







































Ecology, Economy and Society–the INSEE Journal 6(1): 13-30, January 2023 

 

RESEARCH PAPER 

Measurement of Vulnerability to Climate Change in 
Char Areas: A Survey 

Mrinal Saikia* and Ratul Mahanta** 

Abstract: Threats caused to the environment and human life by climate change 
have become an urgent issue. Climate change often aggravates hazards in a given 
area and has harmful effects on the people residing there. Affected by massive 
floods, land erosion, and the destruction of agricultural lands, char people live a 
risky life. Char dwellers are among the communities that suffer the most as a result 
of the effects of climate change. Few studies discuss the vulnerabilities of 
communities living in char areas to climate change. This paper attempts to 
summarize the existing research. It also discusses data-related issues in the 
measurement of vulnerability to climate change. It ends by raising some policy-
related considerations. 

Keywords: Char, LVI, LVI-IPCC, CVI, vulnerability index   

Journal of Economic Literature (JEL) Classification Code: Q540, Q560 

1. INTRODUCTION 

Vulnerabilities induced by floods and soil erosion render it difficult for char 
dwellers to make a living1 and cohabitate with the river (Lahiri-Dutt 2014). 
Floods and sand deposition on cultivable land impact char livelihoods and 
vulnerability (Ashley et al. 2000). Char land erosion is highly unpredictable, 
leading to traumatic shocks to the livelihoods of char dwellers and causing 

 
* PhD Research Scholar, Department of Economics, Gauhati University. 
mrinalsaikia872@gmail.com. 

** Professor, Department of Economics, Gauhati University. rmeco@gauhati.ac.in. 

Copyright © Saikia and Mahanta 2023. Released under Creative Commons Attribution © 
NonCommercial 4.0 International licence (CC BY-NC 4.0) by the author.  

Published by Indian Society for Ecological Economics (INSEE), c/o Institute of  Economic 

Growth, University Enclave, North Campus, Delhi 110007.  

ISSN: 2581–6152 (print); 2581–6101 (web).  

DOI: https://doi.org/10.37773/ees.v6i1.679 

1 Char areas are “the new riverine lands and islands created by the continual shifting of the 
rivers, and emerge from the deposition of sand and silt from upstream. Chars are found 
along all the major river systems, both lining the banks of rivers and as mid-river islands” 
(DFID 2000, 3). 

mailto:mrinalsaikia872@gmail.com
mailto:rmeco@gauhati.ac.in


Ecology, Economy and Society–the INSEE Journal [14] 

 

households to lose their land, assets, and shelter (EGIS 2000; Kamal 2011; 
Rakiba et al. 2019). In the Indian subcontinent, char areas are located in the 
Ganga–Brahmaputra–Meghna plains (Lahiri-Dutt 2014). According to 
Lahiri-Dutt and Samanta (2013), char areas are vastly different from other 
wetlands; the closest geographical structures to char areas are the mouths of 
deltas. In North-East India, char areas are spread across the Brahmaputra 
valley of Assam, across four agro-climatic zones: the upper Brahmaputra 
valley, north-bank plain zone, middle Brahmaputra valley, and lower 
Brahmaputra valley (GOA 2002–2003). These unique landforms in Assam 
are affected by several types of natural disasters, making char dwellers one 
of the poorest and most vulnerable groups in Assam (Kamal 2011). The 
intensity of soil formation in the river, and hence, the survival and 
formation of chars, is influenced by several factors such as riverbank 
erosion, river flow patterns, soil loss, and floods (Goswami 2014; 
Chakraborty 2012/2014). In addition to floods, chars are highly impacted 
by erosion, which makes the lives and livelihoods of char dwellers uncertain 
and highly prone to vulnerability (HDR 2014). In the char areas of Assam, 
income opportunities, health and educational facilities, and so on are limited 
and are further hindered by floods and other climate-driven factors (Kumar 
and Das 2019). 

Following the views of Birkmann (2013, 29), “Environment is the shaper 
where natural hazards and climate variability originated; it is at the same 
time an important resource for many people who are highly exposed to 
these hazards.” Natural hazards have detrimental effects on communities 
and hinder their socio-economic development. Climate change, through its 
effects on natural and human systems, plays a significant role in 
determining the intensity and frequency of these natural hazards and the 
risks associated with them (Islam et al. 2015a; Panthi et al. 2016; Simotwo et 
al. 2018; Azam et al. 2019; IPCC 2014). These climate-induced hazards and 
risks can cause considerable damage to human life and property globally 
(Rakiba et al. 2019). A huge section of the world population lives in 
earthquake zones, floodplains, riverine islands, and low-lying coastal areas 
that are inherently risky (Lahiri-Dutt and Samanta 2007). 

A population’s vulnerability to climate impacts is influenced by local factors 
that vary with time and space (Alam 2017). The study of vulnerability to 
climate change is important in the context of risk assessment; this need has 
also been emphasized by the Intergovernmental Panel on Climate Change 
(IPCC) (2014). Climate vulnerability can be studied using two approaches: 
qualitative and quantitative. Measurement or assessment of vulnerability is a 
quantitative approach to studying vulnerability. Assessment of vulnerability 



[15] Saikia and Mahanta 

 

is important as it helps identify suitable adaptation techniques (O’Brien et al. 
2009). Quantitative approaches to vulnerability may be either indicator-
based or econometric. In indicator-based approaches, an index representing 
vulnerability is constructed, while in econometric approaches, econometric 
tools are used. Econometric methods are useful for understanding the 
factors that influence the extent of which climate hazards impact people’s 
lives and livelihoods and the economic impacts of vulnerability (Noy and 
Yonson 2016). A vulnerability index is important for making comparisons 
across different contexts, monitoring vulnerabilities over space and time, 
and allocating resources to undertake mitigation and adaptation strategies 
(Preston et al. 2011). It can also be used to evaluate the effectiveness of 
development policy frameworks (Eriksen and Kelly 2007). As vulnerability 
is influenced by local factors, several researchers have argued in favour of 
context- and place-specific assessments of vulnerability (Cutter et al. 2003; 
Füssel 2010; Fraser et al. 2011; Wood et al. 2014; Alam 2016; Alam 2017). 
To estimate the extent of vulnerability of char areas, researchers have used a 
variety of indicator-based methods such as the Livelihood Vulnerability 
Index (LVI), LVI-IPCC, and Climate Change Vulnerability Index (CVI). 
Although several methods have been used to measure vulnerability, there is 
no consensus on which tool is best to measure vulnerability, specifically in 
char areas. Hence, this paper briefly describes the methods available to 
measure vulnerability in char areas, discusses various issues related to those 
methods, and identifies the most suitable method of vulnerability 
measurement. 

