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Mapping vulnerability to multiple stressors: climate change and globalisation in India

There is growing recognition in the human dimensions research community that climate change impact studies must take into account the effects of other ongoing global changes, yet there has been no systematic methodology to study climate change vulnerability in the context of multiple stressors. Using the example of Indian agriculture, this paper presents a methodology for investigating regional vulnerability to climate change in combination with other global stressors.

This method, which relies on both vulnerability mapping and local-level case studies, may be used to assess differential vulnerability for any particular sector within a nation or region, and can serve as a basis for targeting policy interventions.

Key findings:

  • Higher levels of adaptive capacity in districts located along the Indo-Gangetic Plains (except Bihar), and lower adaptive capacity in the interior portions of the country, particularly in the states of Bihar, Rajasthan, Madhya Pradesh, Maharashtra, Andhra Pradesh, and Karnataka.
  • Potential shifts in climate change sensitivity may occur as the result of exposure to climate change.
  • Assessment of adaptive capacity in combination with climate change sensitivity and exposure is crucial for differentiating relative vulnerability.
  • Regions with high or very high import sensitivity are found throughout the country, but are most concentrated in the southern and central states of Karnataka, Maharashtra, Madhya Pradesh, and in the eastern state of Assam.
  • Areas of ‘double exposure’ both to climate change and globalisation include Rajasthan, Gujarat, Madhya Pradesh, as well as southern Bihar and western Maharashtra.


  • The results demonstrate a menthod for mapping vulnerability that can be used to assess climate impacts in the context of a range of societal changes.
  • It succeeds in providing a means for evaluating the relative distribution of vulnerability to multiple stressors at a sub-national level.
  • This method helps identify those locations where olicy intervention is most critical, both geographically and thematically.
  • One limitation is that mapping vulnerability at district level may lead to a false sense of precision.
  • While the case studies suggested that institutions play a critical role in both constraining and enabling farmer adaptation, further study of the role of institutions in influencing vulnerability is needed.