Dry and wet spell probability by Markov chain model- a case study of North Lakhimpur (Assam), India - Dabral, Parmendra Prasad; Purkayastha, Kuntal; Aram, Mai (International Journal of Agricultural and Biological Engineering, 2014)
Abstract: For the purpose of crop planning and to carry out the agricultural practices, it is important to know the sequence of dry and wet periods. The present study was undertaken with the objectives to forecast dry and wet spell analysis using Markov chain model and also to find out the exact time of onset and termination of monsoon at study area for North Lakhimpur (Assam), India using weekly rainfall data for a period of 24 years. The results indicated that probability of occurrence of dry week is higher from week 1st to 14th and also from week 41st to 52nd. The range of probability of occurrence of dry week in these weeks varies from 41.67% to 100%. Probability of occurrence of wet week is higher from week 17th to 40th. The range of probability of wet week in these weeks varies from 66.67% to 100%. Week 1st to 4th and 43rd to 52nd of the year remains under stress on an average, as there are 50% to 95.83% chances of occurrence of two consecutive dry weeks. The analysis showed that monsoon starts effectively from week 23rd (4th June to 10th June) in North Lakhimpur. The week 25th (18th June to 24th June) is ideal time for initiation of wet land preparation for growing short duration rice variety. Pre-monsoon effectively starts from week 14th (2nd April to 8th April). On week 14th sowing of summer maize (rain fed) may be done. Week 15th (9th April to 15th April) is ideal time for initiation of wet land preparation for growing long duration rice variety.Keywords: forecast, probability, dry and wet spell, Markov chain model, onset and withdrawal of monsoonDOI: 10.3965/j.ijabe.20140706.002Citation: Dabral P P, Purkayastha K, Aram M. Dry and wet spell probability by Markov chain model- a case study of North Lakhimpur (Assam), India. Int J Agric & Biol Eng, 2014; 7(6): 8－13.