The paper looks at the relationships between climate change, inequality and vulnerability relationship of
disadvantaged groups. It discusses climate change-related hazards, inequalities and research gap, it
determines the impacts of and vulnerability to climate change and it identifies some of the deficiencies in
the discussions on climate change and inequality as well. It also explores evidences of inequality in
human society, such as geographical, social, political and economic inequality and how they play role in
enhancing vulnerability of certain group of people. Moreover, it looks at existing coping mechanism and
provides overviews on potential adaptation measures. Finally, the paper looks at a case study of different
hazards and how these differently affected the vulnerable communities in different countries.
* The authors are affiliated with the Bangladesh Centre for Advanced Studies in Dhaka, Bangladesh.
Views and opinions expressed are those of the authors and do not necessarily reflect those of the United
Nations.
2
1. Introduction
According to Dossa et al. (2016), some groups and regions are more exposed to risks
associated with climate change, such as droughts and floods, than others. Though climate
change affects everyone, some people are more likely to be adversely impacted than others,
exacerbating pre-existing inequalities (Stern, 2007; Otzelberger, 2014; Velan and Mohanty,
2015). Such inequality is partly to blame for the reasons that some people are more adversely
affected by climatic events, such as flooding, droughts, or tropical storms, than others
(Otzelberger, 2014). Even when people and communities are exposed to similar climate
change-related events, they can be affected to different degrees in terms of losses and damage
to property and livelihoods; this is known as differential vulnerability (Oppenheimer et al.,
2014).
Thus, the rest of this chapter will look at the relationships between climate change, inequality
and vulnerability relationship of disadvantaged groups. The next section will discuss climate
change-related hazards, inequalities and research gap. It will determine the impacts of and
vulnerability to climate change. It will identify some of the deficiencies in the discussions on
climate change and inequality as well. Section three will explore evidences of inequality in
human society, such as geographical, social, political and economic inequality and how they
play role in enhancing vulnerability of certain group of people. Section four will look at
existing coping mechanism while Sections five provides overviews on potential adaptation
measures. Section six will look at a case study of different hazards and how these differently
affected the vulnerable communities in different countries.
2. Climate change and inequality – concepts and concerns
2.1. Climate change induced hazards- focusing flood, sea level rise and salinity
intrusion
There is close link between climate change and evolution of inequalities, which needs to be
assessed from different dimension (Aghion, 2015). The same report states that the
geographical dimension will influence the effects of climate change induced hazards
including temperature rise, flood and drought. The countries located close to equator may be
affected more by the changing condition than the northern countries such as Canada (Aghion,
2015). At the country level, many people living in the hard to reach and remote areas
including coastal region, haor1, baor
2, chars
3 and hilly are often disadvantaged and may be
more vulnerable to climate change impacts in Bangladesh (Ahmad, 2016). In addition, the
capacity to deal with climate change consequences also varies from countries to countries.
For example, most of the developed countries are well equipped with technologies while
1 Haors are bowl- shaped depressions of considerable aerial extent lying between natural levees of the rivers or
the high lands of the north eastern region of Bangladesh (Draft Master Plan of Haor Areas, 2012, GoB) 2 Baors are oxbow lakes, formed by dead arms of the river.
3 Char a tract of land surrounded by the waters of an ocean, sea, lake, or stream; it usually means, any accretion
in a river course or estuary.
3
many poor countries in Africa and Asia are extremely vulnerable to climate change but do
not really afford to obtain them. Aghion (2015) states “the world is thus faced with a
problem of deepening inequality where countries most affected by global warming are least
equipped to react.” Socioeconomic factors also play vital role for communities to deal with
climate change impacts in different countries. The education, skills and economic capacity
make people in rich countries much easier to adjust with changing circumstances of climate
but lack of education, skills and poverty keep the people in many developing countries in
danger of climate change. In fact, it is those who are marginalised, whether socially,
culturally, politically, economically or institutionally, who are most vulnerable to the impacts
of climate change (IPCC, 2014). This is because the ability of people to respond to the
impacts of climate change depends on their education and social and economic welfare
(Aghion, 2015). The flood, sea level rise and salinity intrusion caused by climate change will
further intensify the current inequalities.
2.2. Deficiencies of the discussion of the linkages between climate change and
inequality
According to Olsson et al. (2014), climate change research to date has not adequately
addressed the complex poverty dynamics. Most research only focuses on one or two aspects
(Olsson et al., 2014). In addition, crucial assumptions made in many economic models are not
well suited to capture poverty dynamics, making it difficult to accurately predict future
poverty levels (Olsson et al., 2014). It also mentions that conceptualization of poverty has
been widened in different dimension in last six decades. In fact, UNDP (1990) acknowledged
poverty as multidimensional issue, influenced by a number of factors including social,
economic, cultural and other drivers. Olsson et al., 2014 clearly states that “attention to
multidimensional deprivations—such as hunger; illiteracy; unclean drinking water; lack of
access to health, credit, or legal services; social exclusion; and disempowerment—have
shifted the analytical lens to the dynamics of poverty and its institutionalization within social
and political norms”. Moreover, studies looking at climatic effects on livelihoods and poverty
have focused on climate variability on an annual basis rather than long-term climatic trends,
leading to a lack of evidence of climate change impacts on livelihoods and poverty (Cramer
et al., 2014). Furthermore, the imbalances in power and inequalities that determine
differential vulnerabilities to climate change are largely ignored (Olsson et al., 2014). Despite
an increase in awareness of the links between climate change and gender, other social factors
such as race, class/caste, age and (disability are yet to have a sufficient literature base (Olsson
et al., 2014). Indeed, very little research has been conducted to increase knowledge and
understanding of the role of social factors apart from gender, such as those mentioned
previously in addition to religion, ethnicity and health status, in determining how people
respond to climatic shocks (Otzelberger, 2014).
4
3. Climate change, inequality and vulnerability nexus
3.1. Conceptualizing climate change, inequalities and vulnerability of
disadvantaged groups
The following conceptual framework encompasses some key climatic factors and multi-
dimensional inequalities that further enhance the vulnerability of the disadvantaged
population across the world. It depicts how the different types of inequalities play vital role to
catalyse the sensitivity to socially disadvantaged or socially excluded people on the ground
(please see Fig 1 for more details). Social inequality is one of the dimensions of inequality
that breaks down further into several other dimensions that need to be handled individually,
none being less important than the next. Each sub-dimension within can have telling
implications on the wellbeing of the society and the victims that fall under it. Below are given
these sub-dimensions.
