Discrete Dynamics in Nature and Society
Volume 7 (2002), Issue 4, Pages 231-239
doi:10.1155/S1026022602000262

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

Pabitra Banik,1 Abhyudy Mandal,1 and M. Sayedur Rahman2

1Agricultural Science Unit, Indian Statistical Institute, Calcutta 700 035, India
2Associate Professor, Department of Statistics, Rajshahi University, Bangladesh

Received 24 October 2000

Copyright © 2002 Pabitra Banik et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.