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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 N.M. Alam
G.C. Sharma
C. Jana
S. Patra
N.K. Sharma
A.Raizada
ParthaPratim Adhikary
P.K. Mishra
 
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.
Not Available
 
Date 2020-05-15T05:34:17Z
2020-05-15T05:34:17Z
2015-05-30
 
Type Research Paper
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/35645
 
Language English
 
Relation Not Available;
 
Publisher Not Available