During the Cyclone Sidr, that hit the Khulna-Barisal region of Bangladesh in 2007, about
3500 people who died, most were either elderly or young people; age ranges that have
difficulty in quick mobility (BCCSAP, 2009; BBS, 2012; MoDMR, 2010; BCAS, 2010). It
was reported that about 2 millions of families were affected by Cyclone Sidr. Nearly 1.5
millions of houses and crops of about 0.7 million ha were damaged (MODMR, 2010).
Cyclone Aila also affected millions of people in 2009 in the coast. In most of the cases, the
poor were the hardest victims in almost every affected district. The livelihoods of the poor
communities were extremely challenged. Over 60000 people had to migrate to explore jobs in
nearest urban areas or in other districts keeping the family members left behind (IA, 2009).
The women were affected more than men by climate change induced disasters as reported in
a number of studies. For example, cyclone 1991 in Bangladesh and heat wave in Europe in
2003 affected more women than men (Jonsson, 2011). Another report indicates that the
incidences of water borne diseases were higher for women than men (e.g. diarrhoea, skin
diseases, dysentery and so on) immediately after cyclone Aila hit (IA, 2009). Cyclone 1991
killed about 138,000 people in the coast, of which nearly 80% were women (DFID, 2011). In
Philippines, Typhoon Haiyan affected about 16 millions of people, of which 6 millions were
Children (EC, 2014). While experiences from Mali reveals that climate change would cause
higher risks for women by increasing workloads without increasing income (Djoudi and
Brockhaus, 2011). Furthermore, the elderly and the young are also susceptible to the
aftermaths of disasters, being more prone to disease outbreaks and trauma. Cyclones, floods,
intensive rainfall and other such violent and damaging disasters can have big implications on
infrastructure such as school buildings and roads and other forms of communication. In many
areas of the world, schools closing down during such disasters are a common phenomenon.
Since such disasters vary vastly from region to region, a drastic inequality exists in the realm
of education throughout the world. In Bangladesh, schools in the coastal regions have been
reported to be shut down for 6 to 12 months on end due to extensive damage to the buildings
and roads from cyclones and storm surges in many areas including Khulna (BCAS and
ICCCAD, 2014). This does not occur in most other regions of the country. Only in Sylhet and
Sirajganj are their instances of schools having to close down, but these were due to floods.
5
Socioeconomic groups, such as gender, class/caste, ethnicity, religion, sexuality, (dis) ability,
age, and health status play a role in determining vulnerability to the impacts of climate
change, as they contribute to the extent of marginalisation and consequent exposure to
climatic and even non-climatic hazards (Oppenheimer et al., 2014; Otzelberger, 2014).
Female-headed households, children, indigenous communities and people in informal
settlements are especially vulnerable due to multiple factors such as a lack of urban
infrastructure, governmental support and insecure land tenure (Olsson et al., 2014; Ahmad,
2016).
But there are also other vulnerable groups. Campbell et al. (2009) found that, in addition to
the single mothers and female-headed households with small children, in Vietnam, widows,
the disabled and the elderly are vulnerable to storms, floods and slow-onset events such as
drought and salinity intrusion. Even within the poorest communities in the world, there is
inequality: ethnicity, gender and age can play a role in access to resources that enable coping
with the impacts of climate change (Otzelberger, 2014).
Changes in ecosystem
services and loss of environmental resources
Alteration of freshwater
availability
Changes in fisheries, livestock, forestry and
agriculture productivity
Changes in frequency of
health disorders
Modify human productivity
Risks on economic incentives/benefits
Climate Change
Flood
Adaptation
Adaptation to reduce vulnerability and build resilience
Other Elementes
Salinity Intrusion
Sea Level rise
Women
Children
Elderly Group
Single Parent
Low income
Group
Disable People
Indigenous Group
Exposure
Multi-dimensional Inequality
Key Sensitivity Factors
Immediate adaptation to
reduce exposure
Institutions, policy,
programmes and projects
Fig.1.Conceptualframeworkonclimatechange,inequalityandvulnerabilitypathwaysofdisadvantagedgroups
Social inequality
Disadvantaged Groups
Sensitivity, inequality and vulnerability pathway of disadvantaged groups
Income inequality
Gender inequality
Geographic inequality
Political inequality
Cultural inequality
Disproportion
ate rate of vulnerability to hazards
Increased
mortality and mobidity
Least
prepared for resilience
Enhanced
insecurity on food
Increased freshwater
crisis
Vulnerability
ModifiedfromRabbanietal.,2013
6
3.2. Evidences on the adverse effects of climate change (including flooding, SLR
and salinity intrusion) especially on the assets of disadvantaged communities
Out of all the climate change impacts, sea level rise is among the ones that threaten to have
the greatest impacts, particularly along deltas; this is because it will increase the frequency,
duration and intensity of floods (Thuy and Anh, 2015). With rising global temperatures, sea
levels will continue to rise as a result of large-scale glacial melt and the collapsing of ice
sheets (Stern, 2007). Over the past 50 years, a trend has been noticed with regards to extreme
weather events: there has been an increase in the number of hot days and a decrease in the
number of cold ones (Cramer et al., 2014). Such changes are likely to impact both human
comfort and health as well as crops and natural ecosystems (Schneider et al., 2007). In areas
where precipitation does increase both in frequency and intensity, there is likely to be an
increase in the frequency of both flash floods and large-area floods; this is likely to be seen at
high latitudes and will be exacerbated by glacier and snowpack melt (Schneider et al., 2007).
According to Rabbani et al. (2010), about 0.83 million hectares (5.6 % of the total land) of
land in Bangladesh is affected by saline intrusion, which is decreasing crop yields. Poor
health, in the form of diarrhoea and dysentery also coincides with salinization of water and
soil. Such saltwater intrusion will increase with sea level rise. As seawater inundates coastal
areas, both coastal waters and groundwater aquifers ‘will become more saline and soil
salinity will increase’ (Hossain, 2011, p.268). This will adversely affect the health, assets and
common resources on which the community mostly depend.
3.2.1. Exposure
Sea level rise could also cause major flood damage for millions of poor people who live in
the low-lying coastal areas in South Asia, ‘along the coasts from Pakistan, India, Sri Lanka,
and Bangladesh through to Myanmar’ (Rabbani et al., 2010, p.20). IFAD (year not known)
(states “About 70% of South Asians live in rural area and account for about 75% of the poor,
who are the most impacted by climate change”. Millions of people are exposed to severe
flood in most of the South Asia countries including Bangladesh, Pakistan, India and Nepal.
