones are the most devastating natural events in the country. Damage to life and

property due to cyclone storms is enormous. The potential of tropical cyclones to cause damage and

Ioss of life is due to the continuous rainfall and violent winds. In the coastal regions, the damage is

mainly due to induced storm surge, particularly over the low elevation coastal margins. The coastal

zone of Bangladesh could be termed a geographical "death reap" due to its extreme vulnerability to

cyclones and storrn surges (Wamck and Ahmad, 1996). The massive loss of life from cyclone is due

to the large number of coastal people living in poveny within poorly constructed house, the

inadequate number of cyclone shelters, and the extremely low-lying land of the coastd zone.

Most cyclonic storms f o m over the Bay oCBengal, mainly in the pre-monsoon and post

monsoon months (Pant and Kumar, 1997). In the past, most intensive cyclones occurred during the

months ofMay, October, and November. Mooley and Mohile (1984) concluded that the event of a

severe cyclonic storm crossing the Coast around the Bay of Bengal is random in nature, following the

Poisson probability distribution in the time domain.

Though cyclones and floods have occurred in Bangladesh over the centuries, increased

exposure of people due to growing population and development in hazardous areas has made recent

disasters even larger and more fiequent. Generally, cyclones appear out of the Bay of Bengal and

their paîhs are relatively unpredictable (Wamck and Ahmad, 1996). Cyclones pose multiple threats

from severe wind, storm surges, and heavy rainfàll that result in both surface and river flooding. The

flooding dso accelerates the erosion of soils, riverbanks, and coasts. Consequently, cyclones are very

destructive to economic activities.

n i e mean arrivai rate of severe storms that crossed the coast was higher during the penod

1965-77 than for the longer period of 1877-1977 (Table 1.2)( Mooley, 198 1). Mooley (1980)

estimated mean and variance of severe storms forming over the Bay of Bengal and the number of

severe stoms striking during the period 1877- 1977.

TABLE 1.2. Mean and variance of the number of severe stoms forming over the bay and the number

of severe storms striking the coast in each year.

Severe storms formed Severe storrns striking the Coast

Period Mean Variance Mean Variance

1 877- 1964 1.42 1,374 1.16 1.091

1877-1977 1.67 1.910 1.40 1 .530

1891-1964 1.50 1.420 1.22 1.087

1965- 1977 3.38 1.923 3 .O0 1.833

Source: Mooley (1 980).

It is clear that the number of severe storms which fonned over the bay and the severe storms

which stmck the coast each year frorn 1877 to 1977 is increasing (Table 1.2). But we do not know

reliability of this data of certain years beginning from the year 1877. Mooley (1980) showed that the

number of severe storms during the period 1965-1977 is much higher in comparison with the period

1 877- 1964. The direrence between the means for 1964- 1977 and for 1877- 1964 is highly significant

but the ratio of the corresponding variances is not significant (Table 1.2). Murty and Neralla (1996)

showed the number of storm surges in Bangladesh during 1580- 199 1 (Figure 1.2).

Within a few meters of sea-level, Bangladesh has a 720-kilometer coastline that is threatened

with inundation, the intrusion of salinity, and increased frequency of cyclones, humcanes, unusual

tidal bores and erosion. Because of climate change, scientists fear a sea-level nse by one meter will

inundate 17.5 per cent of the land of Bangladesh which is already scarce and densely populated in

the coastal areas. For centuries, the Bay of Bengal not only broke the coastlines, but also the hearts

of the millions of Bangladeshi (Mandal, 1 998).

The number of storms which formed over the Bay of Bengal, the number of storms which

intensified into severe storms, and the severe storms which struck the coast and their intensification

are given in Table-1.3. The number of severe storms which formed over the Bay and the number of

severe stoms which struck the coast during the penod 1965-77 were unusually large in comparison

to other periods (Figure 1.3). The eficiency of intensification of stoms to severe storms over the Bay

and ratio of severe storms which struck coast to the storms which stmck the coast are also high.

During the penod 1948-1988, total of 4 18 depressions and stoms were formed in the area of which

79 were cyclonic stoms in Bangladesh (PCC, 1998).

Fig. 1.3. Number of storms formed over the Bay of Bengal and number which stnick the coast during different 13-years period (source: Mooley, 1980).

i/ilIi Storms Formed

Storms that hit the coast

TABLE 1.3. Number of cyclonic storms which formed over the Bay, the number which intensified

into severe storms and the number which stnick the coast as severe storms in different 13-years

period

Penod S torms Storms Severe storms EEciency of Ratio of formed intensified which struck intensification severe storms

into severe the coast storms into which struck storrns severe storm coast to

storms which stnick coast

Source: Mooley, 1980.

Murty and Neralla (1996) listed 144 aorm surges in the Bay of Bengal for the period 1584

to 1991. Among these storms surges, 70 struck Bangladesh. They also listed the nurnber of deaths

and property losses due to these storm surges. About 10 % of the tropical cyclones occur in the Bay

of Bengal and 40 % of the total deaths occurred in Bangladesh alone (Murty et al. 1986). Between

1877 and 1980,63 out of 392 tropical cyclones fonned in the Bay of Bengal had landfall on the Coast

of Bangladesh (Matsuda, 199 1). Storm surges can Vary fiom 1.5 to 9.1 m (Table 1.4). According

to official statistics, only the cyclone of April29, 1991 devastated about 2000 km of coastal area

and more than 200 families became homeless (Begum, 1996).

Chowdhury (1994) described the maximum wind speed, storm surge height, and deaths and

the Bangladesh Bureau of Statistics (199 1) described the intensity offloods and cyclones that affected

Bangladesh, property damage and losses of lives for the years 1960- 199 1 (Table- 1.4).

The maximum water level also coincides with the tirne of heavy storms in Chittagong port @as,

1972).

Oniy six of the last 32 years were disaster free (Table 1.4). Floods and cyclones occur on an

average of every 1.8 years. Storm surges have killed thousands of people and caused extensive

economic damage around the Bay of Bengal in historic tirnes; but the magnitude of losses has been

highest in this century as increasing population pressure forces, cultivation of even newly- fonned

delta land. This situation will continue and even greater storm surge disasters must be anticipated

(Murty et al. 1986).

TABLE 1.4. Maximum sustained wind speed, storm surge height, flooded area, crop damage and

deaihs reported due to severe cyclones during 1960- 1 99 1

Date Location Maximum Storm wind speed surge (km/ hour) height

(meter)

FIooded Crop Deaths area per darnage reported 1 O00 sq.km 1 O00

ton

October Noakhaii 161 3.0

October 3011960 Noakhali 209 4.6-6.1

May 0911961 Noakhaii 145 2.4- 3.1

May 30/1961 Chittagong 145 6- 8.8

region May 2811963 66 20 1 4.3- 5.2

Apnl 1 111 964 Bangladesh - - May 1111965 Barisai & 16 1 3.7

Noakhali May 3 111965 Chittagong - 6.1- 7.6

Dec. 144965 Cox's Bazar 209 4.6- 6.1

October 0111966 Chittagong 145 4.6- 9.1

October 1 111 967 Noakhali - 1.8- 8.5

October 2411 967 Cox's Bazar 1.5 - 7.6 May 1011968 - 2.7 - 4.6 April 17/1969 Bangladesh - - October 1011 969 Khulna - 2.4 - 7.3

May 07/1970 Cox's Bazar - 3 - 4.9

October 2311970 Chandpur - 4.7

Nov. 1211970 Khulna to 225 6.1- 9.1

Chittagong May 08/1971 Meghna - 2.4 - 4.3

Sept. 3OIW7 1

Nov. O61 1 97 1

Nov. 1811973

Dec. 0911973

Augua 1511974

Nov. 2811974

October 2 11 1 976

May 1311977

Dec. 1011981

October 1 511983

Nov. 0911983

June 0311984

May 2511985

Nov. 2911 988

April291199 1

Chandpur

Chittagong

Barisal

Patuakhali

Khuha

Chittagong

Meghna

Est uary Sunderbans

Bangladesh

Chittagong LL

- Chittagong

Region Khulna

Chittagong

Regio n

Source: Chowdhury (1994), BBS (1 99 l), Wanick and Ahmad (1 996) and Khalil(1990).

The Bangladesh Meteorologicai Department classified the cyclones of vanous intensity on the

basis ofpressure drop and maximum wind speed (Table 1 S). As mentioned earlier, cyclone increases

the intensity of surge and both surge and cyclone cane together. For this reason, we may denote

caiamity as surge or vice versa.

TABLE 1.5. Classification of cyclones on the basis of pressure drop and maximum sustained wind

speed

Cyclonic intensity Range of pressure drop (Mb) Maximum wind speed (km/h)

Depression 3.0 < 3.5

Deep depression 3.5 < 6.0

Cyclonic storm 6.0 < 9.0

Severe cyclonic storm 9.0 < 16.0

Humcane 16.0 or more

44 to < 52

52 to < 63

63 to < 89

89 to< 119

1 19 and above

Source: Begum, 1996

1.6. Location

Although most of the area of Bangladesh is affected by cyclones and water surges, the

frequency and intensity of surges at different locations in the country may be differentiated (Table

1.4). Table 1.6 shows the month and area wise number occurred during 1960- 199 1 .

TABLE 1.6. Month and area wise number of surges during year 1960-1 99 1

Months 1 2 3 4 5 6 7 8 9 10 11 12 Total

Location

Chittagong

Barisai

Cox's Bazar

Khulna

C hand pur

Meghna

Patuakhali

Sunderbans

Bangladesh

Surges occur most fiequently in the Chittagong region (Figure 1.4). It was observed that the number

of surges in the Bay of Bengal follows a Poisson arriva1 process (Mooley, 198 1). On the basis of the

Poisson distribution probabilities for 0, 1 ,2 and 3 surges were estimated (Table 1.7). The chi-square

statistic for the distribution was estimated to be 0.27 which is insignifiant at the 95% confidence

interval. On the basis of the information in Table 1.4 and Figure 1.4, we may conclude that

Chittagong region needs more protection than other parts of the country.

TABLE 1.7. Chi-square test for the surge arrival rate in Bangladesh

Number of surges Observed Cumulative Poisson Expected Chi-square or calamities frequency fiequency probability frequency

O

1

2

3

Total

11 11 0.3456 I l .75 0.0479

13 24 0.3672 12.48 0.02 13

7 3 1 O. 195 1 6.63 O. 0204

3 34 0.009 I 2.3 5 0.1804

34 34 0.977 33.2 1 0.2700

Tabulated Chi-square =7.8 1 50

1.7. Monthly surges

Surges occur most frequently in the months of May, October and November (Figure 1 S).

The arriva1 process of surges in the month of May follows the Poisson distribution and this can be

used to calculate number of surges (Table 1.8). Chi-square value of the distribution was also

calculated as 1.9575 which is insignificant at the 95% cordidence interval.

TABLE 1.8. Chi-square test for surge amvai rate during the month of May

Number of surges Observed Cumulative Poisson Expected Chi-square or calarnities frequency frequency probability frequency

O

1

2

Total

24 24 0.7788 24.92 0.034 1

6 30 O. 1947 6.23 0.0085

2 32 0.0243 0.7788 1.9149

32 32 0.9978 3 1.93 1.9575

Tabulated Chi-square = 5.99 10

1.8. Coastal afïorestation in Bangladesh

The P C C (1 995) noted that coastai zones and small islands contain some of the world's most

diverse and productive resources. They include extensive areas of cornplex and specialised

ecosystems such as mangroves, coral reefs, and seagrasses which are highly sensitive to human

intervention. These ecosystems are the source of a significant proportion of global food production.

In addition, these areas have econornic importance because they increase fisheries activities, tourism,

recreation, and transportation. For these reasons, the global importance of coastal zones and smail

islands in terms of both ecological and socioeconornic values are widely recognised (IPCC, 1995).

Many international organizations, including the IPCC, have called for action to implement strategies

towards better planning and management of coastal areas and resources to prevent them from being

degraded and becoming progressively more wlnerable to the potential impacts of climate change and

associated sea level nse (IPCC, 1995). Bangladesh more or less faces a cyclone hit almost every

27

year. The coastal belt and neighbouring areas are more af5ected. For this reason, the Governent of

the People's Republic of Bangladesh is trying to establish coastal green belts by an fiorestation

program in the coastai areas starting fiom Teknafto the end of Satkhira, Khulna. The objectives of

this program are to protect against natural calamities like cyclone tidal bores by difising the velocity

of cyclone or tidal bores which is widely recognised by scientists of the world (Islam, 1982) and to

produce timber for fuel wood and industrial wood (Imam, 1982).

