Indian Journal of Soil Conservation

Among different weather variables, rainfall is the major determinant and deciding factor for success or failure of rainfed agriculture. For agricultural planning and farming operations, information about occurrence of dry and wet periods is important and will have dominating effect on the crop yield and there by influence the livelihoods of rural community. The successor failure of crop closely linked with the rainfall patterns. Even in high rainfall regions, the occurrence of dry and wet spell during the different phenophases of the crop decides the yield. In this study Markov chain model has been employed to know the initial and conditional probability of having a dry or a wet week and also the occurrence of consecutive dry or wet periods of 2 or 3 weeks for selected stations of Bihar State representing different agro-ecological zones. Average annual rainfall of 1222.4, 1538.0, 1162.7 and 1134.5 mm were received at Pusa, Purnia, Bhagalpur and Patna districts, respectively. This indicates that among the different zones, zone-II gets more annual rainfall followed by zone I, but the annual variability is lower for zone-IIIB followed by zone-I. The initial probability of occurrence of dry week is high (more than 60%) upto 23rd standard meteorological week for zones-I, IIIA and IIIB while it is upto 18th week for zone-II. The probability occurrence of two consecutive wet weeks is high (more than 60%) from 28th to 34th weeks, but it is fluctuating and in the case of probability of occurrence of three consecutive weeks, it is never above 60% even in the peak monsoon months of July and August for zone-I. However, the probability occurrence of three consecutive wet weeks is high (more than 50%) during the 29th week only and all other weeks between 26th to 39th weeks are below 50 per cent for zone-IIIA. Based on the rainfall pattern and its distribution, different crop management strategies as well as remedies are suggested to explore maximum rainfall received during the season to maximize the production and minimize the existing gap between the potential and actual production.