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Statistical Analysis of Community Vulnerability to Tsunami in Nagapattinam Coastal Area

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INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 Statistical Analysis Of Community Vulnerability To Tsunami In Nagapattinam Coastal Area Dr. Ilango Sivakumar , Dr. S.Selvamuthukumar Abstract:The main intention of this study is to analyse the vulnerability condition of coastal community to Tsunami. The study involves in finding out the human vulnerability by means of questionnaire survey made with the community, responsible officials and administration of the considered region for scrutinizing the current Tsunami Warning and Evacuation Process (TWEP) using vulnerability factors. The assessment of community vulnerability tasks on twenty-four issues based on seven factors on the site concerning TWEP. The obtained factors from the assessment are used for the statistical analysis of community vulnerability. Index Terms: Tsunami, Vulnerability, Warning, Evacuation, Statistical Analysis, Coastal area, Risk —————————— —————————— 1. INTRODUCTION and to identify the pitfalls in existing TWEP and to enhance Tsunamis are dangerous and may cause massive loss, a better community based TWEP. destruction and disruption to coastal lives, infrastructure and all other economic activities. the 2004 Tsunami in india 2. DESCRIPTION OF STUDY AREA caused major damages along the coastal areas of In 2004 Tsunami, severe destructions are recorded along Tamilnadu, Andhra Pradesh, and Kerala where, most of the the coast of Nagapattinam because of its geographic damages and death toll were recorded in Nagapattinam setting, prone to much inundation [19]. It is observed that district, tamil nadu due to the inundation of water the maximum run up level of sea water is 3.9 m and transgressed up to 1 km into the mainland of Nagapattinam inundation in land is 750 m in this area (MoES, 2005 & [2] [3]. This is due to that Tsunami hazard management Collectorate, Nagapatinam). Hence, the coast alone was given a low priority by local governments without being recorded 6065 confirmed deaths; which is equivalent to strongly pressed in local plans and lack of public concern 76% of the state‟s total toll. [4]. Hence The 2004 Tsunami significantly raised public The area selected for the study consists of three hamlets awareness about the hazard of Tsunamis and the need for namely Keechankuppam, Akkaraipettai and Kallar whose Tsunami early warning in the Indian Ocean [5]. This event major occupation is fishing. These three hamlets come led to broad international efforts to design and implement under North Poigainallur panchayath in Nagapattinam block the Tsunami early warning system on one hand, and on the which is situated 2 km away from the Nagapattinam town other, to strengthen community based disaster and 8 km from Velankanni. It is surrounded by the river management strategies. Polsky [6] proposed an eight‐step Kaduvaiyar and more so by the Bay of Bengal. method for vulnerability assessment. The steps are Define Nearly 50% of the people who lost their lives in the study area, become aware of the study area and its Nagapattinam district belong to Akkaraipettai, contexts, hypothesize who (or what) is vulnerable to what, Keechankuppam and Kallar fishing hamlets (Collectorate develop a causal model of vulnerability, find indicators for Nagapatinam and NCRC), because of which these villages the components of vulnerability, weight and combine the are almost like an island. The risk factor is high in this place indicators, project future vulnerability, communicate because perpendicular evacuation is not possible during vulnerability creatively. The main objective of this study is to Tsunami. Hence this area is selected for study. analyze the community vulnerability using statistical test ———————————————— Dr Ilango Sivakumar, Assistant Professor in Civil Engineering, Government College of Engineering, Thanjavur, Tamilnadu, India, Email: [email protected] Dr S.Selvamuthukumar, Assistant Professor in Civil Engineering, Government College of Engineering, Thanjavur, Tamilnadu, India, Email: [email protected] Fig. 1 Satellite Map of Study Area 6262 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 3. METHODOLOGY The study involves in drawing an enormous attention on 3.1 Identification of Factors Influencing the Community literature surveys outlining that the community vulnerability Vulnerability is closely related to TWEP. On the basis of the identified With the help of a thorough literature survey and experts weakness a questionnaire is prepared. Even though the opinion the factors greatly influencing the community issue is common to community and officials, the vulnerability