The artificial regeneration of mangroves has never been done extensively in any

coastal area of the world although it helps in natural succession. This is because it is extremely

difficult to have artificial regeneration on a new site where no mangrove vegetation existed before

@as, 1982). According to a World Bank repon, the Bangladesh Mangrove Coastal Anorestation

Program is unique in the world because nowhere else have mangrove plantation been established on

anything like the same scale (Imam, 1982). Artificial regeneration dong the coastal belt was initiated

in 1966 (Saenger and Siddiqi, 1993). The main objective was to bnng the coastal areas under

mangrove cover to minimite the destructive action of alrnost regularly occumng cyclones and tidal

surges. Moreover, coastal florestation can protect soi1 erosion and environmental degradation.

The potential impacts of sea level rise on sedimentation have been outlined by Healy (1990),

PCC (1992) and Healy (1996). Most of the impacts identified relate to the physical impacts on sea

level rise causing natural calamities like floods, cyclones and tornados which will affect most of the

shoreline people. Also, the population in the coastal area of Bangladesh is increasing. This may be

due to the availability of land for homesteads, employrnent, the increase appreciation of naturd

beauties and these areas tend to contain the greatest biological productivity. In the coastal areas of

Bangladesh, fishing is one of the main sources of ernployrnent. Ninety percent of the current world

fisheries harvest comes fiom within national exclusive economic zones and most of what is caught

comes fiom within 9 km of the shore and in southeast Asian regions, seafood averages 60% of the

diet (Turner et al. 1996).

Third - world countries, especially the countnes of south Asia will be more affected than

developed countnes, to climate change (Meier, 1 990). The consensus estimates reported have large

uncertainties, reflecting a lack of sufficient observational data. But even a 30 cm rise by the year

2050 will cause social and economic problems in this low lying area. There would also be intrusions

of saltwater into estuaries and groundwater aquifers, some destruction of coastal wetlands and an

increase frequency of darnage fiom storm surges (Meier, 1990) which has already begun in

Bangladesh. Human intervention in the natural system ( e g , deforestation and flood control activities)

play a major role in aggravating the flood situation in Bangladesh (Begum, 1996).

Coastai plantations proved to be an effective measure in some part of the coastal belt

of Bangladesh during the 1991 cyclone. Coastal communities of Mirsan and Sitakund suffered the

least d t i e s and property darnage, p n m d y due to protection provided by a one to two kilometer

wide belt of plantations dong the coastal belt (Begum, 1996). We have also observed that the

Chittagong region was rnost fiequently affécted during past. So we should give more emphasis to this

region. From the monthly data we observed that most storm surges occurred during the month of

May. Therefore, we should take more precaution dunng this month.

A system of embankments for cyclone protection was constnicted in Bangladesh in the

1960s and 1970s but they have been eroded over the years and are now in need of rehabilitation

(World Bank, 1989). A cyclone preparedness prograrn began after the disaster of 1970 but has yet

to reach every area of the high risk zone. Social customs and poor communications have, in general,

limited the effectiveness of waniings and the use of shelters (Talukder and Ahmad, 1992). But

precaution is better than prevention, so necessary action should be taken to reduce t hese natural

calamities and the loss ofproperty and lives through preventing such calamities. For exarnple, ifwe

can cover the whole coastal belt with forest species then we can partially or wholly resist such storm

surges. We can also try to prevent deforestation and establish new plantations throughout the

country which will help to reduce soi1 and environmental degradation. We can also try to establish

new plantations on the newly accreted land dong the coastal belt. There are at least 706 km of sea

facing and similarly exposed embankments in the coastal districts where there are no trees or very

little trees on the embankment where short term plans should be taken to raise plantations on

embankments to reduce damage from cyclone and storm surge (Begurn, 1996). To offset

environmental deterioration, florestation program should be staned as soon as possible and cutting

of trees from these coastal regions should be made illegai. Tree planting may also take place

embanlonents and various categories of settlements.

The population ofBangladesh is expected to double by the year 2030 and this high population

density dong with dependence on agricultural activities is forcing people to live in more wlnerable

areas. To be successful with any new plan, more job opportunities need to be created and the

population growth rate should be decreased (Begurn, 1996).

1.9. Objective of the present study

The objective of this study is to develop a decision anaiysis process for the coastal

afforestation in Bangladesh so that the ministry of environment and forests may easily decide whether

or not the govenunent should spend money on the coastal florestation prograrn. This process will

include the estimation of flooded area and taking into account alternative flood control aaivities in

Bangladesh with their costs and benefits. The decision should consider strategic flood control

objectives like the minimisation of flooded area, environmental degradation and employment as well.

2.0. Literature Review

2.1. Sustainable forest management and future generations

Every society is placing emphasis on econornic and environmental development,

however, the past decade has witnessed growing awareness of the senous environmental degradation

caused by the use of increasingly powerfil technologies and by the consumption demands of a

growing world population (Maini, 1990). The quality of life is gaining ground, particularly among

the developed nations, because of an increase in environmental awareness. There is now more

commitment to environmental stewardship at local, regional, and global levels than ever before.

The concem for our legacy to future generations is becoming an imponant ethical issue throughout

the world.

Sustainable forest management is essential to meet the needs of the present without

disturbing the needs of the future generations. It is a challenging task because both the environmental

components and human needs change over time. As part of our ethical responsibility towards future

generations, Maini (1990) described sustainable management of forest land and its multiple

environmental values as involving maintaining the productive and renewd capacities, as well as

species and ecological diversity of forest ecosystem.

Our aim should be to maintain existing forests through conservation and management

and to sustain and expand areas under forest and tree cover, in appropriate areas, through the

conservation of forests, protection, forest rehabilitation, regeneration, affcrestation, reforestation

32

and tree planting with a view to maintainhg or restoring the ecological balance and expanding the

contribution of forests and tree cover to human needs and welfare (Tewari, 1994).

2.2. Past forest management in Bangladesh

Forest management in Bangladesh was concerned pnmarily with industrial wood production,

wildlife management, or even the needs of local people. As a result, forest losses in the pst remained

unchecked. In the past, felling rates were higher than the regeneration rate (Forestry Master Plan,

1993). Illicit felling was one of the primary causes of destruction of the forest (Chowdhury, 199 1).

So, for the last few decades, forest protection has become very problematic. This problem will

assume a still worse proportion if the socio-econornic conditions of the large majority of the

population worsens.

During the previous management planning periods in Bangladesh targeted regeneration could

not be sustained due to shortages of funds and manpower. Some of the new plantations were affected

by cattle grazing (Chowdhury, 1991). Also, little attention was given to the needs and demands of

the local people and they were not involved in rnanaging local forest resources.

2.3. Uncertainty in forest management planning

An uncertain quantity may be discrete such as the number of stems per hectare, or continuous

like the volume per tree or the price of timber. In principle, al1 empirical quantities are uncenain.

There is never absolute certainty about the truth of any empirical proportion or about the exact value

of any continuous empincal quantity. No matter how great its precision, no experiment can measure

a real valued quantity with zero error. However, it is common that the uncertainty, for practical

purposes is negligible in many of the empirical quantities and they may be treated as certain in

models (Morgan and H e ~ o n , 1992).

Though in most cases, uncertain forest losses are significant, few planning models have been

developed incorporating uncertainty (Boychuk and Martell, 1996). Forest managers may have to deal

with uncertainty in managing the forests, especially in regenerating, spacing, thinning, species

selection and rotation perspective. In these situations, a manager sometimes has to take crucial

decision. Crucial in the sense that the decision maker not have suficient understanding about the past

and its future implications.

A stand level stochastic forest rotation mode1 which can be used to determine the optimal

planned rotation for fiammable forest stands was developed by Marie11 (1980) may be used to

estimate the value of fire management activities. Hann and Brodie (1980) categorized the basic

question of forest management for timber production into two levels: the stand level, which discusses

questions related to individual stands, and the forest level which deals with determinhg the optimal

schedule of stand treatments.

Several publications over the past decade have demonstrated that the long run timber supply

and the flow of economic benefits fiom a forest can be seriously reduced by fire. This conclusion has

been established using analyticd methods at the stand level (Reed and Emco, 1985) and both

simulation (Van Wagner, 1983) and optimization methods (Reed and Emco, 1986). A forest level

model was described by Gassmann (1989) to determine a harvesting sequence that maximises the

expected total volume of wood harvested fiom the forest over some time penods to corne. He used

Reed and Emco's (1986) model.

Uncertainty about the form of a model is generally harder to deal with than uncertainty about

the value of a quantity. But experienced analysts often argue that uncertainty about stmcture is

usually more important and more likely to have a substantid efTect on the results of the analysis.

In fact, the distinction between uncertainty about model structure and uncertainty about quantity

values is rather slippery.

Unceriainty may be applied by forest mangers to any situation for species and planting

spacing selection but the forest manager needs suficient understanding of the biophysical condition

of the forest. He also needs knowledge about regeneration costs, site index, species composition,

road and river communications, land area and its boundaries, harvesting cost, growing stock and

stumpage rate. Forest management planning is a challenging task in the setting of econornic,

environmental, political, social and uncertainty (Boychuk, 1993). So, before applying any

management activities the forest manager must be aware a vanety of circumstances of the problem

and its analysis that may make this effort worthwhile. These may include the foilowing (Morgan and

H ~ M O R 1992):

(i) Uncertain information tiom several sources must be combined.

(ii) Decisions about whether to buy additional information must be made.

(üi) There is need to assess the reliability of the analysis to help managers decide how much weight

to give it.

There is no doubt that the application of uncertainty in forest management is extremely

important, which in many cases is clearly preferable to other alternatives. Uncertainty presents

particular difnculties due to long terni nature of forests concems (Boychuk and Martell, 1996).

Addressing uncertainty involves identifjhg sources of uncertainty, expressing them in the

f o m of probability distributions, choosing appropriate computational methods for propagating

uncertainty through the mode1 to analyse its effects, and devising clear ways to communkate the

results. It may require substantial knowledge of the occurrence of uncertainty.

Generally, forest managers have a lot of uncertainties at different stages in establishing and

managing the forests. But coastai forest management entails more uncertainty than hilly or plain land

forest management. The additional sources of uncertainty in coastal afforestation prograrns may be

due to weather, high tides and other natural calamities that may destroy the forest partially or fully.

In these situations, decision theory or decision analysis rnay be helpful to take rational decisions. A

necessary condition for uncertainty to be important to a forest manager is that its consideration could

affect his /her decisions. That is, the manager's belief s about the uncertainty can affect which

alternative is most desirable. Hobbs et al. (1 997) showed bow decision analysis can be used to include

climate change uncertainties in water resource planning and how the economic importance of those

uncertainties can be quantified.

Decision theory or decision analysis may be used to determine optimal strategies when a

decision maker is faced with several decision alternatives and an uncertain or risk filled pattern of

results. For example, a forest manager or a decision maker may be interested in knowing whether it

is worthwhile to spend rnoney to establish coastal fiorestation projects. Es/ her ultimate goal is

to give maximum production or revenues or other benefits like environmental protection or protection

tiom natural calarnities. Decision analysis provides not only the philosophical foundations but also

logical and quantitative estimates for decision analysis which is sometimes helpful for resolving

political or social disputes in many situations. Since the decision analysis encodes information,

values, and preferences numerically, it perrnits quantitative evaiuation of the various courses of action

with different degrees of preferences (Howard, 1988). Further, it documents the state of

information at any stage of the problem and helps in determining whether the gathering of further

information is economically justifiable. In addition to these, decision analysis provides the

philosophical foundations for any social disputes. The form of decision analysis would dso confinn

whether any mistakes were made, whether appropriate sensitivities were developed, and in general,

whether the right conclusions were drawn (Howard, 1988). It is also a tool to convince others who

have several options, of any solution in their minds. in other words the policy rnaker can judge the

whole operation to ver@ whether the right course of action was clearly indicated and communicated.

