Storm surges and coastal erosion in Bangladesh - State of ... - WMO

Storm surges and coastal erosion in Bangladesh -
State of the system, climate change impacts and 'low
regret' adaptation measures
By:
Mohammad Mahtab Hossain
Master Thesis
Master of Water Resources and Environmental Management
at
Leibniz Universität Hannover
Franzius-Institute of Hydraulic, Waterways and Coastal Engineering, Faculty of
Civil Engineering and Geodetic Science
Advisor: Dipl.-Ing. Knut Kraemer
Examiners:
Prof. Dr.-Ing. habil. T. Schlurmann
Dr.-Ing. N. Goseberg
Submission date:
13.09.2012

Prof. Dr. Torsten Schlurmann
Managing Director & Chair
Franzius-Institute for Hydraulic, Waterways and Coastal Engineering
Leibniz Universität Hannover
Nienburger Str. 4,
30167 Hannover
GERMANY
Master thesis description for Mr. Mahtab Hussein
Storm surges and coastal erosion in Bangladesh - State of the system,
climate change impacts and 'low regret' adaptation measures
The effects of global environmental change, including coastal flooding stemming
from storm surges as well as reduced rainfall in drylands and water
scarcity, have detrimental effects on countries and megacities in the costal
regions worldwide. Among these, Bangladesh with its capital Dhaka is today
widely recognised to be one of the regions most vulnerable to climate change
and its triggered associated impacts.
Natural hazards that come from increased rainfall, rising sea levels, and
tropical cyclones are expected to increase as climate changes, each seriously
affecting agriculture, water & food security, human health and shelter. It
is believed that in the coming decades the rising sea level alone in parallel
with more severe and more frequent storm surges and stronger coastal erosion
will create more than 20 million people to migrate within Bangladesh
itself (Black et al., 2011). Moreover, Bangladesh’s natural water resources
are to a large part contaminated with arsenic contaminants because of the
high arsenic contents in the soil. Up to 77 million people are exposed to toxic
arsenic from drinking water (Reich, 2011).
Given that background, the current MSc thesis should collect indicators as
well as assess and critically discuss the present and likely future state of the
coastal system and establish strategies as well as solutions in regard to
storm surges and coastal erosion effects in Bangladesh.
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Hannover,
15 March 2012
Nienburger Str. 4
30167 Hannover, Germany
Ph. +49 (0)511 762-19021
Fax +49 (0)511 762-4002
schlurmann@fi.uni-hannover.de
www.fi.uni-hannover.de

Master thesis description for Mr. Mahtab Hussein
Storm surges and coastal erosion in Bangladesh - State of the system climate
change impacts and 'low regret' adaptation measures
In order to conduct a holistic overview of the state of the system, possible
climate change impacts and possible 'low regret' adaptation measures with
special emphasis on storm surges and coastal erosion in Bangladesh, the
thesis should encompass and take into consideration the following aspects:
Description of the country Bangladesh in regard to the theme of the thesis,
i.e. geography and climate, rough overview of economy and demographic
structure.
In-depth review of governmental structure including an institutional mapping
(mandate, experiences, capacities, etc.) of the most relevant institutions
and governmental bodies, research institutes and universities in
Bangladesh related to Disaster Risk Reduction (DRR) and the Hyogo
Framework for Action (HFA) in straight accordance to Djalante et al.
(2012) carried out recently for Indonesia. Where are the missing links and
what needs to be organized or tackled additionally?
Disaster history and experiences: When and what has been affected in
the country and statistics of losses? What have been the lessons learned
from these experiences? How and what experiences did federal government
and local governments take action on creating “goog governance”
structures in relation to climate change effects? What are the synergies in
regard of the preparation and strategies to global change?
Summary of (joint) research projects and international development initiatives
in Bangladesh or in particular in Dhaka, what has been in focus and
to which degree the results have been implemented into preparedness or
adaptation programmes concerning DRR measures.
Anticipated (direct) climate change impacts (Karim and Mimura, 2008;
Madsen and Jakobsen, 2004), effects of SLR related to exposure and vulnerability
of the people and assets. What elements are at risk?
Anticipated (indirect) climate change related impacts concerning storm
surges, and in consequences local sea states and wave action regarding
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Master thesis description for Mr. Mahtab Hussein
Storm surges and coastal erosion in Bangladesh - State of the system climate
change impacts and 'low regret' adaptation measures
coastal erosion (now and then). Set-up and calibration of coastal see
wave atlas by means of phase-averaging model (SWAN) in order to integrate
current sea states and future projections of wave action to derive a
trustworthy data base for the coastline and estuaries of Bangladesh.
Tentative adaptation measures in relation to recent SREX report and
possible solutions encompassing so-called "low-regret" adaptation measures
(technically, politically and socially) recently defined within the IPCC-
Special Report Managing the Risks of Extreme Events and Disasters to
Advance Climate Change Adaptation (SREX)
From the work flow listed above, main scientific emphasis might be put on
the part considering the coastal see wave atlas and is expected to account
for about one third of the given working time of six months of the thesis. For
completing this particular task apart from the other more literature review
work, computational power as well as versions of SWAN, MATLAB and ArcGis
will be made available for the student under supervision of the depicted
examiners and advisor.
Three printed versions of the thesis have to be delivered along with the digital
thesis and a well-arranged work data archive. The data archive has to
contain all raw data, all used computational and MATLAB routines, simulation
input files of all presented simulation runs together with the MATLAB
post-processing routines and plots.
The arranging of the routines for later work and the documentation of the
work flow is part of the work and will thus be taken into account for the grading.
After the thesis is delivered, it will be presented in a talk with following
discussion of 30 minutes to the examiners and advisor.
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Master thesis description for Mr. Mahtab Hussein
Storm surges and coastal erosion in Bangladesh - State of the system climate
change impacts and 'low regret' adaptation measures
Literature
Black et al., Migration as adaptation, NATURE, VOL 478, 2011, p. 449
Djalante, R., Thomalla, F., Sinapoy, M.S., Carnegie, M., Building resilience to
natural hazards in Indonesia: progress and challenges in implementing the
Hyogo Framework for Action, Natural Hazards, 2012, pp. 1-25.
Karim, M.F., Mimura, N., Impacts of climate change and sea-level rise on
cyclonic storm surge floods in Bangladesh, Global Environmental Change,
2008, Vol. 18 (3), pp. 490-500.
Madsen, H., Jakobsen, F., Cyclone induced storm surge and flood forecasting
in the northern Bay of Bengal, Coastal Engineering, 2004, Vol. 51 (4), pp.
277-296.
Murty, T.S., Flather, R.A., Henry, R.F., The storm surge problem in the Bay
of Bengal, Progress in Oceanography, 1986, Vol. 16 (4), pp. 195-233.
Reich, S., Conflicting studies fuel arsenic debate, NATURE, VOL 478, 2011,
p. 437
IPCC-SREX, Managing the Risks of Extreme Events and Disasters to Advance
Climate Change Adaptation, Summary for policy makers, 2011
http://ipcc-wg2.gov/SREX/
Date of issue: 15 th March 2012 Closing date: 14 th September 2012
1. Examiner
Prof. Dr.-Ing. habil. T. Schlurmann
Advisor
Dipl.-Ing. Knut Kraemer
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2. Examiner
Dr.-Ing. N. Goseberg

Master thesis description for Mr. Mahtab Hussein
Storm surges and coastal erosion in Bangladesh - State of the system climate
change impacts and 'low regret' adaptation measures
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ACKNOWLEDGEMENT
This thesis work has been done according to the requirement of the Master of Science degree
of Water Resources and Environmental Management (WATENV), Faculty of Civil
Engineering at Leibniz University Hannover, Germany. First of all, I give thanks to almighty
Allah (God) who has given me the ability to complete the tasks. After that, I would like to
express my sincere gratitude to my advisor, Dipl.-Ing. Knut Kraemer and examiners Dr.-Ing.
N. Goseberg and Prof. Dr.-Ing. habil. T. Schlurmann for their guidance, valuable suggestions,
and insightful comments on my work. Special thanks to Dipl.-Ing. Nils Kerpen, who provided
me an electronic key to work at the Franzius CIP-Pool at any time.
I would like to express my appreciation to Bangladesh Meteorological Department (BMD)
and Bangladesh Water Development Board (BWDB) for their help with data provision which
was very vital for the completion of the required tasks.
I am grateful to World Meteorological Organization (WMO) for providing financial support
and for giving me the opportunity to participate in the WATENV course.
I wish to extend my sincere gratitude to my dearest friend Lojek Oliver, who generously made
an effort to translate my abstract to German and Ellen Bonna who helped to check my
grammatical errors.
Last but not least, I would like to express my thanks to my family, wife, children, relatives,
friends and my parents for their everlasting support and patience.
Thank you all, I am sincerely grateful.
Mohammad Mahtab Hossain
Leibniz University Hannover, Germany
September 2012
i

ABSTRACT
Bangladesh is vulnerable to several natural disasters. Tropical cyclones from the Bay of
Bengal accompanied by storm surges are one of the major disasters in Bangladesh. For many
years, coastal erosion has been becoming a regular natural phenomenon in Bangladesh. This
study is mainly focused on the storm surges and coastal erosion hazard in Bangladesh with
their adaptation measures considering the impact of current and future states of climate. Data
has been collected from different internet sources and Bangladesh Meteorological Department
(BMD) to model the coastal erosion by SWAN (Simulating of Waves Nearshore). SWAN is a
widely used third generation wave model; however this study is the first for Bangladesh. The
study concluded that, although Bangladesh has seriously addressed the Disaster Risk
Reduction (DRR) and climate change issue there is still some commitment and capacities
required to achieve DRR due to lack of resources and research work. Modeling by SWAN
shows that the rate of erosion along the coast of Bangladesh increases with the increasing
wind speed. The study also shows that the rate of erosion in 2030 and 2050 will be increased
due to sea level rise but it will not be increased significantly. However, new areas in the coast
will be inundated and affected by erosion.
Key Words: Tropical Cyclones, Disaster, Storm Surges, Bay of Bengal, Adaptation, SWAN,
Coastal Erosion.
ii

ZUSAMMENFASSUNG
Bangladesch wird durch diverse Umweltkatastrophen bedroht. Tropische Zyklone aus der
Bucht von Bengalen begleitet durch Sturmfluten stellen mit eine der schlimmsten
Katastrophen dar. Küstenerosion ist seit vielen Jahren ein Phänomen mit dem Küstenstaaten
wie Bangladesch zu kämpfen haben. Diese Arbeit behandelt maßgeblich die Sturmfluten
sowie die daraus resultierende Erosionsgefahr für die Küste in Bangladesch unter
Einbeziehung vorhandener Schutzmaßnahmen unter derzeit vorherrschenden, sowie
möglichen zukünftigen Klimaeinflüssen. Die Studie stützt sich maßgeblich auf eine
Literaturrecherche. Daten wurden zum einen von verschiedenen Internetquellen sowie dem
Bangladesh Meteorological Department (BMD) zusammengetragen, um Küstenerosion mit
der Software SWAN (Simulating Waves Near Shore) zu modellieren. SWAN, ein
Wellenmodell der dritten Generation, ist ein weit verbreitetes Programm das bereits zur
Simulation von Seegangsverhältnissen in vielen komplexen Feld Studien auf der gesamten
Welt eingesetzt wurde. Die Simulation für die Küste von Bangladesch die in dieser Studie
durchgeführt wurde, stellt jedoch eine Primäre dar. Die Untersuchungen ergaben, dass
Bangladesch sowohl Maßnahmen zur Katastrophenminderung umgesetzt hat als auch den
Klimawandel ernst nimmt. Dennoch bestehen nach wie vor ein gewisses Restpotential zur
Katastrophenminderung, welches jedoch aufgrund mangelnder Ressourcen nicht voll
ausgeschöpft werden kann. Die Simulation mit SWAN zeigte einen Zusammenhang zwischen
steigender Küstenerosion und zunehmenden Windgeschwindigkeiten auf. Des Weiteren
erlaubt die Simulation eine Aussage über die zukünftige Entwicklung der Erosion zu tätigen.
Demnach werden die Erosionsraten im Jahr 2030 sowie 2050 entlang der Küste aufgrund
steigender Meeresspiegel nicht signifikant ansteigen. Allerdings deuten die Ergebnisse darauf
hin, dass neue Gebiete im Inland überflutet werden und von Erosion betroffen sein könnten.
iii

TABLE OF CONTENTS
ACKNOWLEDGMENTS…………………………………………………………......... i
ABSTRACT....................................................................................................................... ii
ZUSAMMENFASSUNG.................................................................................................. iii
TABLE OF CONTENTS………………………………………………………………… iv
LIST OF TABLES ………………………………………………………………………. ix
LIST OF FIGURES……………………………………………………………………... x
LIST OF APPENDICES………………………………………………………………... xii
ABBREVIATIONS & ACRONYMS…………………………………………………... xiii
CHAPTER 1: INTRODUCTION…………………………………………… 1
1.1 Bangladesh ……………………….………………………………………….. 1
1.1.1 General Background……………………………………………………. 1
1.1.2 Geography and Climate of Bangladesh………………………………….. 1
1.1.3 Demographic, Economic, Social and Cultural Characteristics of
Bangladesh………………………………………………………………………. 3
1.1.4 Governance Style of Bangladesh………………………………………... 4
1.2 Natural Hazards in Bangladesh………..………………………………….. 5
1.2.1 Cyclones and Storm Surges……………………………………………... 5
1.2.2 Floods………………………………………………………………….... 6
1.2.3 River Bank Erosion………………………………………………………. 6
1.2.4 Coastal Erosion ………………………………………………………….. 6
1.2.5 Earthquakes ………………………………………………………............ 6
1.2.6 Droughts ………………………….…………………………………….... 7
1.2.7 Tornados …………………………………………………………………. 7
1.2.8 Arsenic Contamination………………………………………………….. 7
1.2.9 Salinity Intrusion ………………………………………………………... 7
1.3 Climate Change and Sea Level Rise in Bangladesh................................ 8
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1.4 Objectives of the study work…………....................................................... 9
1.5 Outline of the Report…………………..……............................................... 9
CHAPTER 2: PHYSICAL PHENOMENA AND DISASTER RISK
REDUCTION ………………………….…………………….……………………. 11
2.1 Introduction ………………………………………………………………….. 11
2.2 Cyclone and Storm Surges ………………………………………………... 11
2.2.1 Introducing cyclones and storm surges....................................................... 11
2.2.2 Classification of Cyclones …………………..………………………….. 12
2.3 Waves in Coastal Areas ……………............................................................. 13
2.3.1 Introduction …………………………………………………………….. 13
2.3.2 Wind Generation in Coastal Areas……………………………………... 14
2.3.3 White-Capping………………………………………………………….. 14
2.3.4 Bottom Friction…………………………………………………………... 15
2.3.5 Depth-Induced (Surf) Breaking………………………………………….. 17
2.4 Terminology on Disaster Risk Reduction................................................... 18
2.5 Hyogo Framework for Action (HFA) 2005-2015………………………. 20
CHAPTER 3: CLIMATE CHANGE IMPACTS, DISASTER
HISTORY (STORM SURGES) AND EXPERIENCES IN
BANGLADESH …………………………………………………………………. 22
3.1 Introduction ………………………………………………………………….. 22
3.2 Experiences from the Past Disasters (Storm Surges)…………….…... 22
3.3 Climate Change Impacts in Bangladesh ……………….……………….. 26
3.3.1 Climate Change Observed in Bangladesh ………..…………………….. 26
3.3.2 Frequency and Intensity of Cyclone in Future in Bangladesh …………. 28
3.3.3 Intensity of Impacts on different sectors due to Climate Change …..…... 28
3.3.4 Actions in relation to climate change effects in Bangladesh ………….... 29
3.4 Bangladesh’s Exposure and Vulnerability to Natural Hazards ……... 31
v

3.4.1 Exposure in Bangladesh and Elements are at Risk …………………….. 31
3.5.2 Vulnerability to Hazard Risks ………………………………………….. 32
CHAPTER 4: IMPLEMENTATION OF DISASTER RISK
REDUCTION PROGRAMMES - HYOGO FRAMEWORK FOR
ACTION IN BANGLADESH ........................................................................ 34
4.1 Disaster Management System in Bangladesh ……………………….. 34
4.2 Institutional Mapping for Disaster Risk Reduction in Bangladesh ... 35
4.2.1 Institutional Linkages ……………………………………………….….. 35
4.2.2 Missing Links ……………………………………………………….….. 38
4.3 National progress on the implementation of the Hyogo Framework for
Action............................................................................................................................. 38
4.3.1 Implementation of HFA Priorities for Action in Bangladesh ………….. 38
4.3.2 Discussions and Recommendations on the Implementation of HFA in
Bangladesh ………………………………………………………………….….. 43
4.4 Development Projects related to DRR in Bangladesh ………….…….. 46
4.4.1 Key Donor Engagements ……………………………………………….. 46
4.4.2 Situation of the Current Research ……………………………………….. 46
4.4.3 Development Projects Related to DRR in Bangladesh ………………….. 47
CHAPTER 5: MODEL SET-UP, CALIBRATION AND ANALYSIS
OF EROSION ALONG BANGLADESH’S COAST ………………. 50
5.1 Introduction ………………………………………………………………….. 50
5.2 Available Data ………………………………………………………………. 50
5.2.1 Bathymetry ……………………….…………………………………….. 50
5.2.2 Tide and Current ………………………………………………….…….. 51
5.2.3 Water Level …………………………………………………………….. 51
5.2.4 Wind ……………………………………………………………………. 51
5.2.5 Waves ……………………………………..……………………………. 52
5.3 SWAN Model ………….………………………………………………….... 52
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5.3.1 Co-ordinate System in SWAN ……………………………………….... 53
5.3.2 Grid System in SWAN ……………………………………………….... 53
5.3.3 Boundary Conditions in SWAN ……………………………………….. 55
5.4 Overall Model Set-up …….……………………………………………….. 55
5.5 Sensitivity Analysis and Model Calibration …………..……………….. 56
5.5.1 Sensitivity Analysis…………………………………………………..…. 56
5.5.2 Model Calibration …………………….………………………….…….. 58
5.6 Model Application to calculate the Erosion along Bangladesh’s
Coast ………………………………………………………………………………….. 59
5.6.1 Erosion at the Current Sea States ……………………………………….. 62
5.6.1.1 Discussion on the Erosion Scenarios for the Current Sea States……....... 62
5.6.1.2 Causes of Erosion in Coastal Waters……………………………………. 65
5.6.1.3 Analysis of erosions at different cross sections along the coast of
Bangladesh …………………………………………………………..…………. 66
5.6.2 Comparison of Erosion Considering Climate Change …………………. 68
5.6.2.1 Comparison of Erosion at Current Sea State regarding Climate Change… 68
5.6.2.2 Change in rate of Erosion due to Climate Change ………………………. 70
5.6.2.3 Effects of SLR on Erosion ………………………………………………. 71
CHAPTER 6: ADAPTATION MEASURES FOR EXTREME
EVENTS MANAGEMENT …………………………………………………. 72
6.1 Adaptation and Management for Changing Climate …………………. 72
6.2 Low Regret Adaptation in Bangladesh ………………………………….. 73
6.3 Costs of Adaptation Measures to Tropical Cyclones and Storm
Surges …………………………………………………………………………..…….. 76
CHAPTER 7: CONCLUSIONS AND
RECOMMENDATIONS…………………………………………….……….. 78
7.1 Conclusions ……………………………………………………………….… 78
7.2 Recommendations ……………………………………………………….… 79
vii

REFERENCES ……………………………………………..……………..…….. 81
APPENDICES ……..……………………………………………………….……. 86
LIST OF FILES IN CD…………………………………………………….……. 105
DECLARATION…..………………………………………………………….…. 106
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LIST OF TABLES
Table 1.1: The population statistics for Bangladesh according to final census report (BBS,
2011)………………………………………………………………………..……..…………….. 3
Table 1.2: Economic status of Bangladesh (BTI, 2012)……………………………..………….. 4
Table 1.3: The inundation scenarios in Bangladesh due to sea level rise (Ali, 1996)…………... 9
Table 2.1: Classification of cyclones in South Asian Sub-Continent (RRCAP, 2001) ………... 12
Table 2.2: Classification of cyclonic disturbances presently in use by Bangladesh (WMO,
2010)............................................................................................................................................ 13
Table 2.3: The relative importance of the various processes in sea waters (Holthuijsen, 2007)
………………………………………………………………………..…………………….…. 13
Table 3.1: Trend of SLR along the coast of Bangladesh (Singh, 2001) …………………….… 27
Table 3.2: Impact of climate change on various sectors (MoEF, 2005) ………………………. 28
Table 3.3: Typical scenarios in coastal zone (BBS, 2011) ..…………………………..………. 33
Table 4.1: Some development projects that have been taken recently for disaster Management and
climate change adaptation (AKP, 2010)…………………………………..……..…………….. 47
Table 4.2: Donor engagements and plans for medium to long-term (Year- 2022) disaster risk
mitigation in Bangladesh (ISDR, 2009a) ………………………………………….……….. 48
Table 5.1: Season wise maximum daily wind speeds along Bangladesh’s coast during 2001-2011
………………………………………………………………………………………………..... 51
Table 5.2: Recommended discretizations for spectral grid in SWAN…………………..….….. 55
Table 5.3: The default settings in SWAN that have been used in this project…………………. 56
Table 5.4: Two boundary conditions for sensitivity analyses…………………………………... 57
Table 5.5: The formulas and other required constant values that were used in SWAN………... 60
Table 6.1: Adaptation cost to cyclone and storm surges by 2050 in Bangladesh (WB, 2010c)…. 76
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LIST OF FIGURES
Figure 1.1: Three coastal regions in Bangladesh…………………………..……..…………….. 2
Figure 1.2: Map of Bangladesh with some areas prone to a specific natural hazard..………….. 8
Figure 2.1: Storm surge (wunderground.com)…………………………………………………... 12
Figure 2.2: Transferring of wind energy into JONSWAP spectrum in deep and shallow water,
( 3.5 m, and = 20 m/s) (Holthuijsen, 2007)……………………………... 14
Figure 2.3: White-capping source term, in JONSWAP spectrum, in deep and shallow water,
( =3.5 m and (Holthuijsen, 2007).......................................................................... 15
Figure 2.4: The bottom friction dissipation influenced on JONSWAP spectrum, ( =3.5 m
and (Holthuijsen, 2007) ……………………..………………….…………….…. 17
Figure 2.5: The influence of surf-breaking on JONSWAP spectrum, ( =3.5 m and
(Holthuijsen, 2007)………………………………………………………………………….… 18
Figure 3.1: Monthly distribution of recorded storm surges (Cyclones) in Bangladesh during the period
of 1584 to 2009 ……………………………………………………………………….………. 23
Figure 3.2: Season wise distribution of cyclones that hit Bangladesh in year: 1584 - 2009…... 23
Figure 3.3: Frequency of storm surges in Bangladesh in 10 year periods: 1890-2009 …….….. 24
Figure 3.4: Different type of disturbances that hit Bangladesh in the period: 1890-2009……... 25
Figure 3.5: Number of death due to super cyclonic storms that hit Bangladesh recently……... 25
Figure 3.6: Financial damages due to super cyclonic storms that hit Bangladesh recently …... 26
Figure 3.7: Bangladesh’s exposure and vulnerability to natural hazards (a) frequency of occurrence;
(b) number of people died; (c) number of people affected; (d) vulnerability to cyclone hazard (Data
from ISDR, 2009a; MoWCA, 2010) ………………………………………………………..... 31
Figure 3.8: Area exposed to the Bay of Bengal in Bangladesh (Appendix 3.2) ……………... 32
Figure 3.9: Comparions of population (a) density for whole country with coastal area only and (b)
male to female ratio for whole country with coastal area only (BBS, 2011) …………….…... 33
Figure 4.1: Disaster management system in Bangladesh……………….…..……………..….. 35
Figure 4.2: Institutional (key governmental) map to reduce the risk of disaster in
Bangladesh………………………………………………………….………………………..... 37
Figure 5.1: A graphical representation of bathymetry that is used in SWAN model…………... 50
Figure 5.2: Wind stations that were considered to calculate the rate of erosion and different channels
along the coast of Bangladesh………………………………………………………………...... 52
Figure 5.3: Area, points, and buoys that were used in SWAN……………………………...….. 57
x

Figure 5.4: Comparison of SWAN outputs with forecasted data (a) at point-1; (b) at point-2 for Hs, (c)
at point-1; (d) at point-2 for Tp, (e) at point-1; (f) at point-2 for wave direction……………..... 59
Figure 5.5: Cross sections that were considered for comparison and analysis of erosion ……... 61
Figure 5.6: Bottom level (a) along cross section A-A and B-B; (b) along cross section C-C…... 61
Figure 5.7: Comparison of the rate of erosion using different bottom friction model along cross section
(a) A-A; (b) B-B …………………………………………...…………………………………..... 62
Figure 5.8: Erosion scenarios along the coast of Bangladesh at high tides for (a) 5 m/s western wind;
(b) 5 m/s southern wind; (c) 10 m/s western wind; (d) 10 m/s southern wind; (e) 15 m/s southern wind;
(f) 20 m/s southern wind; (g) 30 m/s southern wind …………………………………….……... 64
Figure 5.9: Wave orbital velocity with and without bottom friction along A-A (a) for 5 m/s wind; (b)
for 30 m/s wind…………………………………………………………………….……….…... 65
Figure 5.10: Erosion at current state due to different wind, at high tides along (a) A-A; (b) B-B; (c) C-
C; at Low tides along (d) A-A; (e) B-B; (f) C-C………………………………………………... 67
Figure 5.11: Comparison of the rate of erosion at current state and, in 2030 along (a) A-A; (b) B-B; (c)
C-C; in 2050 along (d) A-A; (e) B-B; (f) C-C………………………………………….……… 69
Figure 5.12: Change in erosion due to 30 m/s wind considering SLR along (a) A-A; (b) B-B; (c) C-
C………………………………………………………………………………………………... 70
Figure 5.13: Simplified model of landward coastal retreat under SLR (modified from UNEP,
2010)…………………………………………………………………………………….….….. 71
Figure 6.1: The approaches to adapt and manage for climate change (IPCC, 2012)…….….….. 72
Figure 6.2: Cyclone and Flood information flows in Bangladesh (modified from UNEP,
2010)……………………………………………………………………………………...….….. 74
Figure 6.3: Closure dam under construction at Jamuna river, Bangladesh (UNEP,
2010)…………………………………………………………………………………….………. 75
Figure 6.4: Plantation of vetiver along polder (Islam, 2003)……………………………..….….. 76
xi

LIST OF APPENDICES
Appendix 3.1: Natural disasters (Cyclones/Storm Surges) in Bangladesh (Khan, 2012; SDC, 2010;
RRCAP, 2001; Karim and Mimura, 2008; Murty et al., 1986; Ali, 1999; Choudhury et al., 1997;
Shamsuddoha, 2008; BMD; Banglapedia; DMB)…………………………..……..…………….. 86
Appendix 3.2: Districts and Upazilas of Bangladesh’s coastal zone (MoEF, 2007)..……….….. 90
Appendix 3.3: Detailed damages by selected cyclones that hit Bangladesh recently (MoWCA, 2010;
DMB)…………………………………………………………………………………………... 91
Appendix 3.4A: Population census in Bangladesh (BBS, 2011) ………………………….…... 92
Appendix 3.4B: Population census in Bangladesh (BBS, 2011)................................................... 93
Appendix 3.5: Population and household scenarios in the coastal area of Bangladesh (BBS, 2011)
………………………………………………………………………..…………………….…. 94
Appendix 3.6: Population and households vulnerable to the natural hazards (BBS, 2011)….… 95
Appendix 5.1: Tide levels that have been considered in SWAN model…………….…………. 96
Appendix 5.2: Number of days of wind blowing from a direction along the coast of Bangladesh for the
period 2001-2011 (BMD) ..……………………………………………………………..………. 98
Appendix 5.3: The results of sensitivity analysis for different condition by using two boundary
conditions (Table 5.4)………………………………..……………………..……..…………….. 99
Appendix 5.4: The data that is considered for the model calibration and comparison of the results at
point- 1 & 2 …………………………………………………………………………….……….. 100
Appendix 5.5: SWAN calibration results and forecasting data at point- 1& 2 for the period 08.06.12
06:00 to 15.06.12 18:00………………………………………………………………………..... 101
Appendix 5.6: The data which is used for model application at current satate…………..….….. 101
Appendix 5.7: Significant wave height and wave period for different wind speeds and
durations…………..………………………………………………………………………...….. 102
Appendix 5.8: A typical command file for SWAN computation………………………..….….. 103
Appendix 5.9: Critical bed shear of soil along the coast of Bangladesh (Barua et al., 1994)….. 104
Appendix 5.10: Data has been used for the future projections along the coast of Bangladesh…. 104
xii

ADB Asian Development Bank
AFD Armed Forces Division
ABBREVIATIONS & ACRONYMS
BADC Bangladesh Agricultural Development Corporation
BAU Bangladesh Agricultural University
BBS Bangladesh Bureau of Statistics
BCAS Bangladesh Centre for Advanced Studies
BCCRF Bangladesh Climate Change Resilience Fund
BCCSAP Bangladesh Climate Change Strategy and Action Plan
BCS Bangladesh Civil Service
BIDS Bangladesh Institute of Development Studies
BIWTA Bangladesh Inland Water Transport Authority
BIWTC Bangladesh Inland Water Transport Corporation
BMD Bangladesh Meteorological Department
BRAC Bangladesh Rural Advancement Committee
BRRI Bangladesh Rice Research Institute
BTRC Bangladesh Telecommunication Regulatory Commission
BTV Bangladesh Television
BUET Bangladesh University of Engineering and Technology
BWDB Bangladesh Water Development Board
CARE Co-operative for Assistance and Relief Everywhere
CC Climate Change
CBA Community Based Adaptation
CCA Climate Change Adaptation
CCC Climate Change Cell
CCDMC City Corporation Disaster Management Committee
CCF Climate Change Fund
CDM Comprehensive Disaster Management
CDMP Comprehensive Disaster Management Programme
CEGIS Center for Environmental and Geographic Information Services
CIDA Canadian International Development Agency
COP Conference of Parties of UNFCCC
CPP Cyclone Preparedness Programme
CPPIB Cyclone Preparedness Program Implementation Board
CRA Community Risk Assessment
CSDDWS Committee for Speedy Dissemination of Disaster Related Warning/ Signals
DAE Department of Agriculture Extension
DANIDA Danish International Development Agency
DC Deputy Commissioner
xiii

DFID Department for International Development
DG Director General
DGoF Directorate General of Food
DM Disaster Management
DMA Disaster Management Act
DMB Disaster Management Bureau
DMC Disaster Management Committee
DMIC Disaster Management Information Centre
DMRD Disaster Management and Relief Division
DMTATF Disaster Management Training and Public Awareness Building Task Force
DNA Damage and Need Assessment
DoE Department of Environment
DoH Directorate of Health
DoRR Directorate of Relief and Rehabilitation
DPHE Department of Public Health Engineering
DRR Disaster Risk Reduction/Directorate of Relief and Rehabilitation
DU Dhaka University
EC European Commission
ECNEC Executive Committee of the National Economic Council
EGPP Employment Generation Programme for the Poorest
EIA Environment Impact Assessment
EOC Emergency Operation Centre
EPAC Earthquake Preparedness and Awareness Committee
ERD Economic Relations Division
EU European Union
FFW Food for Work
FFWC Flood Forecasting and Warning Centre
FPOCG Focal Point Operation Coordination Group of Disaster Management
FSCD Fire Service and Civil Defense
GFDRR Global Facility for Disaster Reduction Recovery
GoB Government of Bangladesh
GPWM Guidelines for Participatory Water Management
GSB Geological Survey of Bangladesh
HFA Hyogo Framework for Action
ICDDR,B International Centre for Diarrhoeal Disease Research, Bangladesh
ICTs Information and Communication Technologies
IDB Islamic Development Bank
IMDMCC Inter-Ministerial Disaster Management Co-ordination Committee
xiv

INGO International Non-Government Organization
IPCC Inter-governmental Panel on Climate Change
IUCN International Union for Conservation of Nature
IWM Institute of Water Modeling
IWRM Integrated Water Resource Management
JBIC Japan Bank for International Cooperation
JICA Japan International Cooperation Agency
LACC Livelihood Adaptation to Climate Change
LDC Least Developed Country
LGD Local Government Division
LGED Local Government Engineering Department
LGI Local Government Institution
MDG Millennium Development Goal
MoA Ministry of Agriculture
MoD Ministry of Defence
MoEd Ministry of Education
MoEF Ministry of Environment and Forests
MoFA Ministry of Foreign Affairs
MoFDM Ministry of Food and Disaster Management
MoF&P Ministry of Finance and Planning
MoHA Ministry of Home Affairs
MoHFW Ministry of Health and Family Welfare
MoH&PW Ministry of Housing and Public Works
MoI Ministry of Information
MoLG&RD Ministry of Local Government, Rural Development and Cooperatives
MoPME Ministry of Primary and Mass Education
MoSh Ministry of Shipping
MoS&T Ministry of Science and Information and Communication Technology
MoWR Ministry of Water Resources
MSL Mean Sea Level
NAPA National Adaptation Programme of Action
NBR National Board of Revenue
NDMAC National Disaster Management Advisory Committee
NDMC National Disaster Management Council
NEC National Economic Council
NFI Non-food items
NGO Non-Government Organization
NLUP National Land-Use Policy
NPDM National Plan for Disaster Management
xv