The paper is divided into six sections. In Section 2, a discussion is 
presented on char areas and how the idea of vulnerability is linked with 
them. Section 3 includes a detailed discussion on the methods used to 
measure vulnerability to climate change in char areas. Section 4 examines 
the data and the measurement-related issues associated with these methods. 
Section 5 summarizes the results of various quantitative studies on 
vulnerability in char areas. Section 6 concludes the paper.  

2. CHAR AND VULNERABILITY 

There are two types of char areas (Figure 1): island chars, or mid-river 
islands, and attached chars, which are connected to riverbanks (GOA 1983; 
Lahiri-Dutt 2014). The formation of a char at a particular time and in a 
specific area is highly dependent on varied factors such as the river’s flow 
pattern, the occurrence of floods, discharge of sediment due to soil loss, 
and erosion of sand material from the riverbanks (Lahiri-Dutt 2014). Rivers 
like the Ganga and Brahmaputra change their courses frequently (Lahiri-



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Dutt 2014); this leads to erosion and the emergence of char lands (Sarker et 
al. 2015). Changes in the course of the river, its flow pattern, and the 
distance of the river from the char all significantly influence the 
permanence of a char (Khandakar 2016). Changes in the size and location 
of chars could adversely affect the habitations of char dwellers and the 
availability of land for agriculture and animal rearing (Mondal et al. 2016; 
Das et al. 2020). 

In Assam, char areas result from sedimentation by the river Brahmaputra. 
The Brahmaputra is considered the second-most sediment-charged river in 
the world (Chakraborty 2009; Hoque 2015). As the river flows, its velocity 
reduces, as does its capacity to carry sediment (Chakraborty 2009). As a 
result, it deposits silt, which eventually gets covered by vegetation. A socio-
economic survey of char areas in Assam estimates that there are 36,092 
hectares of char land in Assam, occupying approximately 5% of the state’s 
total geographical area (GOA 2002–2003). 

Figure 1: Island Char and Attached Char 

 

Source: Lahiri-Dutt (2014) 

The morphology of rivers, the physical characteristics of their geographic 
locations, and the climate during the monsoons make char areas vulnerable 
to natural disasters (Coleman 1969; Baqee 1998; Islam et al. 2015a). Char 
dwellers are extremely vulnerable to hazards caused by climate change, such 
as storm surges, rising salinity, riverbank erosion, floods, irregular rainfall, 
droughts, hailstorms, water logging, and pest infestations. As water levels 
rise, saline water enters cultivable land, which drastically reduces fertility. 



[17] Saikia and Mahanta 

 

Char dwellers live in extreme conditions during floods, which adversely 
affect their crops, livestock, houses, and other property. Char dwellers 
consider normal floods—which are short, predictable, and low in 
intensity—as a blessing as they benefit them environmentally and 
economically by making their land more fertile and suitable for cultivation. 
Moreover, researchers describe char areas as lands ripe with possibility for 
their dwellers (Lahiri-Dutt and Samanta 2013; Hoque 2015; Lafaye de 
Micheaux et al. 2018). Though these lands are risky, unstable, and fragile, 
they attract the attention of some people, mainly those belonging to 
marginal communities, since these lands are fertile and suitable for 
cultivation (Lahiri-Dutt and Samanta 2013). 

 

3. MEASURING VULNERABILITY IN CHAR AREAS 

Two methods are used to measure vulnerability to climate change in char 
areas: the econometric approach and the index-based approach. The 
econometric approach considers factors such as vulnerability as expected 
poverty (VEP), vulnerability as low expected utility (VEU), and vulnerability 
as uninsured exposure to risk (VER). Under the indicator-based approach, a 
number of indices have been developed and used by various researchers. 
These include the Social Vulnerability Index (SoVI) by Cutter et al. (2003), 
another Social Vulnerability Index (SVI) by Vincent (2004), the 
Vulnerability Index by Deressa et al. (2008), LVI and LVI-IPCC by Hahn et 
al. (2009), the Livelihood Effect Index (LEI) by Urothody and Larsen 
(2010), the Climate Vulnerability Index (CVI) by Pandey and Jha (2012), the 
Social Vulnerability Index (SVI) by Ge et al. (2013), the Index of Social 
Vulnerability by Lee (2014), the Socio-economic Vulnerability Index (SeVI) 
by Ahsan and Warner (2014), and the Physical Vulnerability to Climate 
Change Index (PVCCI) by Feindouno et al. (2020). 

A considerable number of researchers have studied vulnerability to climate 
change in char areas. Some of these studies are qualitative in nature (EGIS 
2000; Ashley et al. 2000; Kamal 2011; Lahiri-Dutt and Samanta 2013; 
Chakraborty 2009/2012/2014; Islam and Hussain 2014; Islam et al. 2015b; 
Rakiba et al. 2019); other researchers use quantitative approaches (Toufique 
and Yunus 2013; Alam et al. 2017; Azam et al. 2019; Sarker et al. 2019; Das et 
al. 2020; Ahmed et al. 2021). 

Econometric methods are widely used to study vulnerability to climate 
change. However, few studies on char areas use these methods. Most 
studies are qualitative in nature. These researchers draw on descriptive 
studies, ethnographic research, focus group discussions (FGD), 



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participatory rural appraisals (PRA), and rapid rural appraisals (RRA), and 
generate descriptive statistics. A limited number of studies have used 
indices for quantitative analyses of vulnerability to climate change in char 
areas (Toufique and Yunus 2013; Alam et al. 2017; Azam et al. 2019; Sarker 
et al. 2019; Das et al. 2020; Ahmed et al. 2021). There are three main indices 
used by researchers: LVI, CVI, and LVI-IPCC. The LVI and LVI-IPCC 
were developed by Hahn et al. (2009) and the CVI is the updated version of 
the LVI, developed by Pandey and Jha (2012). This section discusses all 
three methods.  

