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Pathways for drought resilient livelihoods based on people’s perception

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  • Pramod K Singh

    (Institute of Rural Management Anand)

  • Harpalsinh Chudasama

    (Institute of Rural Management Anand)

Abstract

Drought is among the most dreaded threats as far as natural disasters are concerned wielding, as it does, a significant impact on ecosystems, people’s livelihoods, and the socio-economic development of a country. A significantly large geographic area of India happens to be drought prone. In order to understand people’s response to the impacts of drought and their coping strategies, it is crucial to understand their perceptions. Studies investigating community perceptions relevant to drought impacts and concomitant adaptive behaviours are rare in India. This paper documents communities’ perceptions of impacts of drought on their livelihood assets and adaptation practices. It does this with the help of the fuzzy cognitive mapping approach in the Mahabubnagar district of India’s Telangana state. In order to develop pathways for drought resilient livelihoods we ran simulations for future drought scenarios with various bundles of adaptation strategies enabling us to evaluate their effectiveness in providing resilience against drought. The study also tested the suitability of various activation rules and transformation functions, used for running simulations. Incorporating stakeholders’ perceptions, knowledge and beliefs about impacts of droughts, and engaging them in the process of developing drought resilient livelihoods is expected to fine-tune the drought related policy-making.

Suggested Citation

  • Pramod K Singh & Harpalsinh Chudasama, 2017. "Pathways for drought resilient livelihoods based on people’s perception," Climatic Change, Springer, vol. 140(2), pages 179-193, January.
  • Handle: RePEc:spr:climat:v:140:y:2017:i:2:d:10.1007_s10584-016-1817-8
    DOI: 10.1007/s10584-016-1817-8
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    References listed on IDEAS

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    1. Pramod Singh & Abhishek Nair, 2014. "Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach," Climatic Change, Springer, vol. 127(3), pages 475-491, December.
    2. Lopolito, Antonio & Nardone, Gianluca & Prosperi, Maurizio & Sisto, Roberta & Stasi, Antonio, 2011. "Modeling the bio-refinery industry in rural areas: A participatory approach for policy options comparison," Ecological Economics, Elsevier, vol. 72(C), pages 18-27.
    3. Kyriakarakos, George & Patlitzianas, Konstantinos & Damasiotis, Markos & Papastefanakis, Dimitrios, 2014. "A fuzzy cognitive maps decision support system for renewables local planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 209-222.
    4. Vanwindekens, Frédéric M. & Stilmant, Didier & Baret, Philippe V., 2013. "Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems," Ecological Modelling, Elsevier, vol. 250(C), pages 352-362.
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    Cited by:

    1. Konstantinos Papageorgiou & Pramod K Singh & Elpiniki I Papageorgiou & Harpalsinh Chudasama & Dionysios Bochtis & George Stamoulis, 2020. "Participatory modelling for poverty alleviation using fuzzy cognitive maps and OWA learning aggregation," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-28, June.
    2. Pramod K. Singh & Harpalsinh Chudasama, 2017. "Assessing impacts and community preparedness to cyclones: a fuzzy cognitive mapping approach," Climatic Change, Springer, vol. 143(3), pages 337-354, August.

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