Assessing Social Vulnerability to Coastal Hazards: An Examination on Sagar Island of Sundarban Delta

 

Debabrata Mondal

 

Assistant Teacher, Manindranagar High School (H.S.), P.O.– Cossimbazar Raj, P.S. Berhampore, District–Murshidabad, West Bengal, India, PIN - 742101

 

ABSTRACT:

Assessing social vulnerability to coastal hazards is a technique that identifies and measures the degree of copping ability of the social groups from coastal hazard impact. Sagar Island, in the Sundarban delta is one of the unstable landmass where a lot of people each year become homeless by any type of environmental hazards. In the present study, an attempt has been made to assess mouza level social vulnerability of Sagar Island based on census derived socioeconomic data. The study following the methodology developed by HERO vulnerability assessment protocol Wu et al.  (2002), tends to build a composite index for measuring social vulnerability of coastal people to the environmental hazards. Population density, household size, female population, dependent people having age less than six years, male literacy rate, female literacy, agricultural dependency, landless workers, people in household industries are the nine most relevant indicators in the calculation of social vulnerability index (SoVI). Finally, the results reveal that the mouzas in Coastal Regulation Zone (CRZ) are less vulnerable than central part. Only the two mouzas viz. Gangasagar and Sibpur are highly vulnerable that situated at the southern CRZ.  The study draws attention to coastal scientists and policy makers for adopting effective mitigation measures from the coastal hazard impacts by studying micro level social vulnerability index of the mouzas in situ.

 

 

INTRODUCTION:

Social vulnerability is defined as the susceptibility of social groups, or an entire society, to potential losses from hazardous events and disasters or the ability of an individual within a household to recover from a natural hazard impact (Dunno et al. 2011, and Dwyer et al. 2004). Now-a-days, the social vulnerability index (SoVI) affords a relative spatial assessment of human-induced vulnerability to environmental hazards (Cutter et al. 2003) and thereby provides important information for policy makers and emergency managers (Boruff et al. 2005).

 

In our country, about 567.1 million people are affected and 5,225 people had been killed by coastal hazard in between 1985 to 2006 (Source: EM-DAT, CRED, University of Louvain, Belgium). Sagar is such types of coastal island falling in Sundarban region characterized by flatten topography, high population density and place of serious coastal hazards. Here, a lot of people each year become homeless by any type of disaster. The adverse impacts of various hazards are not uniformly distributed among and within nation, regions, communities, and groups of individuals (Clark et al. 1998).

Different communities can have different risks to hazard and vary in spatial as well as temporal dimensions. To evaluate the hazard potential from natural events along the coast, it is important to identify and measure the risk and vulnerability from those elements (Boruff et al. 2005). Risk is defined as the probability that a particular level of loss occurring as a result of a given level of hazard impact while vulnerability refers to the potential for casualty, destruction, damage, disruption or other forms of loss with respect to a particular hazard (Dunno et al. 2011). Here an attempt has made to assess the social vulnerability of different community groups to environmental hazards in the coastal area of Sagar based on census derived socioeconomic data.

 

About The Study Area:

Sagar Island is situated in the Hooghly estuary, southern most part of South 24 Parganas district. With the area of 282.11 sq km, it has about 68 km broad shoreline. It is a fully inhabited island; the 2001 national census estimates the population of the island at 1,85,644, with a population density of 658 people per sq. km and literacy rate about 78.92 percent. The physiographic features of Sagar Island consisting of mud flats, salt marshes, sandy beaches and dunes, are resulted from fluvio-marine geomorphic process. The entire island is well drained by numerous tidal creeks too.

 

A profile of Hazards in the Sagar Island:

Due to having flat topography, the margins of the island are usually inundated during cyclone and tidal surges (Ghosh et al.  2001). Three of the most serious tropical storms that ever affected the island occurred on 21 May 1833, 5 October 1864 and 17 October 1942 (Bandyopadhyay, 1997). On May 25, 2009, a tropical cyclone (Aila) hit the island with a wind speed of 110 km/hr and about 300 people were killed in the Sagar Island alone in Indian Sundarbans (Ghosh et al.  2012).