NPDRR National Platform for Disaster Risk Reduction
OPEC Organization of the Petroleum Exporting Countries
PDMC Pourashava Disaster Management Committee
PRSP Poverty Reduction Strategy Paper
PWD Public Works Department
PMO Prime Minister’s Office
PSTU Patuakhali Science and Technology University
RB Bangladesh Betar
RF Rainfall Station
RRI River Research Institute
RVCC Reducing Vulnerability to Climate Change project
SAARC South Asian Association for Regional Cooperation
SIDA Swedish International Development Authority
SLR Sea Level Rise
SOD Standing Orders on Disasters
SPARRSO Space Research and Remote Sensing Organization
SST Sea Surface Temperature
TBM Tidal Basin Management
TR Test Relief
UDMC Union Disaster Management Committee
UzDMC Upazila Disaster Management Committee
UK United Kingdom
UNDP United Nations Development Programme
UNFCCC United Nations Framework Convention on Climate Change
UN/ISDR United Nations International Strategy for Disaster Reduction
UP Union Parishad
UzP Upazila Parishad
VGF Vulnerable Group Feeding
WB The World Bank
WL Water Level Gauge
WMO World Meteorological Organization
Glossary
Adivasi indigenous people
Char low-lying river island
xvi

Parishad elected council for a local government (e.g. Union, Upazila, etc.)
Pourashava urban local government meant for ‘Municipality’
Union lowest tier of local government in Bangladesh comprised of a number of Wards
Upazila lowest administrative unit comprising of a number of Unions
xvii

1.1 Bangladesh
CHAPTER 1: INTRODUCTION
1.1.1 General Background
Bangladesh is recognized worldwide as one of the most vulnerable countries to natural
disasters and to the impacts of global warming and climate change (SDC, 2010; DOE, 2007).
Almost every year, Bangladesh experiences one or more disasters- such as tropical cyclones,
storm surges, coastal erosion, floods, and droughts- resulting in massive loss of life and
property and hampering the development activities (Ali, 1999). “In 2004, the United Nations
Development Programme (UNDP) ranked Bangladesh the number one nation at risk for
tropical cyclones and number six for floods” (Luxbacher and Uddin, 2011). Rapid global
warming has caused fundamental changes to Bangladesh’s climate and as a result millions are
suffering (DOE, 2007). It is therefore necessary to understand its vulnerability in terms of
population and sectors at risk and its potential for adaptation to climate change (DOE, 2006).
Climate change is not only altering the disaster risk through increased weather related risks,
sea-level rise (SLR) and temperature and rainfall variability, but also through increases in
societal vulnerabilities from stresses on water availability, agriculture and ecosystems
(MoFDM, 2009). In this context, one of the key issues in Bangladesh is to reduce the disaster
risk. For this purpose, more comprehensive and systematic efforts at the international,
national and local levels are important to take into account (Djalante et al., 2012). It was
proved that disaster should be managed holistically from prevention, mitigation through to
rehabilitation and reconstruction. Although global reduction of greenhouse gas emission (i.e.
mitigation) is a must to overcome the challenge in the long-run, adaptation is a short-term but
essential measure to tackle the climate change impact locally. Therefore, disaster risk
reduction and climate change mitigation and adaptation provide a common area of concern:
reducing the vulnerability of communities and achieving sustainable livelihood development
(MoFDM, 2009).
1.1.2 Geography and Climate of Bangladesh
Bangladesh is a low-lying deltaic country in South Asia, which is formed by the Ganges, the
Brahmaputra and the Meghna rivers (DMB, 2010). Bangladesh is a developing country of low
deltaic plain located between 20°34ʹ to 26°38ʹ North latitude and 88°01ʹ to 92°42ʹ East
longitude. The country occupies an area of 147,570 sq. km. (BBS, 2011). Its maximum
extension is about 440 km in E-W direction whereas 760 km in N-S direction (Hoque, 2006).
Bangladesh is located at the interface of two quite different settings. To the north of the
country lie the Himalayas foot plain and the Khasi-Jainta hills, and to the south are the Bay of
Bengal and the Indian Ocean. Those different settings control, modify, and regulate the
climate of the country (Ali, 1996). Geologically it is a part of the Bengal Basin, which is built
up by sediments washed down from the highlands on three sides of it. It is bordered on the
west, north and east by India, on the southeast by Myanmar (Karim and Mimura, 2006). The
total length of the land border of Bangladesh is about 4,246 km, of which 93.9% is shared
with India and the rest with Myanmar (Hoque, 2006). There are 57 cross-boundary rivers, of
1

2
Chapter 1
which 54 are shared with India whereas other three rivers with Myanmar and Bangladesh is
the common lower riparian zone of all these trans-boundary rivers (Chowdhury, 2010). There
are more than 310 rivers and tributaries which have made this country a land of rivers (DMB,
2010).
The coastal area represents an area of 47,201 km 2 , which is about 32% of Bangladesh’s total
geographical area. In terms of administrative consideration, 19 districts out of 64 are
considered as coastal districts (BBS, 2011; MoEF, 2007). About 10% of the country is 1 m
above the mean sea level, and one-third is under tidal excursions (Ali, 1999). The country has
a coastline of about 710 km along the Bay of Bengal (MoWR, 2005). The country covers
three discrete coastal regions - western, central, and eastern coastal zones which are shown in
Figure 1.1. The western part is known as the Ganges tidal plain. Average land elevation is
below 1.5 m MSL. The southwestern part of the region is covered by the world’s largest
mangrove forest (6017 km 2 ), popularly known as Sundarbans. The mangrove forests act as
barriers to the furiousness of tropical cyclones and storm surges. Erosion is comparatively
small in this region but it suffers from salinity and tidal flooding (Karim and Mimura, 2006).
The Sundarbans was declared by the UNESCO as a natural world heritage site in 1997 (Islam,
2008). The central region is the most active one, and this area suffers from continuous erosion
and accretion (Karim and Mimura, 2006). The very active Meghna River estuary situates in
this region. The combined flow of 3 powerful rivers – namely, the Ganges, the Brahmaputra,
and the Meghna, are commonly called as the GBM river system and ranked as one of the
largest river systems in the world - discharges with the name as Lower Meghna into the
northeastern corner of the Bay of Bengal. This estuarial region suffers from the most
disastrous effects of tropical cyclones and storm surges in the world (Ali, 1999; Karim and
Mimura, 2006). The GBM river systems carry 85% of the total dry season flow passing
through the coastal zone of Bangladesh (Islam, 2008). The eastern region has higher elevation
and this zone is relatively stable part among other coastal regions in the country. The world
longest natural beach (120 km) is situated in this region (Karim and Mimura, 2006).
89°0'0"E
89°0'0"E
90°0'0"E
90°0'0"E
91°0'0"E
91°0'0"E
92°0'0"E
23°0'0"N 23°0'0"N
Char Changa
22°0'0"N 22°0'0"N
Hiron Point
Western Region
Central Region
Eastern Region
Cox's Bazar
21°0'0"N
Bay of Bengal
21°0'0"N
92°0'0"E
Figure 1.1: Three coastal regions in Bangladesh

3
Chapter 1
Bangladesh is an agro-based country (Habib, 2011). It has subtropical monsoon climates
which have wide seasonal variations in rainfall, moderately warm temperatures, and high
humidity (Hoque, 2006).
The climate of Bangladesh can be classified under the following four seasons:
The first is Winter or Northeast Monsoon (December to February): maximum temperature is
31.1°C whereas occasional minimum is 5°C with mean temperature is 18-21°C and average
rainfall is about 1.5% of the total annual rainfall. The second is Summer or Pre-Monsoon
(March to May): mean temperature is 23-30°C which occasionally rises 40.6°C and average
rainfall is 17% of the total annual rainfall. The third is Southwest Monsoon or Monsoon (June
to September): monsoon is both hot as well as humid and average rainfall is about 72.5% of
the total annual rainfall. The fourth is Autumn or Post-Monsoon (October and November):
short-living season, average rainfall receives is about 9% of the total annual rainfall (Habib,
2011; DOE, 2006). The mean annual rainfall is about 2300 mm whereas the average annual
rainfall varies from 1,200 mm in the extreme west to over 5,000 mm in the northeast (DOE,
2006).
1.1.3 Demographic, economic, social and cultural characteristics of Bangladesh
Bangladesh is a unitary, independent and sovereign republic called the People’s Republic of
Bangladesh. Bangladesh became an independent country on March 26, 1971 by the liberation
war against Pakistan, which ended on 16 December 1971 with the victory of Bangladesh
forces and the surrender of the occupying Pakistani Army. Bangladesh was under Muslim rule
for five and a half centuries and entered into British rule in 1757. At the time of the British
rule, it was a part of the British Indian province of Bengal and Assam. In August 1947, it
achieved independence from British rule along with the rest of India and formed a part of
Pakistan known as East Pakistan until it became independent on 16 December 1971 (Dhaka,
2006).
Table 1.1: The population statistics for Bangladesh according to final census report (BBS, 2011)
Area (147570 km 2 ) Male Female Population
Total Population
Density/km 2
Total Average Annual
Households Growth Rate %
144,043697 72,109796 71,933901 976 32,173630 1.37
Yearly Growth
Rate %
1974 (-) 1981 (2.32) 1991 (2.01) 2001 (1.58) 2011 (1.37)
Table 1.1 shows that the total number of households is more than 32 million and population
density is 976, which makes Bangladesh one of the most densely populated countries of the
world. The number of male and female is about equal. Population annual growth rate shows a
decreasing trend from 2.32 in 1981 to 1.37 in 2011, which is about half.
About 98% of Bangladeshi are ethnic Bengali and speak Bangla. Urdu-speaking, non-Bengali
Muslims of Indian origin, and various tribal groups make up the rest. Mainly in urban areas,
the educated people can speak English. Most of Bangladeshis (around 88.3%) are Muslims,
but Hindus represent a minority. Small numbers of Buddhists, Christians, and animists are

4
Chapter 1
also present in Bangladesh. Bangladesh has a long and rich historical and cultural past, which
combines Dravidian, Indo-Aryan, Mongol/Mughul, Arab, Persian, Turkic, and Western
European cultures (Dhaka, 2006).
Table 1.2: Economic status of Bangladesh (BTI, 2012)
Economic Indicators 2007 2008 2009 2010
GDP $ mn 68415.4 79554.4 89359.8 100357.0
GDP Growth % 6.4 6.2 5.7 6.1
Inflation (CPI) % 9.1 8.9 5.4 8.1
Foreign Direct Investment % of GDP 1.0 1.3 0.8 1.0
Export Growth % 13.0 7.0 0.0 0.9
Import Growth % 16.0 -2.1 -2.6 0.7
Current Account Balance $ mn 856.9 926.2 3556.1 2502.4
Life Expectancy (68 Years) HDI (0.5)
Poverty (Population living on
less than 2 $ a day) 81.3%
Aid/Capita
$7.6
HDI Rank
146 of 187
Gini Index
31.0
Gender
Inequality
(0.55)
UN Education
Index (0.415)
-
GDP/Capita
$1659
- -
Table 1.2 shows that the Gross Domestic Product (GDP) of Bangladesh is increasing and the
growth rate of GDP is about 6% which is lower than the South Asian GDP growth rate (WB,
2010a). The inflation rate is relatively higher in comparison with the developed countries but
similar to other South Asian countries (WB, 2010a). Export and Import growth rates are
showing a decreasing trend. The Human Development Index (HDI) is a complex statistic,
which is used to rank countries by standard of living. HDI of Bangladesh is 0.5 which
includes the country as one of the low human development countries and ranked 146 out of
187 countries (UNDP, 2011). About 81.3% of populations, whose income is less than 2 USD
per person per day among whom about 34% live with less than 1 USD per person per day
(SDC, 2010). Therefore, it is clear that a large number of populations in Bangladesh are living
below the poverty level which indicates the severity of poverty or vulnerability in
Bangladesh.
1.1.4 Governance Style of Bangladesh
The President in Bangladesh, who is the head of state but holds a largely ceremonial post
because the president has limited administrative power whereas the real power is held by the
Prime Minister, who is the head of the government. The President is elected by the legislature
(Parliament) every five years. The President appoints the legislative, executive and the
judiciary. The President also appoints the Prime Minister who must be a Member of
Parliament (MP) and whom the President thinks commands the confidence of the majority of

5
Chapter 1
other Members of Parliaments. The cabinet is formed of ministers selected by the Prime
Minister but appointed by the President. At least 90% of the ministers must be MPs whereas
the other 10% can be non-MP experts, who are called "technocrats" but the rule is that
technocrats are not otherwise disqualified from being elected MPs. The President can dissolve
Parliament upon the written request of the Prime Minister any time. The Parliament is
unicameral, which is formed by 300 elected MPs by the people of Bangladesh by vote. Extra
45 seats are reserved for women and to be distributed among political parties in proportion to
their numerical strength in the Parliament (Dhaka, 2006).
Bangladesh's judiciary is a civil court system and it is still based on the British model. The
highest court of appeal is the Appellate Bench of the Supreme Court. On the local government
level, the country is separated into divisions, districts (Zila), sub-districts (Upazila), unions,
and villages. Local officials are elected at the union level and they are called Chairman. There
is no election at the village level but members are selected by government. All larger
administrative units are conducted by the members of the civil service (Dhaka, 2006).
1.2 Natural Hazards in Bangladesh
Bangladesh is exposed to a multitude of natural hazards with highly varying occurrence,
season and extent of effects.
1.2.1 Cyclones and Storm Surges
Tropical cyclones accompanied by storm surges from the Bay of Bengal are one of the major
disasters in Bangladesh. The country is one of the worst victims of all kind of cyclonic
casualties in the world (SDC, 2010). Damage to life and property due to cyclonic storms is
enormous. In the coastal regions, the damage is mainly due to induced storm surges,
particularly over the low elevation coastal margins. This is why; the coastal zone of
Bangladesh could be termed a geographical "death trap" due to its extreme vulnerability to
cyclones and storm surges (Shamsuddoha and Chowdhury, 2007). The massive loss of life by
cyclone is due to the high density of population in this area, people living in poverty within
poorly constructed houses, the inadequate number of cyclone shelters, and the extremely lowlying
land of the coastal zone (Ahmed, 1999). A UNDP report (titled ‘Reducing Risk of
Natural Disasters: A Development Challenge’) mentions that among the Asian countries
Bangladesh is most highly prone to cyclonic disaster. The report also states that cyclone
caused the death of 250 thousand people worldwide, of whom 60% were in Bangladesh
during 1980 to 2000 (Shamsuddoha and Chowdhury, 2007). Although cyclones and floods
have occurred in Bangladesh over the centuries, the damage is increasing due to growing
population and infrastructure development in the coastal zone (Ahmed, 1999). Cyclones pose
multiple threats from severe winds, storm surges, and heavy rainfall that cause in both surface
and river flooding. Cyclones associated with tidal waves caused massive loss of lives and
property. Therefore, cyclonic storms have always been a major concern to coastal plains and
offshore islands of Bangladesh (Shamsuddoha and Chowdhury, 2007).

Chapter 1
1.2.2 Floods
Floods are annual phenomena in Bangladesh. Normally the most severe floods occur during
the months of July and August (DMB, 2010). Regular river floods (during monsoon season)
affect 20% of the country which may increase up to 67% in extreme years like the 1998 flood.
The floods of 1988, 1998 and 2004 were simply disastrous (SDC, 2010).
There are four types of flood in Bangladesh (DMB, 2010):
Monsoon floods along major rivers during the monsoon rains (June-September).
Flash floods caused by overflowing of hilly rivers of eastern and northern Bangladesh
(Normally during April-May and September-November).
Rain floods caused by drainage congestion during heavy rains.
Coastal floods caused by storm surges.
1.2.3 River Bank Erosion
River morphology in Bangladesh is highly dynamic. The main rivers are braided, and form
islands (chars) between the braiding channels. Many of these chars are highly unstable, "move
with the flow" and are extremely sensitive to changes in the river morphology (SDC, 2010).
Losses by river erosion happen slowly and gradually. Although losses due to river erosion are
slow and gradual, they are more destructive and far-reaching than other sudden and
devastating calamities. River erosion effects are long-term (DMB, 2010). According to the
Bangladesh Water Development Board about 1,200 km of river banks are actively erodible
(SDC, 2010).
1.2.4 Coastal Erosion
The natural shape of Bangladesh coastal and marine areas are controlled by dynamic
processes such as tides, wave actions, strong winds and sea level variations. Over the last two
centuries, huge changes have taken place due to continuous land erosion and accretion along
the coastline. This process is the most severe in the Meghna estuary (MoEF, 2007). The
people in the coastal area are increasing and they are the worst victims. Studies explain that
major erosion occurs along the wider channels (Meghna estuary). Most of the erosion of the
Bay of Bengal front was due to storm surges and continuous wave actions (Ahmed, 1999).
The area of Sandwip Island, for example, was 1,080 sq km in 1780, but now it has been
reduced to only 238 km 2 and in Hatiya, erosion is taking place at the rate of 400 meter/year
(Ahmed, 1999). Hatiya (Upazila, Noakhali District) has reduced from 1000 km 2 to only 21
km 2 over 350 years whereas Swandip ( Upazila, Chittagong District) has lost 180 km 2 in the
last 100 years. Kutubdia (Upazila, Cox's Bazar District) has reduced from 250 km 2 to only 60
km 2 during the period 1880 to 1980 by the process of strong tidal actions and cyclonic effects.
Bhola (District) Island has been squeezed from 6400 km 2 to 3400 km 2 since 1960. In each
year the GMB river system carries 6 million cusecs of water with 2179 million metric tons of
sediment which causes water logging and flooding in the monsoon period and is responsible
for the accretion process in this area (Shamsuddoha and Chowdhury, 2007).
1.2.5 Earthquakes
Bangladesh and the north-eastern Indian states are one of the seismically active regions of the
6

7
Chapter 1
world, and have experienced numerous large earthquakes during the past 200 years (DMB,
2010). During 1869-1930, five earthquakes with magnitude M≥7 have hit parts of
Bangladesh, out of which two had their epicenters inside Bangladesh. Although no major
event occurred during the last decades, seismicity is still high for Bangladesh. Bangladesh
University of Engineering and Technology (BUET) prepared a new seismic zoning map and
recognized that 43% of the areas of Bangladesh are rated high risk, 41% moderate whereas
16% at low risk (SDC, 2010).
1.2.6 Droughts
Droughts mainly occur in the western parts of Bangladesh (Rajshahi and Rangpur Division)
and in the Chittagong Hill tracts area (SDC, 2010). Bangladesh is at high risk from droughts.
During the period 1949 to 1991, Bangladesh faced droughts 24 times (DMB, 2010). In recent
years, the frequency and intensity of drought has been increasing continuously and affects the
agricultural production, mainly rice (SDC, 2010).
1.2.7 Tornados
Tornados (It is called Kalbaishakhi in Bangladesh) are mainly occurring in two transitional
periods (Pre-monsoon and Post-monsoon). They are suddenly formed and of brief duration
and are extremely localized in nature. Therefore, it is very difficult to locate Tornados or
forecast their occurrence with the available techniques at present. They may cause also a lot
of havocs and destructions (SDC, 2010). Since independence in 1971, Bangladesh has
experienced at least eight major tornados, killed on an average more than 100 people in each
event and caused severe damage in their narrow paths (SDC, 2010).
1.2.8 Arsenic Contamination
Arsenic contamination is growing in Bangladesh and at present, it is considered to be a
dangerous environmental threat as well as a serious health risk (contaminating drinking
water). It is defined as a public health emergency in Bangladesh. Although there are
geological reasons (arsenic complexes present in soils), the excessive extraction of water for
irrigation and domestic water supply have accelerated the problem (SDC, 2010). Ground
water in 61 out of 64 districts in Bangladesh is contaminated with arsenic. According to a
study conducted by the British Geological Survey and DPHE, arsenic concentrations in the
country range from less than 0.25 mg/l to more than 1600 mg/l (DMB, 2010).
1.2.9 Salinity Intrusion
Saline water intrusion is mostly seasonal in Bangladesh. During winter the saline front starts
to penetrate into inland, and the affected areas rise sharply from 10% in the monsoon to over
40% in the dry season. It is observed that dry water flow (Upstream) trend has declined.
Therefore, sea flow (saline water) is moving far inside the country causing in contamination
both in surface and ground waters (DMB, 2010). It is measured that saline water intrusion has
increased which will be intensified with the sea level rise. It is highly seasonal and affects
crop productivity (SDC, 2010).

88°0'0"E
88°0'0"E
89°0'0"E
89°0'0"E
90°0'0"E
90°0'0"E
Figure 1.2: Map of Bangladesh with some areas prone to a specific natural hazard
8
91°0'0"E
91°0'0"E
92°0'0"E
92°0'0"E
93°0'0"E
93°0'0"E
Chapter 1
26°0'0"N 26°0'0"N
25°0'0"N 25°0'0"N
24°0'0"N 24°0'0"N
23°0'0"N 23°0'0"N
22°0'0"N 22°0'0"N
21°0'0"N 21°0'0"N
Coastal Districts
Flash Flood Prone Area
Bay of Bengal
20°0'0"N
Drought Prone Area
Flood Prone Area
20°0'0"N
1.3 Climate Change and Sea Level Rise in Bangladesh
Although the impacts of global warming and climate change are over the world, this problem
is very high for Bangladesh because of the population is chronically exposed and vulnerable
to a range of natural hazards. Climatic hazards, including extremes like floods, cyclones,
tornado, storm surges, tidal bores, etc are not new but climate variability, change and
extremes in Bangladesh due to the effects of global warming have already been evidenced and
may intensify the problems (DOE, 2007). Bangladesh is a low-laying deltaic country which
will face the serious consequences due to sea level rise including permanent inundation of
huge land masses along the coastline. There is a clear evidence of changing climate in
N

9
Chapter 1
Bangladesh which is resulting in changes in the precipitation, increasing annual mean
temperature and sea level rise (Shamsuddoha and Chowdhury, 2007). It is projected that
Bangladesh will be affected by sea level rise (SLR) in future which will be caused by a large
coastal areas inundation (SDC, 2010).
Table 1.3: The inundation scenarios in Bangladesh due to sea level rise (Ali, 1996)
Sea Level Rise (m) Inundation (km 2 ) % of total area (Bangladesh)
1.0 14,000 10.0
1.5 22,320 15.5
Table 1.3 shows the severity of SLR in Bangladesh in future. Bangladesh is a densely
populated county. If it’s 10% or 15.5% area goes under water in future due to sea level rise,
millions of people will migrate to inner area of Bangladesh and the country will face acute
problems.
1.4 Objectives of the Study Work
The study will focus on the disaster history and experience and the implementation of the
Disaster Risk Reduction Progammes with mentioning of the relevant institutions in
Bangladesh. The study also will assess and critically discuss the present and likely future state
of the coastal system (wave action regarding coastal erosion) and focus on the adaptation
measures with special emphasis on storm surges and coastal erosion. As a summary, the
investigations, as the aims of the project are perused in this thesis are listed below:
To introduce Bangladesh in regard to geography, climate, economy, demographic
structure, governance style along with vulnerability to natural hazards, sea level rise
and climate change.
To collect the Disaster (Cyclone) history in Bangladesh and explain the lessons
gathered by the experiences due to cyclones that hit Bangladesh.
To develop an institutional map with most of the relevant institutions and
governmental bodies, research institutes and universities in Bangladesh related to
Disaster Risk Reduction.
To calculate the rate of erosion along the coast of Bangladesh due to wave actions
over the years.
To investigate the impact of climate change regarding coastal erosion in Bangladesh.
To mention the adaptation measures regarding SREX report to manage the Extreme
Events and Disasters due to climate change in Bangladesh.
1.5 Outline of the Report
The present report is arranged as follows:
Chapter 1 contains the introduction to introduce Bangladesh.
Chapter 2 contains the physical phenomena and disaster risk reduction terminology.
Chapter 3 collects the past recorded disaster histories (storm surges) and analyzes to
gather the lessons.

10
Chapter 1
Disaster risk reduction system and an institutional map for disaster risk reduction in
Bangladesh are presented in Chapter 4. Achievements of Bangladesh in implementing
Hyogo Framework for Action are summarized and also discussed here. Few
development projects for disaster risk reduction and climate change adaptation in
Bangladesh are also mentioned here.
Chapter 5 contains the modeling part with the help of SWAN model to analyze the
rate of erosion along the coast of Bangladesh at current and future climate projections.
Chapter 6 presents the low regret adaptation measures in Bangladesh to manage the
impacts of climate change in relation to SREX report.
Finally conclusion and recommendation will be provided in chapter 7.

CHAPTER 2: PHYSICAL PHENOMENA AND DISASTER
RISK REDUCTION
2.1 Introduction
The coast of Bangladesh is a vulnerable zone prone to natural disasters like cyclone, storm
surge, flood, erosion, etc. and it is also a zone of opportunities due to presence of many
economic activities like coastal fisheries and shrimp, forest, salt and minerals, harbors,
airports, tourism complexes, etc. (MoWR, 2005). Cyclonic storms have always been a major
concern to coastal plains and offshore islands of Bangladesh and they also slow down the
pace of social and economic developments in this region (MoWR, 2005). It is forecast that
climate change will increase the frequency and severity of tropical cyclones in Bangladesh
(Luxbacher and Uddin, 2011). River erosion and loss of coastal habitable and cultivable land
is a severe national problem and another major natural hazard in Bangladesh. Although
erosion does not cause loss of lives, it leads to huge economic losses, lessens people’s assets
and making them unable to set up roots (Shamsuddoha and Chowdhury, 2007).
“DRR (Disaster Risk Reduction) is the development and application of policies and practices
that minimize risks to vulnerabilities and disasters” (MoFDM, 2009). Therefore, to reduce the
vulnerability and disaster risk to natural hazard, DRR Programmes e.g. Hyogo Framework for
Action (HFA) should be implemented.
To predict the coastal erosion problem, a numerical model is necessary to simulate the wave
actions along the coast of Bangladesh. Several aspects should be understood to simulate the
wave. Additionally, scales, conditions, and data availabilities have to be determined to
approach the subject. In another words, the information to be obtained must be known
beforehand. To choose a suitable simulation method, some wave processes or parameters
become more noticeable than the others which depend on that particular case. Waves in
coastal waters have to be understood clearly to explain the erosion phenomenon. In general,
the coastline erosion results in serious social and economic consequences. Thus, forecasting
the coastline change in order to carry out the possible solutions to mitigate the erosion is
essential for this area. For this purpose, information on wave conditions in the area of interest
is required. To estimate the wave conditions in coastal areas, a numerical wave model can be
used. In the present study, a wave model (SWAN) has been developed to simulate and predict
the nearshore wave action along the coast of Bangladesh.
2.2 Cyclone and Storm Surges
2.2.1 Introducing cyclones and storm surges
Typhoons are tropical revolving storms. They are called ‘Cyclones’ in English, when they
occur in the area of Indian Ocean. Oscillations of the water level in a coastal or inland,
resulting from atmospheric forces in the weather system are known as storm surges. Its period
may vary in a range from a few minutes to a few days. Storm surges are developed by two
principal factors: pressure drop and wind stress. Therefore, a storm surge is partly caused by
11

12
Chapter 2
pressure differences within a cyclonic storm and partly by high winds acting directly on the
water (Khan, 2012).
Cyclones are formed in the ocean in two characteristic belts in the tropical regions, north of
latitude 10°N and south of 10°S. When the cyclone progresses closer to the coast at shallow
water (where the water depth decreases), a surge is generated. This generated surge is higher
if the continental shelf is longer as well as shallower and the wind is stronger. If the surge
wave coincides with a high tide, the (total) height is further increased which is more
dangerous. At land, the cyclone rapidly dies. The northern part of the Bay of Bengal (the coast
of Bangladesh) is particularly vulnerable to storm surges and coastal flooding, which is
developed by tropical cyclonic activity (Madsen and Jakobsen, 2004).
Figure 2.1 shows a detailed picture of the storm surges. The height of storm surge alone is 15
ft. If this storm surge hits at normal high tide which is 2 ft here, then storm surge coincides
with high tide and forms a total height 17 ft which is more dangerous. If the same storm surge
hits at low tide then the total height must be less than 15 ft which is less hazardous in
comparison to first one.
Figure 2.1: Storm surge (wunderground.com)
2.2.2 Classification of Cyclones
Cyclones have been classified in different areas mainly on the basis of wind speed. Some
time, pressure drops also have been considered.
Table 2.1: Classification of cyclones in South Asian Sub-Continent (RRCAP, 2001)
Depression Winds up to 62 km/h
Cyclonic Storm Winds from 63-87 km/h
Severe Cyclonic Storm Winds from 88-118 km/h
Severe Cyclonic Storm of Hurricane Intensity Winds above 118 km/h
Cyclones have been classified in Table 2.1 on the basis of their intensity of wind speeds. In
South Asian Sub-Continent, mainly these four types of classification have been used.

13
Chapter 2
Table 2.2: Classification of cyclonic disturbances presently in use by Bangladesh (WMO, 2010)
Type of Disturbance Corresponding Wind Speed
Low pressure area Less than 17 knots (less than 31 km/h)
Well marked low 17- 21 knots (31-40 km/h)
Depression 22- 27 knots (41-51 km/h)
Deep Depression 28- 33 knots (52-61 km/h)
Cyclonic Storm 34 -47 knots (62-88 km/h)
Severe Cyclonic Storm 48- 63 knots (89-117 km/h)
Severe Cyclonic Storm with a Core of Hurricane
Wind
64 – 119 knots (118-221 km/h)
Super Cyclonic Storm 120 knots and above (222 km/h or
more)
Table 2.2 shows the classification of cyclonic disturbances that are used by Bangladesh for
national purposes. These classifications are also based on the intensity of wind speeds. After
classification, the warnings are issued by BMD in four stages for the government officials as
per Standing Orders for Disasters (SOD) in Bangladesh. Warnings are provided to ports and
other relevant communities and disseminated it to the stakeholders (WMO, 2010). In this
thesis paper, the classification that is used by Bangladesh for national purposes has been taken
into account to classify the disturbances (Cyclones) that hit Bangladesh.
2.3 Waves in Coastal Areas
2.3.1 Introduction
Evolution of waves is affected by many processes. All physical processes are not equally
important for oceanic and coastal waters. There is a relative importance of various processes.
Table 2.3: The relative importance of the various processes in sea waters (Holthuijsen, 2007)
Oceanic waters Coastal waters
Process Shelf seas Nearshore Harbour
Wind generation ●●● ●●● ● ○
Quadruplet wave-wave interaction ●●● ●●● ● ○
White capping ●●● ●●● ● ○
Bottom friction ○ ●● ●● ○
Current refraction/energy bunching ○/● ● ●● ○
Bottom refraction/shoaling ○ ●● ●●● ●●
Breaking (depth-induced; surf) ○ ● ●●● ○
Triad wave-wave interaction ○ ○ ●● ●
Reflection ○ ○ ●/●● ●●●
Diffraction ○ ○ ● ●●●
●●●=dominant, ●●= Significant but not dominant, ●= of minor importance, ○= negligible.
From the table 2.3, it is clear that the process of generation, wave-wave interaction and whitecapping
are more important in oceanic waters than they are in shallow (near shore) waters but

14
Chapter 2
bottom friction and current refraction are more important phenomena in shallow waters than
they are in deep waters. Shoaling and wave breaking are especially important in coastal
waters for the sediment transport whereas reflection and diffraction are important at harbor. In
coastal waters, the propagation of waves is influenced by a limited (shallow) water depth and
changing wave amplitude (shoaling, refraction and diffraction). Shallow water also influences
the generation, nonlinear wave-wave interaction and dissipation. Therefore, to model the
waves in coastal waters, one needs to take into account more processes than in oceanic waters
(Holthuijsen, 2007).
2.3.2 Wind Generation in Coastal Areas
The formulations and procedures for generating the waves by wind are quite similar in deep
waters and in shallow waters. The important parameter for the generation of waves is the ratio
of wind speed over the phase speed of the waves. When waves propagate from deep to
shallow waters, the phase velocity decreases, thus the ratio of wind speed over the phase
speed of the waves increases consequently, enhancing the transfer of energy to the waves. In
other words, wind generates higher energy into the spectrum in finite depth (shallow waters)
than it does in infinite depth or oceanic waters (Holthuijsen, 2007).
Figure 2.2 depicts that transferring of wind energy into JONSWAP spectrum at shallow
waters (10 m water depth here) is higher than that in the deep waters for the same wind input
but the peak energy develops at the same frequency both at deep and shallow waters.
Figure 2.2: Transferring of wind energy into JONSWAP spectrum in deep and shallow water,
( 3.5 m, and = 20 m/s) (Holthuijsen, 2007)
2.3.3 White-Capping
Wave breaking in deep water is called white-capping, which is a very complicated
phenomenon and a dissipater of energy in JONSWAP spectrum. It involves highly nonlinear
hydrodynamics. Wave breaking itself in general is a poorly understood phenomenon. There is
no generally accepted and precise definition of wave breaking. Quantitative measurements are
also very difficult to carry out. When waves move from deep waters to coastal waters,
shoaling tends to raise their steepness, thus white-capping tends to become more effective in
coastal waters (Holthuijsen, 2007).