2.4. Deforestation

Dickson and Henderson-Sellers (1988) concluded that changes in surface roughness

interacting with the canopy hydrology are significant in determining the mode1 response to

deforestation and in particular are largely responsible for the changes in surface temperature. Shukla

et al. (1990) observed that deforestation may cause atmospheric circulation changes and as a

consequence there exists the possibility that regions adjacent to the deforested area could exhibit

clirnatic disturbance. The net radiation is decreased by deforestation though the solar radiation is

almost unchanged (Henderson-Seller et al. 1993). In this comection, data should be collected on sea

level rise due to green house effect and research should be conduaed in the field so that the nature

of the calarnity cm be properly understood and action should be taken to improve the situation.

Several authors have expressed their opinions that deforestation can exacerbate the green house

effect .

In many regions of the tropics, forest managers are conFronted with the situation that the

natural forest eeither already disappeared or will do so in the very near future (Kleine and Heuveldop,

1993). The world's population is increasing and the human condition directly depends upon natural

resources, especially forests or forests products.

The 60% of the world's remaining tropical moist forests Iocated in Latin America are under

intense pressure, pnmarily for conversion to other land uses that are considered more lucrative than

forest management ('emam et al. 1992). Although deforestation is occumng throughout the world,

the rate of deforestation is rnuch higher in Asia in cornparison with other pans of the world. Tole

(1998) noted that the rate of deforestation in Bangladesh is 3.3 % per year which is the highest rate

of deforestation in Asia. Dunng the year 198 1- 1990, the deforestation rate was 1.2% in Asia but

throughout the world this rate was 0.8% (FAO, 1993). Because of this intensive deforestation rate,

the govenunent of Bangladesh has given special emphasis to the creation and devolvernent of coastal

af5orestation. The govemment has created a new forest circle called a 'plantation circle' and

development project has been supponed with the financial assistance of national budget and

international agencies. Bangladesh dso plans to manage the forests in a sustainable way to prote*

them f?om environmental degradation and natural cdamities.

2.5. Sustaina bility

In forestry, sustainability means the harvesting of timber at a rate less than or equal

to forest growth rate and the goal of sustainability is to include the long term maintenance of al1

forests benefits and the multiple uses of forests thorough management practices that maintain

ecological integrity (Pretro, 1994). The Society of Amencan Foresters descnbes sustainable

management as sustainable yield management (David, 1995). According to Mercier (1 994),

sustainable forest management describes the techniques and tools that can be used to achieve the

objectives of sustainable development and sustainable development of forest takes into account the

social, econornic, and environmental dimensions of the forests in the context of the needs of the

present and future generations. Sustainable forest management is the process of managing forests

to achieve objectives with regard to the production of a continuous flow of forest products and

services without undue reduction of its inherent values and the future productivity of the forest and

without undue desirable effects on the physical and social environment.

The sustainable management of any natural resource is composed of three dimensions:

(1) social expectations, including global responsibilities; (2) economic demands, recognizing markets,

costs and (3) ecological constraints, including wildlife species, their habitat and the retention of

naturd ecological process. Probably for this reason, Wood (1994) noted that managing ecosystems

means managing entire systems by the integration of ecological, economic, and social factors to

control the biological and physical systems. This is difficult because great uncertainty exists about

most ecosystems management.

Generally, the consumption of resources increases as the population increases. This

increase may also happen due to economic and financiai development. But forest resource increment

in generai is not consistent with population increase. So forest resources should be sustainably

managed in a manner that is compatible with environmental conservation and social needs. The

implications of harvesting forest resources for other forests values should be taken fùlly into

consideration. It is aiso possible to increase the value of a forest through non-darnaging uses such

as eco-tounsm and the managed supply of genetic maienais (Tewari, 1994). Concrete action is

needed in order to increase people's perception of the value of forests and al1 the benefits they

provide. A coastai fiorestation prograrn may play a vital role for environmental purposes and human

needs.

2.6. Objectives o f constal amorestation in Bangladesh

In recent years the frequency of floods and their intensities have increased substantially and

the necessity of taking some preventive measures are essential (Alexander 1989). Bangladesh has

urged international assistance for financing to resist this natural calamity and the World Bank has

agreed to coordinate the flood control initiatives (Boyce, 1990).

Saenger and Siddiqi (1993) noted that the main objective of the coastal florestation prograrn

was to convert the coastal areas under mangrove cover to minimize the destructive action of aimost

regularly ocairring cyclones and tidal surges, and to ftlfil this objective artificial regeneration dong

this area was initiated in 1966.

The coastal afforestation project started in Bangladesh in 1975 and continued up to 1994 and

an area about 127,000 hectares was planted in the region (Siddiqi and Khan, 1995). This project has

several objectives including the production of timber, accelerating the rate of accretion of new land

and improving the protection of near shore agriculrural and residentiai lands fiom storm damage

(McConchie, 1990).

The coastal afforestation belt began in 1966 in connection with the construction of WAPDA

(Water and Power Development Authority) embankments, with the objectives of protecting lives and

property from natural calamities like cyclones and tidal bores and of stabilizing the newly accreted

lands @rigo et al. 1987). Originally this program was limited to the embankment areas and planting

al1 areas gained from accretion processes. Initially, the coastal afforestation scheme had the forernost

objective of protecting values but now the major objective is reclarnation of coastal land through

new plantations. This objective is successfulIy achieved because every year the country is getting new

land from the Bay of Bengal. The other objective of the coastal afforestation program is to create

employrnent opportunities for the neighbouring rural people (Imam, 1982).

The species used for coastal aorestation are keora (Sonneraiia apetolu), baen (Avicinia

ofjinaIis), gewa (Ecoecaria agaIIocha), kankara (Bnrguiera &yrnnorrhizu) and babul ( Acacia

nilolica ). 66% of the total area represents the most successfûl plantations and needs silvicultural

treatments such as thinning @rigo et al. 1987). The rest of the areas have less trees. This project

has several objectives including the production of timber, accelerating the rate of accretion of new

land area, and improving the protection of near shore agricultural and residential lands from storm

damage ( McConchie, 1990). A huge amount of sedirnent is carried from the upper catchment areas

fiom India and Nepal and deposited in Bangladesh (Hussain and Archarya, 1994). The rate of

sedimentation is high during the rainy season and with river water some of this sediment deposits on

the coastal and mangrove forests of Bangladesh. Some of these sediments are also redeposited on

the costal forest fioor during high tides. A survey was done by Drigo et al. (1987) on the basis of

aerial photography produced by SPARRSO (Space Research and Remote Sensing Organisation).

They found that the accretion that occurred during the three years period (1984-1987) was 30598

hectares.

As mentioned earlier, the main purpose of coastal afforestation is to reduce fiooding by

creating a drag force. Halliday et al. (1 993) defined the drag force as a force that opposes the relative

motion and points in the direction in which the fluid flows relative to the body. The drag coefficient

(k) of lake Erie was measured by Keulegan (1953) according to the following:

where A , is the average water depth;

p is the density of water;

f is the fiaction of wind stress at the bottom in cornparison to that at the top of the water;

c= surge height;

p a = density of air and

WS = wind speed.

The value off was taken as O. 1 for the lake Erie. Murty (1984) used this method to estimate

the wind stress in the Arabian Sea.

The equations for estirnating surge height (0 were developed by @as, 1972) by solving the

foiiowing linear differential equations:

In the above equations, partial derivatives are denoted by subscripts. The depth of the seabed is

represented by h, p is the density of water, fis the Coriolis parameter and g is the acceleration due

to gravity. The Coriolis parameter f = 2 o sin 4, where o is the angular speed of the earth's rotation

and 4 is the latitude (Flather and Hubbert, 1990). U and V are the cornponents of the total transport

of water in rectangular CO-ordinates, thus

where u and v are the eastward and northward components of motion. Das (1972) adopted the

comrnonly accepted expression for wind stress ( F ,, G , ) as:

F,=k ' p , N , I u ,

G , = k ' p , N , l v ,

where p, is the density of air, Va is the wind velocity at a height of 10 m above sea level and u, and

v, are the easterly and northerly components of V a , k' is a non-dimensional fundon of the stability

of the air and the wind velocity.

2.7. Property damage

Cyclones and water surges cause deaths and property damage. The latter can flood coastal

and nearby areas which damages trees, agricultural crops, roads, cattle, human life, and their houses.

The damage due to these calamities depends on the wind speed and the height of the water nse and

is highly variable. Howard et al. (1983) noted that the darnage due to a hurricane is millions of

dollars may be estimated from the relation, damage = c , (WS)c2, where WS is the wind speed and

c , and c, are empiricd constants which may be obtained fiom historical data. They used this

relationship for estimating the value of property damapd by humcane in the United States. It is

possible to estimate these values fiom historical records by establishing a relationship between the

wind speed and property damage.

2.8. Reduction of damage

One important approach is to reduce the incidence of flood/ cyclone damage. A number of

prograrns have been implemented to achieve this goal. Among these, improvised signal program,

shelter centres, and dams are important. AI1 of these programmes are intended to reduce property

darnage and lives lost but none of them reduce the number of cyclones or floods hitting the country

or their intensities. Therefore it is of great interest to decide whether these programmes should be

augmented or whether other new protective measures should be implemented to reduce the number

of calamities and even if they happen, to reduce amount of darnage by reducing its extent. This can

be performed by scoring rules.

The costs and performance of different measures may be summarised, from literature and

personal expenence, according to Table 2.1.

TABLE 2.1. Cost and performance of different programs

Programme Dam Signal waming Shelter center Coastal afforest ation

Initial cost High High High Low

Maintenance cost Low Low Medium Medium

Revenues No No No Yes

Environmentai No No No Yes

Protection Effectiveness Yes Poor Good Excellent

(water surge) Effectiveness Good Poor Good Poor

(Wind speed) Socially accepted Yes No No Yes

Land Accretion No No No Yes

Ernployment Initiaily Very few Very few Continuous

2.8.1. Different measures for flood control

Due to change in climate and other reasons, natural calamities are increasing throughout the

world. But Bangladesh will be more affected due to sea level rise, its higher population growth rate,

deforestation, and its geographical location.

Severd preventive measures can be taken to protect and help the afEected people, for

example, shelter centres and the construction of dams covering the entire coastai belt could be build.

Generally, poor or disaster aEected people live along the Coast where cyclones strike, because a

reasonable livelihood is obtained under normal conditions in those areas. While ernbankments can

provide some protection fiom the flooding associated with cyclones, they are much less able to cope

with storm surges. Neither are traditional materials able to withstand severe winds. The equation for

estimating surge height was developed by Das (1 972). Human intervention in the natural system

(e.g., deforestation and flood control activities) plays a major role in aggravating the flood situation

in Bangladesh (Begum, 1996).

Coastai plantations proved to be an effective measure in some parts of the coastal belt

of Bangladesh during the 1991 cyclone. The coastal communities of Mirsari and Sitakund suffered

the least casualties and property darnage, primarily due to protection provided by a one to two

kilometres wide belt of plantations along the coastal belt (Begum, 1996).

A system of ernbankments for cyclone protection was constnicted in the 1960s and

1970s but they have been eroded over the years or exceeded in severe events and are now in need of

rehabilitation (World Bank, 1989). Mer the disaster of 1970, cyclone preparedness began but has

yet to reach every high risk zone. Social customs and poor communications have, in general, lirnited

the effeaiveness of wamings and the use of shelters (Tdukder and Ahmad, 1992). But precaution

is better than prevention, so necessary action should be taken to reduce these natural calamities and

the loss of properties and lives by preventing such caiamities. For example, if we can cover the whole

coastal belt with forest species then we can partially or wholly resist such type of calarnities. We can

also try to prevent deforestation and establish new plantations throughout the country which will

help to reduce soi1 and environmental degradation. We cm also try to establish new plantations on

the newly accreted land dong the coastal belt.

2.9. Types of decision making situations

When we have a decision to make, we consider several ways to achieve the desired result.

Our decision is based on what we believe about (a) the different alternatives (b) the state of nature

( C) the outcomes of the decision and (d) the desirability of the outcomes (Lifson, 197 1). Our beliefs

depend on the information available, either through past expenence or current analysis or through

communication with others. When we make a decision, that decision can be based only on the

information available to us at the time of decision- making, otherwise we may need to wait for fùrther

information.