 

Sagar is several times victimized by tropical cyclones tidal fluctuation, heavy rainfall and flooding that modify the morphology of island consequently the beach erosion takes place more and the shoreline changes seriously (Gopinath 2010). The land loss due to erosion in between 2001 to 2009 was about 5.343 sq km or 5.23 percent (Hazra et al. 2010).

 

MATERIALS AND METHOD:

Setting up of social Vulnerability Indices:

Successful assessment of social vulnerability entirely depends upon selection of relevant socioeconomic indicators of a region under study. Cutter and Boruff (2003) identify 39 socioeconomic variables out of 41, to create an index of social vulnerability for the 213 US coastal countries based on 2000 US Census. Later Fekete (2009) used 41 variables to make social vulnerability index in context to river-flood in Germany. The review highlights in the background on developed countries like USA or Germany where Census data can provides micro level socioeconomic information. However, in the developing countries like India limited number of socioeconomic information is available at the village level census database. Based on 1991 Census of India, Leichenko et al.  (2004) choose five socioeconomic indices in their work of social vulnerability analysis. In 2007, Bhattacharya et al.  in their research of vulnerability to drought, cyclone and floods in India, developed three sub-indices of sensitivity and adaptive capacity of people to the former hazards. In the current paper, the vulnerability indicators chosen were derived from 2001 census of India (Table 2).

 

Number of household, density of population, percentage of female population and dependent population have been preferred as the important indicators in the calculation of SoVI indices. These indices are superlative measures of demographic sensitivity of any region. Sensitivity of agriculture is considered important given its role as livelihood supplier for a large segment of population and it is measured through dependency of a region on agriculture (Bhattacharya et al.  2007). A higher level of agricultural dependency will increase the region’s vulnerability to the climatic variability (Leichenko et al.  2004) and various type of coastal hazards. Vulnerability of agricultural and industrial workforce is the measures of inequality in landholdings and inequality in household industrial workforce present in various mouza. A mouza unit with larger amount of landless labourers and household industrial workers have greater sensitivity and more vulnerable to the hazards. Human capital is measured by the male literacy rate that indicates human ability to cope with aftermath of any disastrous event. Leichenko et al. (2004) used female literacy and child survival index at the consent that those have significant impact on child mortality rates and fertility rate. However, in the present study of social vulnerability to coastal hazards in Sagar island the preceding indicator has been incorporated regarding its significant role to reduce vulnerability by taking care of their child to adverse impacts of hazards.   

 

 

 

Table 1: Occurrence of cyclone over Bay of Bengal from 1891 to 1989

Month	January	February	March	April	May	June	July	August	September	October	November	December	Total
No. of Cyclones	6	1	4	21	49	38	41	30	39	79	93	41	442
Source: CPCB, 1999

 

Table 2 Variable chosen in the social vulnerability assessment

Sl. No.	Dimension	Indicator	Dimension Index	Social Vulnerability Index (SoVI)
1	Density of Population	Population density in each mouza  group	Density Index (Di)
2	No. of Household	No. of household in each mouza  group	Household Index (Hi)
3	Female population	Percentage of Female Population	Female Drawback Index (FDi)
4	Agricultural dependency	Percentage of workers employed in agriculture	Agricultural Dependency Index (ADi)
5	Vulnerability of agricultural workforce	Percentage of landless labourers in agricultural workforce	Landlessness Index (Li)
6	Vulnerability of industrial workforce	Percentage of workers employed in household industries*	Industrial Dependency Index (IDi)
7	Human capital	Literacy rate (Male)	Education Index (1- index value) (Ei)
8	Dependent population	Percent of people having age of less than 6 years	Dependency Index (DPi)
9	Female literacy and child survival chances	Female literacy rate	Female Literacy and Child Survival Index (1- index value) (FLi)
Source: Modified from Leichenko et al.  (2004), * only household industries present at the study area

 

 

Preparation of Composite Index:

To examine the social vulnerability in Sagar block of South 24 Parganas, various socioeconomic data were acquired from the 2001 census of India. HERO (Human-Environment Regional Observatory project) vulnerability assessment protocol (Wu et al.  2002) was used in the present study of vulnerability assessment. The formulas are given below:

 

 

Where, Ii is the vulnerability index for each social variable i. Vi is the value of i variable in each Mouza  division. Vmax is the maximum value for variable in the region.