are identified and presented in Table 1. questionnaire set to the officials reflect the view of community. Table 1 Factors Influencing TWEP S.No. TWEP Issues Related Factor 1 Evacuation Programme 2 Mock Drill Awareness 3 New Developments 4 Safe Places 5 Evacuation Instructions 6 Govt. Organization Services Service 7 Government Vehicle Provision 8 Shelter Maintenance 9 Perpendicular Evacuation Route 10 Enough Higher Ground 11 Short Route to Safe Place Facility 12 Place for Movable Assets 13 Shelter Provision 14 Easy Access Shelter 15 Facilities During Emergency 16 Belief in Next Tsunami Belief 17 TWEP Save Lives 18 Managing Night Time Emergencies 19 Warning Alert Through Announcement/Siren Expectation 20 Warning Alert Via TV/Radio 21 Warning Alert Through Mobile 22 Night Time Emergency Experience Experience 23 False Warning Experience 24 View on Current TWEP Appraisal of TWEP 3.2 Data Collection is divided as literate and illiterate for 159 respondents out of A questionnaire is a preferable and a simple technique for which 72.3% (115) and 27.7% (44) are literates and data collection. The questionnaire should be in a sharp, illiterates respectively. The occupation dependency of the apparent and well-designed manner so that it would provide community is classified as, (i) fisheries (ii) cultivation (iii) reliable and relevant data from the respondents. Sample agriculture labour (iv) non worker. Where, 55.3%, 17.6%, sizes of 159 respondents are selected from the three 11.3% and 15.7% are involved in fisheries, cultivators, hamlets (71 members from Keechankuppam, 67 from agricultural labourers and non-workers respectively. The Akkaraipettai and 21 from Kallar). number of respondents selected from three hamlets namely Keechankuppam, Akkaraipettai and Kallar which are 3.3 Data Analysis 71(44.7%), 67(42.1%) and 21(13.2%) respectively. These The collected data is analyzed using SPSS software. The three hamlets belong to Vadakkupoigainallur village, profile of the respondents like gender, education, Nagapattinam district. occupation, name of hamlets, building vulnerability is prepared using descriptive statistics. The received 5. SIGNIFICANCE OF RESPONDENTS responses are grouped under „yes‟ or „no‟ category. Further the group is subdivided into „fair‟ and „should PERSONAL CHARACTERISTICS ON improve‟ groups with respect to community appraisal of VULNERABILITY FACTORS TWEP. On comparing the proportions of „fair‟ and „should The significance level of various respondents of the seven improve‟ groups the vulnerable factors are obtained. The vulnerability factors like awareness, service, facility, belief, same procedure is repeated for official group also. The expectation, experience and building vulnerability are respondents group are tested whether they are statistically discussed below. significant using chi square, ANOVA and t-test. 5.1 Significance of Gender Table shows the number of samples, mean values of each 4. DATA ANALYSIS AND CLASSIFICATION gender, sig. and t-value for the vulnerability factors. The null OF VARIOUS RESPONDENTS hypotheses are considered to find out the significant The details of 159 community respondents, i.e. their relation between the male and female respondents in gender, education, occupation and hamlet are taken for the vulnerability factors. study. Among the 159 respondents, 111 and 48 are males and females respectively. The furnished data on education 6263 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 Table 2 t-test: Vulnerability Factors with Respondents Gender Variables Gender N Mean t-value Sig. (2-tailed) Male 111 6.9 Awareness 3.22 0 Female 48 6.29 Male 111 6.15 Service 0.03 0.97 Female 48 6.14 Male 111 10.91 Facility 0.29 0.77 Female 48 10.83 Male 111 4.55 Belief 0.44 0.65 Female 48 4.47 Male 111 4.81 Expectation -1.08 0.28 Female 48 4.93 Male 111 2.62 Experience -3.73 0.71 Female 48 2.66 Male 111 10.41 Building vulnerability -1.23 0.22 Female 48 10.85 From this table the factor awareness has t-value 3.22 and building vulnerability factors between the male and female the significance value 0 which is lesser than 0.05. So the respondents. null hypothesis is rejected and hence concluded that there is a statistically significant difference in the mean of the 5.2 Significance of Education awareness factor between the male and female The null hypotheses are considered to find out the respondents at 95% confidence level. In the awareness significant relation between the literate and illiterate factor the mean value of male (6.9) is slightly higher than respondents in vulnerability factors that of the female (6.29). The lowest mean indicates lack of awareness in female and when compared with male respondents. All the other variables have significance
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