A systems approach incorporates the concepts, methodology, and tools for obtaining desired

information about systems and is therefore more than merely a way of anaiysing complex systems

problems. In other words, we may define the systems approach as a discipline for identifjing,

processing, and comrnunicating the information needed for rational decision making (LXson, 1971).

The decision makers that deal with any natural resources need quantitative assessments of

social necessities and desires, especially of the local people. The best and latest ecologicai

knowledge must also be available in a form usefûl to decision- makers (Maser, 1994). The decision

making process must be designed to maintain and build sustainability or the overlap of what people

want and what is ecologically possible in both the short and long run so that his\ her decision is

acceptable to the public.

Decision analysis under uncertainty includes procedures and methodologies for assessing the

real nature of a situation in which a decision must be made. It provides insight, knowledge and

motivation to the decision makers and implementers. The classification scheme for decision- making

situations is based upon the knowledge the decision- maker has about the States of the nature of

problem (David et al. 1985). In this regard, there may be three types of decision making situations:

(a) If the decision- maker knows in advance which state of nature will occur then he/ she is in a

position to choose the best alternative on the basis of payoffs for that state of nature. This type of

decision is said to take place under certainty, also called deterministic. This extreme deterministic

case has a very limited use because most naturai phenornena are probabilistic. (b) On the other hand,

if the decision- maker does not know which state of nature will occur but he or she does know their

probabilities of occumng, this type of decision making may be termed decision under risk. ( c) If the

decision- maker has no information at al1 related to the nature of the outcome then the decision is

said to be a decision under uncertainty (Eiselt and Langley, 1990).

Forest management decisions involve uncertainty or uncertainties. In these situations, the

selection of the most appropriate one is diflicult. Fint the decision maker has to select a cnteria such

as maximum volume production or maximum revenues or payoffs or other benefits like environmental

benefit. Then he or she can determine which decision alternative is the best one. By making good

decisions in al1 situations that face us, we hope to ensure as a high percentage of good outcomes

as possible. We may be disappointed to find that a good decision has produced a bad outcome, or

dismayed to leam that someone who has made what we consider to be a bad decision has achieved

a good outcome (Howard, 1983). Decision analysts refer generically to the cost of making wrong

decisions as the expected opportunity loss and may be termed as the expected cost of ignonng

uncertainty (Morgan and Henrion, 1992). To calculate this type of cost we need a procedure for

calculating the expected performance of a given strategy for finding the best one. This requires

explicit characterization of the alternatives and their performance. We can estimate the value of their

performance using decision analysis, also called the Bayesian Analysis (Clemen, 1995). Few authors

have used uncertainty in forest management planning purposes. Forest management under uncertainty

had been discussed by Boychuk and Marte11 (1993) to demonstrate how to assess impact of specific

fire regimes to evaluate fire management programs, and to assess the impact of specific fires.

Uncertainty concerning outcomes, as well as the utility of outcomes, is present in the decision-

making situation. On the bais of best outcome or maximum utility, the forest manager can choose

the best decision.

2.9.1. Criteria for decision mrking under uneertninty

A necessary condition for uncenainty to be important to a forest manger is that its

consideration codd affect hid her decisions significantly. That is, the manager's belief about the

uncertainty can affect which alternative is most desirable. Then the challenging process of selecting

the system variables for the analysis, which are ail variables on which the outcûmds depend or may

have significant influence on friture outcome. The decision maker is invariably concemed with the

friture since decisions made now cm only have consequences in the future. That is why uncertainty

is a critical element of many decisions we face. Unfortunately, the decision maker is seldom absolutely

certain of the consequences of his decisions because the future is uncertain and the most important

part of a decision analysis is the treatment of uncertainty. Decision theory provides sorne helpful

approaches to decision making under risk and uncertainty. The appropriate decision rnaking depends

on the degree of knowledge concerning the hture and the decision maker's attitude towards

uncertainty .

A wide variety of decision critena for risk management decision making may be used. If the

value of benefits cannot be estimated exactly but a choice between the number of alternatives must

be made, a cost effeaiveness criterion may be used. A desired and obtainable objective is selected,

perhaps on noneconomic grounds. One then chooses the best alternative that will achieve this

objective at the lowest cost, al1 other things being kept more or less the same or equal.

The bounded cost criteria is sometimes also tenned the 'regdatory budget' approach. This

strategy sets a maximum budget that society cm fiord to devote to risk management activity, and

then tries to aiiocate resources in a way that maximises the arnount of nsk reduction achieved within

the budgetary constraint. Although the bounded cost approach may not set the budget constraint at

the socially optimum level, within that constraint it does at least provide an incentive for local

efficiency in the allocation of resources (Morgan and H e ~ o n , 1992).

The decision maker or the forest manger can comply with the decision rule to maximise

expected utility. Under the concept of subjective probability, he should assign explicit probabilities

to the States of the nature and to outcornes.

2.9.2. Stochasticity

According to Valsta (1992) stochastic optimization problems may be divided into two

groups- adaptive and anticipatory. In adaptive optimiration, the state of the system is observed a?

regular or irregular intervals. Observations are used to adjust the optimal decision. This approach is

called feedback control or closed loop control. Haight and Monsemd (1990) used this approach to

denve the optimal decision rule of whether or not to harvest a stand when the timber price at

decision time is observed. Kao (1984) applied this type of decision making process in thiming

operation for optimization.

Anticipatory models are used for deriving optimal decisions for the whole planning penod.

In this case, the solution mut take into account the uncertainties over time and according to some

criteria, may be optimal. Kao (1 982) applied this type of model to analyse optimum thinning and

rotation in an anticipatory setting when stand volume growth was probabilistic.

Taylor and Fortson (199 1) developed a stochastic simulation model to estimate the impact

of site index, planting density, and rotation age on the retum and nsk of unthimed loblolly pine

plantations. They approximated risk as the standard deviation of the present value for each

combination. Sources of risk were stumpage rate, survival, and yield nsk. According to Boychuk

(1993), timber production risks involving long term trends include pollution stress, ecosystem

degradation, climate change, land withdrawals, exotic pathogens, and permanent changes in

comparative advantages.

Silver iodide was first used expenmentaily to reduce the speed of a humcane in the USA in

1969 (Gentry, 1970). The cost of seeding is significantly high because it requires a number of

aircrafl, instruments for seeding, and seeding experts. In addition to these, we are uncertain about the

amval of a humcane and it will be more expensive to keep experts reserve al1 the time. Moreover,

though after seeding the wind speed decreased, they were not certain whether the decrease was due

to seeding or natural changes. From the anaiysis of past storms, Gentry(l970) noted that wind speed

change may occur naturally. Experimental seeding has aiso been done in Atlantic Ocean. Howard

et al. (1983) conducted another study using decision analysis as a tool to make proper

recommendation on seeding. They studied the possibility of mitigating the destructive force of

humcanes by seeding with siilver iodide. They also found that the costs involved in equiprnent, crew

training and communications and support facilities, are substantial. Finally, they concluded that

seeding rnay be permitted on an emergency basis.

2.9.3. Nature and sources of uncertainties

Since uncertainty is at the heart of most significant decision problems, decision making

requires specifying the sources and amount of uncertainty that exists. Uncertainty rnay arise because

of incomplete idornation - what will be volurneha at age 30 year. Even when we have complete

information in principle, we rnay be uncertain because of simplifications and approximations

introduced to make analysing the information cognitively or computationally more tractable. As weîî

as being uncertain about what is the case for the other forests, we rnay be uncertain about what we

like, that is, about our preferences, and uncertain about what to do about it, that is, our decisions.

Very possibly, we rnay even be uncertain about the degree of uncertainty and the variety of types and

sources of uncertainty.

Uncertainty rnay arise fiom lack of precise knowledge regarding component mode1 structures

and input parameters (Brand and Small, 1995). Important considerations in conducting an uncertainty

anaiysis rnay include the role of inadequate scientific understanding of important processes, vagueness

in process or parameter definition, meanirement error, sarnpiing error and scientific uncertainty.

Uncertainties in forestry decision making situations may arise fiom a vaiiety of sources. The

appropriate method to characterize the uncertainty, and the appropriate method for trying to reduce

it, generally depend on the particular kind of forest or situations. In the present study the sources of

uncertainty may be due to natural calamities iike depressions, storms, severe storms, humcanes and

water surges.

In principie, ail empirical quantities are uncertain (Morgan and H e ~ o n , 19%). There is never

absolute certainty about the truth of any empiricai proportion or about the exact value of any

continuous ernpiricai quantity. No matter how great its precision, no experiment can measure a real

vaiued quantity with zero error. However, it is cornmon that the uncertainty, for practical purposes,

is negligible in many of the empincai quantities and so we may treat them as certain in the model.

The appropriate method for evaluating uncertainty in rnodels depends to a considerable extent on the

nature and complexity of the component submodels as well as their interactions. Analytical methods

or approximations rnay be available but in the most general case, Monte Carlo or related simulation

methods are required to propagate the uncertainties in the component model inputs through to the

final estimate of risk (Brand and Small, 1995).

2.10. Influence diagram and decision tree

Infiuence diagrams and decision trees may help to take rationai decisions about the

establishment of coastal forest in Bangladesh. The heart of the technique generally used in analysing

the decision through a decisiontree that represents the stmcture of ail possible sequences of decisions

and outcomes and provides cost, value and probability inputs. Two fundamental operations,

expectation and maximisation are used to determine the most appropnate decision f?om the tree. At

each chance node, the expected profit is computed by summing the probabilities of each outcome,

multiplied by the value of that outcome plus the expected profit of the node following that outcome.

Ai each decision node, the expected profit of each alternative is calculated as the expected profit of

the following node less the coa of the alternative. The optimum decision is found by maxirnizing

these values over the set of possible alternatives, Le., by selecting the alternative with the highest

expected profit. The decision to establish a coastal forest in Bangladesh may be shown in the form

of a decision tree. On the basis of the information in a decision tree, on behalf of the Bangladesh

Govemment, the ministry of environment and forests will take the decision whether the country

should proceed to establish a coastal afforestation or not. On behalf of the ministry of environment

and forests, the rninster himselfïherself can take the decision or hdshe can ask to collect more

information or can € o n a cornmittee to estimate the costs of a coastal afforestation program and its

benefits. If it is decided to establish a coastal afforestation program then that program will be carried

out by the forest department. On behalf of the forest department, the divisional forest oficer

(planning and development) will prepare a draft plan indicating when, where and what species will

be planted. That plan wiil consist of two parts; the descriptive and prescriptive part. The descriptive

part generdly descnbes total area, location, climatic conditions, growth and yield projections,

population living nearby areas, their economic conditions, and communications and transportation.

The prescriptive part may include working circles like long rotation and short rotation working

circles, management objectives and strategies, forest regdation, felling series, silvicultural operations,

forest protection. Again, the prescriptive part may be divided into two parts: long and short term

plans. The plan will also include an annuai plan of operations and budget. The chef conservator of

forests and e s t e r of environment and forests have to agree with this plan and then the plan wiii be

sent to the parliament of the country for final approval. Othenvise they can ask for corrections or

modification. M e r approval of the parliament, the divisional forest officer/ conservator in charge

of coastal florestation program will begin implementation. This strategy is represented by Figure

2.1.

A decision anaiysis process should be developed so that the ministry of the environment and

forests may decide whether the governent should spend more money for the coastal florestation

program or they should stop this program.

3.0. Deterministic Phase of a Decision Analysis for the Establishment of a

Coastal Afforestation Program in Bangladesh

3.1. Introduction

Due to recurrent floods, cyclones and tidal surges, Bangladesh is one of the most

environmentally vulnerable countries in the world. Flather (1994) observed following reasons for

this vulnerability:

(i) it lies in the path of tropical cyclones which typically onginate in the central and southem parts of

the Bay of Bengal;

(ii) it has wide and shailow continent shelf. Generally, strong winds acting over shallow water

generate stom surges which in conjunction with the substantial astronomical tides, can produce high

water levels;

(iii) the coastal areas of Bangladesh are low lying and unprotected land. Most of the time banks are

flooded and during cyclone or other s tom surge is heavily flooded and damaged; and

(iv) the population living in this area is high and most of them are poor and their houses are not

strong enough to withstand natural calamities.