15
Chapter 2
Figure 2.3 shows the white capping phenomenon which is an energy dissipater. The energy
loss due to white capping at shallow waters (10 m water depth here) is higher in comparison
with the energy loss at deep waters. As white capping is an energy dissipater, its spectrum
shows negative direction or opposite direction to the JONSWAP spectrum.
Figure 2.3: White-capping source term, in JONSWAP spectrum, in deep and shallow water,
( =3.5 m and (Holthuijsen, 2007)
2.3.4 Bottom Friction
Bottom friction is a very important term for energy dissipation in spectrum. It is a dominant
mechanism for bottom dissipation for continental shelf seas with a sandy seabed. A transfer of
energy and momentum depend on the wave field itself and on characteristics of the bottom.
There are three models to describe the bottom friction. Collin develops the first model. The
time-averaged energy-dissipation rate at the bottom ̅̅̅̅̅ (per unit bottom surface area) can be
expressed as
̅̅̅̅̅
̅̅̅̅̅̅̅̅̅ ̅̅̅̅̅̅̅̅̅ (2.1)
Where and are the magnitude of the (time-varying) shear stress and particle
velocity respectively. Collin (1972) described the shear stress as follows
(2.2)
where is the density of water and is a bottom friction (or drag) coefficient, thus the
energy-dissipation rate becomes
̅̅̅̅̅
̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅ (2.3)
For random waves Collins (1972) expressed the formula:
̅̅̅̅̅
(2.4)

16
Chapter 2
Where, is the root-mean-square orbital velocity at the bottom. By replacing
with [
formula (2.4) becomes:
With
( ]
( [
[∫ ∫ [
( ]
( and estimating from the wave spectrum, the
( ]
Or, in terms of variance density (divide by
(
[
( ]
(
( (2.5)
]
⁄
(2.6)
( (2.7)
Madsen et al., 1988; Weber, 1989, 1991a, 1991b develop the second model. They formulated
the dissipative character of the turbulent boundary layer with the basic parameter such as
grain size of the sand. The results of their model can be also expressed as (2.7). The only
difference is that they estimate for the bottom-friction coefficient in different way. The
parameter which is used to determine the friction (for sandy bottom) is ̃ , which is known as
normalized bottom roughness. It can be calculated as:
̃ =
(2.8)
Where is a bottom roughness length and is the root-mean-square amplitude.
There is another parameter called the Shields parameter ( ), it represents the capacity of the
wave to set the bottom in motion (Tolman, 1995).
(
)
(2.9)
Where and are the densities of sand and water, respectively, is a
representative grain diameter and is the coefficient for skin friction.
Hasselmann et al. (1973; JONSWAP) develops the third model, which can be also expressed
as (2.7) and who estimates for the bottom-friction coefficient, in different way and who
characterized their observations of swell dissipation with
= /(g (2.10)
And = 0.038 m 2 S -3 . For fully developed wind- sea condition, = 0.067 m 2 S -3 (Holthuijsen,
2007).
Figure 2.4 depicts the loss of energy in a JONSWAP spectrum at shallow waters (10 m water
depth here) due to bottom friction which is also a dissipater. In deep water, the wave action
does not reach the bottom. As a result, there is no loss of energy due to bottom friction at deep
waters. Bottom friction is very important to explain the erosion at coastal waters. Bottom
friction can be calculated by using any of those mentioned three models by SWAN.

17
Chapter 2
Figure 2.4: The bottom friction dissipation influenced on JONSWAP spectrum, ( =3.5 m
and (Holthuijsen, 2007)
2.3.5 Depth-Induced (Surf) Breaking
The energy of waves dissipates strongly due to wave breaking. This phenomenon in oceanic
water is known as white-capping, whereas in shallow water additional to white-capping;
depth-induced (surf) breaking is one of the most important energy dissipating processes.
The average energy loss in a single breaking wave (per unit time, per unit horizontal bottom
area) was studied by Battjes and Janssen (1978); they formulated the dissipation in a bore (a
hydraulic jump) as:
(2.11)
Where is a tunable coefficient, is the inverse of the (zero crossing) wave period
and is the height of the breaking wave. In terms of variance, the above equation
can be expressed as
̅̅̅̅̅̅
̅
(2.12)
Where ̅ in the mean zero-crossing frequency of the breaking waves, is the fraction of
breaking waves.
is estimated statistically by Rayleigh distribution as
(
)
(2.13)
Where is the root-mean-square wave height √ , and is the zeroth-order
moment of the wave spectrum. The maximum wave height is generally expressed
( ̅ (2.14)

18
Chapter 2
Where, the value of the breaking index may depend on the wave steepness and bottom slope
(Holthuijsen, 2007).
Figure 2.5 shows the wave breaking due to limited depth in coastal waters. If there is no depth
induce breaking phenomenon, the wave height increased infinitely. But in practically wave
breaks due to limited depth which is another energy dissipater in JONSWAP spectrum.
Figure 2.5: The influence of surf-breaking on JONSWAP spectrum, ( =3.5 m and
(Holthuijsen, 2007)
2.4 Terminology on Disaster Risk Reduction
Disaster
An understanding of the term ‘disaster’ is very important for Disaster risk management. ISDR
(2009b) defines Disaster as a serious disturbance to a community or society which causes
widespread losses and impacts to human, material, economic or the environmental such that it
exceeds the society’s to depend on their own resources. Sheehan and Hewitt (1969) define
Disaster with quantity of losses- as any event which causes at least 100 human deaths or 100
human injuries or 1 million USD economic damages. The severity of a disaster may vary place
to place, community to community. For example, if a cyclone causes serious disturbance or
human deaths/injuries or serious economic damages to a society then that cyclone is a disaster
for that society.
Disaster Risk Reduction
ISDR (2009b) defines disaster risk reduction as a systematic approach to analyze and manage
risk factors of disaster. This approach includes reducing exposure to hazards, lessened
vulnerability of people and property, management of land and the environment and enhanced
preparedness for adverse events. A typical example of such systematic approach is the Hyogo
Framework for Action (HFA).

19
Chapter 2
Mitigation
ISDR (2009b) defines Mitigation as the strategies and actions to reduce the adverse impacts
of hazards. On the other hand, U.N. ISDR (2002) defines Mitigation as those structural and nonstructural
measures which can reduce the adverse impact of hazards and environmental
degradation. Examples of mitigation measures are the strategies to reduce the green house gas
emissions.
Adaptation
Adaptation is defined by the IPCC as the process of adjusting to actual or expected climate to
reduce harm or utilize beneficial opportunities (IPCC, 2001). There are four adaptation
options. These are no-regret, low-regret, win-win, and flexible.
Low-regrets adaption measures
These adaptation measures are those measures that can be beneficial under the current climate
as well as a range of future climate conditions (IPCC, 2012). For example, early warning
systems, ecosystem management and restoration, etc. are the potential low-regret measures.
Hazard
A Hazard is a situation that can be harmful for human and livelihoods or a cause for economic
or environmental damages (ISDR, 2009b). Harriss et al. (1978) defines Hazards as the threats to
human life and well-being, goods, and the environment. A cyclone is a hazard since it can cause
harm to human and livelihood.
Vulnerability
The situation of a society or asset which makes it prone to be adversely affected by a hazard
(ISDR, 2009b). Puente (1999) defines the propensity that may incur loss as Vulnerability. Vulnerability
is measured indirectly on the basis of poverty, construction type, etc.
Risk
ISDR (2009b) defines Risk as the combination of the probability of an event with its adverse
effects. Lerbinger (1997) defines Risk as the probability that death, injury, illness, property damage, and
other undesirable consequences stems from a hazard. For example, a high voltage power supply means
there is hazard. If a person uses that power supply without any precaution, he is at risk. But if he uses the
same power line with sufficient precaution then he is not at risk or is less at risk.
Exposure
Darlington and Lambert (2001) mentioned that, Exposure refers to the number of people,
structures and activities that could be adversely affected by hazards. For example, two cities are
affected by same hazard and 10% of house and 2% of people of both cities affected. But city A
has a population 1 million whereas city B has a population 5 millions. So, city B has higher
exposure in compare to city A to that hazard.

20
Chapter 2
Coping Capacity
ISDR (2009b) mentioned that, coping capacity is the capability of people, organizations and
systems to tackle an adverse situation by using their own skills and resources. Therefore, the
higher the coping capacity of a society, the lesser at risk they are.
Resilience
ISDR (2009b) defines Resilience as the ability of a society or a system to absorb, resist and
recover efficiently from the adverse effects of a hazard but essential basic structures and
functions will be preserved and restored. Resilience includes the coping capacity plus the
capability to completely recover as prior to an event.
2.5 Hyogo Framework for Action (HFA) 2005-2015
The World Conference on Disaster Reduction was held from 18 to 22 January 2005 in Kobe,
Hyogo, Japan, and adopted the present Framework for Action 2005-2015: Building the
Resilience of Nations and Communities to Disasters (here after referred to as the “Framework
for Action”). The Conference presented a strategic and systematic approach to reducing
vulnerabilities and risks to hazards for building the resilience of nations and communities to
disasters.
Three strategic goals are recommended in the conference. The first one is integration of
disaster risk into sustainable development policies, planning and programming at all levels
effectively and focus on disaster prevention, mitigation, preparedness and vulnerability
reduction. The second is strengthening of institutions, mechanisms and capacities at all levels
to building resilience to hazards. The third is integration of risk reduction approaches into the
design and implementation of emergency preparedness, response and recovery programmes
(DMB, 2011; Djalante et al., 2012; ISDR, 2005).
To achieve those three goals, five Priorities for Action have been suggested. The first priority
action is: ensure that disaster risk reduction is a national and a local priority with a strong
institutional basis for implementation. There are four indicators for the first priority action: (1)
The presence of policy and legal framework for DRR, (2) Availability of resources to
implement DRR plans and activities, (3) Community participation and decentralization and
(4) The functioning of a national multi sectoral platform for DRR. The second priority action
is: identify, assess and monitor disaster risks and enhance early warning. There are four
indicators for the second priority action: (1) National and local risk assessments and
vulnerability information, (2) Data monitoring, archiving and disseminating system, (3)
Presence of early warning systems for all major hazards and (4) National, local, regional/trans
boundary risk assessments. The third priority action is: use knowledge, innovation and
education to build a culture of safety and resilience at all levels. There are four indicators for
the third priority action: (1) Availability of information on disasters to stakeholders, (2)
School curricula, education material and relevant trainings on DRR, (3) Research on multirisk
assessments and cost benefit analysis and (4) Countrywide public awareness strategy. The
fourth priority action is: reduce the underlying risk factors. There are six indicators for the
fourth priority action: (1) Integration of DRR with development plans and policies, (2) Social

21
Chapter 2
development policies and plans to reduce people’s vulnerability, (3) Economic plans and
policies to reduce the economic vulnerability, (4) Planning and management of human
settlements considering DRR, (5) DRR into post disaster recovery and rehabilitation
processes and (6) Disaster risk impact assessments of major development projects. The fifth
priority action is: strengthen disaster preparedness for effective response at all levels. There
are four indicators for the fifth priority action: (1) Policy and capacities for disaster risk
management, (2) Disaster preparedness plans and contingency plans at all administrative
levels, (3) Financial reserves and contingency mechanisms and (4) Relevant information
exchanging procedure (DMB, 2011; Djalante et al., 2012; ISDR, 2005).
There are five levels of Progress to score an achievement. The first score is 1, which indicates
a minor progress with few signs of forward action in plans or policy. 1 is the minimum score
for an achievement. The second score is 2, which indicates some progress, but without
systematic policy and/or institutional commitment. The third score is 3, which indicates that
an institutional commitment is attained, but achievements are neither comprehensive nor
substantial. The fourth score is 4, which means substantial achievement attained but with
recognized limitations in capacities and resources. The last and fifth score is 5, which means
comprehensive achievement with sustained commitment and capacities at all levels. 5 is the
highest score for an achievement (Djalante et al., 2012).
Therefore, the degree of progress against all 22 key activities or core indicators is defined on a
scale of 1 (lowest) to 5 (highest). These values are then averaged to assess the progress for
each HFA priority. The scores of all five HFA Priorities are averaged again to obtain a single
score for each country. Higher the score means better the achievement (Djalante et al., 2012).

CHAPTER 3: CLIMATE CHANGE IMPACTS, DISASTER
HISTORY (STORM SURGES) AND EXPERIENCES IN
BANGLADESH
3.1 Introduction
Bangladesh has been identified as one of the most vulnerable countries to climate change by
the international community. This high vulnerability is due to a number of hydro-geological
and socio-economic factors such as geographical location, topography, extreme climate
variability, high population density and poverty incidence and high dependence on agriculture
(DOE, 2006).
Bay of Bengal is particularly vulnerable to storm surges and coastal flooding, which is
developed by tropical cyclonic activity (Madsen and Jakobsen, 2004).
3.2 Experiences from the Past Disasters (Storm Surges)
Bangladesh experienced 157 (recorded) cyclones (wind speed>61 km/h) and cyclone induced
storm surges which caused about two million deaths during 1584-2009 (Appendix 3.1). There
were also lots of depressions (about 68 depressions in Bangladesh during 1877-1995 (Ali,
1999)) that have not been considered here. There is seasonal and monthly variation of cyclone
hitting in Bangladesh. Although cyclones are destructive, their severities are not the same.
The cyclones in 1970, 1991 and 2007 were the most catastrophic for Bangladesh. There was
massive economic loss and thousands of deaths during these years.
Figure 3.1 shows the monthly distribution of cyclones and storm surges that hit Bangladesh.
Monthly distribution shows that the cyclones that hit Bangladesh are not the same over the
year. The maximum number of cyclones occurs in May. The number of cyclones in April,
October and November are also relatively high and statistics show that a lot of cyclones that
hit Bangladesh in these four months are devastating. About 75% of the total cyclones
occurring (from 1584-2009) occurs during these four months. A considerable number of
cyclones also happen in March, June, September and December but these cyclones are
relatively less destructive in comparison with the cyclones that occur in April, May, October,
and November. About 18% of the total cyclones occurring (from 1584-2009) occurs during
March, June, September and December. Few cyclones hit Bangladesh in the rest of four
months (about 7% only) and in these months; the cyclones were not so destructive. So,
Bangladesh is safe from cyclone hazard in February whereas January, July and August are
relatively calm and quite as well.
22

Number of Cyclones
45
40
35
30
25
20
15
10
5
0
23
Chapter 3
Figure 3.1: Monthly distribution of recorded storm surges (Cyclones) in Bangladesh during the period
of 1584 to 2009
There are four seasons in Bangladesh (chapter 1). Seasonal distribution of the occurrence of
cyclones show that cyclones mainly hit Bangladesh in the Pre-Monsoon (March to May) and
the Post-Monsoon (October and November) seasons. More than 80% of the total cyclones in
Bangladesh occur during these two seasons with the Pre-Monsoon alone contributing 48%.
Thus, about half of the total cyclones occur in the Pre-Monsoon. In winter, (December to
February), only 7% of the total cyclones happen whereas the Monsoon season (June to
September) holds 12%. Seasonal distribution of the cyclone’s occurrences is depicted in the
Figure 3.2.
Post-
Monsoon
33%
Monsoon
12%
Month
Winter
7%
Pre-
Monsoon
48%
Figure 3.2: Season wise distribution of cyclones that hit Bangladesh in year: 1584-2009

24
Chapter 3
A ten year period frequency distribution of cyclones (storm surges) shows that frequency of
the occurrence of cyclone since 1960 has increased with maximum cyclones occurred during
1990-1999 (Figure 3.3). However, this frequency decreased 2000-2009. Despite this
observed decrease, Luxbacher and Uddin (2011) forecast that climate change will increase the
frequency and severity of tropical cyclones in Bangladesh. Frequency of occurrence of
cyclonic disturbances is depicted in Figure 3.3.
Frequency
40
35
30
25
20
15
10
5
0
Figure 3.3: Frequency of storm surges in Bangladesh in 10 year periods: 1890-2009
Figure 3.4 depicts the number of different cyclonic disturbances in Bangladesh during 1890-
2009. Among these four cyclonic disturbances (The sequence of the strength of cyclonic
disturbances is Cyclonic Storm < Severe Cyclonic Storm < Severe Cyclonic Storm with
Hurricane < Super Cyclonic Storm) the Super Cyclonic Storm is the strongest whereas
Cyclonic Storm is the weakest due to less wind speeds (Chapter 2). The number of the
occurrence of cyclonic storm is the highest and the number of the occurrence of super
cyclonic storm is the lowest. That means, the stronger the cyclonic disturbances are, the less
frequent they will occur and vice versa. The return period of Hurricane and Severe Cyclonic
Storm are 4.25 (28 numbers in 120 years) and 3.8 (31 numbers in 120 years) years
respectively and Cyclonic Storm hit Bangladesh with about 1.4 (85 numbers in 120 years)
year return period whereas Super Cyclonic Storm with a surge height (surge plus tide) of
about 10 m occurs in Bangladesh with a return period about 20 years (statistics since 1970,
Appendix 3.1).

Number
90
80
70
60
50
40
30
20
10
0
Cyclonic Storm Severe Cyclonic
Storm
Figure 3.4: Different type of disturbances that hit Bangladesh in the period: 1890-2009
25
Severe Cyclonic
Storm with
Hurricane
Super Cyclonic
Storm
Chapter 3
Figure 3.5 shows the number of death due to recent occurring super cyclonic storm in
Bangladesh. Here three super cyclonic storms have been taken for comparisons which are at
similar strength. About 500,000 people died due to super cyclone in 1970 but about 150,000
died due to super cyclone in 1991 which is less than one thirds of the previous one. In 2007,
the number of deaths due to super cyclone was only about 3,500 which indicate that the
number of deaths decreased tremendously although population was about double in 2007
compare with that in 1970. This improvement is due to the implementation of a lot of disaster
risk reduction projects and adaptation measures during this period in Bangladesh e.g. there
were no significant early warning systems in Bangladesh in 1970 whereas Bangladesh has
significantly developed early warning and dissemination systems in 2007.
Number of Death
600000
500000
400000
300000
200000
100000
0
Type of Disturbance
Year: 1970 Year: 1991 Year: 2007
Figure 3.5: Number of death due to super cyclonic storms that hit Bangladesh recently

26
Chapter 3
Figure 3.6 shows the economic damages due to three similar strength super cyclones that hit
Bangladesh in the year 1970, 1991 and 2007. Although all of these three cyclones had similar
strength (similar wind speeds), economic damages were not the same. In 1970, the economic
damages due to super cyclone were very low but increased dramatically in 1991. The
economic damages further increased in 2007. This is due to infra-structural development such
as Schools, Hospitals, Bridges, Culverts, Roads etc. and the improvement of people’s
livelihood conditions in Bangladesh. Thus, the increasing economic development in
Bangladesh results in increasing economic damages by cyclones (disasters). Increasing
exposure of people and economic assets has been the main influence of long-term increase in
economic damages due to natural disasters (IPCC, 2012), which is already proved in
Bangladesh.
4000
3500
3000
2500
2000
1500
1000
500
0
Year: 1970 Year: 1991 Year: 2007
Wind Speed in Km/h Damage in Million USD
Figure 3.6: Financial damages due to super cyclonic storms that hit Bangladesh recently
3.3 Climate Change Impacts in Bangladesh
3.3.1 Climate Change Observed in Bangladesh
Impacts of climate change have already been recorded in Bangladesh in the form of
temperature extremes, irregular or excessive rainfall and increased number of extreme floods,
cyclones, droughts, salinity intrusion into the country.
Bangladesh recorded 5°C (in the three northern districts) in January 2007 which is the lowest
temperature in 38 years. More than 100,000 people were affected by that cold weather and
over 130 people died due to cold-related diseases. Crop production was also affected. An
extremely high temperature (42.08°C) was recorded in Jessore on 27 April 2009 which was
the highest in 14 years. ICDDR,B served a number of patients in that time which they never
experienced since 45 years (DMB, 2010). Habib (2011) showed an increasing trend of annual
maximum and minimum temperature during last 60 years (1950-2010). The annual mean
temperature increased at the rate of 0.0037° C/year during 1961 to 1990 but from 1961 to

27
Chapter 3
2000, the increased rate was 0.0072° C which is about double and an indicator of increasing
warmth in Bangladesh (Shamsuddoha and Chowdhury, 2007).
Heavy rainfall occurred in Dhaka city on 14 August 2004 (341 mm) and 333 mm on 27 July
2009 in 24 hours whereas 290 mm in six hours, a record six-hour rainfall for the capital in 60
years resulted in serious drainage congestion. A total of 425 mm rainfall on 11 June 2007
within 24 hours in Chittagong resulted in a landslide and killed at least 124 people. It also
caused destruction to houses, roads and embankments, as well as electricity, gas lines and
communication facilities. The rainfall was the heaviest previous last 25 years (Habib, 2011).
On the other hand, in 2009 there was 21% less rain during the monsoon period (June-August)
and the northern districts suffered from drought. Droughts were reported even in the coastal
zone. Habib (2011) analyzed a positive trend of average rainfall during last 60 years (1950-
2010). He also showed that the frequency of heavy rainfall has considerable increasing trend
during pre-monsoon (+0.00258/year) and during monsoon (+0.0053/year). An increased
number of severe floods hit Bangladesh in the last decade. Recurring floods occurred in year
2002, 2003, 2004, and twice in 2007 (July-August and September). The number of flash
floods in the hilly terrain of eastern and north eastern part of Bangladesh has also been
increasing.
Additionally, the numbers of cyclones that hit Bangladesh and storm surges are increasing.
For example, Super Cyclonic Storm Sidr hit Bangladesh on 15 November 2007, Cyclone
Nargis on 2 May 2008 hit Myanmar (near the Bangladesh’s coast), Cyclone Rashmi occurred
on 26 October 2008, and Cyclone Aila hit Bangladesh on 25 May 2009. The number of days
with cautionary Signal No. 3 or more increased substantially, which resulted in a reduced
number of fishing days for coastal fishers (DMB, 2010).
SLR along the coast of Bangladesh is a critical variable that may amplify the vulnerability of
the people who live there. Singh (2001) carried out a study on relative sea level rise in
Bangladesh. He used 22 years record of tidal data for the period 1977-1998 pertaining to the
three stations on the Bangladesh coast. This data was obtained by Bangladesh Inland Water
Transport Authority (BIWTA). He showed rising trend of sea level along the coast of
Bangladesh for three different regions. This is shown in the table below:
Table 3.1: Trend of SLR along the coast of Bangladesh (Singh, 2001)
Station Name Region Latitude (N) Longitude (E) Trend (mm/year)
Hiron Point Western 21°48′ 89°28′ 4.0
Char Changa Central 22°08′ 91°06′ 6.0
Cox’s Bazar Eastern 21°26′ 91°59′ 7.8
There are three regions along the coast of Bangladesh (chapter 1). Singh (2001) analyzed the
trend of SLR along the coast of Bangladesh for three different regions separately (Table 3.1).
The result shows an increasing trend of SLR along the coast of Bangladesh for all three
regions but the rate of SLR is not same for all regions. The rate of SLR along the eastern
region is the highest whereas for the western region, is the lowest. By considering the average

28
Chapter 3
SLR of all three regions for future projections, the result shows about 12 cm SLR by year
2030, about 30 cm SLR by year 2050 and about 60 cm SLR by year 2100. The SAARC
Meteorological Research Centre (SMRC) also analyzed sea level changes of 22 years data and
showed 18 cm SLR by 2030, 30 cm SLR by 2050 and 60 cm SLR by 2100 (Mohal et al.,
2006).
3.3.2 Frequency and Intensity of Cyclone in Future in Bangladesh
One of the necessities, but not sufficient condition for the formation of tropical cyclone is that
the sea surface temperature should have a minimum temperature of about 26°-27° C. The
relationship between sea surface temperature and cyclone formation has been well established
that almost all tropical cyclones form in warm water (Ali, 1999). Ali (1996) analyzed the
cyclone frequency in the Bay of Bengal for 1881-1990. He analyzed with ten-year plots of
cyclones, and one plot was made for all types of cyclones: depressions, cyclonic storms, and
severe cyclonic storms. The result showed no increasing or decreasing tendency in cyclone
numbers between 1881 and 1990. Although 27° C SST is necessary to develop a cyclone but
it may not remain constant in future for the Bay of Bengal due to climate change. Global
warming may lead to increased moisture convergence and latent heat release in the Bay of
Bengal that may ultimately increase the number and duration of tropical cyclones in a warmer
atmosphere (Choudhury et al., 1997).
Although there is no clear idea whether global warming and sea level rise will have any effect
on cyclone frequency, there are speculations that cyclone intensity might be affected. If
temperature of the sea surface increases 2°C or 4°C then the maximum wind speed will
increase 10% and 22% respectively, using the threshold temperature of 27°C (Ali, 1996). The
maximum wind speed of the 29 April 1991 cyclone was 225 km/h. Ali (1996) calculated that
if the same cyclone occurred with sea surface temperatures 2°C and 4°C higher, the wind
speed would have been 248 km/h and 275 km/h respectively.
3.3.3 Intensity of Impacts on different sectors due to Climate Change
Bangladesh already experiences the effects of climate change. However, the impacts of
climate change on different sectors are not the same. Some sectors faced acute problems by
some physical processes due to climate change.
Extreme
Temperature
Table 3.2: Impact of climate change on various sectors (MoEF, 2005)
Sea Level Rise
Coastal
Inundation
Physical Vulnerability Contex
Salinity
Intrusion
Drought
River
Flood
Flood Cyclone
Flash
Flood
and
Storm
Surges
Erosion
and
Accretion
Sectoral
Vulnerability
Context
+++ ++ +++ +++ + ++ +++ -
Crop
Agriculture
++ + + ++ ++ + + - Fisheries
++ ++ +++ - - + +++ - Livestock
+ ++ - - ++ + + +++ Infrastructure
++ +++ ++ - ++ + + - Industries

29
Chapter 3
++ +++ +++ - ++ - + - Biodiversity
+++ + +++ - ++ - ++ - Health
- - - - - - +++ +++
Human
Settlement
++ + - - + - + - Energy
Note: +++ refers to high, ++ refers to moderate, and + refers to low level of relationship
Table 3.2 shows the impact of climate change on different sectors in Bangladesh clearly.
Agriculture sector will face the great challenge in future due to climate change. Extreme
temperature, sea level rise are the physical processes that will affect all of the sectors except
human settlement. Drought is only important for crop agriculture and fisheries whereas
erosion and accretion only affect the infrastructure and human settlement sectors. Energy
sector will be mainly affected by extreme temperature. Biodiversity will be highly affected by
sea level rise and cyclone and storm surges will affect all of the sectors.
3.3.4 Actions in relation to climate change effects in Bangladesh
Government of Bangladesh has already developed (BCCSAP) “Bangladesh Climate Change
Strategy and Action Plan 2009” to build the capacity and resilience of the country to meet the
challenge of climate change. Government of Bangladesh also developed (NAPA) “The
national Adaptation Programme of Action” in 2005 to provide a response and to address the
urgent and immediate needs of adaptation and priority programmes (MoEF, 2009).
Bangladesh has seriously addressed the implementation of both actions (BCCSAP and
NAPA) by which good governance to manage climate change effects will be attained.
BCCSAP is a 10 year programme (2009-2018). The first phase (2009-2013) is ongoing which
is based on six major pillars and the BCCSAP lists 44 programmes under the six major
pillars. The first pillar is ensuring the food security, social protection and health. To achieve
this objective, 9 programmes have been recommended. These 9 programmes are building the
institutional capacity of research centres and researchers, building coping system to different
agro-climatic regions, adaption against drought, in fisheries, livestock, and health sectors,
ensuring water supply and sanitation, protecting livelihood for ecologically vulnerable areas
and vulnerable socio-economic groups. The second pillar is further strengthening further the
country’s comprehensive disaster management capacity. To achieve this objective, 4
programmes have been recommended. These 4 programmes are improving early warning and
dissemination system for flood forecasting, cyclone and storm surges, awareness rising and
risk management (insurance). The third pillar is infrastructure development to cope with the
impacts of climate change. To achieve this objective, the implementation of 8 programmes
has been recommended. These 8 programmes are repair and maintenance of flood
embankments, cyclone shelters, polders, improvement of urban drainage, adaptation against
flood, cyclone and storm surges, controlling river bank erosion and dredging. The fourth pillar
is improving research and knowledge management to predict the impact of climate change on
different sectors. To achieve this objective, 7 programmes have been recommended. These 7
programmes are establishing a research centre, developing climate change model, monitoring
and modeling SLR, monitoring of ecosystem and biodiversity, indentifying macro and

30
Chapter 3
sectoral economic impacts, monitoring and supporting the migrated population, and
monitoring tourism related issues in Bangladesh. The fifth pillar is integrating mitigation and
low carbon emissions for development. To achieve this objective, 10 programmes have been
recommended. These 10 programmes are improving energy efficiency, managing gas
exploration and reservoir, developing coal based power stations, utilizing renewable energy,
lowering methane emission, managing urban waste, afforesting and reforesting, intruding
energy saving devices, developing energy and water efficiency, and improving in energy
consumption. The last and sixth pillar is focusing on capacity building and institutional
strengthening. To achieve this objective, 6 programmes have been recommended. These 6
programmes are revising of sectoral policies, mainstreaming climate change, strengthening
human resources capacity, strengthening gender consideration, strengthening institutional
capacity, and incorporating climate change in the media (MoEF, 2009).
The ministry of Environment and Forest is the key ministry to address all climate change
related work including international negotiation. There is a committee called National
Environment Committee to address all environmental related strategy. There is another
committee, National Steering Committee formed by all relevant ministries and civil society
representative to develop and overseeing the implementation of national climate change
action. NDMC, MoFDM, DMD are also involve with MoEF to work with together. The
BMD, SPARRSO, under the MoD, the FFWC, BWDB, under the MoWR are also the key
institutions in this field (MoEF, 2009). Although Bangladesh emits a little green house gas but
it is also focused in BCCSAP to further reduce the green house gas emissions.
Bangladesh seriously started to address the climate change issue after the COP meeting which
was held in 2007 in Bali. Bangladesh has already submitted papers to United Nations
Framework Convention on Climate Change (UNFCCC), which is an initial national
communication (MoEF, 2009).
By considering all of the aspects mentioned above, it is clear that Bangladesh has already
developed strategies to make the country more resilient to climate change. Bangladesh also
implements some CBA programmes. This is a part of good governance. Disaster risk
reduction and climate change adaptation influences decentralization and community
participation which support good governance. But there is still a lot setback with
accountability and transparency to implement the programmes. Corruption is a problem like
other South Asian countries. Although Bangladesh has managed to continue peace and
political stability, make slow but steady progress in civilizing corruption perceptions, and
strengthen public financial management in recent years (WB, 2010b). The current
government’s Digital Bangladesh by 2021 vision suggests mainstreaming ICTs as a pro-poor
tool to eliminate poverty, ensure good governance and social equity through quality
education, healthcare and law enforcement for all, and prepare the people for climate change
(PMO, 2010).