To ensure that the higher index value indicates high vulnerability in all cases the following equation has been used for the selected variable:

 

 

As there is no specific weights to individual variables, the composite social vulnerability index for each census mouza  group  is defined as the arithmetic mean of the vulnerability indices of all variables.

 

The composite vulnerability indices range from zero to one; higher index values indicate higher vulnerability and vice versa.

 

After computing the composite indices, simple cartographic representation technique has been used to prepare the social vulnerability map of this island.  

 

RESULTS AND DISCUSSION:

Social vulnerability refers to the ability of community or social group to get ready and recover from any type of hazards. In the current study, mouza level social vulnerability index has been computed for the Sagar island of Sundarban delta based on socioeconomic data derived from 2001 census of India. SoVI map has also been produced to graphically represent the index value of the mouza divisions. The map illustrates the relative distribution of social ability to respond from disaster. The vulnerability map (Fig. 1) shows that the two southern most mouzas  i.e. Gangasagar (38), and Sibpur (43) are severally vulnerable. The mouzas of Khas Ramkarerchhar (28), Haradhanpur (20), Sumatinagar (22), Krishnanagar (29), in the middle part and Kachubaria (6), Dhaspara (11), in the northern part of the island are falling in the high vulnerable zone.  The analysis of vulnerability reveals that the Gangasagar and Sibpur mouza  falling in category of high vulnerable zone have a risk to the severe bank erosion and cyclonic events relatively more due to their critical location than the mouzas of island located in centre. The mouzas of Naraharipur (30), Radha Krishnapur (32), Chandipur (33), Mahishamari (35), are situuated in the south-western coastal part, and Kastala (4), Muri Ganga (7), Sikarpur (8), Ramkrishnapur (9), Gobindapur (17), Debimathurapur (18), in the north eastern part of the island are falling in the low composite index class. Within this vulnerable group all the factors does not go beyond the index value of 0.3. This signifies that the said mouzas have highest abiltity to cope with any type of coastal hazards than the rest.

 

 

Table 3 Correlations among the 9 socio-economic indicators of SoVI

		Hi	Di	FDi	DPi	Ei	FLi	ADi	Li	Ldi
Hi	Pearson Correlation	1	.328*	.996**	.973**	-.989**	-.966**	.646**	.781**	.384*
	Sig. (2-tailed)		0.034	0	0	0	0	0	0	0.012
Di	Pearson Correlation	.328*	1	.333*	.313*	-.321*	-.324*	0.284	.364*	0.248
	Sig. (2-tailed)	0.034		0.031	0.044	0.038	0.037	0.068	0.018	0.113
FDI	Pearson Correlation	.996**	.333*	1	.984**	-.988**	-.963**	.656**	.791**	.392*
	Sig. (2-tailed)	0	0.031		0	0	0	0	0	0.01
Dpi	Pearson Correlation	.973**	.313*	.984**	1	-.959**	-.921**	.645**	.780**	.395**
	Sig. (2-tailed)	0	0.044	0		0	0	0	0	0.01
Ei	Pearson Correlation	-.989**	-.321*	-.988**	-.959**	1	.988**	-.689**	-.792**	-.380*
	Sig. (2-tailed)	0	0.038	0	0		0	0	0	0.013
Fli	Pearson Correlation	-.966**	-.324*	-.963**	-.921**	.988**	1	-.677**	-.791**	-.396**
	Sig. (2-tailed)	0	0.037	0	0	0		0	0	0.009
Adi	Pearson Correlation	.646**	0.284	.656**	.645**	-.689**	-.677**	1	.534**	.335*
	Sig. (2-tailed)	0	0.068	0	0	0	0		0	0.03
Li	Pearson Correlation	.781**	.364*	.791**	.780**	-.792**	-.791**	.534**	1	.315*
	Sig. (2-tailed)	0	0.018	0	0	0	0	0		0.042
Idi	Pearson Correlation	.384*	0.248	.392*	.395**	-.380*	-.396**	.335*	.315*	1
	Sig. (2-tailed)	0.012	0.113	0.01	0.01	0.013	0.009	0.03	0.042
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