The three indices are based on the IPCC (2001) definition of vulnerability; 
that is, vulnerability is considered a function of exposure, sensitivity, and 
adaptive capacity. Therefore,  

Vulnerability = f (exposure, sensitivity, adaptive capacity) 

However, it is to be noted that in the IPCC’s (2014) definition on 
vulnerability, it has removed exposure component from the idea and 
expressed vulnerability as a function of sensitivity and adaptive capacity 
only.  

The LVI aims to quantify the strength of communities’ livelihoods; people’s 
access to healthcare and water sources; and the capacity of communities to 
adjust to the threats posed by climate change (Hahn et al. 2009). The 
balanced weight approach is used under the LVI approach to calculate 
vulnerability; that is, even though each major component includes various 
subcomponents, each subcomponent contributes equally to the overall LVI. 
Hahn et al. (2009) consider seven major components—social networks, 
livelihood strategy, socio-demographic profile, access to food, healthcare, 
and water, and the impact of climate variability and natural disasters. Again, 
each major component has a number of subcomponents. This method is 
useful in that it allows the addition or subtraction of indicators on the basis 
of the need and scope for research in any particular area (Hahn et al. 2009; 
Pandey and Jha 2011; Alam et al. 2017).  

Since the subcomponents are measured at different scales, it is important to 
standardize them using an index. Standardization is done as follows: 

Index Ya =  

Where Ya is the original subcomponent of area ‘a’. Ymax and Ymin are the 
maximum and minimum values of each subcomponent, respectively. For 
variables measuring frequencies, like the percentage of households having 



[19] Saikia and Mahanta 

 

access to clean water, the maximum value is considered as 100 and the 
minimum as 0. 

After converting the values of the subcomponents into indices, one can 
derive the value of the major component by taking the average of the 
subcomponents.  

Xa =  

Here, Xa is one of the seven major components of area ‘a’.  is the 

ith standardized subcomponent of the respective major component. And ‘n’ 
represents the number of subcomponents present under the major 
component. 

Once the seven major components are calculated, LVI can be calculated 
using the given formula:  

LVIa =  

Where LVIa is the Livelihood Vulnerability Index for area ‘a’, a weighted 

average of all the seven major components, and  indicates the number 

of subcomponents under the Zth major component. Weights are assigned so 
that all subcomponents contribute to the overall LVI.  

The LVI-IPCC is an alternative to the LVI approach. It was developed to 
calculate the LVI by incorporating the IPCC (2001) definition of 
vulnerability; in the LVI-IPCC, the seven major components are organized 
into three dimensions of vulnerability, and the index value of these three 
dimensions are calculated separately. Hence, the LVI-IPCC approach 
comes one step closer to the IPCC (2001) definition of vulnerability to 
climate change. In the calculation of LVI-IPCC, the adaptive capacity 
dimension includes components such as households’ socio-demographic 
profile, livelihood strategies, and social networks. Sensitivity includes access 
to health, food, and water; and exposure refers to the occurrence of natural 
disasters and climate variability in the district. The LVI-IPCC differs from 
the LVI in its method of calculation. The LVI-IPCC presents the overall 
index as the difference between the exposure value and the value of 
adaptive capacity multiplied by the sensitivity index. Now, let’s have a look 
at how the LVI-IPCC is calculated for a district, say ‘a’.  



Ecology, Economy and Society–the INSEE Journal [20] 

 

Da =  

Where Da is a dimension of the LVI-IPCC for district ‘a’.  are the main 

components of the ath district indexed by ‘i’. Each major component’s 

weight is defined by  and the number of main components under each 

dimension is defined by ‘n’.  

Now, LVI-IPCC can be calculated using the following formula:  

LVI-IPCCa = (Ea – Ad.Ca) * Sa 

Where Ea is the estimated exposure score of district ‘a’, Ad.Ca represents 
the index value of the adaptive capacity of the respective district, and the 
sensitivity score of the district ‘a’ is denoted by Sa. The value of LVI-IPCC 
varies from −1 to 1. A value closer to 1 indicates a higher state of 
vulnerability, whereas −1 denotes less vulnerability. The LVI and LVI-
IPCC both consider the same major components and use the same method 
to measure the index value of each major component. The dimensions of 
the CVI are the same as those of the LVI. Each component has relevant 
subcomponents under it. A conceptual improvement of the CVI over the 
LVI is that despite measuring vulnerability, the CVI aims to define a 
society’s capacity to attain a ‘no vulnerability’ status. Therefore, 
methodologically, according to Pandey and Jha (2011, 497), “The inverse 
relationship for sensitivity has been considered keeping in view of analysing 
the per unit strength of the system bearing capability on absolute 
performance under the climate threats.” Based on the three dimensions of 
vulnerability, the major components have been segregated—adaptive 
capability includes socio-demographic profile, livelihood strategies, and 
social networks. The dimension of sensitivity contains the health, food, and 
water components; and exposure captures the occurrence of natural 
disasters and climate variability (Pandey and Jha 2011). The subcomponents 
can be standardized using the same formula used in the LVI. The index 
values for exposure, sensitivity, and adaptive capacity are calculated 
separately, as follows:  

Exp =  

Where Exp is the index of exposure.  and  are considered weights 

of the indicators, which are the number of subcomponents under the 
indicators ND and CV, respectively.   



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Where Sen stands for the index of sensitivity;  are the weights; 

and the number of subcomponents are H, F, and W.  

The index of adaptive capacity (Ada.Cap) is calculated as follows: 

Ada.Cap =  

Where  are the weights, which are the number of 

subcomponents of SD, LS, and SN respectively. 