Floods kill more people than cyclones in Bangladesh (The Daily Star, 1998). Flooding is also

responsible for much destruction, especially near the coastal areas. Storm surge is the greatest threat

to both human and animai lives and property in the coastal region of Bangladesh (The Daily Star,

1998).

58

Mitigation of these disasters requires a number of complementary and coordinated actions.

DiEerent protective measures have been taken to reduce property loss and death from these natural

calarnities. Among these strategies, coastal afforestation, the construction of dams, shelter centers,

and improvised waniing signals are important. No decision, for example, coastal florestation, should

be taken without considering the long term benefits and costs that might result from the decision.

This means that alternatives and their present and fiture costs and benefits should be d p e d in the

decision analysis process.

Decision anaiysis is an appropriate technique for evaluating different alternatives, payoffs and

preferences conceming future costs and outcomes. A rational decision would also consider political

and social factors, especially concerning effective land use planning, the absence of which would

rnake effective land-based resource management impossible. The decision aids for comprehensive and

consistent evaluation of the benefits of coastal fiorestation to reduce flood Sected area are surely

lacking in Bangladesh. As a first step, a decision aid should be developed in the form of a logid and

consistent procedure for evaluating the total flood affected area after establishing coastal forest in

Bangladesh. The development of this type of decision aid should include a deterministic mathematical

mode1 which takes into account the flooded area and the relevant state and decision variables. The

model should provide an estimate of the flood affected area of a particular place and finally the whole

country. In deterministic problems, variability always exists where determinkm is used because of

special circumstances or special assumptions made in order to solve the problem. So in deterministic

cases it is assumed that one knows fuli weli the consequences of any decision. This means that the

values in the model are known and that the probabiiities of chance events are either zero or one.

DEerent phases of a decision analysis cycle are show by Figure 3.1.

The deterministic phase of a decision analysis includes the development of a deterniinistic

mathematicai model which rnay include the important environmental, physical, biological, economic,

and technological factors.

The steps in the deterministic phase were defined by Howard (1983) as follows:

(a) Define the decision;

(b) Identify the alternatives;

( c ) Assign values to the outcornes;

(d) Select the state variables;

(e) Create a structural model by establishing rel

and outcornes;

(f) Create a time preference model.

Analysis: Measure Sensitivity to

(1) Decision variables and

(2) State variables.

33. Decision analysis process

ationships b etwe en state v ari es, de variables,

Fioods, cyclones and storm surges have become regular phenomena and pertinent issues for

60

coastal areas in Bangladesh. The USAID recornmended a combination of structural and nonstructurai

measures to reduce these calamities. More than 700,000 people have been killed in Bangladesh by

storm surges since 1 960 (C howdhury, 1 994).

Several authors have noted that in recent years the fiequency of floods and their intensity have

increased substantially in Bangladesh and for that reason it is essential to take some preventive

measures (Alexander 1989). Bangladesh has requested international assistance in the form of

financing to proted or reduce damage due to these natural calamities and the World Bank has agreed

to coordinate the flood control initiatives (Boyce, 1990).

Decisions are thnist on us by circumstances like natural disasters. Decision theory or decision

analysis may be used to help in determining optimal strategies when a decision maker is faced with

severai decision alternatives and an uncertain or risk filled pattern of results. For example, a forest

manager or a decision maker may be interested in knowing whether it is worthwhile to spend money

for dams or coastal afforestation. His or her ultimate goal is to produce maximum production or

revenues or other benefits like environmental protection or protection from naturd caiamities.

Decision anaiysis provides not only the philosophicai foundations but also the Iogicd and quantitative

estimates which sometimes prove helpfùl for resolving political or social disputes in rnany situations.

Since the decision analysis encodes information, values and preferences numericaily, it permits

quantitative evaiuation of the various courses of action with different degrees of success (Howard,

1988). Further, it documents the state of idormation at any stage of the problem and indicates

whether the gathering of fùrther information is economically justifiable. The decision analysis would

also confirm whether any mistakes were made, whether appropriate sensitivity analyses were

performed, and in general, whether the nght conclusions were drawn (Howard, 1988). So, decision

making usually focuses on the choice among different alternatives. It is also a tool to conwice others

those who have several options in their minds. In other words, the policy rnaker can judge the whole

operation to verifL whether the nght course of action was clearly indicated and communicated and

how much the decision can satis@ strategic objectives. Keeney (1996) described the strategic

objectives hierarchy for British Columbia Hydro to rninimize environmental impacts. Following him,

the strategic objectives for the flood control in Bangladesh may be described according to Table 3.1.

TABLE 3.1. Strategic objectives for flood control in Bangladesh

1. Maximise contribution to flood control

1.1. Minimise flooded area

1.2. Reduce loss of properties

1 -3. Reduce damage to roads and highways.

2. Maximise contribution to economic development

2.1. Minimise cost of construction and planting

2.2. Maximise revenue fiom alternatives

2.3. Minimise maintenance cost.

3. Minimize death hazards

3.1. Reduce deaths of people

3.2. Reduce deaths of cattle and other animds.

4. Maximise environmental benefit

3.1. Maximise environmental benefit for locality

3.2. Increase flora

3 -3. hcrease fauna

3.4. Irnprove wildlife ecosystem

3.5. Increase recreational facilities

3.6. Increase fish cultivation

5. Provide employment

5.1. Provide maximum employment for the local people

5.2. Provide sustainable employment for skilled and unskilled people.

6. Social acceptance

6.1. Must be accepted by local people

6.2. Must be accepted by neighbouring people.

The decision - rnaker should choose a decision in such a way that hisher decision satisfies dl the

objectives. But since it is not feasible, hdshe has to choose the rnost important one or two objectives.

From the objectives of creation of coastal afforestation, 1 believe the most important one is item 1,

that is, flood control in Bangladesh.

3.3. Storm surges

Storm surges are a b n o d l y high water levels produced by cyclones; in other words a stom

64

surge may be defined as the algebraic difference between the measured tide and the predicted

astronomical tide (Blier et al., 1997). According to Welander (1 96 1) the term "Storm surge" means

the effects of wind and atmosphenc pressure on the sea level associated with a single storm. Murty

(1984) noted that the stronger the storm and the shallower the offshore waters, the higher the storm

surge.

It was noted by Danard and Murty (1994) that most of the damage in the coastai areas is due

to storm surges produced by water currents and wind waves and not fiom high water levels

themselves. But much remains unknown about the interactions among cyclones, astronomical tides,

and stonn surges in the Bay of Bengal and there is no numerically calculated result showing the type

of behavioural change of the storrn surges due to the much speculated sea level rises or the bottom

level changes ( As-Salek and Yasuda, 1995).

3.4. Different alternatives for flood control in Bangladesh

Typicaily, we face decision problerns in identifjing alternatives. However, d e r identiwng

alternatives by studying problem with great care we may consider objectives or criteria to evaluate

them. it is reactive, not proactive and it is backward; it puts the art of identdjing alternatives before

the home of articulating values (Keeney, 1994). Reduction of losses due to extreme physical events

may be achieved in two ways: (i) environmental control, and (ii) human vulnerability modification.

Environmentai control involves modifjing the hazard event itself This type of large scale

environmental control involves the suppression of naturd events which is either impossible or

expensive, which the developing country may not be able to afEord. The second method of reducing

loss involve changing human attitudes and behaviour towards nature. This approach is termed human

vulnerability modifications (Haque, 1997). This approach may include hazard loss reduction by using

modern technologies like improvised signal systems, dams, shelter centres and coastal florestation.

Flather (1994) noted that improved forecasts of water levels and better warnings and the provision

of shelters in appropriate locations could significantly reduce casualties in future cyclones and floods.

Several preventive measures could be taken to protect and help the affected people in coastal

areas of Bangladesh. For example, improvised warning systems, shelter centres, coastal &orestation

and dams covering the whole coastal belt of Bangladesh could be built. Flood control strategies and

their different benefits are represented by Figure 3.2.

Haque (1997) noted that warnings could not reach the rural communities in coastai districts.

Hazard waniing systems and preparedness programs have generally proven to be effective in the

developed countnes (Haque, 1997) but not in developing countries. Generdly, poor or disaster

affected people used to live dong the Coast where cyclones stnke, because a reasonable livelihood

is obtained under normal conditions. Their houses are not strong enough to protect against strong

wind or water surges. Moreover, due to road and transportation problems, it is not possible to

evacuate the whole locality on short notice. While embankments can provide some protection fiom

the flooding associated with cyclones, they are much less able to cope with storm surges. M e r a

number of destructive s tom surges in 1% 1, the construction of a sea wall was completed to protect

the city of Nome in West Alaska, but in 1974 Nome was stnick by the most powerful storm in the

history (Blier et al. 1997). Despite the presence of the seawall, Nome was severely damaged and

signincant flooding occurred.

Human intervention in the natural system (e.g., deforestation and flood control activities)

plays a major role in aggravating the flood situation in Bangladesh (Begum, 1996). It was mentioned

earlier that the coastal communities of Mirsarai and S i t h n d suffered the least casualties and

property damage, primarily due to protection provided by a one to two kilometers wide belt of

plantations along the coastal belt (Begum, 1996).

Begum (1996) noted that there are at least 706 km of sea facing and similarly exposed

embankments in the coastal districts where there are no trees or very little trees on the embankment

where short term plans should be taken to raise plantations on embankments to reduce damage fiom

cyclone and stom surge. Finally, she recomrnended to offset environmental deterioration,

florestation program should be started as soon as possible and the cutting of trees fiom these coastal

regions should be made illegal. Tree planting program may also be taken along embankments and

various categories of settlements.

3.5. Description of the deterministic mode1

There are two types of variables in the decision analysis process, namely decision variables

and state variables. Decision variables are those under the control of the decision - rnaker (e.g.,

coastal afforestation, the construction of dams, increasing the total height of the dam and total width

increasing of the fores). State variables are those not under the control of the decision - maker (e-g.,

wind speed, surge height and mean sea level of the area). The outcornes include flooded area, crop

damage and the number of people evacuated and killed.

Floods have many socio-economic, ecologicd, and environmental impacts but I have chosen

to focus on the monetary vdue of property loss only. For simplicity, let us start by considering only

the flood afFected area and the loss of property as the critena for Our decision making. The loss of

property may be estimated on the basis of average loss per unit area. Then the objective of the

decision system is to estimate the present net worth of the future damage by natural calamities for

different protective measures. Since the area flooded is the oniy cnterion for our decision making we

may convert it into monetary value multiplying by a factor which represents the monetary loss per

unit area. The criteria for the number of reported deaths is problematic because the number of people

living in that area is not constant throughout the year. We do not even know their exact rate of

population increment in different coastal areas. The number of people evacuated may be taken as an

outcorne. But the number of people evacuated is related to the presence or absence of shelter centres

and waming signals; but it is not related to dams or coastal fiorestation program. Also, the actud

number of people evacuated is not available because people are usually evacuated by walking and

there is no register to maintain the record of the total number of people that took shelter in different

shelter centres. However, flooded area alone is not a sufficient criterion to descnbe the consecpence

of the decision. There are crop, road and property damage and environmentai impacts that may have

significant impacîs due to our decision. The govemment may have some legal responsibilities for any

direct and indirect results of any decision.

Protective structures may be partially destroyed and afler being repaired may become ready

for use in the future. In other words, we may use sarne protective measure for several consecutive

years. Ifwe take into account that kind of benefit in the decision analysis process then it may reduce

the cost of a flood control program significantly. This means the benefit obtained from previous

construction or salvage rnay significantly reduce the cost of construction the next time. This

contribution d Save money for maintenance or reconstruction of related alternative.

3.6. Other benefits of different alternatives

Decisions ofien are characterized by multiple objectives or benefits. Each objective is a

statement of something that one wants to achieve in his decision. For example, one objective of the

forest department in Bangladesh is to protect or minimize environmental impacts.

It should be mentioned here that there are several benefits for ail the alternatives. For example,

a coastal forest can provide timber in addition to flood control. A dam can protect saline water from

entering inland. Trees can be grown on dams. Cyclone shelter centers are used for multipurpose use

dunng non cyclone periods, such as union council office cum community center, school, mosque,

family welfare center and storage facilities. Al1 these benefits can not be included in the mode1 dunng

a decision analysis because different alternatives provide different type of benefits and most benefits

cannot be expressed in monetary values.

