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WEEKLY RAINFALL ANALYSIS FOR CROP PLANNING USING MARKOV’S CHAIN MODEL FOR KUMULUR
S. VANITHA, V. RAVIKUMAR

Published in: International Journal of Agriculture Sciences
Volume- 9, Issue-42, pp.4679-4682, Sep 2017
DPI :-> 16.10077.IJAS.2017.V9I42.46794682.2019



Abstract
Water scarcity is a major problem in arid and semi-arid areas. Climate change and its outcomes on precipitation and water resource is the other problem in these areas. It is necessary to know the sequence of dry and wet periods for successful agricultural management and planning of soil and water conservation measures. Probability analysis is a very useful tool for making important decisions in agricultural operations. In this study, Markov chain model has been extensively used to study spell distribution. For this purpose a week period was considered as an optimum length of time. In this study, probabilities of occurrence of wet week (Pw), Dry week (Pd), wet week preceded by wet week (Pww),dry week preceded by dry week (Pdd), two and three consecutive wet and dry weeks (P2w,P2d,P3w and P3d) at a threshold rainfall limit of 20 mm/week is calculated. In this analysis, daily rainfall data was converted to weekly period for 30 years from 1986 – 2015 for Kumulur, Trichy district, Tamil Nadu. Markov chain model has been utilized to derive the probability of dry or wet weeks and also forward and backward accumulation of rain water suitable for crop production. This analysis can be helpful to find out different cropping pattern including intercropping and sequence cropping suitable during that period

Key-Words / Index Term
Water scarcity, Rainfall Analysis

How to cite this article
S. VANITHA, V. RAVIKUMAR , “WEEKLY RAINFALL ANALYSIS FOR CROP PLANNING USING MARKOV’S CHAIN MODEL FOR KUMULUR”, International Journal of Agriculture Sciences, 9, Issue-42, pp.4679-4682, Sep 2017. DPI:16.10077.IJAS.V9.I42.2019