The following table provides an overview of the economic and non-economic loss and
damages caused by severe flood in last ten years:
Country Location Death (no) Economic loss (USD) Month/Year
India Uttarkhand 6500 45 Billion June/2013
Pakistan Indus Basin 2000 43 Billion July 2010
Nepal Dadeldhura 98 294.4 Million June-
August/2010
Bangladesh 39 out of 64
districts
500 1.06 Billion June/2007
7
Source: Dewan, 2014
Flooding also poses a major threat to communities globally. Floodwater contaminates the
water, causing an increase in the prevalence of diseases such as diarrhoea and cholera
(Brouwer et al., 2007). The increases in flooding as a result of climate change will not only
damage infrastructure but also result in losses of life (Kasperson and Kasperson, 2001).
Flooding also threatens food security, as the floodwater destroys crops such as rice, cassava
and sugarcane and damages trees (Beckman et al., 2002). But flooding does not only threaten
food security through directly damaging crops. By disrupting transport and communication
systems as well as storage facilities, flooding has the potential to increase loss of food via
damage, thus adversely affecting food security indirectly (Parvin et al., 2015). Furthermore,
whilst coastal and riverine settlements are particularly exposed to the risk of flooding, ‘urban
flooding could be a problem anywhere that storm drains, water supply, and waste
management systems have inadequate capacity’ (IPCC, 2001, p.13).
As mentioned previously, small island states are particularly exposed to the impacts of
climate change, as they often comprise of large settlements along beaches and sand terraces
(Kasperson and Kasperson, 2001). Even a low level of sea level rise will lead to substantial
erosion and loss of land, in addition to increasing the risk of flooding, ‘salinization of
freshwater aquifers, and the loss of protective coral reefs and sand beaches, increasing
exposure to hurricanes and storm surges in the coastal zone where much biological diversity
and most of the population, agricultural land and capital assets are located’ (Pelling and Uitto,
2001, p.56). Yet Bangladesh is expected to be exposed to a 32cm rise in sea levels by 2050
(Ministry of Environment and Forest (MOEF), 2005). Such rises in sea levels are likely to
result in the inundation of low-lying coastal areas and increase the rate of coastal erosion,
adversely impacting agricultural activities, ecosystems and infrastructure (Rabbani et al.,
2015).
Those who are most exposed to the impacts of climate change are those who live along coasts
and floodplains (Dossa et al., 2016). Few and Tran (2010) found a clear connection between
exposure to climatic hazards and poverty – those households that lived in exposed areas had
low incomes. For example, in urban areas, the poor and marginalised often have no choice
but to settle along rivers or canals, which increases their exposure to the risks associated with
flooding or sea level rise (Adger, 2006; Oppenheimer et al., 2014). Indeed, Brouwer et al.
(2007) also found that those who live along floodplains tend to have lower income levels.
This is because such exposed lands are what is left for the poor and marginalised to settle on,
as wealthier households can afford to settle elsewhere. Low-lying coastal regions, such as the
Mekong River Delta in Vietnam, are incredibly exposed to the risk of flooding (Thuy and
Anh, 2015). But agricultural communities who dig canals for irrigation are also likely to
experience increased flood risks. Datta and de Jong (2002) found that, in India, irrigation
canals with poor drainage increased the likelihood that the area would experience
waterlogging.
8
Coastal areas are particularly exposed to saline intrusion. This is because, as mentioned
previously, sea level rise is likely to result in an increase in salinity of both freshwater and
soil. This is because salinity is often caused by seawater intrusion into coastal areas and rivers
(Chaitanya et al., 2014). Intrusion of seawater onto the land leaves much salt in the soils
(Rengasamy, 2006). Indeed, in low-lying coastal areas such as Bangladesh, saltwater is
‘already intruding into fresh water resources and reservoirs, increasing the soil and water
salinity levels’ (Rabbani et al., 2015, p.175). This salinization is most likely to affect arid and
semi-arid regions (Chaitanya et al., 2014), as they experience a lack of regular precipitation.
This, coupled with poor irrigation practices and evaporation of the water, result in the
accumulation of salt ions in the soil (Chaitanya et al., 2014). Indeed, more than 800 million
hectares of land across 100 countries are affected by salinity, most of which is in arid and
semi-arid areas (Chaitanya et al., 2014). It is those who depend on agriculture for their
livelihoods who are most likely to be affected, as such increases in salinity may adversely
affect the production of crops such as rice, but it can also improve the conditions for certain
aquacultural activities such as shrimp farming (Chaitanya et al., 2014;Thuy and Anh, 2015).
3.2.2. Susceptibility (disadvantaged groups)
As a result of social inequalities, as climate change impacts decrease, the ability of people to
cope, ‘the livelihoods, health and future prospects of men, women, boys and girls are affected
in different ways’ (Otzelberger, 2014, p.8). According to Rabbani et al. (2009), different
groups, such as men, women and children, experience potential risks (such as lack of food,
mortality, lack of access to safe drinking water) differently. This is supported by Kundzewicz
and Parry (2001, p.680), which states that ‘climate change impacts will be differently
distributed among different regions, generations, age classes, income groups, occupations and
genders’.
Perhaps the most obvious division when discussing climate change and inequality is the rich-
poor gap. At present, the world’s richest 80 people have as much as the poorest 3.5 billion
(Otzelberger, 2014). Yet it is the poorest, who lack the institutional, economic, scientific and
technical capacity to respond to climate change, who are threatened most by its effects
(Otzelberger, 2014; Velan and Mohanty, 2015). In other words, the impacts of climate
change are mostly affecting the poorest and most vulnerable in the world (Ahmad, 2016).
This is because Climate change vulnerability is determined in part by livelihood resilience
(such as access to assets), household wellbeing (e.g. health and nutritional status) and
governance (for example, power relations and social capital) (Campbell et al., 2009). The
poor lack those assets and resources that are essential for coping with the impacts of climate
change and depend on climate-sensitive resources for their livelihoods (Campbell et al.,
2009). As a result, climate change, by disproportionately affecting those who are already poor
and vulnerable, will increase pre-existing social and economic inequality across the world
(Cramer et al., 2014). This is partly because climate change will damage crops, infrastructure
and houses, destroying economic activities, and thus exacerbating poverty (Ahmad, 2016). In
this way, climate change is displacing an increasing number of people by destroying
9
homesteads and assets through flooding and by decreasing the productivity of agricultural
land, in the case of rural areas, through prolonged periods of drought and through increasing
salinity (Ahmad, 2016). With the increasing frequency of climate-induced disasters and the
consequent economic losses, which are doubling each decade, climate change ‘threatens to
reverse over 20 years of progress in reducing extreme poverty’ and inequality (Otzelberger,
2014, p.32).