The CVI considers an inverse relationship between sensitivity and the 
ability of a system to perform under climate threats. It explains the 
capability of a society to attain the status of no vulnerability. The CVI is 
calculated as follows: 

CVI = 1 – [{ }]*  

Ni is the number of major components under the ith dimension of the CVI. 
No number has been assigned to the sensitivity dimension, because its 
components cancel out each other. The value of the CVI falls within the 
range of 0 to 1. As it reflects the capability of people to reduce their 
vulnerability, the higher the value of the CVI, the lower the level of 
vulnerability, and the smaller the value of the CVI, the greater the level of 
vulnerability. 

4. CHALLANGES IN MEASURING VULNERABILITY IN 
THE CONTEXT OF RIVERINE ISLANDS 

Various methods have been used in the literature to measure vulnerability. 
Some indices are more inclined towards the socio-economic dimension 
while others emphasize the physical or biophysical aspects of vulnerability. 
The biophysical aspect covers the sensitivity components of vulnerability, 
while adaptive capacity covers the socio-economic. However, adaptive 
capacity and sensitivity are interlinked, and it would not be appropriate to 
calculate one without mentioning the other (Deressa et al. 2008).  

All three indices, LVI, LVI-IPCC, and CVI, cover both the socio-economic 
and biophysical aspects of vulnerability. Researchers use primary data on 
social networks, livelihood strategies, socio-demographic profiles; access to 
food, healthcare, and water; and climate variability and natural disasters to 



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calculate vulnerability indices (Toufique and Yunus 2013; Alam et al. 2017; 
Azam et al. 2019; Sarker et al. 2019; Das et al. 2020; Ahmed et al. 2021).  

5. OVERVIEW OF FINDINGS FROM EMPIRICAL 
STUDIES ON RIVERINE ISLANDS  

India and Bangladesh share about 54 transboundary rivers that extensively 
support the livelihoods of a large number of riverine communities. 
However, various climate change associated factors, such as the increased 
frequency of floods, unpredictable changes in the courses of rivers, and a 
continuous increase in the width of these rivers, are having significant 
adverse effects on the lives and livelihoods of communities (Sentinel 2022). 
Sumanta Biswas, Senior Programme Officer, CUTS International, in an 
interview, said that along with climate change, deforestation, rising 
urbanization, and more intensive agricultural practices have adversely 
affected many rivers in South Asia by altering their courses and changing 
their flow rate (Suri 2021). As a result, increased erosion, siltation, and 
unexpected floods have become common in riverine communities. 
Transboundary river systems* are also under serious stress due to various 
factors, including the overuse of resources such as newly emerged sandbars 
for cultivation and sand mining, overfishing, and so on, thus increasing the 
variability of resources. Disruptions in the livelihoods of transboundary 
riverine communities can be clearly observed at the national and sub-
national levels; flooding severely affects these regions and excessive rain 
leads to devastating conditions (Suri 2021). Alam et al. (2018), in their study 
on the vulnerability of people living in the char lands of the Brahmaputra–
Jamuna river system of Bangladesh, argue that the livelihood strategies of 
those living on char lands are considerably different from those of people 
residing on the mainland. The majority of the population is engaged in 
agriculture, and during the off season, char dwellers also take up non-farm 
activities. Thus, their lives are severely affected by floods and land erosion 
compared to the people residing in the mainland. The main challenges 
include seasonal flooding, geographic isolation, and anthropogenic as well 
as climatic stressors. Though riverine communities have adjusted their 
livelihoods and cropping patterns to observed flooding patterns, due to 
climate variability, the occurrence of early floods has become a common 
issue linked to the washing away of crops. Bhuiyan et al. (2017) found that 

 
* The Indus, Ganges, and Brahmaputra are known as the major transboundary river 
systems of South Asia. By providing energy, food, water, and ecosystem services, 
these river systems across the subcontinent support about 700 crore people (Suri 
2014). 



[23] Saikia and Mahanta 

 

massive land erosion is the most significant vulnerability factor among char 
communities in Bangladesh. A study by Salam et al. (2019), on char lands in 
Bangladesh, showed that flooding is the main contributor to vulnerability 
among char dwellers. Floods in char lands affect various aspects, including 
people’s health and habitation, agriculture, economic activities, the 
availability of clean water sources, and sanitation status.  

To quantitatively analyse the livelihood vulnerabilities of char communities, 
three indices—the LVI, LVI-IPCC, and CVI—have been used by different 
researchers. Researchers study vulnerability to climate change in the char 
areas to compare it to the mainland (Toufique and Yunus 3013) and to 
compare island and riverbank chars (Alam et al. 2017; Das et al. 2020). 
Studies have also analysed vulnerability to climate change in terms of the 
distance of the char villages from the administrative headquarters (Sarker et 
al. 2019). This section summarizes the major findings of the research on 
vulnerability to climate change in char areas using quantitative techniques. 

Many studies report the high vulnerability of char areas. River erosion, 
floods, and droughts are the major climate-driven risks facing char dwellers, 
and these events have significant negative effects on char livelihoods, which 
are primarily based on agriculture (Ahmed et al. 2021). Char dwellers are 
highly sensitive and exposed to natural disasters and have a low level of 
adaptive capacity (Azam et al. 2019; Ahmed et al. 2021). Char communities 
with a large number of marginalized households are more vulnerable (Azam 
et al. 2019). 

Char dwellers are more vulnerable to climate change compared to 
inhabitants on the mainland. The major components influencing this 
difference are social networks, food, and access to water (Toufique and 
Yunus 2013). Differences in vulnerability are also evident between the 
island chars and attached chars. Alam et al. (2017) found that the inhabitants 
of island chars are more vulnerable compared to attached ones due to 
relatively less access to educational, health, and financial institutions, greater 
exposure to natural disasters, and more limited crop diversification. Limited 
availability of food and water further exacerbate the vulnerability of char 
areas. Healthcare, education, and government services are less available to 
island char dwellers, making them more vulnerable. Again, island chars are 
more exposed to frequent floods and riverbank erosion compared to 
attached chars. Vulnerability to climate change is also determined by the 
distance of the char villages from the district headquarters. Char villages 
that are nearer the district administrative headquarters are comparatively 
less vulnerable than those char villages that are further away due to the 
latter’s lower access to education, basic public services, healthcare, and 



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financial assets. The latter have comparatively low social capital, making 
inhabitants of further away chars financially more vulnerable (Sarker et al. 
2019). 