3.7. Choice and sue of alternatives

Shce different alternatives provide different benefits it is not possible to express al1 of them

through any cornmon benefit or use. For simplicity, let us take two alternatives: a dam and coastal

florestation, and assess them in tems of their potential impacts on flood control or flood afEected

area for illustrative purposes.

The maximum number of different alternatives is theoretically infinite, as much as we can

spend resources as inputs we can denve more and more benefit from it. For example, as much as we

can increase number of alternatives we can Save more lives and property. Similarly, as much as we

cm build dams we can protect more area fiom flooding. As much as we can establish coastal forests

we can expect more benefits in ternis of flood control and environmental degradation. For

simplification, we may assume that the maximum height and width of the dam should be greater than

the height and width required to resist the water surge. On the basis of these assumptions we can

develop structural models for coastal Sorestation and a dam in relation to flood/surge control in

Bangladesh.

3.8. Organization of the deterministic model

Figure 3.3 shows how the deterministic model is organized. The output from the system

model is the flooded area which shows the effect of the decision variables. Several alternatives of

decision variables and state variables should be examined. AU these variables (i.e., state variables and

State Variables: 1. Slope of area 2, Surge height 3. Wind speed

System Mode!: I

Decision

Alternatives: 1. No Action 2. Forest dong coaçtal belt:

Species, width and densw 3. Dam dong coastal belt:

Height and wiûh

Outcornes - Area flooded - Monetary loss

Preferences: 1 . Time 2. Less damage 3. Employment

Fig. 3.3. Organisation of the deterministic model.

decision variables) enter into the system model. The system model will predict the output (i.e., the

flooded am).

Since the choice of a discount rate, less damage of different alternatives and creation of

maximum employment are in the list of preferences (Table 3. l), the decision maker has to consider

these with great care. Among these, the discount rate may be set by the policy maker.

3.8.1. Structural equrtions

The detemiinistic phase includes the development of a structural model that shows the

relationship between the decision and state variables and the resulting outcornes. State variables are

not under control of the decision maker (Braunstein, 1983). For the present case the outcome is the

flood affected area and property loss and the state variables are water surge, wind speed, and dope

or height of sea level of the area, the number of stems per unit area, diarneter and height of the trees.

A fundamental characteristic is that each decision analysis is developed for a specific decision. For

example, in the present case, whether the Govemment ofBangladesh should spend money for coastal

florestation or dams.

Detailed records of losses at different sea level are not available. However, Rashid (1978)

descnbed land levels and flooding depths (June- October) in Bangladesh. On the basis of flooding

depths and the shape of the land area we can divide coastal area into several rectangles. Let us take

a particular surge which floods a surface distance 'd' from zero sea level. We ais0 assume that the

mean sea level of the end point of flooded area is S meters and shortest length of that point is L km.

If 0 is the angle between d and L then fiorn Figure 3.4, we get

1 S d= -- 1000 (sine)

We may assume that the surge height (0 is approximately equal to S.

Ifwe divide the whole coastal belt into n rectangles, then for any rectangle i, equation (3.1)

1 Cl may be written as - -- di - 1 ooo (sine,)

If we assume that the width of the i th rectangle is W (km), then total area of that particular

rectangle is

Then total area of al1 the rectangles or the flood afTected area (FAA) will be

In equation ( 3 4 , it was assumed that the surge height C is constant everywhere. Equation (3.4) will

give accurate value of FAA when there is no other extemal factor like wind speed or other resistance

and surface of land is uniform. But that is oot true in general.

74

ci = Distance travelled inland by surge water, km; S = Height of sea level at the end of surge, m; L= Horizontal distance surge water travels, km

Fig. 3.4. Surge resistance phenomenon for flooded area estimation.

75

To identi$ aii the state variables and structure them are difficult tasks. Wind can cause

changes in water levels which may senously affect human safety, damage of dams, losses of property,

houses, and roads. h Bangladesh, especially in the monsoon period, both water surge and wind are

in the sarne direction; fiom sea to the land. It should be mentioned here that if the wind speed is in

the direction of the water surge then it increases the FAA but if it is against the water surge then FAA

decreases because it helps to reduce the height and speed of water.

Ifwe assume that wind speed (WS) is in the same direction as the surge then the surge height

may be written by incorporating surge height equation developed by Welander (1 961) and Murty

et al. (1986) as:

where r, is the wind stress on the water;

F = fetch (distance over which the wind acts on the water to the point in question);

g = acceleration due to gravity;

p = density of water;

h = the depth of the sea from where the surge starts; and

K = a constant of order 1.

Welander (1961) took K= 1.5 for case of the North Sea surge of 1953.

The wind stress can be measured with the following formula (Welander, 1961; Danard and

Murty, 1994):

s, = kp,(WS)*

where p , is the density of the air and

k is the drag coefficient.

Findy, the structural equation (3.4) may be expressed with help of equation (3.5) as:

In equation (3.6), it was assumed that wind speed is different for each rectangle but the density of

air is constant everywhere. Thus from equation (3.6) it is clear that the surge produced by a given

meteorological force at a certain state may differ significantly from the surge resulting fiom identical

forcing at a different stage under the assumption that there is no wind. This means that surge and

wind can not be treated independently without causing substantial errors in the predicted total height

of the surge or flooded area. For this reason, in order to use the sea mode1 to predict storm surges,

the changing distribution of atmosphenc pressure or surface wind bas to be defined clearly in

advance over the region of interest and the period to be covered by any forecast. However, if the

wind dies d o m quickly or changes direction, then the gravitational force will lower the water level.

Murty et al. (1986) noted that it is important to predict the development and distribution of

winds with cyclones which generate the surges and then to relate coastal water levels to the

meteorological variables for forecasting flooding. Flather (198 1) used a drag coefficient to estimate

the resultant wind speed for different surface winds

From equation (3.6), using a drag coefficient (k) corn equation 2.1, we obtain

77

1 " FAA = -c KF ( (0-867)Hi 16-Xgn C 1000i=i (hsin0,) (l+n 43

If we assume that h and H o are equal then equation (3.7) becomes

From equation (3.8), we can see that total flooded distance is directly proprtional to the maximum

surge height (0.

If we want to measure the FAA in term of wind speed then we may use equation (3.6). As-

Salek and Yasuda (1 995) noted that present knowledge is insuficient to establish a surge mode1 in

extreme wind conditions. Storm surge studies should incorporate the effects of water nse due to

wind velocity and surge penetrability into the land.

3.8.2. Dam

Dams are constmcted to provide benefits such as flood control and saline water control.

Depending upon the height and width of the dam, the surge can greatly exceed al1 known previous

surge heights. The warning time available may be much shorter than the time for other naturai

hazards. Dams may be destroyed partially or wholly by the overflow of unexpected surge water or

landslides due to waves and seepage.

The American Society of Civil Engineers (1 996) noted that strong winds blowing towards a

dam can increase the water levei. For this reason, structures that might normally be safe from surge

attack may be vuinerable during storm surges.

To estimate the value of the FAA, there rnay be three possibilities:

(i) when surge height, C > height of the dam;

(ü) when C = height of the dam and

(iii) when C < height of the dam.

Then the flooded affected area for al1 the above cases may be expressed with the help of equation

(3.8) as:

(a) When C is greater than the height of the dam

@)When C is equal to the height of the dam

( c ) When C is less than the height of the dam, FAA=O .

Xn the above equations both A an B are constants and lie between O and 1 and A S. A and

B will depen79d on how long the wrge continues and the ciifference between the surge height and

79

the height of the dam. If this difference is higher then A will be higher. Similarly, if the surge

continues for a long tirne then A and B will be higher. But in any circumstances, A and B cannot

exceed unity; that is the value of the FAA in equation (a) and (b) c m not exceed FAA in equation

(3 -8).

3.8.3. The effect of a Lrest on wrter surge

The effect of vegetation on storm surge was first studied by Reid and Whitaker (1976). They

investigated the effects of a canopy on the wind driven flow of water assurning the drag coefficient

of water over the top of vegetation, the vertical sides of the vegetation and the water surface are

equal.

Danard and Murty (1994) studied the effects of partially or wholly flooded vegetation and

noticed that a vegetation canopy can reduce storm surges significantly. Hence possible reduction of

storm surges by vegetational canopies is of great importance. As-Salek and Yasuda (1 995) noted, the

importance of research needs on storm surge incorporating the effects of bonom fiction coefficient.

The magnitude of the drag force will depend on the density of water (p), the speed of

wrge water, the mid diameter (d , ) of the tree, the total height (h , ) of the tree or perturbation

height, and the kinetic velocity. Let N be the number of trees per unit area in the forest. The total

vertical area obstructing water flow N d , h , and the drag force @) will be (Halliday et al. 1993)

as follows:

D = C N ~ ~ , ~ , C I ~

where C is the drag coefficient for the vertical surface of the trees.

For simplicity, let us assume ail the trees are rigid and perpendicular to the surge water flow.

The velocity should be zero or nearly zero imrnediately behind the tree diameter. The dynarnic

pressure force per unit horizontal area opposing the surge water (Danard and Murty, 1994) is

Equating (3.80) and (3.9) we obtain 1 C=- 2

This is of course is the upper lirnit but in general C will be smaller than this value. So we may denote

C as C , . Danard and Murty (1994) estimated C= 0.125 for air flowing over mountain ridges.

if there is forest on the coastal belt through which the flooded water used to pass then the

flooded water wiii be resisted by the drag force created by the trees. The trees wili produce fictionai

forces which will ultimately lower the surge in inland and ultimately will decrease the total flooded

distancdarea. If we have large patches of forest which can produce larger values of drag force; the

surge height will decrease and distancelarea flooded will be less.

Again, on the basis of Danard and Murty (1994) we may estimate the stress created due to

trees ( r , ), assurning a constant wind speed WS, as:

where C , is the drag coefficient due to trees.

Using value of s , in equation (5) we obtain

(Assuming a constant wind speed throughout the whole area).

The total flooded area becomes

1 " P p a ' d Wi) ( ~ ~ 9 2 FAA = -c 1000 i = 1 ([(k+~d,h,~,@hsinû~)

From equation (3.1 1) it is clear that FAA is inversely proportional to C , , N, d , and h , .

Since we can increase the number of trees N (per unit area), d m and h, , we can resist more water

flow. Which means the FAA decreases with increases in the forest. Equation (3.1 1) holds when the

total height of the tree is higher than the surge height. If surge height is higher then the tree cmot

resist al1 the water.

Ewe put the value of k and H o = h then equation (3.1 1) becomes

1 " FAA = -c PCn=) 1000i=i [ [ ( g ~ ) ( ( ~ ~ $ ) ) ( I -0.164 ' +Nd,htCt)]hsinO,

km2) 1

Equation (3.12) will produce an estimate of the flooded area in terms of both wind speed and

urge height .

From equations (3.8) and (3.12) we can estimate the difference of Booded area in terms of the surge

height and wind speed. But equations (3.6) and (3.1 1) will give difference of flooded area in terms

of wind speed done.

3.8.4. Dynamic mode1

Measured data on storm surge height and flooded area at the Coast is scarce in Bangladesh.

To estimate these parameten we require data on stonn surges, tides and wind speed, sea level of the

axa, and vegetation cover.

When there is no forest, the FAA may be expressed by the equation (3.6); but this estimation

is the maximum. If the surge continues for a short period of time, the flood affected area wiii be les.

83

When there is a forest then the storm surge will be resisted and the FAA may be expressed

by equations (3.1 1) or (3.12). But these equations are static and will give the minimum value of

FAA. If the surge continues for some time then the flooded area will be pa ter . If we want to m&e

equations (3.11) and (3.12) dynamic then we have to incorporate tirne in the model.