Social structures, economic capacity, culture and prevalence of environmental disruptions all
play a role in determining the ability to adapt to climate change and, consequently,
vulnerability (Smit and Pilifosova, 2001). Those with ‘limited economic resources, low levels
of technology, poor information and skills, poor infrastructure, unstable or weak institutions,
and inequitable empowerment and access to resources have little capacity to adapt and are
highly vulnerable’ (Smit and Pilifosova, 2001, p.879). This is because the adaptive capacity
(the ability to adapt) is often determined by the socioeconomic, institutional, technological
and political conditions of the area (Smit and Pilifosova, 2001). Because rural people in
developing countries rely on agriculture and aquaculture for their livelihoods and food
security, and both agriculture and aquaculture depend on water, it is those people who are
most vulnerable to the impacts of climate change (Thuy and Anh, 2015). But this can be
broken down into two types of vulnerability: individual and collective vulnerability (Kelly
and Adger, 1999). Individual vulnerability is determined by resource access and income
diversity as well as social status within a community, whereas collective vulnerability is
based on institutional and market structures in addition to infrastructure (Kelly and Adger,
1999). Indeed, diversification of income can lead to greater inequality if opportunities are
only available to those individuals or households that are better-off (Neil Adger, 1999). This
points to Reardon and Taylor’s (1996) findings that income inequality increases in rural areas
where the poorer households lack access to off-farm activities. Furthermore, Few and Tran
(2010) found that those who rely on a particular livelihood (such as net fishing or agriculture)
will wade through floodwaters to continue their livelihood, are more at risk of injury or
waterborne disease, thereby making them more susceptible to health-related impacts.
Flooding can damage crops, thus resulting in food shortages. This is partly because
households, particularly in countries such as Bangladesh, have trouble storing food before
floods, thus reducing the amount of available food after flood events (Parvin et al., 2015).
Such food shortages would increase the risk of nutritional deficiency, which, in turn, would
reduce the ability of people to fight off disease, particularly in children (Dossa et al., 2016;
Few and Tran, 2010). When there are food shortages, women and girls are particularly
vulnerable because gender plays a role in household food distribution (Otzelberger, 2014).
Despite women producing the food, they are often disfavoured when it comes to the
allocation of that food (ADB, 2013). Indeed, Rabbani et al. (2009) found that women
consume less food and water during periods of flooding in order to ensure that the men and
children (particularly boys) have their fill. Furthermore, UNESCAP (2009) suggests that
women often choose to eat less so that the men and children have enough food to eat. This is
because of cultural norms that value men and boys higher than women and girls. Indeed,
limited access to education and employment opportunities weakens the bargaining position of
10
women and girls in the family (ADB, 2013). This, in turn, leads to ‘differential feeding and
caregiving practices favouring boys and men’ (ADB, 2013, p.ix). As a result, women and
children often face higher risks of malnutrition than men (Skinner, 2011). Furthermore,
Rabbani et al. (2009, p.244) argue that females are ‘the most vulnerable in both flood prone
and salinity prone areas’. They found that, during floods, 96% of children suffer from lack of
safe water, whereas 94% of males over the age of 18 suffer, but as many as 97% of women
suffer from the inadequate supply of safe water after floods. This is because women are
responsible for the domestic activities such as cleaning, washing, cooking and taking care of
the elderly and children, and during flood events women find it difficult to collect safe water.
3.2.3. Ability to cope and recover-existing coping mechanism of the disadvantaged
groups
Campbell et al. (2009) identified several key assets that help rural households cope with the
impacts of climate change, including: (i) access to labour; (ii) support through social
networks and relationships; (iii) ability to supplement or diversify income; and (iii) sufficient
savings to enable investment in agriculture. Indeed, large-scale access to credit and extension
services is important for being able to cope in the face of climate change (Campbell et al.,
2009). In developing countries, many poor people have trouble recovering from the impacts
of climate change (Stern, 2007). This is because of their low incomes and consequent
struggle to access loans, credit systems and insurance (Stern, 2007). Furthermore, farmers
often lack the training and education required to maximise the use of the resources available
and to facilitate access to extension services (UNESCAP, 2009). As Otzelberger (2014)
argues, because of the unlikelihood of these poorer households being able to access insurance
and social protection and their inability to mobilise assets to help recover from disasters, they
are less able to cope with the adverse effects of climate change. This inability to respond to
extreme weather and climatic events may move those from transient poverty into chronic
poverty and often there is more than one factor at play (Olsson et al., 2014). Those who are
socially or economically marginalised are particularly likely to become chronically poor
(Olsson et al., 2014). As a result, the ability to change and try new strategies is a crucial asset
in being able to cope with the impacts of climate change (Otzelberger, 2014). This ability
often depends on gender, as social norms often differentiate access for men and women to
financial products, services, technologies and business opportunities (Otzelberger, 2014).
This highlights the ‘gender gap in the distribution of assets, services and information
important for producing food and coping with shocks and stresses’ (Otzelberger, 2014, p.21).
In rural areas, because of gender discrimination, women often have less access to resources,
such as finances, education and land, than men do (Vincent et al., 2014). This, coupled with
exclusion from labour markets and decision-making processes, reduce the ability of women
to cope with the impacts of climate change (Vincent et al., 2014). Indeed, women struggle to
access extension and market services and are often excluded from the benefits of agricultural
research and information (ADB, 2013). They do not have the same access to credit, land,
climate information, agricultural inputs and technologies as men (Otzelberger, 2014).
11
Otzelberger (2014) found that women only hold 10%-20% of land titles and only 5% of
agricultural extension services target women. This is because access to credit and extension
services often depends on having secure land tenure, which is unusual for women (ADB,
2013). This access barrier faced by women reduces the amount of assets available to women,
further magnifying the gender gap (ADB, 2013). Indeed, the challenges women face in
gaining land ownership not only reduce their access to assets, but also reduces their ability to
have a voice (Mukherjee, 2009). However, women are generally able to access micro-credit
and can borrow money from relatives, neighbours and sometimes even from money-lenders,
though that usually comes with high interest rates (Campbell et al., 2009). Furthermore,
where women can access loans, these loans may be controlled by male relatives (ADB,
2013).
Income diversification also facilitates coping with the impacts of climate change. However,
only those households that are relatively better off can diversify their incomes, for example,
by ‘borrowing to invest in farm machinery which can then be leant to others’ (Campbell et
al., 2009, p.viii). Nielsen and Reenberg (2010, p.466) found that many villagers from their
study in Burkina Faso earned most of their money through ‘labour migration, working for
development projects, horticulture, small-scale commerce – especially by the women – and
selling livestock’. Beckman et al. (2002) found that many poor households in Vietnamese
villages engage in work as day labourers or engage in seasonal migration to work in other
provinces during times between crop harvests. Those households that were better off had a
greater diversity of income-generating activities such as engaging in animal husbandry and
generation of cash crops in addition to non-land-dependent activities such as trading
(Beckman et al., 2002). However, in general, rural women struggle to engage in activities to
diversify their incomes, as they lack the financial capital that comes from access to
productive land (Skinner, 2011). This is because women face restrictions when it comes to
land ownership (Skinner, 2011).
