~ 154 ~ Journal of Pharmacognosy and Phytochemistry 2018; SP4: 154-173 E-ISSN: 2278-4136 P-ISSN: 2349-8234 JPP 2018; SP4: 154-173 Sakha Ram Shori Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Dr. HV Puranik Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Sahdev Nag Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Hemant Kumar Sinha Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Jeetentra Kumar Netam Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Pramod Kumar Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India Correspondence Sakha Ram Shori Department of Agricultural Meteorology, IGKV, Raipur, Chhattisgarh, India (Special Issue- 4) International Conference on Food Security and Sustainable Agriculture (Thailand on 21-24 December, 2018) Analyse the probabilities of dry spell status in different districts of Chhattisgarh State Sakha Ram Shori, Dr. HV Puranik, Sahdev Nag, Hemant Kumar Sinha, Jeetentra Kumar Netam and Pramod Kumar Abstract The initial probability of occurrence of dry spell was very high during SMW 22-23 ranging from 56-94, 75-98, 88-100 and 90-100% for 10, 20, 30 and 40 mm rainfall limits, but it was less during 24-38 SMW in most districts and tehsils. It was very low ranging from 00-38, 04-46, 10-54, 39-62% for the corresponding rainfall limits and again increased thereafter ranging as 42-100, 62-100, 71-100 and 81- 100 for the corresponding rainfall limits during 39 to 52 SMW being nearly 100% for nine weeks (44-52 SMW). The conditional probability of dry spell followed by next dry spell was very high during 25-37 SMW ranging from 00-67, 00- 58, 00-57 and 10-54 for rainfall limits of 10, 20, 30 and 40 mm respectively, after the other during rest of the year might have 100% probability of occurrence 22 & 44- 52, 22 & 41-52, 22 & 41-52 and 22-23 & 40-52 SMW. Keywords: Dry spell, Drought, initial probability, conditional probability Introduction Probability concept is usually used to demonstrate the importance of dry and wet spells for planning weather sensitive agricultural operations (Shrivastav et al. 2004) [4] . Markov chain probability model has been found suitable to describe the long-term frequency behavior of wet or dry weather spells. It has found wide application in studies on daily rainfall distribution. Markov chain probability model assumes that the probability of rainfall occurring on any day depends on whether the previous day was wet of rain. In the first order Markov chain the probability of an event that would occur on any single day depends only on the conditions during the proceeding day and is independent of events of further preceding days. The model calculates the initial probabilities of getting a dry spell/ wet spell in a given standard meteorological week. The calculation of conditional probabilities provides the information on the dry spell followed by dry spell or wet spell vice versa. Therefore, for effective crop and water resources planning, it is necessary to access the sequences of dry and wet spells during different growth stages of a crop. The dry and wet spell study can be effectively utilized to adjust the phenophases of the crops in such a way that critical moisture requiring growth stages are likely to coincide wet spells. The information on the length of dry spells could be used for deciding a particular crop or varieties in a given location and for breeding varieties of various maturity durations (Sivakumar, 1991) [5] . Information on dry spell lengths could be used in decision making with respect to supplementary irrigation and field operations in agriculture (Taley and Dalvi, 1991) [6] . The longest period of several long spells is of crucial importance in planning agricultural activities and managing the associated water supply systems. As dry period in one year is not necessarily the same as drying in another year the knowledge of these patterns has become increasingly important to understand (Mathugama and Peiris, 2011) [1] . A major challenge of drought research is to develop suitable methods and techniques for forecasting the onset and termination points of droughts (Panu and Sharma, 2002) [2] . Materials Methods Daily rainfall data of 57 stations to represent 27 districts of Chhattisgarh state has been collected from the Department of Agrometeorology, IGKV Raipur.