3.4 Bangladesh’s Exposure and Vulnerability to Natural Hazards
31
Chapter 3
3.4.1 Exposure in Bangladesh and Elements are at Risk
Cyclones and floods have occupied the greatest risk to Bangladesh (ISDR, 2009a). Cyclone is
one of the hazards that Bangladesh suffers most frequently and most of the people die due to
cyclone hazard (Figure 3.7(a) and 3.7(b)). Figure 3.7(a) shows that the number of occurrences
of cyclone hazard is 137 which is the highest in comparison with other hazards that occurred
during 1907-2004. Figure 3.7(b) depicts that the maximum number of people died in
Bangladesh due to cyclone hazard. So, it is clear that Bangladesh is exposed to cyclone hazard
and Bangladesh remains one of the worst sufferers from cyclonic casualties in the world.
Figure 3.7(c) shows that floods in Bangladesh affect a greater number of populations in
comparison with any other natural hazards. Millions of acres crops and millions of houses and
livestock were washed out and affected by cyclones and storm surges hazard during 1970-
2009 (Figure 3.7(d)). Institutions, bridges, culverts, roads and embankments were also
directly affected by cyclones and coastal erosions (Appendix 3.3).
(a)
(c)
Frequency of Occurence of Major
Natural Disasters (1907-2004)
Cyclone (137) Drought (5)
Earthquake (6) Flood (64)
Hazard
Exposure
Number (000,000) of People Affected
by Major Natural Disasters (1907- 2004)
Cyclone (638) Drought (250)
Earthquake (0) Flood (3697)
Hazard
Vulnerability
Number of People Died in Major
Natural Disasters (1907-2004)
Cyclone (614,112) Drought (18)
Hazard
Vulnerability
Earthquake (34) Flood (50,310)
Figure 3.7: Bangladesh’s exposure and vulnerability to natural hazards (a) frequency of occurrence;
(b) number of people died; (c) number of people affected; (d) vulnerability to cyclone hazard (Data
from ISDR, 2009a; MoWCA, 2010)
Figure 3.8 shows the area of Bangladesh which is directly exposed to coast to cyclone and
erosion hazard. There are 19 districts (147 upazilas) out of 64 districts which are called
coastal districts in Bangladesh and 48 upazilas in 12 districts (out of 19 coastal districts) are
directly exposed to the sea and or lower estuaries. These areas are known as the exposed coast
and the remaining 99 upazilas of the coastal districts are termed interior coast.
(b)
(d)
12 10
Crops
Affected in
Acre
Vulnerability to Cyclone Hazard in
Million (1970-2009)
No. of
Affected
House
37
No. of
People
Affected
4
No. of
Livestock
Died

B a y o f B e n g a l
Area Exposed to the Coast in Bangladesh
Figure 3.8: Area exposed to the Bay of Bengal in Bangladesh (Appendix 3.2)
32
Chapter 3
Cyclone 1991 hit Bangladesh and caused about 150,000 people’s death. Mohal et al. (2006)
calculated that if the same cyclone occurs with sea level rise (32 cm), then the inundated delta
area would increase from 42% to 51.2%. Again, due to the climate change, if SST increases
2°C then the maximum wind speed will increase 10% (Ali, 1996). Therefore, if cyclone 1991
hit Bangladesh with 10% increased wind speed along with 32 cm SLR, then it would increase
the surge height by 1.2-1.7 m near Kutubdia-Cox.s Bazar, eastern coast of Bangladesh (Mohal
et al., 2006).
3.4.2 Vulnerability to Hazard Risks
The people who live in the exposed coast are considered as vulnerable partly or fully to surge
flooding. More than 35 million (now more than 38.5 million (BBS, 2011)) people lived in the
coastal zone of Bangladesh who were exposed to cyclones, storm surges, rough seas, salinity
intrusion and permanent inundation due to sea level rising. Over 3 million people who lived in
an area of 4,200 km 2 in 72 offshore islands were extremely vulnerable. The main source of
income of around 0.5 million households is fishing in the Bay of Bengal. Working days were
lost due to rough weather in the Bay (DMB, 2010).
Population density in coastal area is 816 whereas the density for the whole Bangladesh is 976
which is higher compare to coastal zone (Figure 3.9(a)). One of the reasons for this density
scenario is people’s migration from the coastal area to inner parts. Figure 3.9(b) shows that
the number of female is higher than the number of male in the coastal area. This may be due
to travelling of men for job around the country for life sustenance against the poverty in the
coastal zone. But, a significant number of transitory people come to the coastal areas during
the fishing period from the inner parts of the country. These fishermen are one of the most
vulnerable groups in the coastal zone (Karim and Mimura, 2008).

(a)
Population Density per sq. km
976
816
Bangladesh Coastal
33
Chapter 3
Figure 3.9: Comparions of population (a) density for whole country with coastal area only and (b)
male to female ratio for whole country with coastal area only (BBS, 2011)
Disasters adversely affect all aspects of children’s daily life because children have the right to
get clean water, sanitation, food, health and education which is seriously hampered due to
disasters. Increase of disaster’s frequency and intensity weakens people’s resilience and
increases poverty as a result it affects the children, other dependent and vulnerable groups.
Under these circumstances, infants, young children, and pregnant and lactating women (PLW)
are vulnerable to malnutrition and micronutrient deficiencies. For their dependent and risk
prone positions, women and children are particularly prone to any form of vulnerability. From
the analysis of the damage and loss assessment of different disasters, it is clear that children
are more vulnerable to every disaster. Climate change or particularly SLR will intensify the
problems or alter the problems to new social dimensions (MoWCA, 2010).
Table 3.3: Typical scenarios in coastal zone (BBS, 2011)
Child

CHAPTER 4: IMPLEMENTATION OF DISASTER RISK
REDUCTION PROGRAMMES - HYOGO FRAMEWORK FOR
ACTION IN BANGLADESH
4.1 Disaster Management System in Bangladesh
Disaster management system in Bangladesh is divided into two parts. The first is the disaster
management regulative framework which provides the legislative basis and a detailed
institutional framework for disaster risk reduction. The second is the necessary actions for
disaster management at national and sub-national level which are guided and described in the
regulative framework (SDC, 2010).
Disaster management act provides legal basis for the protection of life and property and
creates mandatory obligations and responsibilities on different ministries, committees and
appointments. Disaster management plans, guidelines for government at all levels and
standing orders on disaster have been formulated under disaster management act (SDC,
2010). The national disaster management plan provides the overall guidelines for the different
sectors and the disaster management committees at all levels (national and local level such as
district, upazila, union) to develop and implement specific plans for their respective areas.
Few hazard specific management plans are also developed, such as flood management plan,
cyclone and storm surge management plan, tsunami management plan, earthquake
management plan, etc. Guidelines for the government at all levels are formulated to assist
ministries, NGOs, disaster management committees and civil society in implementing disaster
risk management. MoFDM issued the standing orders on disaster in January 1997 (revised,
August 2008) to guide and monitor activities related to disaster management in Bangladesh.
Different national and sub-national (local level) committees have been developed by this
standing order on disaster (SDC, 2010; MoFDM, 2009; DMB, 2010).
National Disaster Management Council (NDMC) headed by the Honorable Prime Minister
and Inter-Ministerial Disaster Management Co-ordination Committee (IMDMCC) headed by
the Minister in charge of MoFDM coordinate and ensure disaster management activities at
national level. National Disaster Management Advisory Committee (NDMAC) headed by an
experienced/skilled person having been nominated by the Prime Minister advises NDMC at
crisis situations. National Platform for Disaster Risk Reduction (NPDRR) and Earthquake
Preparedness and Awareness Committee (EPAC) coordinate and facilitate the relevant
stakeholders. Cyclone Preparedness Program Implementation Board (CPPIB) reviews the
preparedness activities in the face of initial stage of an impending cyclone. Focal Point
Operation Coordination Group of Disaster Management (FPOCG), NGO Coordination
Committee on Disaster Management (NGOCC), Disaster Management Training and Public
Awareness Building Task Force (DMTATF), and Committee for Speedy Dissemination of
Disaster Related Warning/ Signals (CSDDWS) headed by DG, DMB coordinate the disaster
related training, public awareness and NGOs activities and ensure the speedy dissemination of
warning among the people. Sub-national committees (DDMC, UzDMC, UDMC, PDMC, and
CCDMC) review and implement the disaster management activities within its own
34

35
Chapter 4
jurisdiction and maintain continuous coordination with DMB (SDC, 2010; MoFDM, 2009;
DMB, 2010). The entire disaster management system in Bangladesh is shown in Figure 4.1.
Guidelines for
Government at
all levels
Hazard Specific
Plans
Cyclone
Management
Plan
Flood
Management
Paln
Earthquake
Management
Plan
Tsunami
Management
Plan
Others
Disaster
Management
Plans
Sectoral
Development
Plans
Disaster
Management
Act
MoFDM
Corporate Plan
Agency Plan
Local Level
Plans
CSDDWS
UzDMC
DRR
NDMAC
DMTATF
UDMC
DMB
DDMC
CCDMC
Standing Orders
on Disaster
NDMC
MoFDM
Figure 4.1: Disaster management system in Bangladesh
DGoF
FPOCG
PDMC
IMDMCC
NPDRR
& EPAC
4.2 Institutional Mapping for Disaster Risk Reduction in Bangladesh
CPPIB
NGOCC
4.2.1 Institutional Linkages
Government of Bangladesh has seriously addressed the issue of disaster risk reduction.
Although all ministry, divisions, departments and autonomous bodies have general roles and
responsibilities to reduce the risk of disaster, there are some key ministries and departments
who are primarily involved in this issue. Cooperation and coordination (links) among
different ministries and departments are mandatory to ensure the disaster risk reduction
effectively (MoFDM, 2009; DMB, 2010).
DMB created in 1992 under the Ministry of Relief at that time (renamed as Ministry of
Disaster Management and Relief which is merged with Ministry of Food in 2002 and
currently called MoFDM). MoFDM is the key ministry for coordinating national disaster
management efforts across all agencies. DMB is the focal point for the Hyogo Framework for
Action (HFA) and it advises the government on all matters relating to disaster management.
Three agencies named DMB, DRR, DGoF are under the MoFDM. MoFDM is linked with

36
Chapter 4
most of the ministries and departments related to disaster risk reduction over the country
(Choudhury, 2008).
A disaster management regulative framework is strongly recommended by HFA. MoFDM is
responsible to develop a legal policy and planning framework with the connection of
MoEstablishment/Molaw. MoEd and MoPME are linked with MoFDM to ensure progressive
learning and capacity building through training and primary, secondary and tertiary level
education about DRR. MoF&P is linked with mainly MoEF, MoA, MoFDM whereas MoEF
is linked with MoFDM, MoWR and Universities to ensure the mainstreaming of disaster risk
reduction. MoFDM (DMB) works with MoEstablishment/MoLaw, MoF&P, MoLG&RD and
MoHA to strengthen institutional mechanisms. MoS&T, MoWR, MoFDM, University
(BUET) and Research Institutions work together to update hazard maps. MoLG&RD, MoHA,
AFD, MoH&PW, MoS&T, MoD, MoEd, Universities help MoFDM (DMB) to conduct
earthquake and tsunami vulnerability assessment. BUET helps MoH&PW as collaboration to
update and ensure compliance of the Bangladesh National Building Code. MoFDM, MoWR
and MoLG&RD work together to strengthen national capacity for erosion prediction and
monitoring and utilize the erosion prediction information at local level. HFA suggested that
early warning systems have to be placed for all major hazards, with outreach to communities.
Cyclones, floods and droughts are the main hazards in Bangladesh. BMD under MoD is the
authorized Government organization for all meteorological activities in the country e.g. to
observe different meteorological parameters and to provide weather forecasts for public,
farmers, mariners and aviators on routine basis. BMD is also authorized for awareness
campaign and warning for cyclone and tsunami. BMD provides the earthquake information as
well. BWDB is responsible to construct and maintain all major surface water development
projects like major polders, embankments, sluice gates and Flood Control, Drainage and
Irrigation projects (FCDI) with command area more than 1000 hectares. BWDB constituted in
1959. FFWC is under BWDB which is authorized to forecast the flood over the country
except coastal area. BWDB is also responsible to collect all hydrological data over the
country. The DAE under MoA is responsible to provide efficient and effective needs based
extension services to all categories of farmer to promote sustainable agricultural and socioeconomic
development over the country. DAE is also responsible for drought warning. MoSh
(BIWTA, BIWTC) receive time to time weather information from BMD to ensure the security
of their ships, signals, lighthouse and buoys, jetties and ferries. MoI receives information
about cyclone, flood, drought, etc. from BMD, FFWC, DAE and disseminate through RB,
BTV, BTRC to the public. CPP volunteers (66,000) disseminate cyclone warnings to the
population at risk and help them to evacuate to cyclone shelters or other safe areas. AFD,
MoS&T and MoHA help MoFDM, MoWR (FFWC) and MoD (BMD) for technical and
technological capacity building to strengthen emergency response system. MoHF (DoH)
trains MoFDM volunteers about oral saline, first aid and preventative medicine. DoH also
undertakes awareness and education campaigns about health care, including public health,
hygiene, sanitation and safe drinking water. MoFA establishs and maintains contact with
Donor/foreign government especially at emergency period and also maintains liaison with
MoFDM. MoLand develops a sector wise risk mitigation and preparedness strategy plan with

37
Chapter 4
MoLG&RD, MoWR, MoA. DPHE helps local government to ensure supply of safe and
arsenic free drinking water. Local government institutions are connected to MoFDM and
MoLG&RD to reduce the risk of disaster within their own jurisdiction (MoFDM, 2009;
DMB, 2011; DMB, 2010; SDC, 2010; FFWC, 2010). All of those links that are presented
above are depicted in Figure 4.2.
MoI
BR,
BTRC,
BTV
MoSh
BIWTC
BIWTA
PMO
AFD
MoH&PW
RAJUK, CDA
KDA, RDA
MoD
BMD
MoEd
MoPME
MoHFW
DoH
Link with MoFDM
Link with Others
Secondary Connection
MoWR
BWDB
FFWC
MoS&T
Universities
BUET, DU,
BAU, PSTU
MoFA
Research
Organization
CEGIS, IWM
BCAS, BIDS
SPARRSO
MoFDM
DMB
DRR
CPP
DGoF
MoEstablish-
ment/MoLaw
MoA
DAE
BADC
MoF&P
MoLand
MoEF
DoE
MoLG&RD
LGED
DPHE
Local
Level
MoHA
BFS&C
D
UN, DFID,
JICA, WB,
UNDP and
Others
Donors
Figure 4.2: Institutional (key governmental) map to reduce the risk of disaster in Bangladesh

38
Chapter 4
4.2.2 Missing Links
Although Government of Bangladesh has made considerable progress in implementing the
issue of disaster management to reduce the risk of disaster there are still few missing links and
gaps in Bangladesh. Links of ministries or departments with universities is relatively less.
There are 31 public, 51 private and 2 international universities in Bangladesh (UGC, 2009).
But links show that few ministries and departments are connected with only 4 of those
universities namely Bangladesh University of Engineering and Technology (BUET),
University of Dhaka (DU), Bangladesh Agricultural University (BAU), and Patuakhali
Science and Technology University (PSTU). This is clearly insufficient. This is mainly due to
lack of research works and research funding. Few ministries and departments are linked with
the local level that is not also sufficient. Local level organizations are not well connected to
universities and research institutions. Research organizations are not also well linked with
universities and those research organizations are situated in Dhaka only instead of all over the
country.
4.3 National progress on the implementation of the Hyogo Framework
for Action
4.3.1 Implementation of HFA Priorities for Action in Bangladesh
Bangladesh’s government has started to seriously address the subject of disaster management
following the Hyogo Framework for Action 2005-2015 (HFA) to which Bangladesh is one the
signatory south Asian countries. The achievements and setbacks of Bangladesh from 2009 to
2011 in the implementation of the five priorities of HFA are presented below:
The first priority action is to ensure that disaster risk reduction is a national and a local
priority with a strong institutional basis for implementation.
A regulative framework for disaster management includes the relevant legislative, policy and
institutional framework which are important to create mandatory obligations and
responsibilities on ministries, committees and appointments (DMB, 2010). There are four
indicators for the first priority action: (1) The presence of policy and legal framework for
DRR, (2) Availability of resources to implement DRR plans and activities, (3) Community
participation and decentralization and (4) The functioning of a national multi sectoral
platform for DRR (ISDR, 2005). Bangladesh achieved a score of 4 out of 5 for the first
priority action (DMB, 2011; Djalante et al., 2012). This means that achievement is not
comprehensive but substantial and there is still a level of commitment and capacity for
achieving DRR. The indicator 1 encompasses the presence of policy and legal framework for
DRR at all levels (at national and local). This study finds that draft of National Disaster
Management Policy has been made and a final draft of the National Disaster Management Act
has been submitted which is under approval process. National Disaster Management Plan
(2010-2015) has been approved in April 2010 and revised standing orders on disaster (SOD)
have also been approved. A number of sectoral plans e.g. agriculture, water management,
education, livestock, fisheries, water and sanitation, health, and small cottage industries have
been taken into consideration by DMRD. There is also the National Renewable Energy

39
Chapter 4
Policy. There is some hazard specific plans e.g. cyclone, flood, tsunami, earthquake, etc.
There is a poverty reduction strategy paper (PRSP-II) in Bangladesh. National Education
Policy 2010 has been approved (DMB, 2011; DMB, 2010). The indicator 2 encompasses the
availability of resources to implement DRR plans and activities. This study finds that about
4.5% of national budget was allocated as DRR budget. Hundred million USD per year was
allocated in the year 2009-2010 and 2010-2011 as climate change fund. As hazard proofing
sectoral development investments 1.5 billion USD was allocated. Hundred million taka for
Capacity Building in Disaster Management and 110 million USD as the Bangladesh Climate
Change Resilience Fund (BCCRF) were allocated. For irrigation and removal of water from
water-logging areas 42.5 million USD was allocated. Agriculture Insurance Scheme’ worth
1.07 billion USD was provided for the small and medium farmers. Budget was allocated to
construct 20 new cyclone shelters. For vulnerability reduction, 127 million USD to support
old age people, 14.5 million USD to support insolvent disabled persons, 4.2 million USD to
support lactating mothers of low income working group, 47 million USD to support widow,
divorced, and distressed women, 10 million USD to support of street children and orphans,
4.7 million USD as endowment fund for Disabled Service and Assistance Centers, 818
million USD as Food Security programmes and 142 million USD as Employment Generation
Programme were provided (DMB, 2011). The indicator 3 is community participation and
decentralization through the delegation of authority and resources to local levels. Desk study
shows that donors, international organizations and civil society have actively involved in
Bangladesh with many aspects of DRR. Local governments have legal responsibility for
DRR. In SOD, it is mentioned that the local authority shall arrange preparedness for
emergency steps to meet the disaster and to mitigate distress without waiting for any help
from the centre. There are also budget allocations for the local government. INGOs, local
NGOs and local level Union Disaster Management Committee (UDMC) members have
already implemented about 60,000 risk reduction small scale interventions. Multi disciplinary
training were held on Comprehensive Disaster Management (CDM) where 800 UDMCs, 100
journalists, 150 university teachers, 150 trainers working for public and private training
institutes, academies and resource centers participated. A large number of civil society
members were also trained. With the support from development partners and World Bank,
initiatives to strengthen the local government system (Upazila and Union level) have been
taken (MoFDM, 2009; DMB, 2011). The indicator 4 is the functioning of a national multi
sectoral platform for DRR. My investigation identified a multi-sectoral National Platform for
Disaster Risk Reduction (NPDRR) under the leadership of DMRD Secretary in Bangladesh.
NPDRR is formed by 4 civil society members, 12 different sectoral organizations member
and 2 women’s organizations member. NDMAC is also a multi-sectoral platform for DRR.
SOD suggested developing a multi-level decentralized mechanism of Councils and
Committees from the national to grassroots levels. There are 12 national level committees and
also committees at the local level (MoFDM, 2009; DMB, 2011).
The second priority action is to identify, assess and monitor disaster risks and enhance early
warning.

40
Chapter 4
Early warning systems, in particular for extreme events e.g. cyclones, floods (that may be
predicted only few hours before) is very important for DRR (UNDP, 2005). There are four
indicators for the second priority action: (1) National and local risk assessments and
vulnerability information, (2) Data monitoring, archiving and disseminating system, (3)
Presence of early warning systems for all major hazards and (4) National, local, regional/trans
boundary risk assessments (ISDR, 2005). Bangladesh achieved a score of 3.5 out of 5 for the
second priority action (DMB, 2011; Djalante et al., 2012). This means that achievement is not
substantial and there is still some commitment and capacity for achieving DRR. The indicator
1 is national and local risk assessments based on available hazard and vulnerability
information and include those risk assessments for key sectors. Literature review shows that
there are national risk assessment methods and tools for flood and cyclone in Bangladesh. In
revised SOD, 12 guidelines are present for risk assessment. DMRD under MoFDM has
already developed detailed risk assessment mapping for earthquake and tsunami for three
major cities, Dhaka, Chittagong and Sylhet and also planned to develop it for new eight cities.
By using participatory tools, GoB and various humanitarian actors assess the local level risk
assessment in most high-risk areas. Drought prone areas and cyclone prone areas have already
been identified. Recently river bank erosion prediction model has been developed. There is
also progress in assessing disaster and climate risk in agriculture sector. Risk assessment of
schools, hospitals and cyclone shelters has still not been done. However, initiatives have been
taken (DMB, 2011). The indicator 2 is data monitoring, archiving and disseminating system
in place. This study finds that there is a disaster loss database and disaster losses are
systematically reported, monitored and analyzed. There is a Disaster Management
Information Centre (DMIC) at Disaster Management and Relief Bhaban which is connected
to local level offices to centralize all of the hazard and disaster information. CDMP is
supporting early warning system for flash flood and key location specific flood warning and
CPP to expand their work in five new upazilas in west coast. BRAC has established 5 microclimatic
weather stations to support BMD. Poverty map is updating to use it for risk
assessment at pre-crisis prriod. Limited progress has been done to develop a detailed
vulnerability map for different specific hazard (DMB, 2011). The indicator 3 is presence of
early warning systems for all major hazards with outreach to communities. Literature review
shows that there are early warning systems in Bangladesh for major hazards. BMD is
responsible for early warning for Cyclone. BMD is also responsible for Tsunami early
warning in collaboration with Intergovernmental Oceanographic Commission (IOC). FFWC
under BWDB is responsible for early warning for Flood. DAE under MoA is responsible for
early warning for Drought. The Community Based Flood Information System (CFIS) is an
innovative initiative to disseminate flood forecasting messages to the local communities
through mobile phones. Two mobile phone companies, Grameenphone (private) and Teletalk
have recently started to disseminate instant early warning messages to their subscribers in two
districts, Shirajgonj (flood prone) and Cox’s Bazar (cyclone prone) and planned to expand it
14 coastal districts which is organized by DMB (DMB, 2011; SDC, 2010). The indicator 4 is
national and local risk assessments will consider regional/trans boundary risks assessments to
ensure a regional cooperation. Institutional arrangements exist between FFWC and India
(Central Water Commission) to deliver upstream hydro meteorological data. At the time of

41
Chapter 4
planning, trans-boundary issues have been considered in Bangladesh. There are arrangements
between Bangladesh and India to share the information regarding avian influenza (FFWC,
2010; DMB, 2011).
The third priority action is to use knowledge, innovation and education to build a culture of
safety and resilience at all levels.
Disasters can be dramatically reduced by informing and motivating people towards a culture
of disaster prevention and resilience, which requires proper data collection, compilation and
dissemination of relevant knowledge and information on hazards, vulnerabilities (DMB,
2010). There are four indicators for the third priority action: (1) Availability of information on
disasters to stakeholders, (2) School curricula, education material and relevant trainings on
DRR, (3) Research on multi-risk assessments and cost benefit analysis and (4) Countrywide
public awareness strategy (ISDR, 2005). Bangladesh achieved a score of 3.25 out of 5 for the
third priority action (DMB, 2011; Djalante et al., 2012). This means that achievement is not
substantial and there is still some commitment and capacity for achieving DRR. The indicator
1 is availability and accessibility of information on disasters to stakeholders at all levels. A
desk study shows that there is a network of experts named Bangladesh Disaster Management
Education Research and Training (BDMERT) in Bangladesh which is actively working. Key
government ministries, research institutions and civil society organizations also have their
own websites. Disaster Management Information Centre (DMIC) of DMB also provides
information services on disaster to country wide stakeholders. The early warning information
(especially flood and cyclone) is available through email and websites and DMB, BMD, CPP
and FFWC have been contributing significantly in dissemination of early warning and disaster
messages to stakeholders. BTRC, RB, BTV, print and electronic media have also involved in
disaster information sharing for community preparedness (DMB, 2011). The indicator 2 is
involvement of DRR concept in School curricula, education material and relevant trainings.
This study finds that DRR concept is already included in the national educational curriculum
in Bangladesh in Primary, Secondary, University levels and also as professional DRR
education programmes. Few public and private universities recently introduce Degree
programme at tertiary level. In 1997, initiatives have been taken to introduce of DRR
programme in various training institutions, universities, research institutions and public
services training centres. The draft Disaster Management Act also suggested an establishment
of an independent institute for DM training and research. MoEd and MoPME decided to
develop a large number of school-cum-flood shelters in flood prone region. Although DRR
concept is included in the educational system there is a lack of trained teachers to attain the
desired outcomes (DMB, 2011). The indicator 3 is research methods and tools for multi-risk
assessments and cost benefit analysis are developed and strengthened. This study finds that
DRR is included in the national scientific application and research agenda. Risk assessment
mechanism is already being practiced by different development organizations in their
respective working areas e.g. for earthquake and tsunami risk assessment. A guideline is
already developed for constructing disaster resilient educational institutes. The economic
costs and benefits of DRR have not been studied yet. DMRD has already decided to establish
a Library to help for the research work (DMB, 2011). The indicator 4 is countrywide public

42
Chapter 4
awareness strategy to stimulate a culture of disaster resilience. There are public education
campaigns on DRR for risk prone communities in Bangladesh. DMB has introduced an
Annual Media Award to encourage media personnel in disaster related reporting. National
debate has been telecasted each year on disaster issues. Bangladesh Television has introduced
a regular programme since April 2008 on DRR and Media has introduced a number of
discussions, talk shows on disaster issues. The development of public awareness is a
challenge due to societal heterogeneity e.g. different class, gender, age, sex, caste, religion,
ethnic minority, old age population. Education has to be done on different levels for better
cooperation of the respective societal groups or classes. Bangladesh is one of the countries in
the world with the largest NGO communities. These NGOs help government of Bangladesh to
create countrywide public awareness on disaster (DMB, 2011; SDC, 2010).
The fourth priority action is to reduce the underlying risk factors.
Reducing the underlying risk factors need to be integrated into different sector development
planning and programmes as well as in post-disaster situations (DMB, 2010). There are six
indicators for the fourth priority action: (1) Integration of DRR with development plans and
policies, (2) Social development policies and plans to reduce people’s vulnerability, (3)
Economic plans and policies to reduce the economic vulnerability, (4) Planning and
management of human settlements considering DRR, (5) DRR into post disaster recovery and
rehabilitation processes and (6) Disaster risk impact assessments of major development
projects (ISDR, 2005). Bangladesh achieved a score of 3.17 out of 5 for the fourth priority
action (DMB, 2011; Djalante et al., 2012). This means that achievement is not substantial and
there is still some commitment and capacity for achieving DRR. The indicator 1 is integration
of DRR with development plans and policies. This study shows that there is a mechanism to
protect regulatory ecosystem service. There is integrated planning e.g. ICZM. Bangladesh has
prepared NAPA and BCCSAP. There are Climate Change Fund (CCF) and Climate Change
Cell (CCC) in Bangladesh. There are some climate change adaptation projects but payment
for ecosystem services has not been implemented yet (DMB, 2011). The indicator 2 is
implantation of social development policies and plans to reduce people’s vulnerability. It was
observed that there are some plans and policies to increase the resilience of risk prone people.
There are some facility e.g. Vulnerable Group Feeding (VGF), Food for Work (FFW), Test
Relief (TR) and Gratuitous Relief (GR) to reduce and support the poor people in Bangladesh.
There is currently no provision for crop and property or micro insurance in Bangladesh.
Experience shows that the programmes to reduce the vulnerability are still insufficient (DMB,
2011; SDC, 2010). The indicator 3 is existence of economic plans and policies to reduce the
economic vulnerability. It was also observed that GoB is implementing coastal and wetland
biodiversity project in partnership with the community and civil society at four ecologically
critical areas and there are some projects which are incorporating DRR (DMB, 2011). The
indicator 4 is planning and management of human settlements considering DRR. There is
little enforcement for the National Building Code. Currently National Building Code is
updating. National Land Zoning and National Land Use Planning are preparing by MoLand.
Building code is a very challenging issue to implement over the country (DMB, 2011). The
indicator 5 is incorporation of DRR into post disaster recovery and rehabilitation processes.

43
Chapter 4
Investigation shows that post disaster recovery programmes are explicitly incorporate for
DRR in Bangladesh. NGOs incorporated DRR in post-disaster response and recovery
projects. This tool is new for Bangladesh. Therefore, it will take time to adjust with these new
methodologies (DMB, 2011). The indicator 6 is disaster risk impact assessments of major
development projects. The Environmental Impact Assessment (EIA) and Disaster Risk
Assessment are now mandatory for any large project in Bangladesh (DMB, 2011).
The fifth priority action is to strengthen disaster preparedness for effective response at all
levels.
If authorities, individuals and communities in hazard-prone areas are well prepared to combat
disaster, this preparation will reduce the disaster impacts and losses dramatically (DMB,
2010). There are four indicators for the fifth priority action: (1) Policy and capacities for
disaster risk management, (2) Disaster preparedness plans and contingency plans at all
administrative levels, (3) Financial reserves and contingency mechanisms and (4) Relevant
information exchanging procedure (ISDR, 2005). Bangladesh achieved a score of 3.75 out of
5 for the fifth priority action (DMB, 2011; Djalante et al., 2012). This means that achievement
is not substantial and there is still some commitment and capacity for achieving DRR. The
indicator 1 is the existence of policy and capacities for disaster risk management.
Investigation shows that there are policies and progremmes for school and hospitals for
emergency preparedness. There are guidelines to build schools and hospitals resilient to
disaster but lack of capacity makes it difficult to implement in the field level (DMB, 2011).
The indicator 2 is the existence of disaster preparedness plans and contingency plans at all
administrative levels. There are plans to face a major disaster in Bangladesh. About 66,000
volunteers are prepared over the country to deal with a major disaster. 30,000 members were
taken part into the training on ‘Comprehensive Disaster Management’. GoB has recently
purchased some rescue equipments. An Emergency Operation Centre (EOC) is developed
under DMRD. Due to lack of resources, training and rehearsals cannot be continued over the
year (DMB, 2011). The indicator 3 is presence of financial reserves and contingency
mechanisms for effective response. There are national contingency funds but no catastrophe
insurance facilities in Bangladesh. GoB has allotted 42 million USD to face climate risk in
Bangladesh. There is a national relief fund (contingency) to address a quick response to a
disaster in Bangladesh up to local level and discussion is ongoing to develop a National
Disaster Response and Recovery Fund (DRF). Experience shows that contingency fund is
sufficient to face a medium-scale disaster but additional support is required for major disaster
(DMB, 2011; DMB, 2010). The indicator 4 is existence of relevant information exchanging
procedure. There are methods and procedures to assess the damage, loss and requirement to
tackle the situation at the time of disaster in Bangladesh. DMB already has a cell named
Damage and Need Assessment (DNA) and another multi-hazard Risk Vulnerability
Assessment Modeling and Mapping (MRVA) cell is going to be established (DMB, 2011).
4.3.2 Discussions and Recommendations on the Implementation of HFA in Bangladesh
A critical discussion Bangladesh’s progress in implementing the HFA to build the community
safe and more resilient to disaster is provided here. Folke et al. (2003) proposed four

44
Chapter 4
important factors to develop resilience: (1) Learning from crises to live with change and
uncertainty, (2) Nurturing ecological and social diversity for reorganization and renewal, (3)
Expanding and combining different types of knowledge for learning and problem-solving, and
(4) Creating opportunities for self-organization to deal with cross-scale dynamics to gain
social-ecological sustainability; including the strengthening of the local institutions.
Learning from crises to live with change and uncertainty: HFA Priority Action 5 includes
measures to strengthen disaster preparedness at all level to provide an effective response to
disaster. Bangladesh achieved a score 3.75 here which means institutional commitment is
attained but there is still a gap. Lack of resources is a problem necessary for consideration by
the Government.
Nurturing ecological and social diversity for reorganization and renewal: Diversity is a part of
resilience which provides a system to continue in the face of change (Folke et al., 2003).
Hence the participation and collaboration of different sectors and institutions is important for
better coordination and achievement of the priorities. Additionally, this will help to reduce the
underlying risk factor (HFA Priority Action 4) which is an important issue. There is some
institutional coordination but a lot of setbacks with implementation in Bangladesh. Due to
this, it achieved the lowest score 3.17 here. So, Bangladesh needs to focus on this issue. Multi
sectoral platform can support the development of sustainable policies to reduce the risk of
disaster (HFA Priority Action 1). Substantial achievement has been gained by Bangladesh
here (a score of 4 was attained in this priority action).
Expanding and combining different types of knowledge for learning and problem-solving:
Knowledge about hazards and physical, social, economic and environmental vulnerabilities to
disaster is very important to reduce the risk of disaster and disaster can be dramatically
reduced by informing and motivating people through knowledge about disasters (ISDR,
2005). Bangladesh achieved a score 3.5 in implementing HFA Priority Action 2 (identify,
assess and monitor disaster risks and enhance early warning) and further improvement is
ongoing under BCCSAP programmes whereas Bangladesh achieved a score 3.25 in
implementing HFA Priority Action 3 (use knowledge, innovation and education to build a
culture of safety and resilience at all levels). So, Bangladesh needs to further emphasis to fill
the gap to expand their knowledge for solving the problems.
Creating opportunities for self-organization to deal with cross-scale dynamics to gain socialecological
sustainability: Resilience may be a precondition for adaptive capacity which
includes learning and resources management rule as experience gathered (Folke et al., 2003).
HFA Priority Action 1 (ensure that disaster risk reduction is a national and a local priority
with a strong institutional basis for implementation) can provide a legal basis for disaster risk
reduction. Although Bangladesh achieved a substantial score 4 to implement HFA Priority
Action 1 there is still a gap because Disaster Management Act is still in a final draft which
needs to be accepted by parliament for field level implementation.
IFRCRCS (2008) mentioned five characteristics which a community can be identified as safe
and resilient to disaster. The first is if the community can assess and monitor risks and are
protected from the disaster risks to minimize losses and damages when a disaster strikes.