Beckman et al. (2002) suggest that many coping mechanisms are reliant on the availability of
land, but sometimes working the land is more difficult due to flooding decreasing the amount
of productive land available. Temporary migration is a common coping strategy, but it is
mostly only an option for men and those who already have some labour capital and resilience
(Campbell et al., 2009). This out-migration by men often increases the workload for the
women and also has emotional costs for the men, who would prefer to stay at home
(Campbell et al., 2009). Permanent migration or relocation is an option, however, to those
households that have a certain underlying asset base that enables them to afford to relocate
(Campbell et al., 2009). Furthermore, when the men are working away from home, the
agricultural workload burden increases for women, but without the resource (technical,
financial, social) access that the men would have (Skinner, 2011). Indeed, many of these ‘de
facto’ female-headed households with men working in urban areas struggle to ensure food
security without vital access to extension, technology, credit and financial services that are
available to men (Mukherjee, 2009). When individuals and households run out of all other
options, they often have no choice but to sell assets and land and migrate to other areas in
search of new livelihoods (Skinner, 2011). However, this is only a viable option to those
12
households that have a certain underlying asset base that enables them to afford to relocate
(Campbell et al., 2009).
4. Case Study on climate induced extreme events, inequalities
and vulnerabilities of disadvantaged communities
4.1. Flood in Bangladesh
Flood (riverine flood, flash flood and tidal flood) affects the people of Bangladesh almost
every year. The country is situated at the convergence of three big rivers; the Ganges, the
Brahmaputra and the Meghna (GBM). About 80 % of the country is low-ying and prone to
seasonal and annual inundation. Salehin et al., 2007 classified the flood events into three
categories-i. When 20 % of the country is inundated by overflow of the surrounding rivers, is
called as a normal flood year; ii. if 35% area is inundated, people often call it as a moderate
flood year, and iii. for more than 60% inundation, it is termed as severe or major flood year.
IPCC, 2002, WGII reports that nearly 26 % of the country may experience annual flooding
and an additional 42 % may be at risk of inundation with different intensity. While another
report states that an increase of 10% monsoon rainfall could cause additional overflow depth
by 18 to 22 % (Qureshi and Hobbie, 1994). The following table provides the differences in
loss and damages caused by flood events in different years in the country. Usually, the
disadvantaged groups including poor communities/farmers, women, children, indigenous and
physically challenged people are the main victims of loss and damages. It appears (Fig 2) that
these people are more vulnerable because of climate change as the inundation will be
intensified by 2080.
Table 1. Loss and damages of the major floods in different years in Bangladesh (Source
World Bank in Kausher, AHM. 2010)
Item 1988 1998 2004 2007
Inundated area of Bangladesh (%) 60 68 38 42
People affected (million) 45 31 36 14
Total Deaths 2300 1100 750 1110
Livestock killed (nos) 172,000 26,564 8,318 40,700
Crops damaged (fully/partially in
million ha)
2.12 1.7 1.3 2.1
Loss of rice production (million tons) 1.65 2.06 1.00 1.2
Road damaged (km) 13,000 15,927 27,970 31,533
13
No of houses partially/fully damaged
(million)
7.2 0.98 4.00 1.1
Total loss in USD (billion) 1.4 2.0 2.3 1.1
Fig. 1. Area of inundation during 1998 flood in Bangladesh (Source: Kausher, AHM. 2010)
14
Fig. 2. Potential area to be inundated because of climate change by 2080 (Source: Kausher,
AHM. 2010)
15
4.2. Exposure to flooding in Bangladesh
The population density along coastal zones and on floodplains in Bangladesh is among the
highest in the world (Werle et al., 2000). As a result, when the country experience major
flooding, people and livestock are killed and property is damage. Indeed, the cyclone in 1991,
which resulted in the deaths of about 138,000 people, revealed that ‘storms and tidal surges
affecting the flat coastal plains and low-lying islands can reach 6 to 7 m in height and
advance many kilometres inland at a rapid rate of about 2.5 m/s’ (Werle et al., 2000, p.149;
MODMR, 2010). This highlights the disastrous effects such storms can have on the rapidly
growing population in these areas. Indeed, as a result of Bangladesh’s flat terrain and the low
gradient of the rivers, a significant proportion of the country is affected by floods each year,
with much damage done to both lives and properties (Akter, 2004). These floods are a result
of the accumulation of rainfall over the entire river basin, rather than simply the rainfall that
occurs in Bangladesh alone (Guiteras et al., 2015).
Flooding in Bangladesh damages infrastructure and destroys crops. Indeed, 55 per cent of
households that were affected by the severe flood in 1998 lost an average of 16 per cent of
their total assets, and 47 per cent of households were subject to a 59 per cent loss in terms of
housing value as a result of flood damage (Ninno et al., 2001). However, these losses were
not distributed evenly. Those households who were exposed to higher levels of flooding
experienced greater losses and damage to their assets (Ninno et al., 2001). Brouwer et al.
(2006) added that flooding also results in losses of fish stock in ponds. These losses and
damages lead to increases in food insecurity and the prevalence of disease where there are
already high poverty and malnutrition rates (Buttenheim, 2006). Furthermore, changes in land
cover and the ways in which the land is used have reduced the ability of the flood plains to
absorb water, while structures such as embankments and levies, which are constructed to
reduce the risk of flooding in some areas, direct the water towards more vulnerable areas
(Buttenheim, 2006). Thus, the presence of an embankment or other means of keeping water
away from a homestead plays a role in determining exposure to flooding in Bangladesh.
4.3. Susceptibility to flooding in Bangladesh
Inadequate facilities and support systems both during and after floods in Bangladesh often
result in health problems and other hardships (Akter, 2004). Though both rich and poor alike
may lose assets as a result of flooding in Bangladesh, the poor are more adversely affected, as
they start with fewer assets (Ninno et al., 2001). For example, the vulnerability of the poor is
exacerbated, as they suffer from loss of assets in the form of material goods in addition to the
fear of losing their social networks (Akter, 2004). As the floodwaters destroy crops and
damage roads, food prices are likely to increase due to reduced access to food (Buttenheim,
2006). This will further exacerbate the food insecurity of the poor, as they struggle to afford
the higher prices. Furthermore, flooding can damage houses and other productive assets,
hindering livelihoods. Indeed, Buttenheim (2006) suggest that employment opportunities for
day labourers are significantly reduced after floods and there are higher levels of food
insecurity coupled with increases in the prevalence of diarrhoeal and respiratory diseases.
