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Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India

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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.

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Acknowledgements

The framework developed in this study for assessment of coastal vulnerability was benefitted by the insights of Sh. V. Rajagopalan, the Former Secretary to Govt. of India, Ministry of Environment, Forests and Climate Change; Dr. Rabikumar, Secretary, National Biodiversity Authority, Government of India and Dr. S. Senthil Kumar, Indira Gandhi National Forest Academy, Dehradun. The study was funded by the Mangrove Cell of Maharashtra, under the UNDP’s Program, “Mainstreaming Coastal and Marine Biodiversity Conservation into Production Sectors in Sindhudurg Coast in Maharashtra”. The authors thank Professor Ramachandra Bhatta, Emeritus Professor, Indian Council of Agricultural Research, New Delhi; Dr. R. Soundararajan, MoEFCC-NCSCM, Chennai; Dr. B. Ganesh Kumar, ICAR-NAARM, Hyderabad; Dr. P.C. Mohanty, INCOIS, Hyderabad and S.P. Subash, ICAR-NCAP, New Delhi for their valuable inputs.

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  1. ICAR-National Academy for Agricultural Research Management (NAARM), Rajendra Nagar, Hyderabad, Telangana, 500 030, India

    Pandian Krishnan, Cherukumalli Srinivasa Rao, Iyyapa Sekar, Kalakada Kareemulla & Regulagedda Kalpana Sastry

  2. ICAR-Central Institute of Fisheries Education (CIFE), Versova, Mumbai, Maharashtra, 400 061, India

    Pachampalayam Shanmugam Ananthan

  3. 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

    Ramachandran Purvaja, Jeyapaul Joyson Joe Jeevamani, John Amali Infantina & Ramachandran Ramesh

  4. Indian Statistical Institute-Chennai Centre, Ministry of Statistics and Programme Implementation, Government of India, Chennai, 600 029, India

    Amit Biswas

  5. Regional Remote Sensing Centre (NRSC-RRSC), Indian Space Research Organization (ISRO), Nagpur, 440 010, India

    Arur Anand

  6. Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences, Govt. of India, Hyderabad, 500 090, India

    Ranganalli Somashekharappa Mahendra

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  1. Pandian Krishnan
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Krishnan, P., Ananthan, P.S., Purvaja, R. et al. Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India. Ambio 48, 192–212 (2019). https://doi.org/10.1007/s13280-018-1061-8

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