45
Chapter 4
Bangladesh achieved a score 3.5 in implementing HFA Priority Action 2 (identify, assess and
monitor disaster risks and enhance early warning). Bangladesh has the capability to assess and
monitor the risk but there is still a gap in the early warning and dissemination systems. This is
why; Bangladesh is implementing programmes to further improve early warning and
dissemination system for flood forecasting, cyclone and storm surges under BCCSAP. The
second characteristic is if they can sustain their basic community functions and structures
despite the impact of disasters. Bangladesh achieved a score 3.75 in implementing HFA
Priority Action 5 (strengthen disaster preparedness for effective response at all levels) and a
score 3.25 in implementing HFA Priority Action 3 (use knowledge, innovation and education
to build a culture of safety and resilience at all levels). That means Bangladesh has an
institutional commitment and knowledge for effective response to disaster but there is still gap
due to lack of sufficient resources which must be focused on. Bangladesh has to focus on
gaining additional knowledge through research work for facing future challenges. The third
characteristic is if the community can be reconstructed after a disaster and work towards
reducing the vulnerability in future. Bangladesh achieved a score 3.75 in implementing HFA
Priority Action 5 and a score 3.17 in implementing HFA Priority Action 4 (reduce the
underlying risk factors). Although Bangladesh has preparation to respond to disaster there are
still risk factors which need addressing. The fourth characteristic is if they clearly understand
developing safety and resilience as a long-term process which needs a continuous
commitment to tackle the effects of climate change in future and to adapt the future problems
and challenges. Bangladesh achieved a score 3.25 in implementing HFA Priority Action 3 and
a score 3.17 in implementing HFA Priority Action 4. Bangladesh understands that time is
needed to achieve resilience. So, Bangladesh has focused on knowledge gathering and
reducing the risk factors which is a lengthy process. The last characteristic is whether the
community understands the meaning of safety and disaster resilience in such a way that it will
provide a greater opportunity to meet development goals. Bangladesh achieved a score 4 in
implementing HFA Priority Action 1 (ensure that disaster risk reduction is a national and a
local priority with a strong institutional basis for implementation). Bangladesh has already
developed policy, plan for disaster risk reduction and gained a substantial achievement.
Bangladesh achieved a score 3.53 out of 5 in implementing Hyogo Framework for Action
which is higher than the world average 3.0. The score achieved by Bangladesh is also higher
than some South Asian countries e.g. Nepal, Bhutan, etc. (Djalante et al., 2012). But there is
still some commitment and capacity for achieving DRR in Bangladesh. So, my first
recommendation is to focus on reducing the underlying risk factors. Participation and
collaboration of different sectors and institutions need to be ensured to reduce the risks.
Enforcement of rules and regulations need to be implemented at all levels. My second
recommendation is to focus on achieving knowledge to understand and solve future problems.
Research work will help to understand future problems and to develop the sustainable way to
solve the problems. My third recommendation is to update the early warning systems and to
enhance proper dissemination systems. Mobile companies, media, local authorities, and
NGOs should work together to develop a sustainable dissemination systems. My fourth
recommendation is to improve the institutional capacity and capability. Continuous training

46
Chapter 4
for governmental officials and other related stakeholders should be provided. My fifth
recommendation is to ensure sufficient budgetary allocation to enforce DRR initiatives.
Government should focus to develop cooperative international relationship to find necessary
support for DRR.
4.4 Development Projects related to DRR in Bangladesh
4. 4.1 Key Donor Engagements
The national disaster management institutes have collaborative linkages with a host of
technical and scientific organizations, like the Flood Forecasting and Warning Centers
(FFWCs) under BWDB, Bangladesh Meteorological Department (BMD), Center for
Environmental and Geographical Information Services (CEGIS), Institute for Water Modeling
(IWM), and the Space Research and Remote Sensing Organization (SPARRSO). GoB and
other donors are providing the financial support to them for further development. A number of
international financing institutions such as WB, UNDP, JICA, ADB, IDB, DFID, NGOs etc
are also involved in financing and supporting disaster management and risk mitigation
interventions in Bangladesh. The Disaster Emergency Response Group (DER) is a forum for
information sharing, together with government representatives, donor agencies and the NGO
community. DANIDA, SIDA, CIDA, Saudi Arabia and other Arab countries are also involved
in financing in Bangladesh for different DRR and climate change adaptation programmes.
The Arab countries especially, and private donors are involved for the construction of multipurpose
disaster shelters (ISDR, 2009a; SDC, 2010).
4.4.2 Situation of the Current Research
There is a considerable overlap between disaster risk reduction and climate change adaptation
(SDC, 2010). Bangladesh is an agro-based country (Habib, 2011). This is why; research work
is mainly focused on Agriculture or there is few disaster risk reduction and climate change
adaptation integrated research works. But the reality is there is no broadly accepted research
agenda existing in Bangladesh (IIED, 2009).
Recently Bangladesh completed few of research works related to climate change adaptation
along with DRR. National Adaptation Programme of Action (NAPA) was developed in 2005
after which BCCSAP was also developed in 2009. CARE-Bangladesh along with BCAS, and
Bangladesh Rice Research Institute (BRRI), has completed a project namely Reducing
Vulnerability to Climate Change (RVCC) to observe the vulnerabilities of the poorest to
extreme weather events. Adaptation research mainly focuses on local level responses to
climate change, agricultural impacts and responses to crop adaptations, the health impacts of
floods, droughts and disasters. Comprehensive Disaster Management Programme (CDMP)
was started in 2003, which was a strategic, institutional and programming approach to provide
long-term support for risks reduction. The second phase of this project is running and will
continue until the end of 2014. A lot of research has also been carried out to know how the
climate change affects different sectors like land, water, food, health, nutrition, etc. IUCN,
Action Aid and Practical Action are the three international organizations who are working for
community-based adaptation to climate change (AKP, 2010). IIED (2009) includes few

47
Chapter 4
research priorities e.g. modeling of future climate scenarios to understand the trend of land
and water which may be affected in future, vulnerability, impact, risk assessments and
sectoral cost-benefit analysis to know the impacts of climate change on human, to develop
infra-structure development standards.
4.4.3 Development Projects Related to DRR in Bangladesh
There is some development and research projects that are ongoing or expected in the future
for DRR and to adapt the future climate change in Bangladesh are presenting below.
Table 4.1: Some development projects that have been taken recently for disaster Management and
climate change adaptation (AKP, 2010)
Project Period Funding
Agency
Activities
National Adaptation Programme 2005 UNDP The project was implemented by Ministry of
of Action to Climate Change
Environment and Forests to cover the area of
agriculture, water, forestry, fisheries, livestock,
health, infrastructure, industry, communication
and socio-economic aspects to identify the
required action.
Climate Change and Disaster 2006- DFID Screening of DFID –Bangladesh Portfolio.
Risk
2007
Climate Change Cell 2004- DFID To support the Ministry of Environment and
2009
Forests to establish the Climate Change Cell
(CCC). Current support focuses on adaptation
that includes work on modeling, research, crossministerial
coordination and inputs to
Chars Livelihoods Programme 2004- DFID
community risk assessment processes.
A programme working in Jamuna chars on a
2010
range of livelihoods support activities.
Structured consultation on a 2007- DFID To develop a climate change strategy by the
Climate Change Strategy and
Action Plan for Government of
Bangladesh
2008
Department of Environment/CCC.
Economic Empowerment of the 2008 - DFID Challenge fund for NGOs targeting the extreme
Poorest Challenge Fund
2015
poor – to help them lift themselves out of
poverty.
Community based Adaptation to 2007- UNDP To reduce vulnerability of coastal communities
Climate Change through Coastal 2010
to impacts of climate change by increasing
Afforestation.
resilience.
Community-Based Adaptation 2007- UNDP Interventions are in line with national priorities
(CBA) Programme under CDMP 2009
with respect to vulnerability and/or adaptive
(Comprehensive Disaster
capacity development of local communities.
Management Programme).
Climate Management Plan for the 2008 DANIDA Assist GoB partners to conduct a climate
Agricultural Sector
screening and develop a climate management
plan for the Agricultural Sector.
EC Support to NAPA 2008- EC- To implement one or more of the priority
implementation
2012 Bangladesh projects identified under NAPA
Comprehensive Disaster 2009- EC and To implement climate change related
Management (CDMP-II)
2014 DFID components.
Maximum projects that are mentioned above are already implemented and few of them are
still ongoing financed by different donor agencies (Table 4.1). NAPA is an important project
to identify the immediate necessary actions to adapt the climate. Recently climate change cell

48
Chapter 4
is established under the MoEF and BCCSAP is completed in 2009. There are some CBA
projects which are important for good governance and disaster risk reduction. CDMP
(Comprehensive Disaster Management project) is for long-term disaster risk reduction and
capacity building project. There are few projects that are already implemented to reduce the
vulnerability. Community based Adaptation to Climate Change through Coastal Afforestation
is a cross-sectoral measure by which forestation, preservation of environment and barrier
against cyclone will be provided. So, few of mentioned projects are research projects and
others are the adaptation projects. All of the projects mentioned above (Table 4.1) are to
reduce the climate risk and thus all are based on HFA Priority Action 4.
Table 4.2: Donor engagements and plans for medium to long-term (Year- 2022) disaster risk
mitigation in Bangladesh (ISDR, 2009a)
Strategy Planned Activities Probable Development
Partners
(i) Detailed, National Level Multi- Hazard Risk and Vulnerability WB/GFDRR, UNDP,
Assessment & Modeling.
Others
1) Risk
Identification
and
Assessment
2)
Strengthening
and
Enhancing
Emergency
Preparedness
3)
Institutional
Capacity
Building
4) Risk
Mitigation
Investments
5) Climate
Change Risk
Mitigation
and
Adaptation
(ii) Supporting Community Risk Assessments up to Union Levels. UNDP, DFID, CDMP
(i) Disaster Forecasting and Warning systems. JICA, EC, CDMP
(ii) Construction of New, and Rehabilitation of Existing, Disaster
Shelters.
WB,ADB, JICA/JBIC,
IDB, Kuwait, Saudi,
and OPEC Funds
(iii) Strengthening and institutionalizing disaster preparedness. UNDP, DFID , CDMP
(iv) Strengthening Local Communication and Sustained Public
Awareness and Sensitization Campaigns.
WB, CDMP, IFRC
(i) Establishing an Institute for Disaster Management Training. UNDP, DFID ,CDMP
(ii) Professionalizing the Present Disaster Management Institutions. UNDP, CDMP
(iii) Building the Capacity of DMB for Damage, Loss and Needs WB, ADB, UNDP,
Assessments
CDMP
(iv) Mainstreaming disaster risk reduction and mitigation process. UNDP, CDMP
(v) Fostering Public-Private Partnership Forums at National level.
WB, ADB, UNDP,
CDMP
(i) River Bank Protection Improvement Program.
WB, ADB, Dutch
Govt.
(ii) Coastal Embankment Improvement Program.
WB, ADB, Dutch
Govt.
(iii) Upgrading the Standards for roads construction.
WB, ADB,
JICA/JBIC, Others
(iv) Aforestation of Coastal Belt. WB, ADB, Others
(v) Sundarbans restoration and improvement programme.
WB, ADB, Dutch
Govt., Others
(vi) Gorai River Restoration Program.
WB, ADB, Dutch
Govt., Others
(i) Capacity building and Strengthening the Climate Change Cell
(CCC) within DoE.
DFID , UNDP, CDMP
(ii) Developing climate change and climate variability scenario and
prediction models.
DFID , UNDP, CDMP
(iii) Conducting research to strengthen knowledge on climate DFID , UNDP, CDMP
change and climate variability impacts.
And Others
(iv) Identifying climate change adaptation options through action
research.
DFID , UNDP, CDMP
(v) Incorporating climate change and climate variability impact DFID , UNDP,
information in DRR programs and strategies.
CDMP, WB, ADB,
JBIC/JICA, Others

6)
Introducing
Catastrophe
Risk
Financing
7) Support to
the Disaster
Management
Programme
(vi) Designing and Implementing capacity building programs to
understand the climate change impacts.
(i) Establishment of Disaster Response Fund
(ii) Catastrophe Risk Financing of Rare Events
49
Chapter 4
DFID , UNDP,
CDMP,
Others
GOB , IFIs, UN,
Bilateral Donors
GOB , WB, GFDRR,
ADB
Partial implement of Hyogo Framework for Action 1, 2, 3, 4, 5 GFDRR
Table 4.2 shows some long-term projects to reduce the risk of disaster in Bangladesh. Few of
them are already ongoing and rest is proposed for the future. Project 3(v) is based on HFA
Priority Action 1. Project 1(i), 1(ii) and 2(i) are based on HFA Priority Action 2. Project 2(iv),
3(i), 3(ii) and 3(iii) are based on HFA Priority Action 3. Project 2(ii), 3(iv), 4(i), 4(ii), 4(iii),
4(iv), 4(v), 4(vi), 5(i), 5(ii), 5(iii), 5(iv), 5(v), and 5(vi) are based on HFA Priority Action 4.
Project 2(iii), 6(i), and 6(ii) are based on HFA Priority Action 5. Project 7 is already ongoing
and at the end of 2012, it will be completed which is based on HFA different sub-priority
wise. All of these projects are planned to complete by year 2022 to make Bangladesh resilient
to disasters.

CHAPTER 5: MODEL SET-UP, CALIBRATION AND
ANALYSIS OF EROSION ALONG BANGLADESH’S COAST
5.1 Introduction
In the coastal regions of Bangladesh, there is continual erosion and accretion due to inland
fresh water flows, tides, tidal surges, and high winds. Most of the frontal erosion of the Bay of
Bengal was due to storm surges and continuous wave actions. An overall seaward extension
of the delta was observed due to presence of net accretion at certain places on the Bay side
(Ahmed, 1999).
The SWAN (Simulating Waves Nearshore) model has been used in this thesis to investigate
the erosion problem along the coast of Bangladesh. Scenarios of erosion problems due to
climate change (Sea level rise) in future also will be investigated with the help of SWAN.
5.2 Available Data
The coastal zone of Bangladesh is characterized by a low elevation, a lot of small and large
river mouths, scattered islands (known as chars) of different sizes and strong hydromorphodynamics.
The Meghna Estuary, one of the largest estuaries on the earth, is situated at
the central part of the coastline and plays a vital role on the coastal hydraulics of the upper
Bay of Bengal. The eastern coastline is north-south aligned and relatively higher in elevation.
Due to sedimentation and erosion induced by tidal flow and river discharge, the location and
geometry of channels along the coast of Bangladesh strongly changes even within a few years
(Ahmed, 1998; Azam et al., 2004). The following subsections will discuss all the available
data needed to investigate the erosion problem along Bangladesh’s coast with the help of
SWAN model.
5.2.1 Bathymetry
The data for bathymetry was obtained from NOAA, National Geophysical Data Center in
spherical co-ordinates. It has then been converted into SWAN structural grid format by using
MATLAB. Figure 5.1 shows the bottom level that is considered in SWAN.
Figure 5.1: A graphical representation of bathymetry that is used in SWAN model
50

51
Chapter 5
5.2.2 Tide and Current
Tides in Bangladesh coast originate from the Indian Ocean. After that, it enters into the Bay
of Bengal through the two submarine canyons, the ‘Swatch of No Ground’ and the ‘Burma
Trench’ and thus arrives very near to the 10 fathom contour line at Hiron point and Cox’s
Bazar respectively around the same time. There are two most dominant principal constituents
are M2 and S2 whose natural periods of oscillations are 12 hours 25 minutes and 12 hours
respectively. Due to extensive shallowness of the North-Eastern Bay (Bangladesh’s Coast),
the tidal range and friction distortions concurrently increased by the rise to partial reflections
(Mondal, 2001).
Tidal waves are affected at least by four main factors causing amplification and deformation
of the waves when they approach the coastal belt and coastal islands of Bangladesh. These
are: Coriolis acceleration, the width of the transitional continental shelf, the coastal geometry,
and the frictional effects due to fresh water flow and bottom topography. Tidal velocity was
measured during pre-monsoon and post-monsoon season at different channel along the coast
of Bangladesh. Result shows that the maximum velocity at Lower Meghna river is 1.14 m/s,
the velocity at Shahbazpur Channel varies 1 3.2 m/s, the velocity at Hatia Channel varies
1 m/s, the velocity at Sandwip Channel varies 1 1 0 m/s (Ahmed, 1998).
Locations of different Channels are depicted in Figure 5.2.
5.2.3 Water Level
Water level (Tide level) data has been downloaded from the web site for Cox’s Bazar (Figure
5.2) tidal station. Water level for different time in June, 2012 has been taken into account for
the sensitivity analysis and model calibration whereas maximum high tide and low tide in
May, 2012 have been chosen for the model application. Tidal level data is given in appendix
5.1.
5.2.4 Wind
Bangladesh Meteorological Department (BMD) is the authorized Governmental organization
for all meteorological activities in the country. Wind data has been taken from BMD for the
period from 2001 to 2011. Figure 5.2 depicts four wind stations that have been used for wind
calculations. Forecasted wind data is also downloaded from Bangladesh Marine weather
website which is used for the model sensitivity analysis and model calibration. Seasonal
maximum wind speeds is calculated and presented in the Table 5.1.
Table 5.1: Season wise maximum daily wind speeds along Bangladesh’s coast during 2001-2011
Maximum wind speed in (
Winter Summer Monsoon Autumn
) 7.72 29.32 15.02 11.52
Table 5.1 shows the maximum daily mean wind speeds in different seasons along the coast of
Bangladesh. BMD presents wind data as daily mean speed and a daily mean direction for a
wind station. Wind data is collected from BMD for the period 2001-2011 and are processed
season wise. Table 5.1 shows that the maximum daily mean wind speed is in summer whereas
the minimum daily mean wind speed is in winter. The maximum daily wind speed is about 30

52
Chapter 5
m/s in summer. This is why; the calculation of the rate of erosion has been done up to 30 m/s
wind speed. Season wise number of days of wind blowing from different directions along the
coast of Bangladesh for the period 2001-2011 is given in (Appendix 5.2).
Mongla
Wind Station
A Sandwip Channel
B Shahbazpur Channel
C Hatiya Channel
D Lower Meghna River
D
Khepupara
Hatiya
Cox's Bazar
Figure 5.2: Wind stations that were considered to calculate the rate of erosion and different channels
along the coast of Bangladesh
5.2.5 Waves
Wave data is not available along the coast of Bangladesh. However, there are few websites
that provide forecasted wave and wind data. Such data was downloaded and used for this
study. Nearshore forecasted wave and wind data was downloaded daily for the period from 5 th
June, 2012 to 14 th June, 2012. This data is based on Global Wave Watch III model. After that
the data was processed and used in SWAN. Offshore wave data was downloaded from NOAA
Wave watch III, web site. Other required data are also downloaded from website.
5.3 SWAN Model
In SWAN the basic equation that is used to describe the waves is the action balance equation;
(5.1)
Formula 5.1 represents the action balance equation where N ( , ; x, y, t ) is the action
density as a function of intrinsic frequency , direction , horizontal co-ordinates x and y and
time t. The first term on the left-hand side denotes the local rate of change of action density in
time. The second and third terms represent the propagation of action in geographical space
(with propagation velocities ). The fourth term denotes shifting of the relative
frequency due to variations in depth and current (with propagation velocity in ).
The fifth term represents depth-induced and current-induced refraction (with propagation
velocity At the right hand side, the term S [=S ( , ; x, y, t ) ] is a source
B
B a y o f B e n g a l
C
A

53
Chapter 5
term; which represents the effects of generation, dissipation, and non-linear wave-wave
interactions (Ris et al., 1999).
The basic equation can be expressed in spherical coordinates:
with longitude, λ and latitude, .
(5.2)
5.3.1 Co-ordinate System in SWAN
In order to perform the wave computation model, it is necessary to have clear idea of the basic
co-ordinate system that is applied in a numerical model. In SWAN, two co-ordinate systems
must be selected to set up the model.
The first co-ordinate system is for geographical locations. All geographical locations must be
defined in the so-called problem co-ordinate system according to the two following coordinate
systems in SWAN:
CARTESIAN: All locations and distances are in meters. Co-ordinate is given with
respect to x and y axes chosen arbitrarily by the user.
SPHERICAL: All co-ordinates of locations and geographical grid sizes are given in
degrees, x is longitude x=0 means Greenwich meridian and x>0 is the East of
meridian; y is latitude with y>0 means the Northern hemisphere. Input and output
grids have to be oriented with their x-axis to the East, mesh sizes are in degrees. All
other distances are in m.
The second co-ordinate system is for the directions of winds and waves. There are two
options for the convention of the directions of winds and waves in SWAN, they are:
The CARTESIAN convention: The direction where waves are going to or where the
wind is blowing to that means the direction to where vector points, measured counter
clockwise from the positive x-axis of this system in degrees.
The NAUTICAL convention: The direction where waves are coming from or where
the wind is blowing from, measured clockwise from geographic North.
5.3.2 Grid System in SWAN
The grid system is used in SWAN model may be either curvilinear or rectangular grid. Three
grids must be defined in SWAN computations are mentioned below.
Input grid
Input grid is a grid on which the bathymetry, current, water level, friction coefficients and
wind field are defined. Input grids may be different from each other, both in dimension and
orientation. The spatial resolution of the input grid depends on the accuracy of the spatial
details required. Users should choose the spatial resolutions for those input grids in such way
that the relevant spatial details are properly resolved and special care is needed in case with
extremely complex coastal area and estuary. However, it should be noted that higher the

54
Chapter 5
resolution, higher the accuracy of the results will be, but at the same time, it needs more time
and computer space.
Computational grid
Computational grid is a grid on which model solves action balance equation. In SWAN, users
can define the orientation (direction), the dimension and the resolution of computational grid,
which include the geographical and spectral grids. These two grid systems can be defined
independently from each other.
Geographical grid: Geographical grid describes the orientation, dimension and the resolution
of the area in which wave computation are to be performed. Three types of grid can be used: a
regular rectangular grid ( x=constant, =constant), an irregular rectangular grid
( x=variable, =variable) and a curvilinear grid. If higher grid resolution is locally required,
grid nesting is optionally available in the SWAN model. By this nesting option, the
computations are performed on a coarse grid for a higher area and subsequently on a finer
grid for a smaller area. The boundary conditions for the finer grid are obtained from the
coarse grid.
The x, y resolution and the orientation of the computational grid is defined by the user. In case
of spherical coordinates regular grids must always oriented E-W, N-S. The spatial resolution
of the computational grid should be selected in such a way that it is sufficient to solve relevant
details of the applied wave field. To get the better results, the resolution of the computational
grid and the input grid could be used approximately equal, by this way the error due to
interpolation between grids could be minimized.
In principle the input grid should cover a larger area than the computational grid both in space
and time. If the computational grid exceeds the dimensions of an input, the region outside the
input grid, SWAN assumes that the particular parameter is identical to the value closer to the
boundary.
In addition to the computational grid in geographical space, SWAN also calculates also wave
propagation in spectral space. So, for each geographical grid the spectral grid has to be
mentioned as explained below.
Spectral grid: The computational spectral grid needs to be provided, which consists of the
frequency space and directional space.
Frequency space: frequency space is simply defined as a minimum and maximum frequency
and the frequency resolution that is proportional to the frequency itself (common is =0.1f),
where f is the frequency.
Directional space: In directional space, usually the directional range is the full 360° unless
when waves travel within a limited directional range, which is convenient to reduce the
computer time and/or space. The directional resolution is determined by the number of
discrete directions provided by the user. Table 5.3 contains the recommended guide lines to
choose the discretization in SWAN for application in coastal areas.

Table 5.2: Recommended discretizations for spectral grid in SWAN
Directional resolution for wind sea conditions
Directional resolution for swell sea conditions
Frequency range 0.04 f
Spatial resolution
55
Chapter 5
Table 5.2 shows the guidelines for choosing spectral grid in SWAN. Table 5.3 presents all
required values that have been used in SWAN for this thesis.
Output grid
SWAN can provide outputs on spatial grids that are independent from input grids and
computational grids. An output grid must be specified by the user. It must be kept in mind that
the information on an output grid is obtained from the computational grid by bi-linear
interpolation. Therefore if possible, it is wise to keep three grid systems identical to avoid the
interpolation error.
5.3.3 Boundary Conditions in SWAN
It is essential to mention the boundary conditions both in the geographical and spectral space
to facilitate the integration process of the action balance equation.
Boundary conditions in the geographical space: The boundaries of the computational grid in
SWAN are either land or water. In case of land there is no problem. The land does not
generate waves and in SWAN it absorbs all incoming wave energy. But in the case of water,
boundary is a problem. If no wave conditions are known along such a boundary, SWAN then
assumes that no waves enter the area and that waves can leave the area freely. This
assumption is obviously wrong if incorporated in the model. If there are available
observations, they can be used as input at the boundary.
Boundary conditions in spectral space: In frequency space the boundaries are fully absorbing
at the lowest and highest discrete frequency so that wave energy can freely propagate across
these boundaries. If the full circle is used then no boundary conditions are required. But for
the reason of economy, it is also possible to provide directional sectors instead of a full circle.
5.4 Overall Model Set-up
In this assignment, calculations have been carried out with the latest version SWAN 40.85.
The standard settings were applied here to select the different processes in all computations as
pre SWAN implementation manual guidelines (SWAN team, 2011). The processes that have
been used in this project are tabulated below:

Table 5.3: The default settings in SWAN that have been used in this project
Process Explanation
56
Chapter 5
Generation Mode GEN3 1) This is strongly recommended by the manual. 2) Employing the
quadruplet wave-wave interaction. 3) Using three different theories of
Komen et al., 1984, Janssen, 1991 and Hasselmann et al., 1985 to
define the Whitecapping and Quadruplets processes whereas 1 st and
2 nd generations have used only Holthuijsen and De Boer, 1988.
Physical process Whitecapping Komen et al., 1984. Default coefficients.
Quadruplets Default coefficients.
Depth induced Battjes and Janssen, 1978. Default coefficients.
wave breaking
Bottom friction (Hasselmann et al., 1973, JONSWAP). Default value.
Triads Trfac= 0.10 cutfr= 2.20 urcrit=0.02 urslim=0.01.
Set Constant water level, RHO= 1025 and NAUT convention.
Stationary/
nonstationary
mode
Stationary 2D
mode
2D mode is more realistic than 1D mode. Due to lack of available
data, only stationary mode is used here.
Coordinates Spherical The area is large enough to use spherical coordinates.
Computational Regular 83°E to 95°E and 18°N to 23°N,1 minute resolution.
Grid
Circle fmin=0.05, fmax=1.00, mdc=36, msc=31.
Bathymetry Structural Mesh 1 minute resolution for whole domain.
Wind condition Uniform wind condition in computational grid.
Current effect Absence of Although the effect of current near the estuary is significant at least in
current effect Monsoon but this study is made without current due to lack of
available data.
Boundary The shape of JONSWAP spectrum. Default value. Because the result of
condition spectra
JONSWAP over fetches that are most relevant to the Engineer
(Holthuijsen, 2007).
Accuracy Standard accuracy Drel=2%, Dhoval=0.02m, Dtoval=0.02s, Npnts=98.5%, Nmax or
command criterion
mxitst=15 iterations.
Output Block & Point Mat file, 2 points (91.25, 21.00) & (88.75, 21.00) to check the model
result for sensitivity analysis and model calibration.
A typical command file for SWAN computation is given in the Appendix 5.8.
5.5 Sensitivity Analysis and Model Calibration
5.5.1 Sensitivity Analysis
In general, as part of the task to calibrate the model, a sensitivity analysis needs to be carried
out. The results from the sensitivity analysis will be helpful to decide a set of parameters that
is necessary for model calibration.
Figure 5.3 shows the area that has been considered in SWAN and two points (Point-1 & 2)
where the model outputs have been taken to compare the results with the forecasted data for
the sensitivity analysis and model calibration. Two buoys that are considered for sensitivity
analysis and model calibration are also shown in the Figure 5.3.

Figure 5.3: Area, points, and buoys that were used in SWAN
57
Chapter 5
There are two boundary conditions that have been used in SWAN for sensitivity analysis.
Data has been presented at Table 5.4.
Date and
Time
07.06.12
18:00
08.06.12
00:00
Water
Level
(m)
83°0'0"E
Table 5.4: Two boundary conditions for sensitivity analyses
Wind Condition
Wind
Speed
(m/s)
85°0'0"E
Direction
(Nautical
Degree)
87°0'0"E
87°0'0"E
89°0'0"E
89°0'0"E
91°0'0"E
91°0'0"E
Offshore Forecasted Data
(90.14, 18.13) Buoy-1
93°0'0"E
93°0'0"E
95°0'0"E
24°0'0"N 24°0'0"N
83°0'0"E
India
85°0'0"E
Bangladesh
23°0'0"N 23°0'0"N
22°0'0"N 22°0'0"N
21°0'0"N 21°0'0"N
Point- 2 Point- 1 Myanmar
20°0'0"N 20°0'0"N
19°0'0"N Buoy- 2 Buoy- 1
19°0'0"N
18°0'0"N 18°0'0"N
Bay of Bengal
17°0'0"N 17°0'0"N
95°0'0"E
Offshore Forecasted Data
(87.56, 18.35) Buoy-2
Hs (m) Tp (s) Direction Hs (m) Tp (s)
Direction
(Nautical
Degree)
0.7 6.05 202.5 2.15 9.1 214 2.23 8.9 205
3.25 6.30 191.25 2.11 9.2 213 2.04 9 202
By using these two boundary conditions in SWAN, a number of parameters have been
investigated to select the parameters that should be used for the model calibration. The results
of the sensitivity analysis are presented in Appendix 5.3.
The results of sensitivity analysis (Appendix 5.3) show similar model output results whether
used Buoy-1 or Buoy-2 is used with constant boundary option. When both Buoys with
variable boundary option are used at the boundary, the model result at point-1 & 2 are also
look similar to the previous results. Therefore, the Buoy-1 with constant boundary option has
been selected for further calculations. Model without considering the bottom friction shows
relatively higher significant wave height than with friction condition. Model is fixed for 15
iterations; otherwise the accuracy level may be less than 98.5%. So, 15 iterations have been
considered for further calculation. Bathymetry was used with one minute resolution for the
whole area. However, it is better to use higher resolution at nearshore if this type of
bathymetry is available. Due to lack of high resolution data for this study, the model output

58
Chapter 5
with and without nesting looks similar. Therefore, nesting will not be considered in other
calculations. Same resolutions for all grids (Computational grid, input grid) have been
considered here to avoid the interpolation errors.
5.5.2 Model Calibration
Average wind speeds and wind directions of forecasted data at point- 1 & 2 have been used
for model calibration. Forecasted data depicts that the significant wave height at point- 1 & 2
is similar but peak wave period at point-2 is sometimes higher than that at point-1. The
forecasted data at point-1 shows that wave direction is constant over the calibration period (8 th
June, 2012 to 15 th June, 2012) but at point-2, it is fluctuated. The data that has been used for
model calibration is given in Appendix 5.4.
The main objective of model calibration is to compare the model results with measured data
and adjust some model parameters to coincide with the model results with the measured data.
The modeled outputs of significant wave height Hs, peak wave period Tp and mean wave
direction at two points are presented in Appendix 5.5. To compare the SWAN outputs with
forecasted data, a graphical representation is shown in Figure 5.4.
Significant wave height Hs, at point- 1 & 2 show similar trends for forecasted data and
SWAN outputs for the thirty calibrations but both of them did not completely coincide
(Figure 5.4(a) and 5.4(b)). For maximum the calibrated points, the forecasted significant wave
height is higher than SWAN output significant wave height. The discrepancies in Peak wave
period, Tp at point-1 are comparatively less with the forecasted Tp whereas at point-2, the
discrepancies of peak wave period were high (Figure 5.4(c) and 5.4(d)). Although forecasted
wave direction is constant over the calibration period at point-1, SWAN output is fluctuated
whereas at point-2 both forecasted and calculated wave direction are fluctuated over the
calibration period (Figure 5.4(e) and 5.4(f)). The SWAN outputs never match completely with
forecasted data. The reasons may be:
The resolution of the bathymetry over the domain is considered same. But to get the
better output, at nearshore the resolution should be higher.
At nearshore, there is no availability of measured data. Only 48 hours forecasted data
was used. The forecasted data used is the output of another model. So, forecasted data
may not be as accurate as measured data, hence the variability of results.
Wind over the domain is considered uniform, which is another source of error. Wind
data that is used in SWAN for model calibration is also forecasted data.
Instead of measured data, the forecasted wave data at buoy-1 is used as boundary in
SWAN and this forecasted buoy data are also downloaded from another website.