16
This suggested reduction in employment of day labourers was supported by Brouwer et al.’s
(2006) findings that there were income losses from both trade and day labourers during flood
events. Such decreases in crop production in addition to asset losses and reductions in
employment opportunities as a result of flooding in Bangladesh all exacerbate food insecurity
issues (Ninno et al., 2001). Furthermore, Ninno et al. (2001) found that both agricultural and
non-agricultural economies in addition to transport systems continued to be affected by the
1998 floods for several months after the floodwaters receded. This would leave households
even more vulnerable to additional floods.
Women are perhaps among those who are most affected by floods, as they bear the burden of
‘the disruption of normal livelihood in terms of collection of safe water, sanitation, preparing
and distributing whatever food they could manage among family members (keeping little for
themselves and keeping the family together’ (Akter, 2004, p.6). The difficulties surrounding
collection of safe water during flood events come from the contamination of the water
sources, which result in a scarcity of safe drinking water (Akter, 2004). In cases such as
these, women sometimes need to travel much greater distances to fetch water from
undamaged tubewells and, when no such water can be found or people do not have the know-
how nor the ability to treat the water, dirty water is drunk (Ninno et al., 2001).
4.4. Ability to cope and recover from flooding in Bangladesh
Flood events exacerbate the erosion of riverbanks, which results in the displacement of more
than 20,000 Bangladeshi families each year (Akter, 2004). This often pushes them into a
cycle of chronic poverty, from which they struggle to recover. Though many people can
borrow money in order to survive, they often struggle to repay it. Indeed, in order to cope
with the aftermath of floods, households often enter into debt or buy food on credit and many
depend on the availability of food aid and cash transfers from NGOs and the government
(Buttenheim, 2006). Ninno et al. (2001) found that households tend to cope with floods by
trying to reduce their spending in addition to selling assets, though borrowing was the most
common coping mechanism. They found that richer households borrowed more than the
poorer households. However, this was likely because the wealthier households tend to have
greater access to credit and borrow large amounts of money for agricultural and business
purposes, whereas poorer households borrow primarily to enable them to purchase food.
In order to cope with the increases in food insecurity as a result of lower crop yield, asset
losses and the lack of employment opportunities that come from flood events, households
tend to alter their food consumption, be it reductions in the number of meals and/or the
variety of foods that are eaten (Ninno et al., 2001). Furthermore, Ninno et al. (2001) suggest
that in extreme cases of food scarcity, household food distribution may discriminate against
some household members (primarily women as discussed previously in this paper) in order to
ensure that others survive. In addition, there are occasions where flooding in areas of
Bangladesh makes people’s homes unliveable to the point where they have to temporarily
move to a flood shelter (Ninno et al., 2001). However, these shelters are often unhygienic
17
with human waste out in the open (Akter, 2004). This increased the prevalence of illnesses,
particularly diarrhoeal ones, and the medical supplies available in the flood shelters were
found to be inadequate (Akter, 2004). Thus, climate change in Bangladesh adversely affects
those who are poorest and most exposed as well as women more than other socioeconomic
groups.
18
References
ADB (2013). Gender Equality and Food Security: Women’s Empowerment as a Tool against
Hunger. Mandaluyong City, Philippines: Asian Development Bank (ADB).
Adger, W.N. (2006). Vulnerability. Global Environmental Change. 16 (3). pp. 268–281.
Aghion, P. (2015). Action on Climate Change will Deepen Inequality Globally. Queries.
Ahmad, Q.K. (2016). Addressing poverty, inequality and climate change. The Daily Star. 4
February.
Akter, N. (2004). BRAC’s Experience on Flood Disaster Management. Dhaka: BRAC.
BBS (2012). Statistical Yearbook of Bangladesh 2012. Bangladesh Bureau of Statistics,
Ministry of Planning, the Government of Bangladesh.
BCAS (2010). Impacts of Cyclone Sidr on water supply and sanitation services in the
affected coastal districts in Bangladesh. A study report prepared by Bangladesh
Centre for Advanced Studies (BCAS). Dhaka, Bangladesh.
BCAS and ICCCAD (2015). Non-Economic Loss and Damage Caused by Climatic Stressors
in Selected Coastal Districts of Bangladesh. A study report prepared by Bangladesh Centre
for Advanced Studies and International Centre for Climate Change and Development. Dhaka,
Bangladesh.
BCCSAP (2009). Bangladesh Climate Change Strategy and Action Plan. Ministry of
Environment and Forests of the Government of Bangladesh. Dhaka, Bangladesh.
Beckman, M., Van An, L. and Bao, L.Q. (2002). Living with the Floods: Coping and
Adaptation Strategies of Households and Local Institutions in Central Vietnam.
Stockholm Environment Institute, SEI/REPSI Report Series No. 5. Stockholm.
Brouwer, R., Aftab, S., Brander, L. and Haque, E. (2006). Economic valuation of flood risk
exposure and flood control in a severely flood prone developing country. Poverty
Reduction and Environmental Management (PREM) Working Paper PREM06/02.
Amsterdam.
Brouwer, R., Akter, S., Brander, L. and Haque, E. (2007). Socioeconomic vulnerability and
adaptation to environmental risk: A case study of climate change and flooding in
Bangladesh. Risk Analysis. 27 (2). pp. 313–326.
Buttenheim, A.M. (2006). Flood Exposure and Child Health in Bangladesh. California
Center for Population Research On-Line Working Paper Series CCPR-022-06. Los
Angeles.
Campbell, B., Mitchell, S. and Blackett, M. (2009). Responding to Climate Change in Viet
Nam: Opportunities for improving gender equality. A Policy Discussion Paper, Oxfam
and UN-Viet Nam. Ha Noi, Vietnam.
19
Chaitanya, K., Krishna, C.R., Ramana, G.V. and Beebi, S.K. (2014). Salinity Stress and
Sustainable Agriculture - A Review. Agricultural Reviews. 35 (1). pp. 34–41.
Cramer, W., Yohe, G.W., Auffhammer, M., Huggel, C., Molau, U., da Silva Dias, M.A.F.,
Solow, A., Stone, D.A. and Tibig, L. (2014). Detection and Attribution of Observed
Impacts. In: C. B. Field, V. R. Barros, D. J. Dokken, K. J. Mach, M. D. Mastrandrea, T.
E. Bilir, M. Chatterjee, K. L. Ebi, Y. O. Estrada, R. C. Genova, B. Girma, E. S. Kissel,
A. N. Levy, S. MacCracken, P. R. Mastrandrea, & L. L. White (eds.). Climate Change
2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects.