The correlation matrix of the socioeconomic indicators portrays the relative importance of the indicators by showing the association between different variable. Variables of education index (Ei), female literacy rate and child survival index (FLi) are negatively correlated with all the indices of social vulnerability indicators. Since the Education Index and Child Survival Index portray the reverse situation of the matters to all the indicators of social vulnerability thus it react negatively. The r-values are maximum to Household Index (Hi), Density Index (Di) but low to the Agricultural Dependency Index (ADi) and Index of Household industry. In analysis of correlation, it was vivid that the Household Index (Hi), which is one of the significant causes of vulnerability, is more or less highly interrelated with all other categories. This means that bigger the household size leads to the larger command over indices of vulnerability. The index of household industries is poorly correlated with all other categories. This indicates that the less importance of this variable to control vulnerability indices.  

 

Overpopulation is one of the foremost problem of the island that increasing pressure on the landmass by means of space to live, resources, pollution, and environmental degradation (Gopinath 2010). Correlation matrix reveals the significant impact of household size on density of population and number of female in those mouza divisions. Fig. 2 explain that three indices, viz. household (Hi), density (Di) and female drawback (FDi) are roughly high (greater than 0.6) in those mouzas of high vulnerable category. Agriculture is the pre-dominant economic activities practiced through the study area. The total cultivable land of Sagar Island is 12388.76 hectares, which provides livelihood to a total of 15.08% cultivator of that area. Since the quality of agricultural field as well as soil

 

Health largely determines the productivity of agricultural crops, degradation of its quality influences upon basic livelihood pattern of the associating people. Table 1 indicates that most of the cyclonic events occur during the harvesting periods of paddy cultivation. Apart from that, the island being situated at mouth of Hugli estuary, most of agricultural field bordering the coast is highly influenced by the salinity.

 

Hence, the villages with greater agricultural dependency index have significant impact to the coastal hazards and thereby creates maximum index of social vulnerability. Fig. 3 shows that Sumatinagar, Khas Ramkarerchhar, Krishnanagar and Harinbari mouza having higher standardized values of agricultural dependency (greater than 0.5), experiences maximum composite value of social vulnerability. On the other hand, landless agriculture workers are comparatively more sensitive than the cultivator do. Household industries developed here as an allied activity with agriculture and people involved in this sector in the form of dry fish making, pottering etc. that bears a significant role in the socioeconomic condition of the communities of Sagar island. The maximum index value of said indicator is only found in the Sibpur, Mandirtala, Sapkhali, Kachubaria and Dhaspara mouza. 

 

CONCLUSION:

The concept of social vulnerability is a multidimensional process that changes over space and time, with amplifying of developmental activities and prospers of economy the picture may be proficient to alter. The result of social vulnerability measurement is composed of nine census derived socioeconomic data for the year 2001, revealing greater composite index value of major villages in the central part of the island. The low vulnerable mouzas are found along the CRZ of the island, especially northeastern and southwestern part. Since the population of the Sagar Island increase rapidly, the people are migrating toward the coastal regulation zone (Gopinath 2010), consequently the mouzas in this zone gradually converted into more vulnerable in terms of socioeconomic settings. Adding to woos, climatic change and sea level rise are the foremost trouble in coastal zones around the world.  At a convenient, the Sagar Island also gets affected from the said problems gradually. Finally, the results of the study can provide a rough estimation of survival chance of the villagers from exposure condition to environmental hazards and thereby it may help planners and researchers to figure out about planning necessity at micro level.

 

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