6. CONCLUSION 

Both socio-economic and environmental factors determine social groups’ 
vulnerability to climate change (Deressa et al. 2008). In the discussion on 
the socio-economic impacts of climate change, vulnerability and adaptive 
capacity have been gaining importance over the last few years, more 
specifically, after the IPCC (2001) report on climate change, indicating a 
growing prioritization of the field of vulnerability research (Ahsan and 
Warner, 2014). According to Hoddinott and Quisumbing (2003), VEP and 
VEU determine a benchmark of welfare (poverty or utility). The VER 
model studies both biophysical and socio-economic factors and the impact 
of these factors on loss of welfare in the form of a reduction in 
consumption (Narayanan and Sahu 2016). Researchers have used only 
indicator-based approaches to quantitatively study vulnerability to climate 
change in char areas. Three indices are used: the LVI, LVI-IPCC, and CVI. 

It is important to note that all the three vulnerability indices are based on 
the IPCC (2001) definition, where vulnerability to climate change is a 
function of sensitivity, exposure, and adaptive capacity. However, the IPCC 
(2014) report separates the exposure component from the idea of 
vulnerability and expresses it as a function of sensitivity and adaptive 
capacity only. However, even after the reformulation of the concept of 
vulnerability in the report, later studies on vulnerability to climate change in 
char areas have continued to use the exposure component as part of the 
measurement (Alam et al. 2017; Azam et al. 2019; Sarker et al. 2019; Das et al. 
2020; Ahmed et al. 2021) Therefore, some adjustments to these indices may 
be necessary to incorporate the updated idea of vulnerability to climate 
change.  

As discussed earlier, the research on vulnerability to climate change in char 
areas using quantitative approaches employs indicator-based methods; an 
econometric approach has not yet been applied. However, since both the 
econometric and indicator-based approaches have advantages, using both in 
tandem may lead to a better understanding of vulnerability. For instance, an 
indicator-based approach will facilitate an understanding of the extent of 
vulnerability to climate change, while an econometric-based approach 
would help to study the economic impact. 

Declaration: The authors declare that there is no conflict of interest. 



[25] Saikia and Mahanta 

 

Data sharing not applicable—no new data generated: Data sharing is 
not applicable to this article as no new data was created or analysed in this 
study. 



Ecology, Economy and Society–the INSEE Journal [26] 

 

REFERENCES  

Ahmed, Zobaer, Gauri S Guha, Aaron M Shew, and Monirul GM Alam. 2021. 
“Climate Change Risk Perceptions and Agricultural Adaptation Strategies in 
Vulnerable Riverine Char Islands of Bangladesh.” Land Use Policy 103. 
https://doi.org/10.1016/j.landusepol.2021.105295. 

Ahsan, Nasif, and Jeroen Warner. 2014. “The Socioeconomic Vulnerability Index: 
A Pragmatic Approach for Assessing Climate Change Led Risks – A Case Study in 
the South-western Coastal Bangladesh.” International Journal for Disaster Risk 
Reduction 8: 32–49. https://doi.org/10.1016/j.ijdrr.2013.12.009. 

Alam, Monirul GM. 2016. “An Assessment of the Livelihood Vulnerability of the 
Riverbank Erosion Hazard and its Impact on Food Security for Rural Households 
in Bangladesh.” PhD diss., School of Commerce, University of Southern 
Queensland, Australia. 

 

—. 2017. “Livelihood Cycle and Vulnerability of Rural Households to Climate Change and 
Hazards in Bangladesh.” Environmental Management 59: 777–791. 
https://doi.org/10.1007/s00267-017-0826-3. 

 

Alam, Monirul GM, Khorshed Alam, Shahbaz Mushtaq, and Michele L Clarke. 
2017. “Vulnerability to Climate Change in Riparian Char and River-bank 
Households in Bangladesh: Implication for Policy, Livelihoods and Social 
Development.” Ecological Indicators 72: 23–32. 
https://doi.org/10.1016/j.ecolind.2016.06.045. 

 

Alam, Md Rakibul, Md Abdul Malak, and Quader Mohammad. 2018. “Livelihood 
Vulnerability of Char Land People in Brahmaputra–Jamuna River System.” Journal 
of Life and Earth Sciences 4 (1): 54–64. 

 

Ashley, Steve, Kamal Kar, Abul Hossain, and Shibabrata Nandi. 2000. “The Chars 
Livelihood Assistance Scoping Study.” DFID Department for International Development. 

 

Azam, Gausal, Mohammad Emadul Huda, Mohammad Amit Hossain Bhuyan, 
Mohammad Mohinuzzaman, Md Bodrud-Doza, and SM Didar-Ul Islam. 2019. 
“Climate Change and Natural Hazards Vulnerability of Char Land (Bar Land) 
Communities of Bangladesh: Application of the Livelihood Vulnerability Index 
(LVI).” Global Social Welfare 8 (1): 93–105. https://doi.org/10.1007/s40609-019-
00148-1. 

 

Baqee, MA. 1998. Peopling in the Land of Allah Jaane: Power, Peopling and Environment: 
The Case of Char-lands of Bangladesh. Dhaka: University Press Limited. 

 

Bhuiyan, Mohammad Amir Hossain, SM Didar-Ul Islam, and Gausal Azam. 2017. 
“Exploring Impacts and Livelihood Vulnerability of Riverbank Erosion Hazard 
Among Rural Household Along the River Padma of Bangladesh.” Environmental 
System Research 6 (25). https://doi.org/10.1186/s40068-017-0102-9. 

 

Birkmann, Jörn. 2013. “Measuring Vulnerability to Promote Disaster-Resilient  

https://doi.org/10.1016/j.landusepol.2021.105295
https://doi.org/10.1016/j.ijdrr.2013.12.009
https://doi.org/10.1007/s00267-017-0826-3
https://doi.org/10.1016/j.ecolind.2016.06.045
https://doi.org/10.1007/s40609-019-00148-1
https://doi.org/10.1007/s40609-019-00148-1
https://doi.org/10.1186/s40068-017-0102-9


[27] Saikia and Mahanta 

 

Societies and to Enhance Adaptation: Conceptual Frameworks and Definitions.” 
In Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient Societies 
(second edition), edited by Jörn Birkmann, p 29. New York: United Nations 
University Press. 

