**ABSTRACT**

The objective of the study is to analyze the wet and dry spells for *Maha* crop season at the Kantale, Trincomalee, Sri Lanka. The agricultural operations mainly depend on the success of dry and wet spell conditions. The Markov Chain probability model is a very useful tool for studying wet and dry spells which helps in planning, irrigation schedules, and farming operations ensuring optimal water use of crops. The success or failture of crops is determined by the amount, pattern, and intensity of rainfall particularly in rainfed agriculture. In this study, the Markov Chain probability model has been employed to compute and predict the initial and conditional probabilities of the occurrence of wet and dry spells. The probabilities of wet week (W), wet week preceded by wet week (W/W), dry week (D) and, dry week preceded by dry week (D/D) have been computed for 10, 20, and 40mm threshold limits. The initial and conditional probability results exhibited that the occurrence of wet spells is more than 50% starting from week 38 and continuing up to succeeding week 2 at a 10mm/week threshold limit which ranges between 53% – 91%. Consequently, the land preparation could be taken up from week 38th and finished on or before week 41st (before 14th October), week 42 is a more suitable time for sowing/planting especially for 3-month paddy varieties. Taking into consideration the various threshold limits, the 3 and 3 1/2-month paddy varieties are the most suited for this study area. The long-term paddy varieties such as 4 or more months paddy variety will be affected by dry spells during either mid or late-crop season in *Maha* cultivation.

**Reference**

[1] N. Subash, Alok K. Sikka1 and A. Abdul Haris. Markov chain approach – dry and wet spell rainfall probabilities for rice-wheat planning, *Indian Journal of Soil Cons.*, 37 (2), (2009) 91-99.

[2] P. Kandasamy, & M. Chellamuthu. Dry spell analysis for effective water management planning, *International Journal of Applied Sciences and Engineering Research*,1(2), (2012)127-137.

[3] J.J. Barrom, Rockstrom, F. Gichuki and N. Hatibu. Dry Spell Analusis and Maize Yield for Two Semi-arid Locations in East Africa, *Agriculture and Forest Meteorology*, 117, (2003) 23-27.

[4] M. Manikandan, G. Thiyagarajan, J. Bhuvaneswarari, and N.K. Prabhakaran. Wet and Dry Spell Analysis for Agricultural Crop Planning using Markov Chain Probability Model at Bhavanisagar, *International Journal of Mathematics and Computer Applications Research*,7(1), (2017) 11-22.

[5] K. Rajendram. An Assessment of Drought in Mannar District, Sri Lanka. *International Journal of Humanities and Applied Social Science*, 11 (2019) 1-13.

[6] Fitsume Yemenu. Dry and Wet Spell Analysis of the Two Rainy Seasons for Decision Support in Agricultural Water Management for Crop production in the Central Highlands of Ethiopia, *Journal of Biology, Agriculture and Healthcare*,3, (11), (2013)1-6.

[7] N. Subash, Alok K. Sikka and A. Abdul Haris, Markov chain approach – dry and wet spell rainfall probabilities for rice-wheat planning, *Indian J. Soil Cons., *37 (2): 9 (2009) 91-99.

[8] W. Admasu, K. Tadesse, F. Yemenu, B. Abdulkadir. Markov chain analysis of dry, wet weeks and statistical analysis of weekly rainfall for agricultural planning at Dhera, Central Rift Vally Region of Ethiopia. *African Journal of Agric. Res.* 9 (29), (2014) 2205-2213

[9] D. Tandel, Verma.S., K. Kumar, K.K., and M. K. Verma, Impact Assessment of Wet and Dry Spell on Agriculture Productivity of Chhattisgarh, India, *Journal of Environmental Informatics Letters, *XX(X) XX-XX (XXXX), (2023)1-13.

[10] S.M. Virn. The agricultural climate of the Hyderabad Region in relation to crop planning. A simple analysis, in hone be publication of *ICRISAT*, Hyderabad, india. (1976) 54.

[11] G.C. Green.Wet and Dry Spells at Nelsprui, *Agrochemophysica *1, (1969) 43-52.

[12] N. Shahraki, Bakhtiari, B., & M.M. Ahmadi. Markov chain model for probability of dry, wet days and statistical analysis of daily rainfall in some climatic zone of Iran. Aerul si Apa: Compon. Ale *Mediului,* 4, (2013) 399-416.

[13] N.Pandrinath. Morkov chain model probability of dry and wet weeks during monsoon period over Andhra Pradesh. *Mausam*, 42(4): (1991) 393-400.

[14] S.M. Taley, and V.B. Dalvi. Dry spell analysis for studying the sustainability of rainfed agriculture in India – The case study of the Vidarbha region of Maharashtra state. *Large Farm Development Projec*t, (1991).

