(untitled) (MAUSAM, 2010)
The Primary aim in this paper is to find an alternative approach that consists of modeling the pattern of dry and wet spell over some districts of Assam. The Markov Chain Model is used to predict the length of dry and wet spells during the Indian summer monsoon season (June to September). This information may help the agronomists and agricultural scientists in crop planning. Five districts viz., Dibrugarh, Kamrup, Sonitpur, Dhemaji and North Lakhimpur are considered here for this study. Markov Chain Model is fitted for each of the district and the results of the five districts are pooled. This pooled result reveals that during the period 1987-1992, the probability for the day being wet when the immediately preceding day is dry for different years varies from 0.44 to 0.54 while the probability of the day being wet when the immediately preceding day is wet for different years varies from 0.74 to 0.86. It is also found that in the Indian summer monsoon season after about every consecutive 4 - 7 wet days a dry day is expected to occur whereas alter about consecutive 2 dry days, a wet day is expected to occur. The number of days required for the process to reach the state of equilibrium varies from 4 - 7 days.