Chakraborty, Gorky. 2009. Assam’s Hinterland: Society and Economy in the Char Areas. 
New Delhi: Akansha Publishing House. 

 

—. 2012. “The ‘Ubiquitous’ Bangladeshis.” Economic & Political Weekly 47 (38): 21–23.  

—. 2014. “The Demographic Question in the Char Areas of Assam.” Review of 
Char Settlers of Assam: A Demographic Study, by Goswami, M. Social Change and 
Development 11 (2). 

 

Coleman, James M. 1969. “Brahmaputra River Channel Processes and 
Sedimentation.” Sedimentary Geology 3 (2–3): 129–239. 
https://doi.org/10.1016/0037-0738(69)90010-4. 

 

Cutter, Susan L, Bryan J Boruff, and W Lynn Shirley. 2003. “Social Vulnerability to 
Environmental Hazards.” Social Science Quarterly 84: 242–261. 
https://doi.org/10.1111/1540-6237.8402002. 

 

Das, Manob, Arijit Das, Sahil Momina, and Rajiv Pandey. 2020. “Mapping the 
Effect of Climate Change on Community Livelihood Vulnerability in the Riparian 
Region of Gangatic Plain, India.” Ecological Indicators 119. 
https://doi.org/10.1016/j.ecolind.2020.106815. 

 

Deressa, Temesgen, Rashid M Hassan, and Claudia Ringler. 2008. “Measuring 
Ethiopian farmers’ Vulnerability to Climate Change across Regional States.” 
Environment and Production Technology Division, International Food Policy Research Institute. 

 

DFID. 2000. “The Chars Livelihood Assistance Scoping Study.” DFID Department 
for International Development. 

 

EGIS. 2000. “Riverine Chars in Bangladesh: Environmental Dynamics and 
Management Issues. Environment and GIS Support Project for Water Sector 
Planning (EGIS).” University Press. 

 

Eriksen, S, and P Kelly. 2007. “Developing Credible Vulnerability Indicators for 
Climate Adaptation Policy Assessment.” Mitigation and Adaption Strategies for Global 
Change 12 (4): 495–524. https://doi.org/10.1007/s11027-006-3460-6. 

 

Feindouno, Sosso, Patrick Guillaumont, and Catherine Simonet, C. 2020. “The 
Physical Vulnerability to Climate Change Index: An Index to be Used for 
International Policy.” Ecological Economics 176. 
https://doi.org/10.1016/j.ecolecon.2020.106752. 

 

Fraser, Evan DG, Andrew J Dougill, Klaus Hubacek, Claire H Quinn, Jan 
Sendzimir, and Mette Termansen. 2011. “Assessing Vulnerability to Climate 
Change in Dryland Livelihood Systems: Conceptual Challenges and 
Interdisciplinary Solutions.” Ecology and Society 16: 33–42. 
https://doi.org/10.5751/ES-03402-160303. 

 

https://doi.org/10.1016/0037-0738(69)90010-4
https://doi.org/10.1111/1540-6237.8402002
https://doi.org/10.1016/j.ecolind.2020.106815
https://doi.org/10.1007/s11027-006-3460-6
https://doi.org/10.1016/j.ecolecon.2020.106752
https://doi.org/10.5751/ES-03402-160303


Ecology, Economy and Society–the INSEE Journal [28] 

 

Füssel, HM. 2010. “How Inequitable is the Global Distribution of Responsibility, 
Capability, and Vulnerability to Climate Change: A Comprehensive Indicator-based 
Assessment.” Global Environmental Change 20: 597–611. 
https://doi.org/10.1016/j.gloenvcha.2010.07.009. 

 

Ge, Yi, Wen Dou, Zhihui Gu, Xin Qian, Jinfei Wang, Xu Wei, Peijun Shi, et al. 
2013. “Assessment of Social Vulnerability to Natural Hazards in the Yangtze River 
Delta, China.” Stochastic Environmental Research and Risk Assessment 27: 1899–1908. 
https://doi.org/10.1007/s00477-013-0725-y. 

 

GOA. 1983. Char Area Development Department. Government of Assam.  

GOA. 2002–2003. Socio-economic Survey (2002–2003). Directorate of Char Areas 
Development Assam, Dispur, Guwahati. 

Goswamy, Manoj. 2014. Char Settlers of Assam: A Demographic Study. Guwahati: 
MRB Publishers. 

 

Hahn, Micah B, Anne M Riederer, and Stanley O Foster. 2009. “The Livelihood 
Vulnerability Index: A Pragmatic Approach to Assessing Risks from Climate 
Variability and Change – A Case Study in Mozambique.” Global Environmental 
Change 19 (1): 74–88. https://doi.org/10.1016/j.gloenvcha.2008.11.002. 

 

HDR. 2014. Assam Human Development Report 2014. Government of Assam.  

Hoddinott, John, and Agnes Quisumbing. 2003. “Methods for Microeconometric 
Risk and Vulnerability Assessment.” Social Protection Discussion Paper Series, The World 
Bank. 

 

Hoque, Md Deluwar. 2015. “A Study of Livelihood Pattern in the Socio-economic 
Milieu of Char Areas in Assam.” PhD diss., Gauhati University. 

 

International Collective in Support of Fishworkers. 2022. “India and Bangladesh: 
Transboundary Rivers Support Millions of Riverine Communities.” 
https://www.icsf.net/newss/india-and-bangladesh-transboundary-rivers-support-
millions-of-riverine-communities/.  

 

IPCC. 2001. Climate Change 2001: Impacts, Adaptation and Vulnerability: Summary for 
Policymakers. Cambridge: Cambridge University Press. 

 

IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups 
I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on 
Climate Change [Core Writing Team, RK Pachauri and LA Meyer (eds)]. Geneva, 
Switzerland: IPCC. 

 

Islam, M Rezaul, and Delwar Hossain. 2014. “Island Char Resource Mobilization 
(ICRM): Changes of Livelihoods of Vulnerable People in Bangladesh.” Social 
Indicators Research 117: 1033–1054. 
https://doi.org/10.1007/s11205-013-0375-y. 