Tp (s)
PeaK Wave Direction
Hs (m)
12
10
4
3.5
3
2.5
2
1.5
1
0.5
8
6
4
2
0
0
250
200
150
100
50
Comparison of Hs (m) at Point- 1
SWAN Forecasted
1 5 9 13 17 21 25 29
Number of observations
1 5 9 13 17 21 25 29
Number of observations
0
(c)
(a)
Comparison of Tp (s) at Point- 1
SWAN Forecasted
Comparison (Deg.) at Point-1
(e)
SWAN Forecasted
1 5 9 13 17 21 25 29
Number of observations
59
Chapter 5
Figure 5.4: Comparison of SWAN outputs with forecasted data (a) at point-1; (b) at point-2 for Hs, (c)
at point-1; (d) at point-2 for Tp, (e) at point-1; (f) at point-2 for wave direction
5.6 Model Application to calculate the Erosion along Bangladesh’s Coast
After calibration, the model has been applied to calculate the rate of erosion along the coast of
Bangladesh. High tide and low tide water levels in May, 01 at Cox’s Bazaar have been used
in SWAN (Appendix 5.1). Wind analysis results show that among required 9 wind directions;
the southern wind direction is the dominant wind direction along the coast of Bangladesh in
summer, monsoon, and autumn (Appendix 5.2). Additionally, western wind direction also has
been used for winter to investigate the directional influence on the rate of erosion. Therefore,
for the erosion investigation, both southern and western wind directions have been considered
for 5 m/s and 10 m/s wind whereas for 15 m/s, 20 m/s, and 30 m/s winds, only southern
direction is being selected for model application. Boundary conditions (offshore wave) have
been selected with the help of forecasted data and downloaded data from another website.
Tp (s)
Peak Wave Direction
Hs (m)
4
3.5
3
2.5
2
1.5
1
0.5
16
14
12
10
8
6
4
2
0
0
250
200
150
100
50
0
Comparison of Hs (m) at Point- 2
(b)
SWAN Forecasted
1 5 9 13 17 21 25 29
(d)
Number of observations
Comparison of Tp (s) at Point- 2
SWAN Forecasted
1 5 9 13 17 21 25 29
Number of observations
(f)
Comparison of (Deg.) at Point-2
SWAN Forecasted
1 5 9 13 17 21 25 29
Number of observations

60
Chapter 5
Data that is used for erosion investigation along the coast of Bangladesh is given in Appendix
5.6 and required wave data is presented in Appendix 5.7.
There are few formulas used to calculate the rate of erosion. Maximum orbital velocity at
bottom, can be calculated by SWAN and by using these formulas; the rate of erosion
is also possible to calculate.
(5.3)
Where is the bottom shear stress N/m 2 is the density of sea water 1,025 Kg/m 3 ; is the
wave friction factor, ranging from 0.077 to 0.30; is the maximum wave orbital velocity,
which is set to in SWAN (Shi et al., 2008).
(5.4)
(5.5)
Where is expressed as dry mass of material eroded per unit area per unit time Kg/m 2 s;
experimental/site-specific erosion constant, its value varies between 0.0002 Kg/Ns and
0.002 Kg/Ns; =Critical bed shear stress for erosion around 0.1 N/m 2 0.6 N/m 2 but it
should not exceed 1.0 N/m 2 (Pandoe and Edge, 2008). The formulas and other related constant
values that have been used to calculate the rate of erosion are tabulated below.
Table 5.5: The formulas and other required constant values that were used in SWAN
Formulas Range of Values Values that is used in SWAN
(Average value)
(SWAN manual)
(Shi et al., 2008)
(Barua et al., 1994)
Table 5.4 shows the values that were used in SWAN. The critical bed shear stress for erosion
along the coast of Bangladesh, value is less than the range (Table 5.5), because this value
is calculated by physical investigation along the coast of Bangladesh (Appendix 5.9) and
mentioned in the paper (Barua et al., 1994).
A simplified rate of erosion was calculated here as it just shows the rate of erosion in coastal
waters along the coast of Bangladesh. The calculated rate of erosion cannot explain the
sediment transport which is very important to explain the morphodynamics. Morphodynamics
can show the change in bottom topography and beach profile. Morphodynamics includes
bathymetry, hydrodynamics, sediment transport, and Bottom-level change (Molen et al.,
2004). Therefore, morphodynamics can show that eroding materials whether it will
transported or not. To explain the coastal shape and profile, a morphodynamics model should
be considered. The rate of erosion cannot explain all Morphodynamics processes as a result
cannot show changing beach profile.
The rate of erosion at different selected cross sections is compared to show the changes due to
different wind speed and direction. Investigation will be done for the current sea state and at a

Chapter 5
projected future considering the climate change (sea level rise). Three selected cross sections
along the coast of Bangladesh are depicted in Figure 5.5.
22°30'0"N
22°15'0"N
22°0'0"N
21°45'0"N
21°30'0"N
21°15'0"N
21°0'0"N
20°45'0"N
89°0'0"E
B
89°0'0"E
89°45'0"E
89°45'0"E
90°30'0"E
Bangladesh
90°30'0"E
91°15'0"E
Bay of Bengal
91°15'0"E
92°0'0"E
22°35'0"N
92°0'0"E
22°20'0"N
22°5'0"N
21°50'0"N
21°35'0"N
21°20'0"N
21°5'0"N
20°50'0"N
Figure 5.5: Cross sections that were considered for comparison and analysis of erosion
Figure 5.6 shows the bottom level along different selected cross sections along the coast of
Bangladesh. Figure 5.6(a) shows that the bottom level along cross section A-A is shallower
than the bottom level along the cross section B-B. Parts of cross section A-A are dry and wet
but the whole cross section B-B is wet. The maximum bottom level elevation (depth) along
the cross section A-A is about 13 m whereas along the cross section B-B, it is about 48 m.
The bottom level elevation initially fluctuated along the cross section B-B, after that it
increases gradually up to zero. Figure 5.6(b) shows the bottom level along the cross section C-
C. The maximum bottom level elevation along C-C is about 57 m. The bottom level gradually
increases after initial fluctuation.
Depth in m
Bottom Level in m
-5
-10
-15
-20
-25
-30
-35
-40
-45
A
-50
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0
-5
-10
-15
-20
-25
-30
-35
-40
-45
-50
-55
0
Bottom Level along the Coast of Bangladesh for the cross section A-A & B-B
Bottom Level along the Coast of Bangladesh for the cross section C-C
Figure 5.6: Bottom level (a) along cross section A-A and B-B; (b) along cross section C-C
61
C
C
A
B
Bottom Level along A-A
Bottom Level along B-B
-60
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude
(a)
(b)

62
Chapter 5
Bottom friction is an energy dissipater in JONSWAP spectrum. SWAN can calculate the
bottom friction by using Collins, Madsen or JONSWAP expression. In this thesis, JONSWAP
expression was used for bottom friction consideration. Figure 5.7(a) and 5.7(b) present the
rate of erosion due to 20 m/s southern wind along A-A and B-B at high tide by considering
three different bottom friction models (chapter 2). Both of the graphs show that Jonswap
model gives the highest rate of erosion whereas Madsen model gives the lowest rate of
erosion in comparison with the other two models (Jonswap and Collins). However,
JONSWAP model was used here for bottom friction calculation which provides the highest
rate of erosion. Figure 5.7 shows the rate of erosion along the coast of Bangladesh due to
Collins, Madsen, and JONSWAP expression separately.
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
0.25
0.2
0.15
0.1
0.05
0.35
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
0.3
0.25
0.2
0.15
0.1
0.05
Erosion Rate at High Tide for 20 m/s wind considering different friction formulas at the cross section A-A
(a)
Figure 5.7: Comparison of the rate of erosion using different bottom friction model along cross
section (a) A-A; (b) B-B
5.6.1 Erosion at the Current Sea States
Longitude
Erosion for Collins
Erosion for Jonswap
Erosion for Madsen
Erosion Rate at High Tide for 20 m/s wind considering different friction formulas at the cross section B-B
(b)
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Erosion for Collins
Erosion for Jonswap
Erosion for Madsen
5.6.1.1 Discussion on the Erosion Scenarios for the Current Sea States
Figure 5.8 depicts the erosion scenarios due to different winds in Bangladesh. Generally, the
rate of erosion increases with increasing steady wind fetches. All this investigations were
done at high tides. Figure 5.8(a) shows an erosion scenario for 5 m/s western wind. The rate
of erosion is very low over the coastal waters in Bangladesh due to 5 m/s western wind.
Erosion occurs at small regions with a maximum value of 0.55 Kg/m 2 s. Figure 5.8(b) shows

63
Chapter 5
an erosion scenario for 5 m/s southern wind. The erosion scenarios are similar to that of (a)
and there is no significant change in erosion scenarios due to the changing wind direction.
Figure 5.8(c) shows an erosion scenario for 10 m/s western wind. The scenario is still similar
to that of (a) and (b). However, erosion occurs at some small regions at maximum value of
0.70 Kg/m 2 s. The erosion scenario did not change even with changing wind direction and
occurred at similar maximum values (Figure 5.8(d)). It can therefore be concluded here that
the 5 m/s and 10 m/s wind speeds have no significant erosion effects along the coast of
Bangladesh despites its directional changes. For 15 m/s, 20 m/s and 30 m/s wind speeds,
investigations have been done only for southern wind because in autumn, monsoon and
summer mainly southern wind is dominant along the coast of Bangladesh (Appendix 5.2 and
Table 5.1). With southern wind speed of 15 m/s, significant erosion takes place along the
coast of Bangladesh at a maximum value of 0.80 Kg/m 2 s (Figure 5.8(e)). Erosion is mainly
taking place along the shoreline. Figure 5.8(f) shows an erosion scenario due to 20 m/s
southern wind. More areas are affected by erosion in compared to erosion at (e). The
scenarios show that erosion is taken place not only along the shoreline but also some areas
into the sea were also affected by erosion. The maximum value of rate of erosion due to 20
m/s southern wind is 1.60 Kg/m 2 s. Figure 5.8(g) shows an erosion scenario due to 30 m/s
southern wind. Large areas in coastal waters are affected by erosion with a maximum value of
(the rate of erosion) 1.80 Kg/m 2 s.

(a)
(d)
(g)
Chapter 5
(b)
(e)
Figure 5.8: Erosion scenarios along the coast of Bangladesh at high tides for (a) 5 m/s western wind; (b) 5 m/s southern wind; (c) 10 m/s western wind; (d) 10 m/s southern wind; (e) 15 m/s southern wind; (f) 20 m/s southern wind;
(g) 30 m/s southern wind
64
(c)
(f)

65
Chapter 5
5.6.1.2 Causes of Erosion in Coastal Waters
Dissipation means the loss of energy, and it is very important for the understanding the
erosion phenomena in coastal waters. Dissipation in coastal waters includes white-capping,
Bottom friction and Depth-induced breaking. Bottom friction is directly related to erosion and
depends on the wave orbital velocity near the bottom. Due to this wave orbital velocity near
bottom, shear stress at the bottom is developed. If this developed shear stress is higher than
the critical shear stress of the soil, then the soil will be eroded. Therefore, the higher the wave
orbital velocity nears the bottom, the higher the tendency of erosion. From the figures 5.9(a)
and 5.9(b), it is clear that wave orbital velocity without bottom friction is higher or at least
equal to the wave orbital velocity with bottom friction and bottom friction reduces the wave
orbital velocity. In this study, critical bed shear stress for erosion used was 0.07 N/m 2 (Table
5.5). By using this critical shear stress, the threshold velocity for erosion (formula in Table
5.5) can be calculated. The calculated threshold orbital velocity at bottom was 0.0269 m/s.
Therefore, if the wave orbital velocity with bottom friction (that means considering bottom
friction, white-capping and depth-induced breaking) is higher than 0.0269 m/s, erosion will
take place and vice versa. These graphs also indicate that cross section A-A is in coastal
waters thus affected by bottom friction. Figure 5.9(a) shows that the wave orbital velocity
with and without bottom friction due to 5 m/s wind speed is relatively small but wave orbital
velocity with bottom friction is still higher than the threshold velocity along A-A thus erosion
happens. The wave orbital velocity with bottom friction is comparatively high (Figure 5.9b)
for 30 m/s wind thus the rate of erosion along A-A is higher than that in 5 m/s wind speed.
Wave Orbital Velocity near the bottom in m/s
Wave Orbital Velocity near the bottom in m/s
Orbital velocity at High Tide for 5 m/s Southern Wind with and without bottom friction at the Cross section A-A
1.5
Cross Section A-A with bottom friction
Cross Section A-A without bottom friction
1
0.5
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Orbital velocity at High Tide for 30 m/s Southern Wind with and without bottom friction at the Cross section A-A
1.5
Cross Section A-A with bottom friction
Cross Section A-A without bottom friction
1
0.5
(a)
(b)
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Figure 5.9: Wave orbital velocity with and without bottom friction along A-A (a) for 5 m/s wind; (b)
for 30 m/s wind

66
Chapter 5
5.6.1.3 Analysis of erosions at different cross sections along the coast of Bangladesh
Figure 5.10 shows comparative erosion scenarios at high tide and low tide along the cross
sections A-A, B-B, and C-C. The trend of erosion along all cross sections is similar and this
means that the higher the wind speed the higher the rate of erosion. There is fluctuation in the
rate of erosion along different cross sections which is mainly due to fluctuation in water depth
along that cross section (Figure 5.6 shows the bottom level along A-A, B-B, and C-C). In
general, the rate of erosion along B-B is higher than that along A-A. From the longitude
89.75° E to 90.75° E, the rate of erosion along the cross section A-A is higher than that of
cross section B-B; this is mainly due to the water depth. The water depth suddenly increases
along B-B after 89.75° E and decreases again sharply. Thus this bottom level significantly
influences the erosion in the areas along B-B. Shallow coastal areas are continuously affected
by high tides and low tides but in the coastal waters where the water level is relatively higher,
those regions are not significantly influenced by high tides and low tides. Figure 5.10(a) and
5.10(d) show that the rate of erosion along A-A is influenced by high tide and low tide. The
maximum rate of erosion along A-A at low tides due to 30 m/s wind is about 0.2 Kg/m 2 s
whereas at high tides, the rate is about 0.25 Kg/m 2 s. That means cross section A-A is shallow
enough to be affected significantly by high tides and low tides. But there is no significant
change in the rate of erosion along B-B due to high and low tides because along B-B, the
water depth is sufficiently higher than that along A-A (Figure 5.10(b) and 5.10(e)). Along C-
C, initially the rate of erosion is high after that it decreases (water depth gradually decreases
along C-C) both at high tides and low tides (Figure 5.10(c) and 5.10(f)). The rate of erosion
due to 30 m/s wind speed is the highest while 5 m/s and 10 m/s wind speed shows very low
rate of erosion along A-A, B-B, and C-C. So, the higher the wind speed or the higher the
steady wind fetch, the higher the rate of erosion and vice versa. Along parts of the cross
section A-A, the rate of erosion is discontinuous because the water depths at those parts are
fluctuated and whole area is not under water (Figure 5.10(a) and 5.10(d)). For 15 m/s wind
speed, the rate of erosion increases sharply in comparison with 5 m/s and 10 m/s wind. That
means, wind speed 15 m/s or higher is sufficient enough to influence for erosion in the coastal
waters in Bangladesh. For 5 m/s and 10 m/s wind, wind direction cannot significantly
influence the rate of erosion along the coast of Bangladesh.

Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Erosion Rate at High Tide for different Wind along the Coast of Bangladesh along the cross section A-A
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
(a)
Erosion Rate at High Tide for different Wind along the Coast of Bangladesh along the cross section C-C
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
Erosion Rate at Low Tide for different Wind along the Coast of Bangladesh along the cross section B-B
(e)
(c)
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
67
Chapter 5
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Figure 5.10: Erosion at current state due to different wind, at high tides along (a) A-A; (b) B-B; (c) C-C; at Low tides along (d) A-A; (e) B-B; (f) C-C
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Erosion Rate at High Tide for different Wind along the Coast of Bangladesh along the cross section B-B
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
Erosion Rate at Low Tide for different Wind along the Coast of Bangladesh along the cross section A-A
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
(b)
(d)
Erosion Rate at Low Tide for different Wind along the Coast of Bangladesh along the cross section C-C
(f)
5 m/s,West wind
5 m/s,South wind
10 m/s,West wind
10 m/s,South wind
15 m/s,South wind
20 m/s,South wind
30 m/s,South wind
0
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude

5.6.2 Comparison of Erosion Considering Climate Change
68
Chapter 5
5.6.2.1 Comparison of Erosion at Current Sea State regarding Climate Change
Bangladesh has been identified as one of the most vulnerable countries to climate change by
the international community (DOE, 2006). This climate change may include change in
temperature, rainfall, and increase in sea level, salinity intrusion into country, etc. But for
erosion comparison, only sea level rise has been taken into consideration. There are different
studies for the sea level rise scenarios in Bangladesh. For this study, the projected scenarios of
the sea level rise in 2030 and 2050 due to climate change in Bangladesh by IPCC and NAPA
were considered. Only sea level rise was considered here whereas other values were
considered same as current state. Data that is used in SWAN for erosion calculation regarding
climate change is given in Appendix 5.10.
Figure 5.11 shows comparative erosion scenarios at current climate, and in 2030 and 2050
considering the climate change (sea level rise) along A-A, B-B, and C-C for different wind.
Figure 5.11(a) shows that there is no significant change in the rate of erosion due to sea level
rise along A-A in 2030 for different winds. Figure 5.11(b) and 5.11(c) also show that there is
no significant change in the rate of erosion along B-B and C-C respectively in 2030 for
different winds. In 2050, the rate of erosion along A-A, B-B, and C-C also show that there is
no significant change in comparison to the current rate of erosion due to same wind (5.11(d),
5.11(e), and 5.11(f)). There are eight lines in each graph but four lines are depicted. Depicted
four lines represent the rate of erosion regarding climate change in 2030 and 2050. The
current rate of erosion lines are not seen here. That means, the rate of erosion regarding
climate change is higher than that in current state for same wind but change is not significant
thus the lines overlap and change cannot be seen clearly in this scale. Therefore, it can be
concluded that the rate of erosion in coastal waters in Bangladesh in 2030 and 2050 is higher
than the current state but the change is not significant.
.

Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Erosion Rate at High Tide in 2030 Considering Climate Change along the Coast of Bangladesh along A-A
5 m/s, present southern wind
5 m/s, 2030 Southern wind
10 m/s, present southern wind
10 m/s, 2030 Southern wind
20 m/s, presen Southern wind
20 m/s, 2030 Southern wind
30 m/s, presen Southern wind
30 m/s, 2030 Southern wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
(a)
Erosion Rate at High Tide in 2030 Considering Climate Change along the Coast of Bangladesh along C-C
(c)
5 m/s, present southern wind
5 m/s, 2030 Southern wind
10 m/s, present southern wind
10 m/s, 2030 Southern wind
20 m/s, presen Southern wind
20 m/s, 2030 Southern wind
30 m/s, presen Southern wind
30 m/s, 2030 Southern wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
69
Chapter 5
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Figure 5.11: Comparison of the rate of erosion at current state and, in 2030 along (a) A-A; (b) B-B; (c) C-C; in 2050 along (d) A-A; (e) B-B; (f) C-C
Erosion in Kg/m 2 S
Erosion in Kg/m 2 S
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.4
0.3
0.2
0.1
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Erosion Rate at High Tide in 2030 Considering Climate Change along the Coast of Bangladesh along B-B
5 m/s, present southern wind
5 m/s, 2030 Southern wind
10 m/s, present southern wind
10 m/s, 2030 Southern wind
20 m/s, presen Southern wind
20 m/s, 2030 Southern wind
30 m/s, presen Southern wind
30 m/s, 2030 Southern wind
Erosion Rate at High Tide in 2050 Considering Climate Change along the Coast of Bangladesh along A-A
5 m/s, present southern wind
5 m/s, 2050 Southern wind
10 m/s, present southern wind
10 m/s, 2050 Southern wind
20 m/s, presen Southern wind
20 m/s, 2050 Southern wind
30 m/s, presen Southern wind
30 m/s, 2050 Southern wind
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
Erosion Rate at High Tide in 2050 Considering Climate Change along the Coast of Bangladesh along B-B
Erosion Rate at High Tide in 2050 Considering Climate Change along the Coast of Bangladesh along C-C
0.8
(e)
5 m/s, present southern wind
5 m/s, 2050 Southern wind
10 m/s, present southern wind
0.7 (f)
5 m/s, present southern wind
5 m/s, 2050 Southern wind
10 m/s, present southern wind
10 m/s, 2050 Southern wind
10 m/s, 2050 Southern wind
20 m/s, presen Southern wind 0.6
20 m/s, presen Southern wind
20 m/s, 2050 Southern wind
20 m/s, 2050 Southern wind
30 m/s, presen Southern wind
30 m/s, 2050 Southern wind
0.5
30 m/s, presen Southern wind
30 m/s, 2050 Southern wind
Erosion in Kg/m 2 S
(b)
(d)
0
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude

70
Chapter 5
5.6.2.2 Change in rate of Erosion due to Climate Change
Figure 5.12 shows the change in the rate of erosion due to sea level rise along A-A, B-B, and
C-C due to 30 m/s wind in 2030 and 2050 in compare to current states. Graphs are plotted in
small scale to see the change in the rate of erosion. Figure 5.12(a) show that the change in the
rate of erosion in 2030 and 2050 is positive. That means, the rate of erosion increases in 2030
and 2050 in comparison with the rate of erosion at current seas state along A-A and change in
2050 is higher than that in 2030. Figure 5.12(b) and 5.12(c) also show similar increasing trend
along B-B and C-C respectively. Although the change in the rate of erosion along different
cross section is less, there is increasing trend. Therefore, it can be concluded that the rate of
erosion will be increased due to sea level rise in coastal waters in Bangladesh but the
increased rate is not significant in 2030 and 2050.
Change in Erosion in Kg/m 2 S
Change in Erosion in Kg/m 2 S
Change in Erosion in Kg/m 2 S
0.05
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
Change in rate of Erosion at High Tide for 30 m/s Southern Wind along A-A
Change in rate of Erosion by 2030 along A-A
Change in rate of Erosion by 2050 along A-A
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0.05
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0.005
Change in rate of Erosion at High Tide for 30 m/s Southern Wind along B-B
Change in rate of Erosion by 2030 along B-B
Change in rate of Erosion by 2050 along B-B
0
89 89.25 89.5 89.75 90 90.25 90.5 90.75 91 91.25 91.5 91.75 92
Longitude
0.05
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
(a)
(b)
(c)
Change in rate of Erosion at High Tide for 30 m/s Southern Wind along C-C
Change in rate of Erosion by 2030 along C-C
Change in rate of Erosion by 2050 along C-C
0
20.75 20.9 21.05 21.2 21.35 21.5 21.65 21.8 21.95 22.1 22.25
Latitude
Figure 5.12: Change in erosion due to 30 m/s wind considering SLR along (a) A-A; (b) B-B; (c) C-C

71
Chapter 5
5.6.2.3 Effects of SLR on Erosion
From the discussion presented above, it is clear that the rate of erosion will increase due to sea
level rise in 2030 and 2050 in Bangladesh but the change is very low. However, the main
effect of SLR on erosion is clearly presented in Figure 5.13. Though the rate of erosion will
not change significantly, new areas in the coast will start to erode due to SLR- landward
coastal retreat (Figure 5.13). Thus, new areas will inundate and erode and the deposition of
erosion materials further into the sea will also take place. Therefore, sea will intrude the
coastal areas and the country land area will be reduced by a developing new beach profile.
Eroded material moves
further into sea with time
Figure 5.13: Simplified model of landward coastal retreat under SLR (modified from UNEP, 2010)

CHAPTER 6: ADAPTATION MEASURES FOR EXTREME
EVENTS MANAGEMENT
6.1 Adaptation and Management for Changing Climate
IPCC (2012) presents six approaches to adapt and manage the risk of disaster for a changing
climate. These approaches are reducing exposure, reducing vulnerability, transformation of
disaster management system, preparation, responding and recovering to climate change, risk
sharing and transfer, and increasing resilience to climate change. All of these approaches are
connected to each other. Exposure and vulnerability are key determinant to reduce the risk of
disasters and depend on economic, social, geographic, demographic, culture, institutional,
governance and environmental factors. Reducing exposure and vulnerability will significantly
reduce the risk of disaster for climate change. Transformation of disaster management system
includes altering rules, regulation, legislative, financial institutions, and technological or
biological systems to provide legal basis for climate change adaptation. Risk sharing and
transfer, which include insurance, micro-insurance, reinsurance at all levels, are important to
reduce vulnerability and thereby, increase resilience to climate extreme. Preparation and
respond especially at post-disaster to provide an opportunity for recovering by rebuilding
houses, reconstructing infrastructures, and rehabilitating livelihood at least as prior to disaster
will help to enhance resilience and sustainable development. Therefore, adaptation to climate
change is an integrated approach to reduce the climate risk in future (Figure 6.1).
Transfer
and Share
Risks
Prepare,
Respond,
and Recover
Reduce
Exposure
Approaches
Reduce
Vunerability
72
Increase
Resilience
to Changing
Risks
Transformation
Figure 6.1: The approaches to adapt and manage for climate change (IPCC, 2012)
UNDP (2005) divided adaptation measures into three groups. The first is sectoral which
means adaptations for sectors which may be affected by climate change e.g. in agriculture, for
example, due to less rainfall and higher evaporation, extension in irrigation is required. The
second is multi-sectoral which means the management of natural resources that cover sectors

73
Chapter 6
e.g. water resources management, river basin management. The third is cross-sectoral which
means measures can cover several sectors e.g. education and training, public awareness
campaigns, monitoring, observation and communication systems, climate research, and data
collection, etc.
6.2 Low Regret Adaptation in Bangladesh
Low regret adaptation is an option for managing the risks of climate extremes and disasters
which provides a benefit now and a range of projected climate scenarios. IPCC (2012) listed
few potential low regret measures e.g. early warning systems; risk communication between
decisionmakers and local citizens; sustainable land management; and ecosystem management
and restoration. Improvements to health surveillance, water supply, sanitation, and irrigation
and drainage system; climate proofing of infrastructure; development and enforcement of
building codes; and better education and awareness also mentioned as low regret measures.
Many of these adaptation provides co-benefits e.g. improvement in livelihoods, human well
being, and biodiversity conservation (IPCC, 2012).
Bangladesh is the worst victim to climate change. This is why; different adaptation measures
are already present here. Both hard infrastructures and soft policy measures jointed with
communal practices, sectoral, multi-sectoral, and cross-sectoral adaptation are in place in
Bangladesh as adaptation measures to extreme climate events. Hard infrastructures include
coastal embankments, foreshore afforestation, cyclone shelters, early warning systems, and
relief operations whereas soft measures include design standards for roads and agricultural
research and extension like the introduction of high-yielding varieties of crops. Due to the
implementation both of adaptation measures, the country has become more resilient in facing
hazards that can be evidenced by reducing number of fatalities due to recent disasters (WB,
2010c). Some of these measures are presented below:
Coastal embankments: In the early sixties and seventies, 123 polders (of which 49 are seafacing)
were constructed to protect the low-lying coastal areas of Bangladesh from tidal flood
and salinity intrusion to reduce the exposure. Although polders are an effective measure for
protection against storm surges and cyclones, breaking of embankments due to overtopping,
erosion, inadequate operation and maintenance are a common phenomenon (WB, 2010c).
Foreshore afforestation to protect sea-facing dikes: Foreshore afforestation is a cost-effective
technique to decrease the impacts of cyclonic storm surges by dissipating wave energy and
reducing hydraulic load on the embankments during storm surges. This is also an exposure
reducing approach. Recently 60 km of forest belts exist on the 49 sea-facing polders with a
total combined length of 957 km (WB, 2010c).
Cyclone shelters: Although cyclone shelters are currently very important to protect human
lives and livestock during cyclones, from the focus group interviews, it is clear that there are a
lot of limitations to use the cyclone shelters. These limitations mainly include the lack of
convenient facilities in the existing design; distance from the homestead; difficulties in
accessing the shelters; the unwillingness to leave livestock behind; deficiencies of userfriendly
facilities for women and people with disabilities; overcrowding; and lack of

74
Chapter 6
sanitation facilities (WB, 2010c). There are total 2133 cyclone shelters in the coastal districts
in Bangladesh (Shamsuddoha and Chowdhury, 2007). This is also an exposure reducing and
resilience increasing approach.
Early warning systems: Early warning and evacuation systems have played a vital role to save
lives during cyclones. The BMD tracks cyclones and issues a forewarning to indicate the time
and the areas that are likely to be affected by the cyclonic storm. FFWC is authorized to
forecast the flood over the country except coastal area. This information of flood or cyclone is
broadcast through newspapers, televisions, and through other media to stakeholders (Figure
6.2).
Radar
Observatio
ns (hourly
½ hourly
Cyclone
Preparedness
Program
(CPP)
Shipping
Authority
Satellite
imagery
from
SPARSS
O, Dhaka
(3 hourly)
Data from
35 field
observatio
ns
(hourly)
Bangladesh
Meteorological
Department
(BMD)
Storm Warning Center
T/P
Channels
Warning
International
exchange
stations
Message
from
RTH,
New
Delhi
(continuou
s)
Data from
BMD, 86
WL, 56
RF by
SSB
wireless,
mobile
Primary connection
Secondary connection
Radio
Bangladesh
Newspapers
Bangladesh
Television
(BTV)
Mobile
Company
Relief
control
National
Coordination
Center
All concern
Authority
Data from
India
(Central
Water
Commissi
on)
FFWC,
using
MIKE 11
Public
Forecast
for 24h,
48h, 72h
DAE
Satellite
images
from
NOAA
and IMD
Figure 6.2: Cyclone and Flood information flows in Bangladesh (modified from UNEP, 2010)

Chapter 6
Closure dam: Closure dam is very effective and frequently used technology for flood and
erosion protection in Bangladesh. Closure dams are hard engineered structures which main
function is to prevent coastal flooding. It is used to shorten the required length of defences
behind the barrier. Its construction cost is low because mainly local materials are mainly used
to construct closure dam in Bangladesh. Construction materials includes e.g. clay filled sacks
bamboo, reed rolls, stell beams, bricks and blocks, palm leaves, reed bundles, timber piles,
jute reed bundles, golpata leaves, etc (UNEP, 2010). This is another exposure reducing
approach. A picture of closure dam construction is given below (Figure 6.3).
Figure 6.3: Closure dam under construction at Jamuna river, Bangladesh (UNEP, 2010)
Grass plantation at the slope of polders: Vetiver grass is a type of grass that is planted along
the slope of polders to protect it from erosion. Vetiver grass is commonly found in different
districts of Bangladesh but it is not common in the coastal region including offshore islands.
Vetiver is commonly known over the country by different names like Binna or Binnaghas or
Khas-khas (common in most of the districts), Binnachoba (Manikgonj, Mymensing,
Kishoregonj, and greater Sylhet), Biana (Rajshahi, Chapainawabgonj), Chengamura or
Chengamuri (greater Noakhali and greater Comilla) and Bana, Bena, Bena-jhar, Binithoa
(southern districts). Vetiver has been integrated for vegetation model in Coastal Embankment
Rehabilitation Project (CERP) and it has been introduced in eighteen coastal polders over
eighty-seven kilometers of earthen embankment combined with other economic plants.
Vetiver has also been planted in different types of low-cost toe-protection trials with soilcement
mixture bags, pre caste concrete frames, zigzag beams, octagonal hollow blocks etc.
There are successful cases where the initial protection and watering could be ensured but
vertical growth of roots were shorter than expected in some places (Islam, 2003). Islam
(2003) has suggested that Vetiver plantation be started by early March with continuous one
month irrigation then followed by second stage by end of October with continuous one month
irrigation with sweet water to get the better plantation output. This is also to reduce the
exposure and increase the resilience. A picture of Vetiver grass is depicted in Figure 6.4.
75

Figure 6.4: Plantation of vetiver along polder (Islam, 2003)
76
Chapter 6
Decentralization of relief operations: Historical relief operations were centralized in Dhaka
which was far away from the actual impacts and affected location and population, resulting in
a long chain of command and delayed effective relief. Recently this system has improved by
decentralizing the operations. Pre-positioning of emergency relief materials like life-saving
drugs and medical supplies are playing an important role in quick response to save lives (WB,
2010c). This is a preparation, respond and recover approach for disaster management.
The NAPA suggested few urgent adaptation measures for Bangladesh to address adverse
effects of climate change including variability and extreme events based on existing coping
mechanisms and practices. These adaptation measures are for capacity building, awareness
rising, intervention, and research. Maximum of these suggested measures are Multi-sectoral
and cross sectoral (MOEF 2005).
6.3 Costs of Adaptation Measures to Tropical Cyclones and Storm Surges
WB (2010c) calculated adaptation cost by 2050 to cyclone in Bangladesh is presented below:
. Table 6.1: Adaptation cost to cyclone and storm surges by 2050 in Bangladesh (WB, 2010c)
Baseline scenario Additional risk due to Climate change scenario
(Existing risks) (1)
climate change (2)
total risk= (1) +(2)
Adaptation
option
Investment
cost (USD)
million
Annual
maintenance
cost (USD)
million
Investment
cost (USD)
million
Annual
maintenance
cost (USD)
million
Investment
cost (USD)
million
Annual
maintenance
cost (USD)
million
Polders 2,462 49 893 18 3,355 67
Afforestation 75 75
Cyclone
shelters
628 13 1,219 24 1,847 37
Resistant
housing
200 200
Early warning
system
39 8 39 8
Toatal 3,090 62 2,426 50 5,516 112

77
Chapter 6
Table 6.1 presents the cost of adaptation for different adaptation measures to climate change
for cyclone and storm surges in Bangladesh by 2050. Bangladesh has already invested in the
adaptation to the tropical cyclones and storm surges since 1960. This investment provides for
construction of embankments, cyclone shelters; coastal afforestation; and development of
early warning systems. Recently climate change e.g. sea level rise adds a new dimension
which needs addressing. Embankment and Polder’s height need to increase due to Sea level
rise. Cyclone shelters need frequent maintenance; Houses in the coastal areas need cyclone
resistance development; more areas in the coast need afforestation. Implementation of all
these require a lot of investment to adapt to climate change in Bangladesh. A lot of
development is necessary in the forecasting sector for reliable early warning and effective
dissemination. World Bank calculated that Bangladesh requires 5,516 million USD to adapt
the climate change scenario by 2050 and in addition 112 million USD as annual maintenance
cost (WB, 2010c).

CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS
7.1 Conclusions
From the cyclonic disaster history of Bangladesh, it is clear that at least 157 cyclones hit
Bangladesh and about two million people died along with massive economic damages
occurring due to cyclones and cyclone-induced storm surges during 1584-2009, which makes
Bangladesh the number one nation at risk of tropical cyclones. Climate change may intensify
this severity in future. Extreme events and disasters like irregular or excessive rainfall,
temperature extremes, and droughts are already observed in Bangladesh. Natural hazards may
not be stopped but they can be managed to reduce the risk. So, disaster risk reduction
approach like Hyogo Framework for Action is very important to take into account.
Achievements of Bangladesh to implement the disaster risk reduction programmes are
significant and Bangladesh achieved a score 3.53 out of 5 to implement HFA during 2009-
2011, which indicates that there is still some commitment and capacities to achieving disaster
risk reduction due to lack of resources and research. Research work is very important to know
the future scenarios of disasters and to develop a plan of action to manage the new risk
scenarios. Recently, a number of institutes and universities of Bangladesh have started climate
change and disaster risk reduction related education and research work but this is still
insufficient to manage the current and future risks.
Coastal erosion is another natural hazard suffered by the coastal population of Bangladesh.
This erosion phenomenon along the coast of Bangladesh is also investigated here with the
help of SWAN under a number of assumptions below:
There is no influence of currents
Wind condition is considered uniform over the computation grid
Water level over the computation grid is uniform
Only stationary mode has been carried out here
Structured grid has been used
The main reason for these assumptions is the lack of data. The study established the following
findings by erosion modeling:
In summer the maximum wind speed of daily wind average is the highest along the
coast of Bangladesh whereas in winter, it is the lowest.
In summer and monsoon, the wind is mainly blown from south but in winter, it is
opposite whereas in autumn, it is from different directions or calm.
Although the trend of forecasted significant wave height Hs and model output Hs is
similar, maximum model output value of Hs is lower than the forecasted Hs.
The rate of erosion is increased with the increasing wind speed or wind energy.
Critical bed shear stress for erosion along the coast of Bangladesh is relatively low
= 0.07 N/m 2 , since the usually used range is 0.1 N/m 2 to 0.6 N/m 2 .
The threshold wave orbital velocity near the bottom for erosion along the coast of
Bangladesh is 0.0269 m/s.
78

79
Chapter 7
For 5 m/s and 10 m/s wind speed, the rate of erosion is very low but for 15 m/s or
higher wind speeds, the rate of erosion increases dramatically.
The rate of erosion along a cross section at nearshore is significantly influenced by the
water depth along that cross section.
The rate of erosion in 2030 and 2050 considering climate change (SLR) is higher in
comparison with the current rate of erosion in the coastal waters in Bangladesh but the
increased rate is not significant. New areas in the country will be affected by erosion.
Generally, it can be concluded that SWAN can describe 2D effects along the coast of
Bangladesh satisfactorily even with the aforementioned assumptions. However, it can also be
derived from the study that SWAN gives the overall scenarios of erosion correctly but for
characterization of the beach profile due to erosion, detailed input data and sediment transport
model (morphodynamics model) are required.
7.2 Recommendations
Based on this study the following recommendations can be suggested:
Integration, cooperation, coordination and harmonization among different DRR
institutions in Bangladesh are very important to ensure the sustainability to manage
the future disaster risk in Bangladesh.
There is a significant overlap between DRR and CCA. So, to implement any DRR
activities, it needs to take into account the shifting risks associated with climate
change and ensure that DRR activities will not increase the medium or long term
vulnerability to climate change.
Pre-disaster approaches like door-to door awareness campaigns for capacity building,
early warning and dissemination systems, and research on forecasting natural disasters
will be focused and funds for those activities will be ensured whereas implementation
of relief and rehabilitation programmes with accountability must be ensured at postdisaster.
Recent bathymetry of higher resolution and unstructured grid should be used in
SWAN for better prediction of erosion.
For an improvement of the results, future research should try to consider the current
along the coast of Bangladesh and a variable wind field in the computational grid.
Morphodynamics’ model needs to consider getting the real profile along Bangladesh’s
coast.
For climate change analysis, long term authentic data is necessary which is absent in
this study. So, a digital system to collect the required data should be established.
Insurance for coastal population must be enforced. Special provision must be made for
women, children, the aged and disabled people.
Agricultural/development time schedule should be arranged in such a way that cyclone
period may be avoided.
Education and training is very important. Bangladesh is a democratic country and
local level election is normally held in every five years in which a lot of new officials

80
Chapter 7
are elected as local level public authority. Therefore, continuous training for public
sector is very important to ensure the sustainability of DRR and CCA programmes.

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Si.
No.
Year Month Date
Nature of the
phenomena
86
Wind
Speed
(km/h)
Storm
Surge
Height
(m)
Death
1 1584 200,000
Appendix
Damage
(US $
Million)
2 1585 Severe Cyclonic Storm
3 1789 20,000
4 1797 November Severe Cyclonic Storm
5 1822 May Severe Cyclonic Storm 40,000
6 1831 October Cyclonic Storm
7 1864 Severe Cyclonic Storm 100,000
8 1872 October Cyclonic Storm 270
9 1876 October 31 Super Cyclonic Storm 12-14
100,000-
400,000
10 1895 October Cyclonic Storm
11 1897 October 24
Severe Cyclonic Storm
with Hurricane
175,000
12 1898 May Cyclonic Storm
13 1901 November Cyclonic Storm
14 1904 November Cyclonic Storm 143
15 1909 October 16 Cyclonic Storm 698
16 1909 December Cyclonic Storm
17 1911 April Severe Cyclonic Storm 120,000
18 1912 Severe Cyclonic Storm 40,000
19 1913 October Cyclonic Storm 500
20 1917 May Severe Cyclonic Storm 70,000
21 1917 September 24 Cyclonic Storm 432
22 1919 September 20-25 Severe Cyclonic Storm 40,000
23 1922 April Cyclonic Storm
24 1923 May Cyclonic Storm
25 1926 May Cyclonic Storm 606
26 1941 May 26 Cyclonic Storm
7,000-
7,500
27 1942 October Severe Cyclonic Storm
28 1948 May 17-19 Cyclonic Storm 1,200
29 1950 November 15-20 Cyclonic Storm
30 1955 October Cyclonic Storm 1700 63
31 1958 May 16-19 Cyclonic Storm 870
32 1958 October 21-24 Severe Cyclonic Storm 89 2.0 12,000
33 1959 October 10 Cyclonic Storm 14,000
34 1960 May 25-29 Cyclonic Storm 3.2 106
35 1960 October 9-11
Severe Cyclonic Storm
with Hurricane
160-201 6.6
5149-
6,000
36 1960 October 30-31
Severe Cyclonic Storm
with Hurricane
161-210 4.5-8.8
8149-
15,000
37 1961 May 6-9
Severe Cyclonic Storm
with Hurricane
145-160 4.5-7.5
1,000-
11,468
38 1961 May 27-30
Severe Cyclonic Storm
with Hurricane
95-160 7.0-9.0 10,466
39 1962 October 26-30
Severe Cyclonic Storm
with Hurricane
200 5.8 50,000
40 1963 May 28-29
Severe Cyclonic Storm
with Hurricane
201-209 5.0-8.1
11520-
50,000
50
41 1963 June 5-8 Cyclonic Storm 3.1
42 1963 October 25-29 Cyclonic Storm 105 2.2
43 1964 April 11 Cyclonic Storm 196
44 1965 May 10-12
Severe Cyclonic Storm
with Hurricane
162 6.0
12,000-
19,279
58

45 1965 May 31 Severe Cyclonic Storm 6.0-7.1 12,000
46 1965 November 5 Severe Cyclonic Storm 160 3.5
47 1965 December 14-15
Severe Cyclonic Storm
with Hurricane
200-210 4.0-6.1
870-
1,000
48 1966 October 1
Severe Cyclonic Storm
with Hurricane
146 4.7-9.1 500-850
49 1966 October 27-31
Severe Cyclonic Storm
with Hurricane
120-145
6.7-
10.0
850
50 1966 December 12 Cyclonic Storm
51 1967 May 18 Cyclonic Storm 0.9
52 1967 October 9-11
Severe Cyclonic Storm
with Hurricane
160 3.0
53 1967 October 23-24
Severe Cyclonic Storm
with Hurricane
130 2.0-7.6 128
54 1968 April 14 Cyclonic Storm 850
55 1968 May 10 Cyclonic Storm
56 1969 April 14-17 Cyclonic Storm 75-922
57 1969 October 10-11 Cyclonic Storm 8.0 175
58 1970 May 5-7
Severe Cyclonic Storm
with Hurricane
148 5.0 18
59 1970 October 22-23
Severe Cyclonic Storm
with Hurricane
118-163 5.5 300
60 1970 November 12-13 Super Cyclonic Storm 222-241
5.6-
10.6
300,000-
500,000
61 1971 May 7-8 Cyclonic Storm 80 5.0-5.5 163
62 1971 September 28-30 Cyclonic Storm 5.0
63 1971 November 5-6 Severe Cyclonic Storm 105 5.5
64 1971 November 28-30 Severe Cyclonic Storm 110 1.0 11,000
65 1973 April 9 Cyclonic Storm 700
66 1973 April 12 Cyclonic Storm 200
67 1973 November 16-18
Severe Cyclonic Storm
with Hurricane
165 3.8
68 1973 December 6-9
Severe Cyclonic Storm
with Hurricane
118-122 4.5-6.2
183-
1,000
69 1974 August 13-15 Severe Cyclonic Storm 80-100 4.5-6.5
600-
2,500
70 1974 November 24-29
Severe Cyclonic Storm
with Hurricane
161 6.0 20-200
71 1975 May 9-12 Severe Cyclonic Storm 110 5
72 1975 June 5-7 Cyclonic Storm 4.0
73 1975 June 24-28
Severe Cyclonic Storm
with Hurricane
161 4.8
74 1975 November 8-12
Severe Cyclonic Storm
with Hurricane
143 3.1
75 1976 October 18-21 Severe Cyclonic Storm 105 5.0
76 1976 November 20 Severe Cyclonic Storm 111 3.1
77 1977 April 1 Severe Cyclonic Storm 600
78 1977 April 24 Severe Cyclonic Storm 13
79 1977 May 9-13 Severe Cyclonic Storm 113-122 1.3
80 1978 April 9 Severe Cyclonic Storm 1,000
81 1978 May 5 Cyclonic Storm 30
82 1978 October 1-3 Cyclonic Storm 74
83 1979 May 2 Cyclonic Storm 3
84 1979 August 17 Cyclonic Storm 50
85 1980 April Cyclonic Storm 11
86 1981 March 6 Cyclonic Storm 15
87 1981 December 10 Severe Cyclonic Storm 80-120 2 15
88 1983 March 21 Cyclonic Storm 6
89 1983 October 14-15
Severe Cyclonic Storm
with Hurricane
93-122 43-600
87
Appendix
63-86.40

88
Appendix
90 1983 November 9-13
Severe Cyclonic Storm
with Hurricane
122-136 2.5 67-300
91 1985 March 28 Cyclonic Storm 50
92 1985 May 24-25
Severe Cyclonic Storm
with Hurricane
154 5.0
4,264-
11,069
50
93 1985 July 5 Cyclonic Storm 27
94 1985 October 16 Cyclonic Storm 71
95 1986 March Cyclonic Storm 19
96 1986 April 4 Severe Cyclonic Storm 100
97 1986 September 26 Cyclonic Storm 40
98 1986 November 8-9 Severe Cyclonic Storm 110 25
99 1987 June 4 Cyclonic Storm 12
100 1988 May 23 Cyclonic Storm 28
101 1988 June 13 Cyclonic Storm 5
102 1988 October 19 Cyclonic Storm 31
103 1988 November 24-30
Severe Cyclonic Storm
with Hurricane
162 5.0
1,498-
9,590
310
104 1989 April 26 Severe Cyclonic Storm 800 16.2
105 1989 May 26 Cyclonic Storm 15
106 1990 October 7-8 Cyclonic Storm 2.0 370
107 1990 December 18-21 Severe Cyclonic Storm 115 250
108 1991 April 29 Super Cyclonic Storm 225-235 7.5
138,000-
150,000
1780-
3000
109 1991 June 2 Severe Cyclonic Storm 100-110 2.0
110 1992 January 31 Cyclonic Storm 7
111 1992 April 22 Cyclonic Storm 16
112 1993 January 9 Cyclonic Storm 50
113 1993 January 12 Cyclonic Storm 31
114 1993 February 19 Cyclonic Storm 8
115 1993 March 27 Severe Cyclonic Storm 300
116 1993 May 7 Cyclonic Storm 9
117 1993 May 9 Cyclonic Storm 15
118 1993 May 13 Cyclonic Storm 14
119 1993 May 17 Cyclonic Storm 25
120 1994 March 28 Cyclonic Storm 40
121 1994 April 2 Cyclonic Storm 20
122 1994 May 2
Severe Cyclonic Storm
with Hurricane
210 130-400
123 1994 May 18 Cyclonic Storm 15
124 1995 April 12 Cyclonic Storm 69
125 1995 May 15 Severe Cyclonic Storm 525
126 1995 November 21-25
Severe Cyclonic Storm
with Hurricane
210 172-650
127 1996 April 23 Cyclonic Storm 17
128 1996 May 8 Severe Cyclonic Storm 140
129 1996 May 13 Severe Cyclonic Storm 525
130 1996 July 27 Cyclonic Storm 60
131 1996 October 29 Cyclonic Storm 24
132 1997 March 23 Cyclonic Storm 11
133 1997 May 18-19 Super Cyclonic Storm 225 5.00 111-200
134 1997 August 27 Cyclonic Storm 100
135 1997 September 25-27
Severe Cyclonic Storm
with Hurricane
150 3.05 155-188
136 1998 March 23 Cyclonic Storm 28
137 1998 April 23 Cyclonic Storm 14
138 1998 May 16-20
Severe Cyclonic Storm
with Hurricane
150-165 2.5 12
139 1998 July 3 Cyclonic Storm 60
140 1998 November 19-25 Severe Cyclonic Storm 90 2.44 200

141 1999 April 7 Cyclonic Storm 7
142 1999 April 10 Cyclonic Storm 66
143 1999 May 7 Cyclonic Storm 3
144 1999 October 28 Cyclonic Storm
145 2000 October 28 Cyclonic Storm 83
146 2002 November 12 Cyclonic Storm 65-85 2.0
147 2003 April 21 Severe Cyclonic Storm 230
148 2004 April 18-19 Cyclonic Storm 15
149 2004 May 19 Cyclonic Storm 65-90 1.5
150 2005 March 20-23 Cyclonic Storm 83
151 2005 May 6-23 Severe Cyclonic Storm 80
152 2005 September 19-21 Cyclonic Storm
153 2007 June 8-17 Severe Cyclonic Storm 130
154 2007 November 15-17 Super Cyclonic Storm 223 6.0
3,363-
89
3,500
Appendix
155 2008 October 26 Cyclonic Storm 7
156 2009 April 17 Cyclonic Storm 5
157 2009 May 25 Cyclonic Storm 70-90 2.0 190-500 270
Appendix 3.1: Natural disasters (Cyclones/Storm Surges) in Bangladesh (Khan, 2012; SDC, 2010;
RRCAP, 2001; Karim and Mimura, 2008; Murty et al., 1986; Ali, 1999; Choudhury et al., 1997;
Shamsuddoha, 2008; BMD; Banglapedia; DMB)
3775

Appendix 3.2: Districts and Upazilas of Bangladesh’s coastal zone (MoEF, 2007)
90
Appendix
District
Area (km 2 Total
)
Exposed Interior Exposed
Upazilas
Interior
Bagerhat
3,959 2,679 1,280
Mongla, Saran Khola,
Morrelganj
Bagerhat Sadar, Chitalmari,
Fakirhat, Kachua, Mollahat
Rampal
Barguna 1,831 1,663 168
Amtali, Barguna Sadar
Patharghata, Bamna
Betagi
Agailjhara, Babuganj, Bakerganj,
Barisal
2,785 2,785
Bhola Sadar, Manpura,
Gaurnadi, Hizla, Mehendiganj,
Muladi, Wazirpur, Banari Para,
Barisal Sadar
Bhola
3,403 3,403
Lalmohan, Daulatkhan
Burhanuddin, Char
Fasson, Tazumuddin
Chandpur
1,704 1,704
Anowara, Banshkhali,
Chandpur Sadar, Faridganj,
Haimchar, Hajiganj, Kachua,
Matlab, Shahrasti
Chittagong port, Boalkhali, Chandanaish,
Double Mooring, Lohagara, Rangunia, Chandgaon,
Chittagong
5,283 2,413 2,870
Mirsharai, Pahartali,
Panchlaish, Sandwip,
Fatikchhari,
Hathazari, Patiya, Raozan,
Sitakunda, Patenga, Satkania, Bakalia, Karanaphuli,
Halisahar, Kotwali,
Boijid Bostami,
Chakaria, Cox’s Bazar
Kulshi
Cox's Bazar
2,492 2,492
Sadar, Kutubdia,
Ukhia,
Maheshkhali, Ramu,
Teknaf
Feni
928 235 693 Sonagazi
Chhagalnaiya, Feni Sadar,
Parshuram, Daganbhuiyan
Gopalganj
1,490 1,490
Gopalganj Sadar, Kotali Para,
Muksudpur, Kashiani,, Tungipara
Bagher Para, Chaugachha,
Jessore
2,567 2,567
Jhikargachha, Manirampur,
Abhaynagar, Keshabpur, Jessore
Sadar, Sharsha
Jhalokati
749 749
Jhalokati Sadar, Kanthalia,
Nalchity, Rajapur
Batiaghata, Daulatpur, Dumuria,
Khulna
4,394 2,767 1,627 Dacope, Koyra
Dighalia, Khalishpur, Khan Jahan
Ali, Khulna Sadar, Paikgachha,
Phultala, Rupsha, Sonadanga,
Terokhada
Lakshmipur
1,456 571 885 Ramgati
Lakshmipur Sadar, Raipur,
Ramganj
Narail
990 990
Lohagara, Narail Sadar, Kalia,
Narigati
Noakhali 3,601 2,885 716
Companiganj, Hatiya,
Noakhali Sadar
Chatkhil, Senbagh, Begumganj
Patuakhali
3,221 2,103 1,118
Dashmina, Rangabali,
Galachipa, Kala Para
Bauphal, Mirzaganj, Patuakhali
Sadar
Pirojpur
1,308 353 955 Mathbaria
Bhandaria, Kawkhali, Nazirpur,
Pirojpur Sadar, Nesarabad
(Swraupkati)
Satkhira
3,858 2,371 1,487 Assasuni, Shyamnagar
Debhata, Kalaroa, Kaliganj,
Satkhira Sadar, Tala
Shariatpur
1,182 1,182
Bhederganj, Damudya, Palong
Goshairhat, Naria, , Zanjira
Total 47,201 23,935 23,266

Year
No. Affected
District People
Crops
damaged
Fully
(Acre)
Crops
damaged
Partially
(Acre)
91
No. of
House
damage
Fully
No. of House
Damaged
(Partially)
No. of
Dead
People
Appendix
No. of Dead
Livestock,
Cattles and
Goats
1970 5 1100000 - 3350000 3350000 - 250000 470000
1985 9 167500 39500 86590 10095 7135 10 2020
1986 7 238600 17800 84837 1116 3446 12 1050
1988 21 1006536 2316042 1597780 788715 863837 9590 386766
1989 33 346087 38712 38629 12173 20008 573 2065
1990 39 1015866 171099 242897 75085 63562 132 5326
1991 33 121229 11760 8725 34791 20274 76 25
1991 19 13798275 133272 791621 819608 882750 138882 1061029
1994 2 422020 23986 57912 52057 17476 134 1296
1995 28 305953 2593 42644 22395 44664 91 1838
1996 2 81162 - 2431 15868 15976 545 4933
1997 10 3784916 254755 59788 290320 452886 127 7960
1997 12 2015669 16537 72662 51435 163352 78 3196
2007 30 8923259 743322 1730317 564967 957110 3363 1778507
2009 11 3928238 77486 245968 243191 370587 190 150131
Table 3.3 is continued
Year
No. Affected
District People
No. of
Damaged
Institution
(Fully)
No. of
Damaged
Institution
(Partially)
Road
Damaged
Fully
(Km)
Road
Damaged
Partially
(km)
No. of
Damaged
Bridge/
Culvert
Embankment
Damaged
1970 5 1100000 - - - - - -
1985 9 167500 - - 32 - 11 10
1986 7 238600 2 47 132 1
1988 21 1006536 2442 5444 515 976 39 18
1989 33 346087 74 166 - - - -
1990 39 1015866 233 461 - - - -
1991 33 121229 62 151 - - - -
1991 19 13798275 3865 5801 - 764 496 707
1994 2 422020 96 98 169 - 83 97
1995 28 305953 127 537 - - - -
1996 2 81162 85 64 - - - -
1997 10 3784916 1824 3000 174 1527 527 122
1997 12 2015669 2500 2256 218 2379 85 280
2007 30 8923259 4231 12723 1714 6361 1687 1875
2009 11 3928238 445 4588 2233 6621 157 1742.53
Appendix 3.3: Detailed damages by selected cyclones that hit Bangladesh recently (MoWCA, 2010;
DMB)

District Name
Area in
sq. km
Total
Households
92
Population
Appendix
Total Male Female Sex Ratio density
sq. km
BARISAL Division 13297 M*100/F
BARGUNA 1831 215842 892781 437413 455368 96 488
BARISAL 2785 513673 2324310 1137210 1187100 96 835
BHOLA 3403 372723 1776795 884069 892726 99 522
JHALOKATI 749 158139 682669 329147 353522 93 966
PATUAKHALI 3221 346462 1535854 753441 782413 96 477
PIROJPUR 1308 256002 1113257 548228 565029 97 871
CHITTAGONG
Division
33771
BANDARBAN 4479 80102 388335 203350 184985 110 87
BRAHMANBARIA 1927 538937 2840498 1366711 1473787 93 1510
CHANDPUR 1704 506521 2416018 1145831 1270187 90 1468
CHITTAGONG 5283 1532014 7616352 3838854 3777498 102 1442
COMILLA 3085 1053572 5387288 2575018 2812270 92 1712
COX'S BAZAR 2492 415954 2289990 1169604 1120386 104 919
FENI 928 277665 1437371 694128 743243 93 1451
KHAGRACHHARI 2700 133792 613917 313793 300124 105 223
LAKSHMIPUR 1456 365339 1729188 827780 901408 92 1200
NOAKHALI 3601 593918 3108083 1485169 1622914 92 843
RANGAMATI 6116 128496 595979 313076 282903 111 97
DHAKA Division 31120
DHAKA 1464 2786133 12043977 6555792 5488185 119 8229
FARIDPUR 2073 420174 1912969 942245 970724 97 932
GAZIPUR 1800 826458 3403912 1775310 1628602 109 1884
GOPALGANJ 1490 249872 1172415 577868 594547 97 798
JAMALPUR 2032 563367 2292674 1128724 1163950 97 1084
KISHOREGONJ 2689 627322 2911907 1432242 1479665 97 1083
MADARIPUR 1145 252149 1165952 574582 591370 97 1036
MANIKGANJ 1379 324794 1392867 676359 716508 94 1007
MUNSHIGANJ 955 313258 1445660 721552 724108 100 1439
MYMENSINGH 4363 1155436 5110272 2539124 2571148 99 1163
NARAYANGANJ 700 675652 2948217 1521438 1426779 107 4308
NARSINGDI 1141 477976 2224944 1102943 1122001 98 1934
NETRAKONA 2810 479146 2229642 1111306 1118336 99 798
RAJBARI 1119 238153 1049778 519999 529779 98 961
SHARIATPUR 1182 247880 1155824 559075 596749 94 984
SHERPUR 1364 341443 1358325 676388 681937 99 995
TANGAIL 3414 870102 3605083 1757370 1847713 95 1056
Appendix 3.4A: Population census in Bangladesh (BBS, 2011)

Area
in sq.
km
Total
Households
93
Population
Appendix
District Name
Total Male Female
Sex
Ratio
M*100/F
density
sq. km
KHULNA Division 22272
BAGERHAT 3959 354223 1476090 740138 735952 101 1027
CHUADANGA 1177 277464 1129015 564819 564196 100 962
JESSORE 2567 656413 2764547 1386293 1378254 101 1060
JHENAIDAH 1961 422332 1771304 886402 884902 100 902
KHULNA 4394 547347 2318527 1175686 1142841 103 1046
KUSHTIA 1601 477289 1946838 973518 973320 100 1210
MAGURA 1049 205902 918419 454739 463680 98 884
MEHERPUR 716 166312 655392 324634 330758 98 872
NARAIL 990 162607 721668 353527 368141 96 746
SATKHIRA 3858 469890 1985959 982777 1003182 98 1044
RAJSHAHI Division 18197
BOGRA 2920 867137 3400874 1708806 1692068 101 1173
JOYPURHAT 965 242556 913768 459284 454484 101 903
NAOGAON 3436 655801 2600157 1300227 1299930 100 757
NATORE 1896 423875 1706673 854183 852490 100 898
CHAPAI
NABABGANJ 1703 357982 1647521 810218 837303 97 968
PABNA 2372 590749 2523179 1262934 1260245 100 1062
RAJSHAHI 2407 633758 2595197 1309890 1285307 102 1070
SIRAJGANJ 2498 714971 3097489 1551368 1546121 100 1290
RANGPUR Division 16317
DINAJPUR 3438 715773 2990128 1508670 1481458 102 868
GAIBANDHA 2179 612283 2379255 1169127 1210128 97 1125
KURIGRAM 2296 508045 2069273 1010442 1058831 95 922
LALMONIRHAT 1241 290444 1256099 628799 627300 100 1007
NILPHAMARI 1580 421572 1834231 922964 911267 101 1186
PANCHAGARH 1405 228581 987644 496725 490919 101 703
RANGPUR 2368 720180 2881086 1443816 1437270 100 1200
THAKURGAON 1810 320786 1390042 701281 688761 102 780
SYLHET Division 12596
HABIGANJ 2637 393302 2089001 1025591 1063410 96 792
MAULVIBAZAR 2799 361177 1919062 944728 974334 97 686
SUNAMGANJ 3670 440332 2467968 1236106 1231862 100 659
SYLHET 3490 596081 3434188 1726965 1707223 101 995
Total 147570 32173630 144043697 72109796 71933901 100,2 976
Appendix 3.4B: Population census in Bangladesh (BBS, 2011)

94
Appendix
District Name
Area in
sq. km
Total Population
Households Total
% of population in the age group
0-4 5-9 10-14 65+ Disable%
BARGUNA 1831 215842 892781 9,9 12,4 11,5 6 2,10
BARISAL 2785 513673 2324310 9,8 12,9 13 5,8 1,30
BHOLA 3403 372723 1776795 12,1 15,2 13,4 4,8 1,50
JHALOKATI 749 158139 682669 9,3 12,5 13,1 6,6 1,90
PATUAKHALI 3221 346462 1535854 10,4 13,4 12,3 5,6 1,6
PIROJPUR 1308 256002 1113257 9,6 12,2 12,1 6,5 2,00
CHANDPUR 1704 506521 2416018 10,9 13,2 13 5,9 1,90
CHITTAGONG 5283 1532014 7616352 10 11,9 12 3,8 1,30
COX'S BAZAR 2492 415954 2289990 13,3 15,8 13,9 3,1 1,50
FENI 928 277665 1437371 10,6 12,4 12,7 5,4 1,30
LAKSHMIPUR 1456 365339 1729188 11,9 14,6 13 5,2 1,30
NOAKHALI 3601 593918 3108083 12,3 14,9 13,5 4,9 1,40
GOPALGANJ 1490 249872 1172415 10,7 13,7 12,8 5,5 1,40
SHARIATPUR 1182 247880 1155824 11,3 14,3 13,4 5,9 1,30
BAGERHAT 3959 354223 1476090 9 11,5 11,8 6,3 1,70
JESSORE 2567 656413 2764547 8,9 10,7 11 5,3 1,30
KHULNA 4394 547347 2318527 8,5 10,4 10,9 5,3 1,70
SATKHIRA 3858 469890 1985959 8,6 10,9 11 5,7 1,70
NARAIL 990 162607 721668 10,3 12,8 11,9 5,9 1,60
Total 47201 8242484 38517698
District Name
Area in
sq. km
Total Population
Households
Total
Literacy
%
Both
Type of Structure (%)
Semi-
Pucka Kutcha Jhupri
pucka
BARGUNA 1831 215842 892781 57,6 2 4,8 89,6 3,6
BARISAL 2785 513673 2324310 61,2 7,3 10,9 80 1,8
BHOLA 3403 372723 1776795 43,2 1,7 7,6 86,3 4,5
JHALOKATI 749 158139 682669 66,7 6,7 11,4 79,5 2,5
PATUAKHALI 3221 346462 1535854 54,1 2,6 5,7 86,6 5
PIROJPUR 1308 256002 1113257 64,9 4 8 86,2 1,8
CHANDPUR 1704 506521 2416018 56,8 7,3 8,8 83,3 0,6
CHITTAGONG 5283 1532014 7616352 58,9 25 20,6 48,3 6,1
COX'S BAZAR 2492 415954 2289990 39,3 6,2 11,6 68,9 13,3
FENI 928 277665 1437371 59,6 16,6 17,8 64,3 1,3
LAKSHMIPUR 1456 365339 1729188 49,4 7,6 7,4 82,6 2,4
NOAKHALI 3601 593918 3108083 51,3 7,6 7,6 80,6 4,2
GOPALGANJ 1490 249872 1172415 58,1 4 12,3 82,7 1
SHARIATPUR 1182 247880 1155824 47,3 2,8 8,4 87,7 1
BAGERHAT 3959 354223 1476090 59 5,1 11,8 78,3 4,8
JESSORE 2567 656413 2764547 56,5 16,4 33,6 44,9 5,2
KHULNA 4394 547347 2318527 60,1 18,3 23 56,6 2
SATKHIRA 3858 469890 1985959 52,1 14,3 28,5 55,8 1,4
NARAIL 990 162607 721668 61,3 6,4 24,3 68,3 1
Appendix 3.5: Population and household scenarios in the coastal area of Bangladesh (BBS, 2011)