Contribution of Working Group II to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New
York, NY, USA: Cambridge University Press, pp. 979–1037.
Datta, K.K. and de Jong, C. (2002). Adverse effect of waterlogging and soil salinity on crop
and land productivity in northwest region of Haryana, India. Agricultural Water
Management. 57 (3). pp. 223–238.
Dewan, T.H. (2014. Societal impacts and vulnerability tofloods in Bangladesh and Nepal.
Weather and Climate Extremes 7 (2015) 36-42.
DFID (2011). Defining Disaster Resilience: A DFID approach paper. Department for
International Development. United Kingdom.
Djoudi, H and Brockhaus, M. (2011). Is adaptation to climate change gender neutral?
Lessons from communities dependent on livestock and forests in northern Mali.
International Forestry Review Vol.13(2), 2011
Dossa, A., Omstedt, M., Olmsted, P., Iaci, N., Zareyan, S. and McKenzie, S. (2016).
Inequality Explained: 7 ways climate change and inequality are connected.
OpenCanada.
EC (2014). ECHO fact sheet-Typhoon Haiyan. European Commission, Humanitarian Aid
and Civil Protection.
Few, R. and Tran, P.G. (2010). Climatic hazards, health risk and response in Vietnam: Case
studies on social dimensions of vulnerability. Global Environmental Change. 20 (3). pp.
529–538.
Guiteras, B.R., Jina, A. and Mobarak, A.M. (2015). Satellites, Self-reports, and Submersion:
Exposure to Floods in Bangladesh. American Economic Review. 105 (5). pp. 232–236.
Hossain, M.A. (2011). Global Warming induced Sea Level Rise on Soil, Land and Crop
Production Loss in Bangladesh. Journal of Agricultural Science and Technology. B1.
pp. 266–271.
Huq, S. and Rabbani, G. (2011). Climate change and Bangladesh: policy and institutional
development to reduce vulnerability. Journal of Bangladesh Studies. 13. pp. 1–10.
Huq, S. and Rabbani, M.G. (2015). Climate adaptation technologies in agriculture and water
supply and sanitation practice in the coastal region of Bangladesh. In: B. Glavovic, M.
Kelly, R. Kay, & A. Travers (eds.). Climate Change and the Coast: Building Resilient
Communities. Boca Raton, FL: CRC Press, Taylor & Francis Group, pp. 185–202.
20
IPCC (2014). Summary for Policy Makers. In: C. B. Field, V. R. Barros, D. J. Dokken, K. J.
Mach, M. D. Mastrandrea, T. E. Bilar, M. Chatterjee, K. L. Ebi, Y. O. Estrada, R. C.
Genova, B. Birma, E. S. Kissel, A. N. Levy, S. MacCracken, P. R. Mastrandrea, & L. L.
White (eds.). Climate Change 2014: Impacts, Adaptation and Vulnerability -
Contributions of the Working Group II to the Fifth Assessment Report. Cambridge, UK:
Cambridge Journals Online, pp. 1–32.
IPCC (2001). Summary for Policymakers. In: J. J. McCarthy, O. F. Canziani, N. A. Leary, D.
J. Dokken, & Kasey S. White (eds.). Climate Change 2001: Impacts, Adaptation and
Vulnerability. Contribution of Working Group II to the Third Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University
Press, pp. 1–18.
IA, (2009). In-depth Recovery Needs Assessment of Cyclone Aila Affected Areas.
International agencies (ActionAid, Concern Worldwide, DanChurchAid, MuslimAid,
Islamic Relief, Oxfam-GB and Save the Children-UK) currently involved in Aila
response programme funded by ECHO.
Jonsson, S. (2011). Virtue and vulnerability: Discourses on women, gender and climate
change. Global Environmental Change 21 (2011) 744–751.
Kasperson, R.E. and Kasperson, J.X. (2001). Climate Change , Vulnerability and Social
Justice. Risk and Vulnerability Programme, Stockholm Environment Institute (SEI).
Stockholme.
Kelly, P.M. and Adger, W.N. (1999). Assessing Vulnerability to Climate Change and
Facilitating Adaptation. Centre for Social and Economic Research on the Global
Environment (CSERGE) Working Paper GEC 99-07. Norwich.
Kundzewicz, Z.W. and Parry, M.L. (2001). Europe. In: J. J. McCarthy, O. F. Canziani, N. A.
Leary, D. J. Dokken, & K. S. White (eds.). Climate Change 2001: Impacts, Adaptation
and Vulnerability. Contribution of Working Group II to the Third Assessment Report of
the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge
University Press, pp. 641–692.
MoDMR (2010). National Plan for Disaster Management 2010-2015. Disaster
Management Bureau, Ministry of Disaster Management and Relief, Government of
Bangladesh.
MOEF (2005). National Adaptation Programme of Action (NAPA) Final Report. Dhaka:
Ministry of Environment and Forests (MOEF), Government of the People’s Republic of
Bangladesh.
Mukherjee, A. (2009). Eight food insecurities faced by women and girl children: four steps
that could make a difference, with special reference to South Asia. Paper for the
Regional Conference on Child Poverty and Disparities at the invitation of UNICEF
Regional Office for South Asia, 6-8 May. Katmandu.
Neil Adger, W. (1999). Exploring income inequality in rural, coastal Viet Nam. The Journal
of Development Studies. 35 (5). pp. 96–119.
21
Nielsen, J.Ø. and Reenberg, A. (2010). Temporality and the problem with singling out
climate as a current driver of change in a small West African village. Journal of Arid
Environments. 74 (4). pp. 464–474.
Ninno, C., Dorosh, P.A., Smith, L.C. and Roy, D.K. (2001). The 1998 Floods in Bangladesh
- Disaster Impacts, Household Coping Strategies, and Response. Research Report 122.
Washington, DC: International Food Policy Research Institute (IFPRI).
Olsson, L., Opondo, M., Tschakert, P., Agrawal, A., Eriksen, S.H., Ma, S., Perch, L.N. and
Zakieldeen, S.A. (2014). Livelihoods and poverty. In: C. B. Field, V. R. Barros, D. J.
Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilir, M. Chatterjee, K. L. Ebi, Y. O.
Estrada, R. C. Genova, B. Girma, E. S. Kissel, A. N. Levy, S. MacCracken, P. R.
Mastrandrea, & L. L. White (eds.). Climate Change 2014: Impacts, Adaptation, and
Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press,
pp. 793–832.
Oppenheimer, M., Campos, M., Warren, R., Birkmann, J., Luber, G., O’Neill, B. and
Takahashi, K. (2014). Emergent Risks and Key Vulnerabilities. In: C. B. Field, V. R.