 

Islam, Md Sirajul, Md Solaiman, MS Islam, TR Tusher, and MH Kabir. 2015a. 
“Impacts of Flood on Char Livelihoods and Its Adaptation Techniques by the 
Local People.” Bangladesh Journal of Scientific Research 28 (2): 123–135. 

 

https://doi.org/10.1016/j.gloenvcha.2010.07.009
https://doi.org/10.1007/s00477-013-0725-y
https://doi.org/10.1016/j.gloenvcha.2008.11.002
https://www.icsf.net/newss/india-and-bangladesh-transboundary-rivers-support-millions-of-riverine-communities/
https://www.icsf.net/newss/india-and-bangladesh-transboundary-rivers-support-millions-of-riverine-communities/
https://doi.org/10.1007/s11205-013-0375-y


[29] Saikia and Mahanta 

 

https://doi.org/10.3329/bjsr.v28i2.26783. 

Islam, Didar-Ul Islam, Mohammad AH Bhuiyan, and AL Ramanathan. 2015b. “Climate 
Change Impacts and Vulnerability Assessment in Coastal Region of Bangladesh: A 
Case Study on Shyamnagar Upazila of Satkhira District.” Journal of Climate Change 1 
(1–2): 37–45. https://doi.org/10.3233/JCC-150003. 

 

Kamal, Sabkat. 2011. Livelihood Dynamics and Disaster Vulnerabilities of Char Land 
Areas. Department of Urban and Regional Planning Bangladesh University of 
Engineering and Technology Dhaka. 

 

Khandakar, Abdullah. 2016. Social Exclusion of Inhabitants of Chars: A Study of Dhubri 
District in Assam. Department of Sociology School of Social Sciences, Sikkim 
University. 

 

Kumar, Balram, and Debarshi Das. 2019. “Livelihood of the Char Dwellers of 
Western Assam.” Indian Journal of Human Development 13 (1): 90–101. 
https://doi.org/10.1177/0973703019839808. 

 

Lafaye de Micheaux, Flore, Jenia Mukherjee, and Christian A Kull. 2018. “When 
Hydrosociality Encounters Sediments: Transformed Lives and Livelihoods in the 
Lower Basin of the Ganges River.” Environment and Planning E: Nature and Space 1 
(4): 641–663. https://doi.org/10.1177/2514848618813768. 

 

Lahiri-Dutt, Kuntala. 2014. “Chars, Islands that Float Within Rivers.” Shima: The 
International Journal of Research into Island Cultures 8 (2). 

Lahiri-Dutt, Kuntala, and Gopa Samanta. 2007. “Like the Drifting Grains of Sand. 
Vulnerability, Security and Adjustment by Communities in the Charlands of the 
Damodar River, India, South Asia.” Journal of South Asian Studies 30 (2): 327–350. 
https://doi.org/10.1080/00856400701499268. 

 

—. 2013. Dancing with the River: People and Life on the Chars of South Asia. Yale University Press. 
https://doi.org/10.12987/yale/9780300188301.001.0001. 

 

Lee, Yung-Jaan. 2014. “Social Vulnerability Indicators as a Sustainable Planning 
Tool.” Environmental Impact Assessment Review 44: 31–42. 
https://doi.org/10.1016/j.eiar.2013.08.002. 

 

Mondal, Jayanta, Sandipta Debanshi, and Sujit Mandal. 2016. “Dynamicity of the River 
Ganga and Bank Erosion Induced Land Loss in Manikchak Diara of Malda 
District of West Bengal, India: A RS and GIS based Geo-spatial Approach.” 
International Journal of Applied Remote Sensing and GIS 3 (1): 1316–1323. 

 

Narayanan, K, and Santosh Kumar Sahu. 2016. “Effects of Climate Change on 
Household Economy and Adaptive Responses among Agricultural Households in 
Eastern Coast of India.” Climate Change Impacts and Adaptation 110 (7): 1240–1250. 

 

Noy, Ilan, and Rio Yonson. 2018. “Economic Vulnerability and Resilience to 
Natural Hazards: A Survey of Concepts and Measurements.” Sustainability 10: 2850. 
https://doi.org/10.3390/su10082850. 

 

O’Brien, Karen, Siri Hallstrom Eriksen, Ane Schjolden, and Lynn Nygaard. 2009.  

https://doi.org/10.3329/bjsr.v28i2.26783
https://doi.org/10.3233/JCC-150003
https://doi.org/10.1177/0973703019839808
https://doi.org/10.1177/2514848618813768
https://doi.org/10.1080/00856400701499268
https://doi.org/10.12987/yale/9780300188301.001.0001
https://doi.org/10.1016/j.eiar.2013.08.002
https://doi.org/10.3390/su10082850


Ecology, Economy and Society–the INSEE Journal [30] 

 

“What’s in a Word? Conflicting Interpretations of Vulnerability in Climate Change 
Research.” Centre for International Climate and Environmental Research, Oslo. 
https://www.researchgate.net/publication/242171299_What's_in_a_word_Confli
cting_interpretations_of_vulnerability_in_climate_change_research 

 
Pandey, Rajiv, and Shashidar Kumar Jha. 2012. “Climate Vulnerability Index – 
Measure of Climate Change Vulnerability to Communities: A Case of Rural Lower 
Himalaya, India.” Mitigation and Adaptation Strategies for Global Change 17 (5): 487–
506. https://doi.org/10.1007/s11027-011-9338-2. 

 

Panthi, Jeeban, Suman Aryal, Piyush Dahal, Parashuram Bhandari, Nir Y Krakauer, 
and Vishnu Prasad Pandey. 2016. “Livelihood Vulnerability Approach to Assessing 
Climate Change Impacts on Mixed Agro-livestock Smallholders around the 
Gandaki River Basin in Nepal.” Regional Environmental Change 16 (4): 1121–1132. 
https://doi.org/10.1007/s10113-015-0833-y. 

 

Preston, Benjamin L, Emma J Yuen, and Richard M Westaway. 2011. “Putting Vulnerability 
to Climate Change on the Map: A Review of Approaches, Benefits, and Risks.” 
Sustainability Science 6: 177–202. https://doi.org/10.1007/s11625-011-0129-1. 