95
Appendix
District Name
Total
Household
Population Number of Child Old Total
s Total 0-4 5-9 10-14 65+
BARGUNA 215842 892781 88385 110705 102670 53567 355327
BARISAL 513673 2324310 227782 299836 302160 134810 964589
BHOLA 372723 1776795 214992 270073 238091 85286 808442
JHALOKATI 158139 682669 63488 85334 89430 45056 283308
PATUAKHALI 346462 1535854 159729 205804 188910 86008 640451
PIROJPUR 256002 1113257 106873 135817 134704 72362 449756
CHANDPUR 506521 2416018 263346 318914 314082 142545 1038888
CHITTAGONG 1532014 7616352 761635 906346 913962 289421 2871365
COX'S BAZAR 415954 2289990 304569 361818 318309 70990 1055685
FENI 277665 1437371 152361 178234 182546 77618 590759
LAKSHMIPUR 365339 1729188 205773 252461 224794 89918 772947
NOAKHALI 593918 3108083 382294 463104 419591 152296 1417286
GOPALGANJ 249872 1172415 125448 160621 150069 64483 500621
SHARIATPUR 247880 1155824 130608 165283 154880 68194 518965
BAGERHAT 354223 1476090 132848 169750 174179 92994 569771
JESSORE 656413 2764547 246045 295807 304100 146521 992472
KHULNA 547347 2318527 197075 241127 252719 122882 813803
SATKHIRA 469890 1985959 170792 216470 218455 113200 718917
NARAIL 162607 721668 74332 92374 85878 42578 295162
Total 8242484 38517698 4008377 4929878 4769531 1950728 15658514
Child 35,6 Total Dependent 40,7 15658514
District Name
Total
Households
Population
Total
Literature Rate %
Male Female
Disable
People
Vulnerable
House %
No. of
Vuln.
House
BARGUNA 215842 892781 59,2 56,1 18748 93,2 201165
BARISAL 513673 2324310 61,9 60,6 30216 81,8 420185
BHOLA 372723 1776795 43,6 42,9 26652 90,8 338432
JHALOKATI 158139 682669 67,6 65,8 12971 82 129674
PATUAKHALI 346462 1535854 56,2 52 24574 91,6 317359
PIROJPUR 256002 1113257 65 64,7 22265 88 225282
CHANDPUR 506521 2416018 56,1 57,3 45904 83,9 424971
CHITTAGONG 1532014 7616352 61,1 56,7 99013 54,4 833416
COX'S BAZAR 415954 2289990 40,3 38,2 34350 82,2 341914
FENI 277665 1437371 61,1 58,3 18686 65,6 182148
LAKSHMIPUR 365339 1729188 48,9 49,8 22479 85 310538
NOAKHALI 593918 3108083 51,4 51,2 43513 84,8 503642
GOPALGANJ 249872 1172415 60,3 56 16414 83,7 209143
SHARIATPUR 247880 1155824 48 46,6 15026 88,7 219870
BAGERHAT 354223 1476090 60 58 25094 83,1 294359
JESSORE 656413 2764547 59,4 53,7 35939 50,1 328863
KHULNA 547347 2318527 64,3 55,9 39415 58,6 320745
SATKHIRA 469890 1985959 56,1 48,2 33761 57,2 268777
NARAIL 162607 721668 63,3 59,3 11547 69,3 112687
576566 Vulnerable 5983170
Total 8242484 38517698 Disable % 1,5 House 72,6%
Appendix 3.6: Population and households vulnerable to the natural hazards (BBS, 2011)

Tide Levels in May, 2012 at Cox's Bazar
96
Appendix
Day Time
Water
Level (m)
Day Time
Water
Level (m)
Day Time
Water
Level (m)
1 6:00 2,5 11 1:30 2,9 21 4:05 0,7
11:50 1,1 7:35 0,8 10:30 3,4
18:25 2,7 13:55 3,1 16:35 0,7
2 0:35 0,9 20:20 0,8 22:40 3,1
7:10 2,7 12 2:30 2,7 22 4:35 0,6
13:05 0,9 8:30 1 11:00 3,4
19:25 2,9 14:55 2,8 17:05 0,7
3 1:35 0,7 21:20 1 23:10 3,1
8:00 3,1 13 3:45 2,5 23 5:05 0,7
14:05 0,7 09:40 1,1 11:30 3,4
20:20 3,1 16:15 2,7 17:40 0,7
4 2:25 0,5 22:35 1 23:40 3,1
8:45 3,4 14 5:20 2,5 24 5:40 0,7
14:55 0,6 11:05 1,2 12:00 3,3
21:05 3,3 17:45 2,6 18:15 0,8
5 3:10 0,4 23:55 1 25 0:15 3
9:30 3,6 15 6:35 2,6 6:15 0,8
15:40 0,4 12:35 1,1 12:35 3,2
21:45 3,4 18:55 2,6 18:50 0,8
6 3:55 0,3 16 1:05 1 26 0:55 2,9
10:15 3,7 7:35 2,7 6:55 0,8
16:25 0,4 13:40 1,1 13:15 3,1
22:30 3,5 19:45 2,7 19:35 0,9
7 4:35 0,3 17 1:55 0,9 27 1:35 2,8
10:55 3,8 8:15 2,9 7:40 0,9
17:10 0,4 14:25 1 14:00 3
23:10 3,5 20:25 2,8 20:20 0,9
8 5:20 0,3 18 2:30 0,8 28 2:30 2,7
11:35 3,7 8:55 3,1 8:35 1
17:50 0,4 15:00 0,9 14:55 2,9
23:55 3,4 21:05 2,9 21:20 1
9 6:00 0,4 19 3:05 0,8 29 3:45 2,7
12:20 3,6 9:25 3,1 9:45 1,1
18:35 0,5 15:35 0,8 16:10 2,8
10 0:40 3,1 21:35 3 22:30 1
6:45 0,6 20 3:35 0,7 30 5:10 2,7
13:05 3,4 9:55 3,3 11:05 1,1
19:25 0,7 16:05 0,7 17:30 2,8
22:10 3,1 23:40 0,9
31 6:25 2,9
Maximum tide level in May 3,8 Model
Minimum tide level in May 0,3 Application
12:25 1
18:45 2,9
Tide Levels for first half of June, 2012 at Cox's Bazar (Data used for Model calibration by
interpolation, connected to Appendix 5.4 for water level data)
Day Time
Water
Level (m)
Day Time
Water
Level (m)
Day Time
Water
Level (m)
1 0:50 0,8 6 5:05 0,5 11 3:05 2,7
7:30 3,1 11:25 3,8 9:00 1,1
13:35 0,9 17:45 0,5 15:25 2,8
19:45 3,1 23:45 3,4 21:40 1
2 1:50 0,7 7 5:50 0,5 12 4:20 2,7
8:20 3,4 12:10 3,6 10:00 1,2
14:35 0,8 18:25 0,6 16:35 2,7
20:40 3,2 8 0:30 3,3 22:40 1,1
3 02:45 0,6 6:35 0,7 13 5:35 2,7

Water Level (m)
Water Level (m)
97
Appendix
09:10 3,6 12:50 3,5 11:15 1,3
15:25 0,6 19:10 0,7 17:50 2,6
21:30 3,4 9 1:15 3,1 23:50 1,1
4 3:35 0,5 7:20 0,8 14 6:45 2,7
9:55 3,7 13:40 3,3 12:40 1,2
16:15 0,5 19:55 0,8 18:55 2,7
22:15 3,4 10 2:10 2,9 15 0:55 1,1
5 4:20 0,5 8:05 1 7:40 2,9
10:40 3,8 14:30 3 13:45 1,2
17:00 0,5 20:45 0,9 19:50 2,7
23:00 3,4
4
3.5
3
2.5
2
1.5
1
0.5
0
4
3.5
3
2.5
2
1.5
1
0.5
0
Tide Level at Cox's Bazar in May, 2012
Time
Tide Level at Cox's Bazar in June (1st fort), 2012
Time
Appendix 5.1: Tide levels that have been considered in SWAN model

Country Side
GRID AREA
270° 90°
247.5°
225°
202.5°
180°
Sea Side
157.5°
135°
112.5°
Among these 9 directions, only seasonal dominant
direction has been taken into account. In summer,
monsoon and autumn, southern wind is dominant. For
winter additionally western wind has been also
considered to look the directional effect.
98
Wind blows
Mean
wind
from direction
(Degree)
N 0
NNE 22.5
NE 45
ENE 67.5
E 90
ESE 112.5
SE 135
SSE 157.5
S 180
SSW 202.5
SW 225
WSW 247.5
W 270
WNW 292.5
NW 315
NNW 337.5
CLM calm
Appendix
Season wise number of days of wind blowing from a wind direction
Winter Summer Monsoon Autumn
Wind
blows from
Days
Wind
blows from
Days
Wind
blows from
Days
Wind
blows from
Days
N 1157 N 132 N 21 N 469
NNE 199 NNE 31 NNE 8 NNE 144
NE 155 NE 36 NE 13 NE 155
ENE 29 ENE 12 ENE 4 ENE 27
E 66 E 91 E 223 E 139
ESE 14 ESE 20 ESE 38 ESE 21
SE 32 SE 107 SE 491 SE 67
SSE 17 SSE 89 SSE 439 SSE 60
S 280 S 2058 S 3140 S 241
SSW 51 SSW 246 SSW 285 SSW 60
SW 40 SW 175 SW 173 SW 32
WSW 38 WSW 110 WSW 73 WSW 28
W 308 W 415 W 171 W 145
WNW 122 WNW 70 WNW 15 WNW 54
NW 475 NW 210 NW 32 NW 226
NNW 427 NNW 138 NNW 18 NNW 153
CLM 558 CLM 108 CLM 224 CLM 663
Total 3968 4048 5368 2684
Appendix 5.2: Number of days of wind blowing from a direction along the coast of Bangladesh for
the period 2001-2011 (BMD)

Nearshore Forecasted
Data at (91.25, 21.00)
Point-1
Hs (m) Tp
(s)
Direction Hs
(m)
Model Results at
(91.25, 21.00) Point-1
Tp
(s)
Nearshore Forecasted
Data at (88.75, 21.00)
Point-2
Direction Hs (m) Tp
(s)
99
Direction Hs
(m)
Model Results at
(88.75, 21.00) Point-2
Tp
(s) Direction
2.2-2.9 9 202.5 1.96 9.23 200.76 2.3-3 9 202.5 1.98 9.23 195.56
2.2-2.8 9 202.5 1.96 9.23 198.86 2.3-2.9 9 202.5 1.99 9.23 192.44
2.2-2.9 9 202.5 2.02 9.23 197.38 2.3-3 9 202.5 2.05 9.23 191.23
2.2-2.8 9 202.5 1.95 9.23 195.4 2.3-2.9 9 202.5 2 9.23 188.3
Appendix
Conditi
on
Only
Buoy-1
CON.
Only
Buoy-2
CON.
2.2-2.9 9 202.5 2.02 9.23 197.38 2.3-3 9 202.5 2.06 9.23 191.23 Buoy-1
& 2
2.2-2.8 9 202.5 1.95 9.23 195.4 2.3-2.9 9 202.5 2 9.23 188.3 VAR.
Hs (m) Tp
(s)
Direction
Hs
(m)
Tp
(s)
Tp
Direction Hs (m)
(s)
Direction
Hs
(m)
Tp
(s)
Direction Buoy-1,
Without
2.2-2.9
2.2-2.8
9
9
202.5
202.5
1.99
2.01
9.23
9.23
201.7
200.5
2.3-3
2.3-2.9
9
9
202.5
202.5
2.03
2.04
9.23
9.23
196.1
193.17
Bottom
Friction.
Hs (m) Tp
(s)
Direction Hs
(m)
Tp
(s)
Direction Hs (m) Tp
(s)
Direction Hs
(m)
Tp
(s) Direction
2.2-2.9 9 202.5 2.01 9.23 200.73 2.3-3 9 202.5 2.03 9.23 194.23
10
Iteration
s, Acc=
98.97
2.2-2.9 9 202.5 1.9 9.23 199.56 2.3-3 9 202.5 1.94 9.23 196.06 With
Nesting
2.2-2.8 9 202.5 1.91 9.23 197.5 2.3-2.9 9 202.5 1.96 9.23 192.65
Appendix 5.3: The results of sensitivity analysis for different condition by using two boundary
conditions (Table 5.4)

No
Date and Time
Water
Level
(m)
Modeled
Wind
Wind
Speed
(m/s)
Dir.
(Naut.)
Nearshore Forecasted
Data at Point-1
Hs (m)
Tp
(s)
100
Dir.
(Naut.)
Offshore Forecasted
Data at Buoy-1
Hs
(m)
Tp
(s)
Dir.
(Naut.)
Appendix
Nearshore Forecasted
Data at Point-2
Hs (m)
Tp
(s)
Dir.
(Naut.)
1 08.06.12 06:00 0.80 2.84 157.50 2.1-2.7 9.00 202.50 1.95 9.20 212.00 2.2-2.8 9.00 202.50
2 08.06.12 12:00 3.30 3.86 146.25 2.0-2.6 9.00 202.50 1.90 9.10 208.00 2-2.6 9.00 202.50
3 08.06.12 18:00 1.00 6.95 213.75 2.0-2.6 9.00 202.50 1.81 9.00 208.00 1.9-2.5 9.00 202.50
4 09.06.12 00:00 2.90 7.97 202.50 1.9-2.4 9.00 202.50 1.91 9.30 210.00 1.9-2.5 9.00 202.50
5 09.06.12 06:00 1.10 2.06 146.25 1.8-2.3 9.00 202.50 1.84 9.10 210.00 1.9-2.4 9.00 180.00
6 09.06.12 12:00 2.95 5.15 180.00 1.8-2.3 9.00 202.50 1.67 8.90 210.00 1.8-2.4 9.00 202.50
7 09.06.12 18:00 1.20 5.53 191.25 1.8-2.3 9.00 202.50 1.61 8.70 210.00 1.8-2.3 9.00 202.50
8 10.06.12 00:00 2.45 6.95 180.00 1.7-2.2 9.00 202.50 1.68 8.80 212.00 1.8-2.3 9.00 202.50
9 10.06.12 06:00 1.50 6.31 168.75 1.6-2.1 8.00 202.50 1.95 9.00 215.00 1.8-2.3 9.00 202.50
10 10.06.12 12:00 2.30 7.47 157.50 1.6-2.1 8.00 202.50 2.03 9.00 215.00 1.7-2.2 9.00 202.50
11 10.06.12 18:00 2.00 6.69 202.50 1.6-2.1 9.00 202.50 1.81 8.70 216.00 2-2.5 9.00 202.50
12 11.06.12 00:00 1.90 7.21 180.00 1.7-2.2 9.00 202.50 1.70 8.50 217.00 2.1-2.7 9.00 202.50
13 11.06.12 06:00 2.00 6.31 168.75 1.8-2.3 8.00 202.50 1.73 8.50 215.00 1.9-2.5 9.00 202.50
14 11.06.12 12:00 1.90 8.10 157.50 1.7-2.2 8.00 202.50 1.84 8.90 210.00 1.8-2.3 9.00 202.50
15 11.06.12 18:00 2.10 7.08 157.50 1.7-2.2 8.00 202.50 1.85 9.00 206.00 1.8-2.3 9.00 202.50
16 12.06.12 00:00 1.48 8.75 146.25 1.8-2.3 9.00 202.50 1.79 9.10 203.00 1.9-2.5 9.00 180.00
17 12.06.12 06:00 2.35 6.69 157.50 1.9-2.5 9.00 202.50 1.51 9.70 189.00 1.9-2.5 10.00 180.00
18 12.06.12 12:00 1.45 5.80 157.50 1.9-2.5 9.00 202.50 1.95 9.20 199.00 1.8-2.4 10.00 180.00
19 12.06.12 18:00 2.50 6.18 146.25 2.1-2.7 9.00 202.50 1.84 9.00 196.00 1.8-2.3 10.00 180.00
20 13.06.12 00:00 1.25 7.08 168.75 2.2-2.8 9.00 202.50 2.04 9.90 193.00 1.8-2.3 15.00 202.50
21 13.06.12 06:00 2.65 6.05 168.75 2.2-2.9 9.00 202.50 2.77 9.90 200.00 1.8-2.3 14.00 202.50
22 13.06.12 12:00 1.35 4.50 213.75 2.3-3 9.00 202.50 3.22 9.70 205.00 1.9-2.5 14.00 202.50
23 13.06.12 18:00 2.60 9.00 225.00 2.5-3.3 10.00 202.50 3.24 9.60 210.00 2.4-3.1 11.00 180.00
24 14.06.12 00:00 1.15 10.04 225.00 2.8-3.7 10.00 202.50 3.20 9.50 211.00 3-3.9 10.00 180.00
25 14.06.12 06:00 2.60 9.65 225.00 3-3.9 9.00 202.50 3.11 9.30 213.00 3.1-4 10.00 180.00
26 14.06.12 12:00 1.30 9.78 236.25 3.1-4 9.00 202.50 2.77 9.10 211.00 3.1-4 10.00 180.00
27 15.06.12 00:00 1.15 10.68 213.75 2.8-3.6 8.00 202.50 2.72 9.00 212.00 3.1-4 8.00 202.50
28 15.06.12 06:00 2.55 9.78 225.00 2.8-3.6 8.00 202.50 2.74 8.80 214.00 3.1-4 9.00 202.50
29 15.06.12 12:00 1.40 10.04 213.75 2.8-3.6 8.00 202.50 2.67 8.60 215.00 2.9-3.7 9.00 202.50
30 15.06.12 18:00 2.50 10.80 225.00 2.7-3.5 8.00 202.50 2.54 8.70 217.00 2.8-3.6 9.00 202.50
Appendix 5.4: The data that is considered for the model calibration and comparison of the results at
point- 1 & 2

Nearshore Forecasted
Data at Point- 1
No Hs (m) Tp
(s)
Direction Hs (m)
Nearshore Model Result at
Point-1
Tp
(s)
Direction Hs (m)
101
Nearshore Forecasted Data at
Point- 2
Tp
(s)
Direction Hs (m)
Appendix
Nearshore Model Result at
Point- 2
Tp
(s)
Direction
1 2.1-2.7 9 202.50 1.78 9.23 201.84 2.2-2.8 9 202.50 1.72 9.23 189.85
2 2.0-2.6 9 202.50 1.7 9.23 194.96 2-2.6 9 202.50 1.74 9.23 187.81
3 2.0-2.6 9 202.50 1.88 9.23 202.86 1.9-2.5 9 202.50 1.96 9.23 197.91
4 1.9-2.4 9 202.50 2.16 9.23 202.62 1.9-2.5 9 202.50 2.17 9.23 196.15
5 1.8-2.3 9 202.50 1.71 9.23 203.43 1.9-2.4 9 180.00 1.66 9.23 189.83
6 1.8-2.3 9 202.50 1.65 9.23 195.65 1.8-2.4 9 202.50 1.69 9.23 189.44
7 1.8-2.3 9 202.50 1.63 8.38 196.85 1.8-2.3 9 202.50 1.67 8.38 190.99
8 1.7-2.2 9 202.50 1.79 8.38 191.11 1.8-2.3 9 202.50 1.83 9.23 185.58
9 1.6-2.1 8 202.50 1.87 9.23 192.93 1.8-2.3 9 202.50 1.93 9.23 186.87
10 1.6-2.1 8 202.50 2 9.23 185.54 1.7-2.2 9 202.50 2.03 9.23 179.81
11 1.6-2.1 9 202.50 1.81 8.38 202.65 2-2.5 9 202.50 1.82 8.38 197.96
12 1.7-2.2 9 202.50 1.8 8.38 194.63 2.1-2.7 9 202.50 1.81 8.38 188.57
13 1.8-2.3 8 202.50 1.72 8.38 191.35 1.9-2.5 9 202.50 1.77 8.38 184.53
14 1.7-2.2 8 202.50 1.95 9.23 177.5 1.8-2.3 9 202.50 2.03 9.23 170.58
15 1.7-2.2 8 202.50 1.91 9.23 185.3 1.8-2.3 9 202.50 1.97 9.23 177.86
16 1.8-2.3 9 202.50 2.12 9.23 168.67 1.9-2.5 9 180.00 2.19 9.23 164.26
17 1.9-2.5 9 202.50 1.83 9.23 180.2 1.9-2.5 10 180.00 1.9 9.23 172.02
18 1.9-2.5 9 202.50 1.85 9.23 188.56 1.8-2.4 10 180.00 1.93 9.23 181.05
19 2.1-2.7 9 202.50 1.82 9.23 183.21 1.8-2.3 10 180.00 1.88 9.23 176.3
20 2.2-2.8 9 202.50 2.12 10.2 185.74 1.8-2.3 15 202.50 2.23 10.2 177.53
21 2.2-2.9 9 202.50 2.4 10.2 190.83 1.8-2.3 14 202.50 2.5 10.2 183.08
22 2.3-3 9 202.50 2.56 10.2 194.75 1.9-2.5 14 202.50 2.64 10.2 186.66
23 2.5-3.3 10 202.50 2.82 10.2 205.27 2.4-3.1 11 180.00 2.86 10.2 200.38
24 2.8-3.7 10 202.50 2.91 9.23 207.95 3-3.9 10 180.00 2.96 9.23 203.01
25 3-3.9 9 202.50 2.81 9.23 209.75 3.1-4 10 180.00 2.8 9.23 203.53
26 3.1-4 9 202.50 2.63 9.23 216.26 3.1-4 10 180.00 2.61 9.23 210.52
27 2.8-3.6 8 202.50 2.79 8.38 205.09 3.1-4 8 202.50 2.82 8.38 202.52
28 2.8-3.6 8 202.50 2.54 8.38 211.01 3.1-4 9 202.50 2.53 9.23 206.57
29 2.8-3.6 8 202.50 2.5 7.61 205.97 2.9-3.7 9 202.50 2.55 7.61 202.13
30 2.7-3.5 8 202.50 2.68 7.61 216.25 2.8-3.6 9 202.50 2.61 8.38 210.7
Appendix 5.5: SWAN calibration results and forecasting data at point- 1& 2 for the period 08.06.12
06:00 to 15.06.12 18:00
Case Tide
Water Level
(m)
1
W=270
High Tide 3.8 5
2 S=180
3
W=270
Low Tide 0.3 5
4 S=180
5
W=270
High Tide 3.8 10
6 S=180
7
Low Tide 0.3 10
Modeled Wind Modeled Offshore Wave Climate
Wind (m/s) Direction Hs (m) Tp (s) Direction
W=270
2.17 9.1 208
2.17 9.1 208
2.94 9.05 213
2.94 9.05 213
8 S=180
9 High Tide 3.8 15 S=180 3.98 9.6 180
10 Low Tide 0.3 15 S=180 3.98 9.6 180
11 High Tide 3.8 20 S=180 5.95 11.75 180
12 Low Tide 0.3 20 S=180 5.95 11.75 180
13 High Tide 3.8 30 S=180 9.5 13.25 180
14 Low Tide 0.3 30 S=180 9.5 13.25 180
Appendix 5.6: The data which is used for model application at current satate

Wind
km/h
41
48
56
67
74
83
93
102
111
120
130
139
148
157
167
102
Appendix
Downloading Date: 08-06-2012 Time: 14:00 (Wave data for Model Application)
Wind Duration (Hours)
6 12 18 25 35 45 55 70 80 90 100 120 140
Property
1.74 2.38 2.74 3.05 3.35 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 height (m)
6 7 8 9 10 11 11.5 12 12.5 12.5 13 13 13 period (s)
80 185 296 463 741 1019 1296 1852 2222 2593 2871 3611 4352 fetch (km)
2.13 3.05 3.66 3.96 4.27 4.57 4.88 4.88 4.88 5.18 5.33 5.33 5.33 height (m)
6.6 8 9 10 11 12 13 13.5 14 14.5 15 15 15.5 period (s)
89 204 315 519 759 1111 1482 2037 2500 2871 3426 4167 4815 fetch (km)
2.29 3.66 4.27 4.88 5.49 6.1 6.1 6.71 6.71 6.71 7.01 7.01 7.01 height (m)
7.2 9 10 11 12 13 14 15 16 16 16.5 17 17.5 period (s)
94 232 389 556 926 1296 1667 2222 2778 3241 3704 4630 5556 fetch (km)
3.54 4.88 5.79 6.71 7.62 8.38 8.84 9.14 9.14 9.45 9.45 9.45 9.45 height (m)
8 10 11.5 13 14 15 16 17.2 18 18.5 19 19.5 20 period (s)
111 259 435 667 1000 1482 1852 2593 3148 3704 4260 5371 6297 fetch (km)
4.27 5.79 7.01 7.92 8.84 9.75 10.36 10.97 11.28 11.58 11.89 12.19 12.5 height (m)
8.8 11 12.5 14 15 16.2 17 19 19.5 20 21 21 22 period (s)
119 278 482 741 1093 1630 2222 2778 3334 4074 4630 5741 7038 fetch (km)
4.88 7.01 8.23 9.45 10.67 11.89 12.5 13.72 13.72 14.33 14.94 15.24 15.24 height (m)
9.3 12 13.5 15 16 18 18.5 20 21 22 22.5 23 24 period (s)
130 315 528 787 1167 1759 2315 2963 3704 4260 5000 6667 7593 fetch (km)
5.79 8.23 9.45 11.3 13.11 14.02 14.63 16.46 16.76 17.68 17.98 18.29 18.29 height (m)
10 12.5 14.5 16 17.5 19 21 22 23 23 24 25.5 26.5 period (s)
139 333 556 833 1296 1945 2500 3241 3889 4630 5371 7038 7871 fetch (km)
6.86 9.14 10.97 13.4 15.24 16.76 17.98 18.9 19.81 20.12 21.03 21.34 21.34 height (m)
11 13 15 17 19 21 22 23 24 25 26 27 28 period (s)
148 352 593 926 1408 2130 2685 3519 4260 4815 5741 7223 8519 fetch (km)
7.62 10.67 12.8 15.2 17.07 20.42 21.34 22.86 24.08 24.38 24.38 24.99 25.91 height (m)
11.5 14 16.5 18 20 22 23.5 25 26 28 28 30 30 period (s)
154 370 648 945 1482 2222 2778 3704 4537 5186 6019 7408 9260 fetch (km)
8.38 11.89 14.63 16.8 19.81 22.86 24.38 25.91 27.43 28.04 28.96 30.48 30.48 height (m)
12 15 17 19 21 22 25 26.5 28 28.5 30 31 33 period (s)
163 407 704 1037 1574 2315 2963 3889 4630 5463 6297 7778 9445 fetch (km)
9.14 13.11 16.76 18.9 21.64 24.99 27.43 29.87 30.48 31.7 33.22 35.05 36.27 height (m)
13 16 18 20 22 25 26 29 29.5 30.5 31 32.5 35 period (s)
169 435 732 1111 1630 2454 2963 4167 4815 5649 6667 8334 10371 fetch (km)
10.36 15.24 18.29 21.3 24.38 27.43 30.18 32 33.53 35.97 36.58 38.1 39.62 height (m)
14 17 19 21 23 25.5 27 29 31 32 33 34 36 period (s)
178 454 750 1148 1667 2593 3148 4260 5000 5834 7038 8890 11112 fetch (km)
11.28 16.46 19.81 22 25.91 30.48 32.61 36.27 36.88 40.54 41.45 42.67 42.67 height (m)
14.5 17.5 20 22 23.5 26.5 28 30 32 33 34 35 36.5 period (s)
185 472 787 1185 1806 2685 3334 4445 5278 6112 7223 9167 11297 fetch (km)
12.19 17.37 22.56 24.4 28.96 33.22 37.19 40.54 42.37 42.67 44.2 47.24 48.77 height (m)
15 18 21 22 25 27.5 30 32 33.5 35 35.5 37.5 39.5 period (s)
191 482 824 1259 1852 2778 3519 4630 5556 6482 7501 9353 12038 fetch (km)
13.72 19 24.38 28 32.61 36.58 39.62 42.67 44.81 47.24 50.29 51.82 57.91 height (m)
16 19 22 24 26.5 29 31.5 33 34.5 36.5 37 40 44 period (s)
204 500 852 1296 2037 2871 3704 4815 5741 6945 7871 9630 12594 fetch (km)
Appendix 5.7: Significant wave height and wave period for different wind speeds and
durations

103
Appendix
$*************HEADING****************************************
$
PROJECT 'swanbangladesh' '01'
$'Sensitivity analysis'
$'Hs=6.0 Tp=10 Wave angle=190 Wind=41.50m/s'
$
SET LEVEL=3.80 NOR=90.00 DEPMIN=0.05 MAXMES=200 MAXERR=1 _
GRAV=9.81 RHO=1025.00 INRHOG=1 HSRERR=0.10 NAUT
$
MODE STAT TWOD
$
COORD SPHERICAL
$
$ --|--------------------------------------------------------------|--
$ | This SWAN input file is part of the bench mark tests for |
$ | SWAN. |
$ --|--------------------------------------------------------------|--
$
$***********MODEL INPUT**************************************
$
CGRID REGULAR 83.00 18.00 0. 12.00 5.00 720 300 CIRCLE 36 0.05 1.00 31
$
INPGRID BOTTOM REGULAR 83.00 18.00 0. 720 300 0.016667 0.016667
READINP BOTTOM -1.0 'swanbangladesh.bot' 1 0 FREE
$
WIND VEL=15.00 DIR=180.00
$
BOUN SHAPE JONSWAP 3.30 PEAK DSPR DEGR
BOUN SIDE S CON PAR 3.98 9.60 180 30
$
GEN3
BREAK CONSTANT 1.00 0.73
FRICTION JONSWAP 0.067
TRIAD 0.1 2.20 0.2 0.01
$
NUM DIR cdd=0.50 SIGIM css=0.50
NUM ACCUR 0.02 0.02 0.02 98.50 15
$
$************ OUTPUT REQUESTS *************************
$File name CTA11 should be same otherwise it will not work
$
BLOCK 'COMPGRID' NOHEAD 'UBOT_1.mat' LAY-OUT 1 UBOT RTP HS XP YP DIR
$
CURVE 'CTA11' 88.75 18.00 10 88.75 21.00
SPEC 'CTA11' SPEC1D 'swanbangladesh01.spc'
TABLE 'CTA11' HEAD 'swanbangladesh01.tab' DIST HS RTP DIR DSPR DEP DISSIP WLEN UBOT
$
CURVE 'CTA12' 91.25 18.00 10 91.25 21.00
SPEC 'CTA12' SPEC1D 'swanbangladesh02.spc'
TABLE 'CTA12' HEAD 'swanbangladesh02.tab' DIST HS RTP DIR DSPR DEP DISSIP WLEN UBOT
$
CURVE 'CTA13' 89.00 18.00 12 89.00 21.60
SPEC 'CTA13' SPEC1D 'swanbangladesh03.spc'
TABLE 'CTA13' HEAD 'swanbangladesh03.tab' DIST HS RTP DIR DSPR DEP DISSIP WLEN UBOT
$
POINTS 'POINT1' 91.25 21.00 88.75 21.00
SPEC 'POINT1' SPEC1D 'swanbangladesh04.spc'
TABLE 'POINT1' HEAD 'swanbangladesh04.tbl' XP YP DIST DEPTH HS RTP TM01 WLENGTH DIR UBOT
$
TEST 0,0
COMPUTE
STOP
$
Appendix 5.8: A typical command file for SWAN computation

Critical bed shear stress
Dyne/cm^2 N/m^2
1 0.441 0.0441
2 0.464 0.0464
3 0.425 0.0425
4 0.531 0.0531
5 0.445 0.0445
6 0.957 0.0957
7 0.943 0.0943
8 0.784 0.0784
9 0.943 0.0943
10 0.942 0.0942
11 1.017 0.1017
12 1 0.1
13 0.478 0.0478
14 0.531 0.0531
15 0.911 0.0911
16 0.872 0.0872
17 0.982 0.0982
18 0.469 0.0469
19 0.95 0.095
20 0.432 0.0432
21 0.413 0.0413
22 0.561 0.0561
Average 0.704136364 0.070413636
104
Appendix
Appendix 5.9: Critical bed shear of soil along the coast of Bangladesh (Barua et al., 1994)
Sea Level Rise for Bangladesh (in cm)
Year
3rd IPCC
Upper Range
SMRC
NAPA
Scenario
2030 14 18 14 For the Calculation
2050 32 30 32 For the Calculation
2100 88 60 88
Case
Water
Level
(m)
Sea
Level
Rise (m)
Water Level Modeled
Offshore climate
Wind
after SLR Wind
Direction
Hs Tp Wave
(m) (m/s)
(m) (s) Direction
1 High Tide 3.8 0.14 3.94 5 S=180 2.17 9.1 208
2 High Tide 3.8 0.14 3.94 10 S=180 2.94 9.05 213
3 High Tide 3.8 0.14 3.94 20 S=180 5.95 11.75 180
4 High Tide 3.8 0.14 3.94 30 S=180 9.5 13.25 180
5 High Tide 3.8 0.32 4.12 5 S=180 2.17 9.1 208
6 High Tide 3.8 0.32 4.12 10 S=180 2.94 9.05 213
7 High Tide 3.8 0.32 4.12 20 S=180 5.95 11.75 180
8 High Tide 3.8 0.32 4.12 30 S=180 9.5 13.25 180
Sea Level
Rise Upto
2030
Sea Level
Rise Upto
2050
Appendix 5.10: Data has been used for the future projections along the coast of Bangladesh

LIST OF FILES IN CD
Serial Number Type of File
1 All Matlab plots including Individual mfile
2 SWAN input files for each Run Individually
3 Population Analysis in Bangladesh
4 All Gis Graphs
5 Full Master Thesis
6 Bathymetry Raw Data
7 Bathymetry plotting by Matlab
8 All required Wind and Wave Data
105
List of Files in CD

DECLARATION
106
DECLARATION
I, Mohammad Mahtab Hossain declare that I have written this Master’s Thesis independently.
No other that the given sources and resources were used. The quotations for the consulted
materials have been identified as such.
I declare that this research paper for my degree of Master of Water Resources and
Environmental Management, Faculty of Civil Engineering at Leibniz University Hannover,
Hereby submitted has not been submitted by me or anyone else for a degree to any recognized
institution. This is my own work and that material consulted have been properly
acknowledged.
Hannover, 13.09.2012 Signature: ............................................