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Probabilistic Drought Analysis of Weekly Rainfall Data using Markov Chain Model

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Title Probabilistic Drought Analysis of Weekly Rainfall Data using Markov Chain Model
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Creator Alam NM, Sharma GC, Jana C, Patra S, Sharma NK, Raizada, Adhikary PP, Mishra PK
 
Subject Drought Proneness Index, Dry Spell, Markov Chain Probability Model, Stationary Distribution, Steady State Probability.
 
Description Not Available
This paper makes an attempt to investigate the pattern of occurrence of wet and dry weeks in three different locations of drought prone areas of India, i.e. Datia in Madhya Pradesh, Bellary in Karnataka and Solapur in Maharashtra. An index of drought proneness to evaluate its extent of degree has been worked out. Besides the probability of getting wet weeks consecutively for more than six, eight and ten weeks have been worked out. Also, the probability of sequence of more than three dry weeks is computed. The results of application of the Markov models are presented and discussed, exhibiting in particular the usefulness of transition probability matrix to agricultural planners and policy makers to understand the climatology of drought in rain fed areas so as to plan long term drought mitigation strategy.
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Date 2017-03-22T07:31:09Z
2017-03-22T07:31:09Z
2015-05-30
 
Type Research Paper
 
Identifier Alam NM, Sharma GC, Jana C, Patra S, Sharma NK, Raizada, Adhikary PP, Mishra PK (2015) Probabilistic Drought Analysis of Weekly Rainfall Data using Markov Chain Model. Journal of Reliability and Statistical Studies 8(1): 105-114
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http://krishi.icar.gov.in/jspui/handle/123456789/3207
 
Language English
 
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Publisher Not Available