[15] G.V.S. Reddy, Bhakar SR, Purohit RC, A.K. Chittora. Markov chain probability of dry, wet weeks and statistical analysis of weekly rainfall for agricultural planning at Bangalore. Karnataka *Journal of Agricultural Sciences,*2, (2008)12-16

[16] R. Purohit, G. Reddy, S. Bhaskar, A. Chittora. Markov Chain Model Probability of Dry, Wet weeks and Statistical Analysis of Weekly Rainfall for Agricultural Planning at Bangalore.” Karnataka, *Journal of Agricultural Science*, 2(1) (2008).

[17] A.K. Shrivastavo, C.V. S Shastri, R.N. Garg. Rainfall analysis and crop planning in Uttar Pradesh. *Annals Agricultural Research*, 25(2):2(2004)57-264.

[18] S.J. Reddy. Methodology: Agroclimatic Analogue Technique and Applications as relevant to dry land agriculture. *Agro climatology Series Eth* 86/21-WMO/UNDP, NMSA, (1990) 60.

[19] Paulino Omoj Omay, Nzioka John Muthama et. al. Observed Changes in wet days and Dry Spells over IGAD region of Eastern Africa, (2023), Scientic Reports,1-26, DOI: https://doi.org/10.21203/rs.3.rs-2735204/v1.

[20] P.M. Piyadasa, and D.U.J. Sonnadara. Analysis of wet and dry behavior of weather through Markov models, Proceedings of the Technical Sessions, 26 (2010) 25-32 Institute of Physics – Sri Lanka.

[21] K. Rajendram and K.S. Sivasami. Markov Chain Model for robability of Weekly Rainfall and its Agro-Climatic Implications to Paddy Crop over Batticaloa., Srilanka., *The Indian Geographical Journal*, 79., (2006)83-96.

[22] P.N.P Fernando, and K. Senevirathne. A Markov chain model for daily rainfall data, *Proceedings of the Sri Lanka Association of Advancement of Science*, (1987)171.

[23] K.Rajendram. Rainfall Variability and Drought in the Dry and Wet Zones of Sri Lanka. *World Scientific News*, 160(2021) 172-189.

[24] H.P. Das, and S.V Datar. Prospect of Double Cropping Rain-fed rice in West Bangal, *Mausam,* 49, (1998)121-126.

[25] S. Suthakaran, and K. Rajendram, Flood Occurrence and Risk Assessment in Trincomalee District, Using Open Source Geo-Spatial Technology. *World Scientific News*, 161 (2021) 45-65.

[26] Sindhuja Sriram and K. Rajendram. An Assessment of Flood Hazard at Eravoor Pattu Divisional Secretariat Division, Batticaloa Using Geospatial Technology, *World Scientific News*, 174(2022), 112-130.

[27] N. Piratheeparajah, and K. Rajendram. Occurrences of Flood Hazards in the Northern Region of Sri Lanka. *Journal of South Asian Studies,* 3(3), (2015)363-376

[28] K. Rajendram. Rainfall Variability and Drought Occurrences in the Batticaloa District, Sri Lanka. *World News of Natural Sciences,* 39 (2021) 30-45.

[29] District Secretary, Kachcheri, Resource Profile, Trincomalee District, 2023.

[30] Omkar D Rajmane, JD Jadhav, Samiksha G Ahire, ST Majik and PA Sondawale. Dry and wet spell probability analysis by Markov chain model for Sangli District (Maharashtra), India, *The Pharma Innovation Journal*,12(2) (2023)1131-1142.

[31] P. P. Dabral. Dry and wet spell probability analysis by Markov chain model for Kohima (Nagaland), India. Agricultural Engineering International: CIGR Journal, 21(4), (2019) 43-47.

[32] A. Pradhan, Nag, S., Sao, A., & S. Mukherjee. Distribution of Weekly Rainfall and Probability Analysis for Crop Planning in Bastar Region of Chhattisgarh. Journal of Experimental Agriculture International, 25(2), (2018)1-7.

[33] M. Ray, Biswasi, S., Sahoo, K. C., & H.A. Patro. Markov chain approach for wet and dry spell and probability analysis. Int. J. Curr. Microbiol. App. Sci, 6, (2018)1005-1

[34] H.V. Sakha Ram Shori, Puranik. Analyse the probabilities of dry spell status in different districts of Chhattisgarh State, *Journal of Pharmacognosy and Phytochemistry* (2018) SI 4:154-173.

[35] S.J. Reddy. Agroclimatic/Agro-meteorological Techniques- As applicable to Dry Land Agriculture in the Developing Countries, Secunderrabad, India: Jeevan Charitable (1993).

#### Download all article in PDF