Citation

Krishnan P, Ananthan PS, Purvaja R, Joyson Joe Jeevamani J, Amali Infantina J, Srinivasa Rao C, Anand A, Mahendra RS, Sekar I, Kareemulla K, Biswas A, Kalpana Sastry R, Ramesh R. Ambio 2019; 48(2): 192-212.

Affiliation

National Centre for Sustainable Coastal Management (NCSCM), Ministry of Environment Forest and Climate Change, Govt. of India, Anna University Campus, Guindy, Chennai, 600 025, India.

Copyright

(Copyright © 2019, Royal Swedish Academy of Sciences, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s13280-018-1061-8

PMID

29855893

Abstract

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

Language: en

Keywords

Adaptive capacity; Climate change; Exposure; Multi-hazard map; Sensitivity; Socio-economic