Barros, D. J. Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilar, M. Chatterjee, K. L.
Ebi, Y. O. Estrada, R. C. Genova, B. Birma, E. S. Kissel, A. N. Levy, S. MacCracken, P.
R. Mastrandrea, & L. L. White (eds.). Climate Change 2014: Impacts, Adaptation and
Vulnerability - Contributions of the Working Group II to the Fifth Assessment Report.
Cambridge, UK: Cambridge University Press, pp. 1039–1099.
Otzelberger, A. (2014). Tackling the Double Injustice of Climate Change and Gender
Inequality. CARE International.
Parvin, G.A., Fujita, K., Matsuyama, A., Shaw, R. and Sakamoto, M. (2015). Climate
Change, Flood, Food Security and Human Health: Cross-Cutting Issues in Bangladesh.
In: U. Habiba, M. A. Abedin, A. W. R. Hassan, & R. Shaw (eds.). Food Security and
Risk Reduction in Bangladesh. Tokyo: Springer, pp. 235–254.
Pelling, M. and Uitto, J.I. (2001). Small island developing states: natural disaster
vulnerability and global change. Global Environmental Change Part B: Environmental
Hazards. 3 (2). pp. 49–62.
Rabbani, G., Huq, S. and Rahman, S.H. (2013). Impacts of Climate Change on Water
Resources and Human Health : Empirical Evidences from a Coastal District ( Satkhira )
in Bangladesh. In: V. I. Grover (ed.). Impact of Climate Change on Water and Health.
Boca Raton, FL: CRC Press, Taylor & Francis Group, pp. 272–285.
Rabbani, G., Rahman, A.A. and Islam, N. (2010). Climate Change and Sea Level Rise: Issues
and Challenges for Coastal Communities in the Indian Ocean Region. In: D. Michel &
A. Pandya (eds.). Coastal Zones and Climate Change. Washington, DC: The Henry L.
Stimson Center, pp. 17–29.
Rabbani, M.D.G., Rahman, A.A. and Mainuddin, K. (2009). Women’s vulnerability to water-
related hazards: Comparing three areas affected by climate change in Bangladesh.
Waterlines. 28 (3). pp. 235–249.
Rabbani, M.G., Rahman, A.A., Shoef, I.J. and Khan, Z.M. (2015). Climate Change and Food
22
Security in Vulnerable Coastal Zones of Bangladesh. In: U. Habiba, M. A. Abedin, A.
W. R. Hassan, & R. Shaw (eds.). Food Security and Risk Reduction in Bangladesh.
Tokyo: Springer, pp. 173–186.
Rahman, A.A., Alam, M., Alam, S.S., Uzzman, M.R., Rashid, M. and Rabbani, M.G. (2007).
Risk, Vulnerability and Adaptation in Bangladesh. A Background Paper Prepared for
Human Development Report 2007/2008.
Reardon, T. and Taylor, J.E. (1996). Agroclimatic shock, income inequality, and poverty:
Evidence from Burkina Faso. World Development. 24 (5). pp. 901–914.
Rengasamy, P. (2006). World salinization with emphasis on Australia. Journal of
Experimental Botany. 57 (5). pp. 1017–1023.
Schneider, S.H., Semenov, S., Patwardhan, A., Burton, I., Magadza, C.H.D., Oppenheimer,
M., Pittock, A.B., Rahman, A., Smith, J.B., Suarez, A. and Yamin, F. (2007). Assessing
key vulnerabilities and the risk from climate change. In: M. L. Parry, O. F. Canziani, J.
P. Palutikof, P. J. van der Linden, & C. E. Hanson (eds.). Climate Change 2007:
Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth
Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK:
Cambridge University Press, pp. 779–810.
Skinner, E. (2011). Gender and Climate Change Overview Report. Brighton: Institute of
Development Studies (IDS).
Smit, B. and Pilifosova, O. (2001). Adaptation to Climate Change in the Context of
Sustainable Development and Equity. In: J. J. McCarthy, O. F. Canziani, N. A. Leary,
D. J. Dokken, & K. S. White (eds.). Climate Change 2001: Impacts, Adaptation and
Vulnerability. Contribution of Working Group II to the Third Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University
Press, pp. 877–912.
Stern, N. (2007). The Economics of Climate Change: The Stern Review. Cambridge, UK:
Cambridge University Press.
Thuy, N.N. and Anh, H.H. (2015). Vulnerability of Rice Production in Mekong River Delta
under Impacts from Floods, Salinity and Climate Change. International Journal on
Advanced Science Engineering Information Technology. 5 (4). pp. 272–279.
UNDP (1990). Human Development Report 1990: Concept and Measurement of Human
Development. United Nations Development Program (UNDP), Oxford
University Press, Oxford, UK and New York, NY, USA, 189 pp.
UNESCAP (2009). Sustainable Agriculture and Food Security in Asia and the Pacific.
Bangkok: United Nations Economic and Social Commission for Asia and the Pacific
(UNESCAP).
Vasquez, G.C. (2015). Indigenous People and Climate Change: Causes of Flooding in the
Bolivian Amazon and Consequences for the Indigenous Population. In: G. C. D. Ramos
(ed.). Inequality and Climate Change: Perspectives from the South. Dakar: Council for
the Development of Social Science Research in Africa (CODESRIA), pp. 121–136.
Velan, N. and Mohanty, R.K. (2015). Gender-wise Rural-to-Urban Migration in Orissa,
India: An Adaptation Strategy to Climate Change. In: G. C. D. Ramos (ed.). Inequality
23
and Climate Change: Perspectives from the South. Dakar: Council for the Development
of Social Science Research in Africa (CODESRIA), pp. 137–170.
Vincent, K.E., Tschakert, P., Barnett, J., Rivera-Ferre, M.G. and Woodward, A. (2014).
Cross-chapter box on gender and climate change. In: C. B. Field, V. R. Barros, D.J.
Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilir, M. Chatterjee, K. L. Ebi, Y. O.
Estrada, R. C. Genova, B. Girma, E. S. Kissel, A. N. Levy, S. MacCracken, P. R.
Mastrandrea, & L. L. White (eds.). Climate Change 2014: Impacts, Adaptation, and
Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press,
pp. 105–107.
Werle, D., Martin, T.C. and Hasan, K. (2000). Flood and coastal zone monitoring in
Bangladesh with Radarsat ScanSAR: Technical experience and institutional challenges.
Johns Hopkins APL Technical Digest (Applied Physics Laboratory). 21 (1). pp. 148–
154.
World Bank (2000). Bangladesh: Climate Change and Sustainable Development. Dhaka:
World Bank.