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Original Articles

Mapping and analysis of the physical vulnerability of coastal Tamil Nadu

, , &
Pages 1879-1895 | Received 18 Jan 2019, Accepted 30 Mar 2019, Published online: 24 Apr 2019
 

Abstract

This is an integrated study to classify Tamil Nadu Coast in terms of its vulnerability to coastal processes. It is accomplished through estimating Coastal Vulnerability Index (CVI) for the entire stretch of the said coast using weighted averages of six parameters, viz., geomorphology, shoreline changes, coastal slope, and relative sea level rise, mean significant wave height and mean tidal range. Thus, CVI evaluates the state of the coast in terms of level of risk hovering on it as and when it is affected by oceanic hazards. The target of this study is to evaluate the vulnerability status of coastal stretches of 35 taluks of Tamil Nadu. Twenty one percent of the coastal stretch is under very high vulnerability level. Following this is 36% stretch under high vulnerability state. Another 34% coastal stretch is in moderate setting. Low vulnerability state prevails about 6%. Further, it is learnt that there are only 2% of Tamil Nadu coastal region coming under the least vulnerable category. The study revealed the very high vulnerability of Nagapattinam coastal region. The present study may also help create awareness among people about marine natural hazards such as coastal erosion, inundation, loss of life and their properties.

Acknowledgments

Authors sincerely thank the Indian National Center for Ocean Information Services (INCOIS) and for providing tide data for three different stations. They also thank Dr. R. Jegankumar (Professor and Head) and Mr. A. Balasundareshwaran, Department of Geography, Bharathidasan University, Thiruchirappalli, for their guidance and help during this study.

Notes

1 Districts and taluks are administrative divisions of land areas based on population strength; several taluks make a district.

2 European Centre for Medium Range Weather Forecasts

3 WXTide32 - a free Windows tide and current prediction program.

Additional information

Funding

The first author Sasi Mary Priya Rajan acknowledges the financial support from the University Grants Commission (UGC) under its scheme of Maulana Azad National Fellowship [Contract No. F1-17.1/2012-13/MANF-2012-13-CHR-TAM-13890/(SA-III/Website)]

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