From the equation of continuity we can express the differential equation for the velocity of

surge water (u) dong x-component (Pond and Pickard, 1983) as:

where x is the distance traveled by the surge water. But as the water enters inland, its velocity u

decreases with time due to fiction created by the forest vegetation and the higher sea level of that

area, which means

0 ( O ; which means acceleration is negative. P t )

But since this velocity u does not depend on x,

If we assume t hat - - - -al (sorne constant) (4

du Then becomes

Here a , is the negative acceleration (retardation) due to forest vegetation. This acceleration must

be directly related to the drag coefficient C ,. For simplicity let us assume C , = a , . Therefore at any point of time surge water will enter inside the forest ar the rate

Therefore considering constant width W of the forest, the total flooded area at any point of time may

be expressed with the help of equation (3.1 1) as:

1 FAA = fl-c (WC&) (Wa2 + (U -- 1 Cr I) t ] (3.13) 1000,, 1 ([(k+Nd,,,h,C&phsinO,) 2

Equation (3.13) will give the value of FAA at any particular time starting from beginning of time

when the surge water first hits the forest.

3.9. Numerical exrmple

The detednistic structural mode1 for estimating the area flooded has been descnbed in

equations (3.4), (3.6), (3.7) and (3.8). Equations (3.11) and (3.12) will give us an edimate of the

flood affected area afler coastal florestation throughout the entire coastal belt of Bangladesh.

85

The strategy described above is complex because it requires the greatest number of

intemediate variables in order to determine the total flooded distancefarea. By having the greatest

number of intermediate variables the example strategy will explain us most of the expression

mentioned above. This will produce greater level of understanding ofboth the mode1 and the system

it represents.

To describe the above mentioned models we need some simplimng assumptions. For

example, density of air (pJ may be assumed to be 1-25 kg per cubic meter (= 0.00 1-5 gm/ cm ' . K = 1.5, F = 2 û 0 km

WS = 100 km/hour

C,=0.5; < = S m ; h=lOOOm

f = 0.1; C , = 0.06; k= 0.0025;

dm=0.2rn; h , = S m ; W i = 1 km;

Width of plantation = 1 km;

if we have plantation spacing of 2 rn X 2 rn

then N = 500 X 500 stems/km= 0.25 stem/m2;

n=lOO; 0 = l 0

A = 0.5 and B = 0.2.

Using equation (3.6), without a forest the total flooded area is 2 155 km 2. With a dam the

FAA is 1077 km * when the surge height is greater than the height of the dam and FAA is 43 1 km2

when the surge height is equal to height of the dam. If we have a coastal forest with a width of 1 km

then the total flooded area is only 640 km (using equation # 3.1 1). The ratio between these two

(equation #3.6 and # 3.1 1) is approximately 0.297. If we assume the flooded area has a uniform loss

everywhere, then through coastai aorestation we cm Save 15 15 km ' of loss. This result is for a 1

km width only. If we have a wider coastal forest we can protect against even more surge water and

property loss will be less.

4.0. Determinis tic Sensitivity Anal ysis

Sensitivity analysis rnay be defined as the analysis of the responsiveness of conclusions to

changes in model parameters and assumptions. In other words the analysis based on the deterministic

phase centres on observing how changes in the independent variables affect the FAA. It is very

effective because with the heip of sensitivity analysis we rnay think about how to refine the

formulation of the problem.

First we may fix ali other state variables or independent variables in the problem at their

nominal values and ailow one of our independent variables to traverse its assigned range and observe

how the FAA changes. If we observe that a particular variable has a major effect then we rnay

conclude that we are correct in including it in the formulation. But if a variable has little or no effect,

we rnay remove that variable from the fomulat ion.

Deterministic sensitivity andysis was performed through the spread sheet model. This was

done for al1 the dependent variables in the model. Sensitivity analysis for the flooded area in terms

of wind speed was performed using equation 3.6 (Figure 4.1). Sensitivity analysis of wind speed was

performed for forest cover using equation 3.1 1 (Figure 4.2). In a similar way, sensitivity analysis for

surge height was performed by using equation 3.6 (Figure 4.3). Sensitivity analysis for mean sea level

is represented by Figure 4.4. Sensitivity anaiysis of the forest in terms of stems per unit area was

perfomed by using equation 3.11 (Figure 4.5) and sensitivity anaiysis of the width of the forest is

represented by Figure 4.6. Sensitivity of wind speed without a dam or forest is represented by Figure

4.7. Here the square of the wind speed was taken because the flooded area is proportional to the

square of the wind speed. Since aii these variables have signifiant contributions to the fiooded area

we may conclude that we are right to include them in the modei. Among these variables, maximum

surge height and wind speed are more important because these two variables are more crucial.

Wind speed (kmlhour) Fig. 4.1. Sensitivity analysis of wind speed

(using equation 3.6)

5.0. Probabilistic Phase

The uncertainty concerning the arriva1 of water surges was incorporated in the decision

analysis process. For this purpose, a water surge was classified as being either low or high on the

basis of its maximum height in meters. If the maximum surge height was greater than 3 meters it was

considered to be a high surge. Othenvise it was considered to be a low surge. The probabilities of

high and low surges were estimated on the basis of the information given in Table 1.4. Natural

calamities like depressions, cyclones, severe cyclones, and humcanes were explicitly incorporated in

the decision analysis process. Their probabilities were also estimated from the information given in

Table 1.4, on the basis of wind speed. It was noted earlier that oniy six of the last 32 years were

disaster free. We assume that in the cases where wind speeds were not given (Table 1.4), the wind

speeds were low and those were depressions. We rnay assume that in these cases, the wind speed

varied fiom 30 to 60 km per hour. It is clear that from 1960 to 1991, Bangladesh was hit 34 times

(Table 1.4). Among these calamities, 13 were classified as depressions, 2 were stoms, 4 were severe

storms, and 15 were hurricanes. On the basis of this information, we c m estimate the probabilities

of depressions, stoms, severe storms, and humcanes. In some years, more than one calamity

occurred, however, on the basis of the above information, we can estimate the arriva1 rate of

calamities and we cm also estimate the intensity of a calamity on the basis of the maximum wind

speed or the height of the water surge.

TABLE 5.1. Probabilities of different calamities

Calamity Probabiiity (Pi)

Depression

Storm

Severe storm

Humcane

The arrivai of depressions, storm surses, severe storms, and humcanes were modelled on the basis

of the information provided in Tables 1.4 and 1.5 and are given in Table 5.1. Though in Table 1.5,

depressions and deep depressions are differentiated, due to their Iow intensities, 1 considered them

to be one class of calamity called a depression.

5.1. Influence diagram

An innuence diagram is a graphical representation of a decision problem. Influence diagrarns

were first introduced to describe decision problems in the mid 1970s (Smith et al. 1993). Shachter

(1988) described an infiuence diagram as a network consisting of a directed graph with no directed

cycles, and detailed data stored within the nodes of the graph. Each node in the graph represents a

variable which may be a constant or an uncertain quantity on the basis of which a decision is to be

made. Decision makers who may be unskilled in the art of complex probabilistic modelling may find

that influence diagrams provide them with a language to describe their conception of a decision

problem (Howard, 1988). The influence diagram representation is compact and unWte the decision

tree representation, clearly indicates the dependence and independence assumptions in the model.

Smith et al. (1993) noted that the d u e n c e diagram has proven valuable for cornputation and the

computational methods have achieved substantial efficiencies over decision trees methods. They also

noted few drawbacks of a influence diagram and among these drawbacks poor representation of

highly asymmetric problems are important. It shows uncertain events, the value of outcornes, and

decisions to be made as different shapes.

The quantities in the circles or ovals of an influence diagrams are considered to be uncertain.

Arrows entering circles mean that the quantities in the circles are probabilistically dependent on

whatever is at the other end of the mow. Rectangles are decisions under the control of the decision

maker. Arrows entenng such decision nodes show the information that is available at the time of the

decision. Squares represent decisions and are caiied decision nodes. Circles represent chances and are

cailed chance nodes. Rectangles with rounded corner represent values and are cailed value nodes.

Double lines represent deterministic values. The influence diagram for coastal florestation in

Bangladesh is represented by Figure 5.1. Forecasts conceniing calamities are represented by chance

nodes and the intensities of calamities are also represented by chance nodes. Outcomes of different

calamities are represented as deterministic which are equal to payoffs.

Decision makers c m quickly identie relationships among the factors in the problem and can

readiiy determine if any pertinent factors have been ornitted. That is why the influence diagram,

though simple, is extremely usefùl. Shachter (1988) noted that the influence diagram has become a

useful tool for analysis in communicating with decision makers and experts. It can be explained both

to a politician and analyst who is going to perform the ultimate calculations. Another advantage of

an innuence diagram is that after drawing influence diagram ive rnay leave it with a client like the

chef conservator of forests or even with the minister of environment and forests for fiirther

consideration and possible change upon reflection. In this way they may be given an opportunity

to think of new factors those were not included or even new interactions that must be taken into

account. The analyst is able to fiarne the problem from the perspective of the decision maker and to

maintain and reverse the mode1 from that perspective. The diagram is thus an extremely helpfùl tool

for presenting information concerning a decision (Howard, 1988).

Both the decision tree and influence diagrams are analytical tools to convince ministers and

others, but decision trees show sequence and more detail (Griggs et al. 1997). The influence diagram

ornits some details but focuses the viewer on the major aspects of the problem. Still, both of these

tools are helpfiil for decision making for flood control in Bangladesh because the decision is based

on cost and benefits analysis of different measures.

5.2. Estimation of the cost of each type of calamity

The expeaed damage due to calamities each year and the damage incurred over many years

may be estimated from the foilowing formula:

(wected Damage) = A 2 P, x COS^ of 0 ~ y p e J calmi0 Year I = I

Where A is the expected number of calamities per year and P is the probability that a calamity is a

type j calamity.

Cost cf o Type j columity = Area flooded X value lest($) per unit area (5.2)

In 1991, the total area fiooded w s estimated to have been 28.6 thousand square kilometres

(Table 1.4) and total darnage was estimated to have been 2.5 billon dollars. The average damage per

square kilometre is therefore ap proximately 0.087 million dollars.

Chowdhury (1994) and others noted maximum wind speed, storm surge height, flood affected

area, crop damage and number of deaths for several calamities fkom the years 1960 to 199 1 (Table

1.4). Keeping al1 the information in mind, a hypothetical forest was considered and different types of

cdamities with different wind speed, surge height, mean sea level were assumed. Using these values

we can estimate the flooded area for any type of calamity. For example, flood affected area (FAA)

for surge height = 6 meters; width of area = 500 meters and MSL= 3 meters may be estimated when

there is forest as:

(a) FAA= 6357.19 1 Sq. Km for a depression with a wind speed of 60 km per hour;

@) FAA = 995 1.85 1 S q . h for a storm with a wind speed of 80 km per hour;

(c )FAA= 14437.32 Sq. km for a severe storm with a wind speed of 1 10 km per hour and

(d) FAA= 27137.40 Sq.km for a humcane with a wind speed of 150 km per hour.

The cost of any type of calamity may be estimated by using equation 5.2 according to the following:

(1) Cost of a depression is 553 .O76 million dollar;

(2) Cost of a storm is 865.8 1 1 million dollar;

(3) Cost of a severe storm is 1256.047 million dollar and

(4) Cost of a humcane is 2360.954 million dollar.

5.3. Determination of the cost of protective measures

The total present cost of any strategy is determined by a series of steps in different years. In

the first step, the major costs are identified and determined. The initial cost for a dam may include

the cost of labour, planning, supervision and materials. The cost of alternative coastai aflorestation

may be divided into the cost of seedlings or nursery, transportation, labour, and management. In the

second step we determined the present cost of maintenance or management. In the final step the

present cost was determined by summing al1 the costs. The discounted value of fiinire costs or present

net worth of future cost (PNWC) was calculated with the formula:

Where t is the year that cost occurs; and

C , is the cost hcurred in year t and i is the rate of interest.

5.3.1. Cost of a dam

The c o s of a dam is a fùnction of labour, planning, supervision, materiai, and

miscellaneous costs. The length of the dam is also an important factor. The total length of dam was

assumed to be 100 km dong the coastai belt. The Canadian Dam Association (1999) estimated

the cost of dam in South Afiica as 1 US $ per cubic rnetre of water stored for agricultural dams.

It is assumed that the land required for the dam is free. The cost of planning may be included in

the supervision. Planning may also be perforrned by govemment oficials or intemationau donor

agencies. The present net worth of future costs for a dam was calculated with equation (5.3)

(Table 5.2).

