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Markov chain analysis of weekly rainfall data in determining drought-proneness

Author

Listed:
  • Pabitra Banik
  • Abhyudy Mandal
  • M. Sayedur Rahman

Abstract

Markov chain models have been used to evaluate probabilities of getting a sequence of wet and dry weeks during South-West monsoon period over the districts Purulia in West Bengal and Giridih in Bihar state and dry farming tract in the state of Maharashtra of India. An index based on the parameters of this model has been suggested to indicate the extend of drought-proneness of a region. This study will be useful to agricultural planners and irrigation engineers to identifying the areas where agricultural development should be focused as a long term drought mitigation strategy. Also this study will contribute toward a better understanding of the climatology of drought in a major drought-prone region of the world.

Suggested Citation

  • Pabitra Banik & Abhyudy Mandal & M. Sayedur Rahman, 2002. "Markov chain analysis of weekly rainfall data in determining drought-proneness," Discrete Dynamics in Nature and Society, Hindawi, vol. 7, pages 1-9, January.
    • Handle: RePEc:hin:jnddns:493051
    DOI: 10.1155/S1026022602000262
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    Cited by:

    1. Wentao Yang & Min Deng & Jianbo Tang & Rui Jin, 2020. "On the use of Markov chain models for drought class transition analysis while considering spatial effects," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2945-2959, September.

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