 

Rahman, Saydur, Md Touhiduzzaman, and Irteja Hasan. 2017. “Coastal Livelihood 
Vulnerability to Climate Change: A Case Study of Char Montaz in Patuakhali 
District of Bangladesh.” American Journal of Modern Energy 3 (4): 58–64. 
https://doi.org/10.11648/j.ajme.20170304.11. 

 

Rakiba, MA, Jun Sasaki, Sosimohan Pal, Md Asif Newaz, Md Bodrud-Doza, and 
Md AH Bhuiyan. 2019. “An Investigation of Coastal Vulnerability and Internal 
Consistency of Local Perceptions under Climate Change Risk in the South West 
Part of Bangladesh.” Journal of Environmental Management 231: 419–428. 
https://doi.org/10.1016/j.jenvman.2018.10.054. 

 

Salam, Md Abdus, Md Shohel Khan, and Md Abu Hena Sarker. 2019. “Impacts 
and Coping Techniques of Flood: The Case Study of Two Adjacent Char Lands of 
Jamuna River in Sirajgonj District, Bangladesh.” International Research Journal of 
Environmental Science 8 (3): 53–61. 

 

Sarker, Md Nazirul Islam, Md Arshad Ali, and Md Shahidul Islam. 2015. “Causes 
and Possible Solutions of Poverty Perceived by Char Dwellers in Bangladesh.” 
International Journal of Natural and Social Sciences 2 (1): 37–41. 

 

Sarker, Md Nazirul Islam, Min Wu, GM Monirul Alam, and Roger C Shouse. 2019. 
“Livelihood Vulnerability of Riverine-island Dwellers in the Face of Natural 
Disasters in Bangladesh.” Sustainability 11: 1623. 
https://doi.org/10.3390/su11061623. 

 

Sentinel Digital Desk. 2022. “Livelihoods Along India–Bangladesh Trans-
boundary Rivers in Peril.” The Sentinel, March 28, 2022. 
https://www.sentinelassam.com/topheadlines/livelihoods-along-india-bangladesh-
trans-boundary-rivers-in-peril-584771. 

 

Simotwo, Harrison K, Stella M Mikalitsa, and Boniface N Wambua. 2018. “Climate  

https://www.researchgate.net/publication/242171299_What's_in_a_word_Conflicting_interpretations_of_vulnerability_in_climate_change_research
https://www.researchgate.net/publication/242171299_What's_in_a_word_Conflicting_interpretations_of_vulnerability_in_climate_change_research
https://doi.org/10.1007/s11027-011-9338-2
https://doi.org/10.1007/s10113-015-0833-y
https://doi.org/10.1007/s11625-011-0129-1
https://doi.org/10.11648/j.ajme.20170304.11
https://doi.org/10.1016/j.jenvman.2018.10.054
https://doi.org/10.3390/su11061623
https://www.sentinelassam.com/topheadlines/livelihoods-along-india-bangladesh-trans-boundary-rivers-in-peril-584771
https://www.sentinelassam.com/topheadlines/livelihoods-along-india-bangladesh-trans-boundary-rivers-in-peril-584771


[31] Saikia and Mahanta 

 

Change Adaptive Capacity and Smallholder Farming in Trans-Mara East Sub-
county, Kenya.” Geoenvironmental Disasters 5 (5). https://doi.org/10.1186/s40677-
018-0096-2. 

Surie, Mandakini Devasher. 2014. “Desecuritizing Transboundary Water in South 
Asia.” The Asian Foundation, September 17, 2014. 
https://asiafoundation.org/2014/09/17/desecuritizing-transboundary-water-in-
south-asia/.  

Surie, Mandakini Devasher. 2021. “Valuing Water from a Transboundary 
Perspective in South Asia.” South Asia Nadi Sambad, April 7, 2021. 
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-
asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20rive
r%20systems%20%E2%80%94%20the,sub-
continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and
%20ecosystem%20services. 

 

Toufique, Kazi Ali, and Mohammad Yunus. 2013. “Vulnerability of Livelihoods in 
the Coastal Districts of Bangladesh.” The Bangladesh Development Studies 36 (1): 95–
120. 

 

Urothody, Ashique and Helle Overgard Larsen. 2010. “Measuring Climate Change 
Vulnerability: A Comparison of Two Indexes.” Banko Janakari 20: 9–16. 
https://doi.org/10.3126/banko.v20i1.3503. 

 

Vincent, Katharine. 2004. “Creating an Index of Social Vulnerability to Climate Change for 
Africa.” Working paper. Tyndall Centre for Climate Change Research. 

 

Wood, Stephen A, Amir S Jina, Meha Jain, Patti Kristjanson, and Ruth S DeFries. 
2014. “Smallholder Farmer Cropping Decisions Related to Climate Variability 
across Multiple Regions.” Global Environmental Change 25: 163–172. 
https://doi.org/10.1016/j.gloenvcha.2013.12.011. 

 

 

https://doi.org/10.1186/s40677-018-0096-2
https://doi.org/10.1186/s40677-018-0096-2
https://asiafoundation.org/2014/09/17/desecuritizing-transboundary-water-in-south-asia/
https://asiafoundation.org/2014/09/17/desecuritizing-transboundary-water-in-south-asia/
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20river%20systems%20%E2%80%94%20the,sub-continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and%20ecosystem%20services
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20river%20systems%20%E2%80%94%20the,sub-continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and%20ecosystem%20services
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20river%20systems%20%E2%80%94%20the,sub-continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and%20ecosystem%20services
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20river%20systems%20%E2%80%94%20the,sub-continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and%20ecosystem%20services
https://soanas.org/valuing-water-from-a-transboundary-perspective-in-south-asia/#:~:text=South%20Asia%E2%80%99s%20major%20transboundary%20river%20systems%20%E2%80%94%20the,sub-continent%2C%20providing%20water%2C%20food%2C%20energy%2C%20and%20ecosystem%20services
https://doi.org/10.3126/banko.v20i1.3503
https://doi.org/10.1016/j.gloenvcha.2013.12.011