TABLE 5.2. Model input for detemination of the present net wonh of future costs for a 100 km

dm

Items Cost (1,000,000 $)

Labour

Planning & supe~s ion

Materiais

Miscellaneous

Total = 67.0 M $

5.3.2. The cost of coastal afl'orestation

The present cost of coastal afforestation is a fùnction ofthe cost of seedlings which may

include the cost of seed and nursery raising, cleaning the area, transportation and planting,

maintenance and management cost. Maintenance may include gap fiiling as well. We assumed a

total of 100 square kilometres of coastal florestation is to be raised dong the coastal belt. The

Forest Resource Management Project (1992) estimated a cost per hectare of US% 500.00

(approximately). The present net worth of future costs for coastal afforestation was calculated

with equation (5.3) and presented in Table 5.3.

TABLE 5.3. Mode1 input for the determination of present net worth of future costs for 100 sq.

Km coastal aorestation

Items Cost (1,000,000 $)

Seedlingd nursery 6.5

Transportation 8.4

Planting 12.5

Gap fillinghaint enance 8.6

Management 2.5

Total = 38.5 (M S)

5.4. Benefits

In general, a dam or coastal florestation will not destroyed fully by one or two surges.

It may continue for several surges and several years. In such a case we may assume that our retum

is for infinite horizon of time or infinite stream.

The retum for an infinite stream, in each period will be identical and this constant value cm

be interpreted as the equivalent average retum (BR ) of the stream. tf'the present net worth (PNW)

(cost of dam) is the value of a specified value of a, then BR is

B R =(La) PNW (5.4)

Here a is the single period discount factor and may be expressed as:

The higher the interest rate i, the smaller the value of a. For this reason, the interest rate relevant

for a decision making is an important factor. We may assume here that the approximate value of

Equivalent retum for a dam

Using equation (5.4) we can estimate average equivalent retum (B 3 per year as:

B = S 1.9515 million.

106

Equivalent return for coastal afforestation

Using equation (5.4) we can estimate average equivalent retum (B 3 per year as:

BR = $ 1.1505 million.

Equivdent nturn for both coastal afTorestation and dam

Using equation (5.4) we can estirnate averaçe equivalent retum for both the flood control

strategies Le., coastal afforestation and dam per year as:

BR = !§ 3 .O728 million.

5.5. Total cost of different calamities with protective measures

The total costs of different calamities with different protective measures were estimated

by adding the total cost due to damage of that calamity and the equivalent retum of that protective

measure. This can be done in the following way:

Net loss of alternative k

= Annual cost of altemative k + expected darnage with alternative k.

In this way the cost for ail four types of calamities with coastal fiorestation, dam, both coastal

&orestation and dam and without any protective measures were estimated and presented in Table

5.4.

TABLE 5.4. Total cost of different calamities with protective measures

Protective measure Depression Storm Severe storm Humcane

Dam 64 1.3 58 954.12 1344.356 2449.263

Coastal forest 554.226 866.96 1 1257,197 2362.104

Coastid forest & Dam 0.0 104.409 494.645 1299.552

Nothing 78 1.69 1 1094.426 1484.662 2589.589

Using these values ofdifferent calamities and their probabiiities values given in Table S. 1,

we can estimate the average damage for one calarnity per year using equation (5.1) according to

the following:

DamPge) = 1452.92 million dollar for coastal afforestation. Year

Similady, we can estimate the expected damage per year for al1 the alternatives and presented by

a decision tree.

5.6. Decision tree

A decision tree may help to identify a rational decision about the establishment of coastal

forests in Bangladesh. Two fiuidamental operations, expectation and maximisation are used to

108

determine the best decision fiom the tree. At each chance node, the expected profit is computed

by summing the probabilities of each outcome multiplied by the value of that outcome plus the

expected profit of the node following that outcome. At each decision node, the expected profit of

each alternative is the expected profit of the following node less the cost of the alternative. The

optimum decision is found by optimization of these values over the set of possible alternatives, i.e.

by selecting the alternative of highest expected profit or minimum loss. The decision to establish

coastai forest or/and dam in Bangladesh may be show in the fom of a decision tree (Figure 5.2).

The average value of the property darnaged by a humcane in USA is approximately 1.5

billion dollars (Howard et al. 1983). The total loss due to 1988 flood in Bangladesh was estimated

by UNDP (1989) to be more than 2 billion US dollars. The economic loss due to a 1991 cyclone

in Bangladesh was estimated as 2 billion US dollars (Haque, 1997); but C D A (1996) noted that

the 1991 cyclone caused $2.7 billion of damage. Considenng al1 these estimates, we rnay assume

that the present value of maximum average loss is 2.5 billion US dollars and this value may be

considered as the maximum expected loss due to humcane and high surge when there is no forest.

If there is no calamity then the expected value of the loss is zero. From these two extreme values

we may assume the intemediate values of the expected loss due to depressions, storms, severe

storms and humcanes.

The expected value of each alternative may be computed by multiplying the property

damage for each ofthe possible outcome by the probability that the outcome wiil be achieved and

surming over the possible consequences as is given in Figure 5.2. Expected values are given in

billions of dollars. On the basis of low payoffs or loss the optimal path is easily found out. This

figure shows that when there is coastal forest and dam payoffs will be the least. But this strategy

is expensive.

5.7. Cornparison of the cost and return from decision tree

We have seen that ifwe do not take any flood control strategy then the damage due to a

humcane which produces a high surge is !§ 2.5 billion. We can reduce the property loss with less

amount of cost or resource input. But if we implement a coastal fiorestation strategy the cost is

lower than the cost of a dam. However, on the basis of damage per year which includes the cost

of darnage and the equivalent retum, a decision tree was drawn (Figure 5.2). The loss of property

is the least for the decision coastal fiorestation and dam. Moreover coastal afforestation cm play

vital role in environmental degradation and we can produce timber or fùelwood and eam revenues.

In addition, coastd florestation can provide employment at the sustainable levei but a dam can

provide employment dunng construction. Maintenance of a dam requires less labour than coastal

florestation. Finally, we rnay conclude that the coastal fiorestation program is more beneficial

for the country. It was observed that for both the protective measures (Le., a dam and a foresr) the

average cost per year is the lowest (770.722 million dollars). This means that the country should

proceed with both coastai florestation and dam, but if there is budget constra.int the country

should proceed with coastal Sorestation only.

6.0. Discussion

6.1. Deterministic mode1

Disasters in Bangladesh not only kill people but sometimes destroy the backbone of the

national economy. For example, the total cost of reconstruction and rehabilitation of the physical and

social infi.astructure in the 1988 flood has been estimated to have been 4.4% of the total GDP of the

country and the total loss of the catastrophic cyclone of April 29, 1991 has been estirnated at US%

2.4 billion (Karim, 1995). Not only cyclones and floods, river bank erosion, earthquakes and other

disasters cause heavy loss of life and property, but dso damage infrastructure and disturb

development projects and economic growth. However, the Government of Bangladesh has

developed an elaborate and comprehensive plan to cope with different kinds of disasters in order to

reduce the loss of human lives, properties, infrastructure and other losses. The economic condition

of the afliected people is becoming weaker every year. But most of the problem may be solved if we

can establish coastal afforestation throughout the whole coastal belt of Bangladesh. Coastal

&orestation can check the surge water, improve environmental condition, and at the same time,

improve the economic condition of the people by employment.

The socio-economic consequences of floods and other disasten have a tremendous impact

on the socioeconornic condition of the country. In a predominantly agricultural economy, the death

of large numben of livestock and poultry will also make many rural people become more poor.

Damage to standing crops and other properties lead to the loss of other assets through indebtness.

Moreover, cyclones, floods, river erosion, and other disasters cause substantid destruction of the

physical structure and land by which many of the poor people become destitute overnight. Only a

small proportion of the aected people is able to overcome this loss. A few people also migrate to

urban areas to search for food, shelter and employment. Besides these, the lack of communic~tion

and proper logistic supports, afEected people do not get drinking water, food, shelter, medicine and

other relief materials in tirne.

From equations (3.8) and (3.12) we cm estimate the flood affected area when there is no

forestldam and when there is a forest. These two equations estimate the flood affected area (FAA)

on the basis of the maximum surge height and the wind speed. But equations (3.6) and (3.11) will

predid the difference in flooded area in terms of wind speed alone.

It was mentioned earlier that there are several benefits of forests which could be achieved by

coastal florestation. The first and most obvious, is a reduction of flooded area and ultimately the

savings of property and lives. Other possible benefits are associated with environmental degradation.

This program cm provide employment in the remote areas where people are poor and other

ernployment is limited. Finally, coastal afforestation can provide fuelwood and timber for local and

national consumption and it can produce revenues. These benefits are not included in the structural

mociel.

It was assumed that ail species resist the water current equally but that depends on the

density of the forest (the number of stems per hectare) and the size of the trees. The FAA also

depends on the width of the forest; if the width of the forest is higher, then the FAA will be lower and

vice versa.

For simplicity, it was assumed that wind speeds (WS) in different areas are not significantly

different. This means that we rnay use same value for WS throughout the entire affected area. This

assumption rnay not be true everywhere. The maximum height of the water surge is directly

proportionai to the FAA which means it increases the flood Sected area. We assumed that the

density of water is constant everywhere and that rnay not be always true.

It should be noted here that al1 the area rnay not be unifom in terms of surge resistance. For

example, some areas rnay have larger trees. This type of variation is not considered in the rnodel.

Also, some areas rnay have more canais and rivers that allow surge water to enter easily. This type

of variation is not also considered in the model. Even the eEect of tree branches on water surge was

not included in the model. However, the above mentioned equations wiil predict average flooded area

for the coastal belt of the country.

Coiiecting data on a stonn surge requires a fair degree of prior organization because most of

the local seMces are disturbed or inactive d u ~ g cyclones and floods. Complete records are required

for several consecutive days. In this connection, valid up-to-date topographic maps should be

available. When al1 the available data fiorn different sources are available, it is important that it should

be reserved in such a way that when any researcher wants, it should be available. In this way, we can

expect to prepare good models for better estimation of flooded area. However, it was shown that a

forest canopy, where ail the tree heights are higher than the surge height, can significantly dissipate

storm surges and reduce total flooded area.

6.2. Probibilistic analysis

Probabilities for difEerent chance nodes were based on the years 1960 through 1991 because

proper information before that time was not available. Also, the probability for each caiamity was

estimated on a yearly basis which may not be useful for other short term plans. The cost of planting

was considered to be small in cornparison to the damage due to natural calamities. People can use

coastal anorestation for recreational purpose and coastal &orestation can increase fish and shrimp

cultivation. But al these benefits were not considered during t his decision anal ysis. Sirnilarly, there

may have been a few more calamities at the regional level which were not recordeci and not included

in the estimating of probabilities. We rnay obtain revenues from coastal florestation but this type of

benefit was ignored because they may be negligible in cornpanson with property and other losses.

If there are legitimate differences of opinions among experts, the analyst should examine

the extent to which this range of opinions has important consequences for the results. Ifthe range of

opinions has no signifiant consequences for the outcorne, we should not spend money to collect or

analyse more information. For the present analysis it was assumed that when the water rise was 3m

or less it was considered as low surge, otherwise it was a high surge that is a rough approximation

and we should collect proper information on dl kinds of damage and the basis on which we can

identify the actual intensity of a calamity. The expecteâ value of perfect information (EVPI) was not

estimated because data is not available for the purpose. We should collect proper information tiom

different sources and estimate the actual value of the EVPI. The decision analysis was performed on

the basis of property loss which can be expressed as monetary value but post flood effects (like

epidemics) were not considered. Even the loss of human life was not considered in the analysis

though it is the most important.

However, this research will heip decision - makers take rational decisions whether the

country should spend money for coastai aorestation program or not. Also, it will be helpfùl for

forest managers to convince donor agencies of the importance and benefits of coastal aorestation.

If we can establish a coastal belt successtùlly then we can produce fuel wood and other timber for

industrial purposes. More local people will find jobs in coastai florestation and the country will be

saved from naturai calamities like cyclones and fioods. Local people will also get more area for cattle

grazing and recreational purposes.

6.3. Future research

(a) Field data should be collected and exact costs for different calamities with protective

measures should be estimated.

(b) Data of different calamities should be collected and the expected value of perfect

information should be estimated.

(C ) A mathematical mode1 should be developed for the coastal florestation of Bangladesh

incorporating uncertainty, labour employment and social benefits for the local people.

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