WEEKLY RAINFALL ANALYSIS USING MARKOV CHAIN MODEL FOR V.C. FARM, MANDYA DISTRICT, KARNATAKA

B.S. SOWMYALATHA1*, K.S. SHUBHASHREE2, S.B. YOGANANDA3, P. THIMMEGOWDA4, S.R. SAHANA5
1Department of Agronomy, College of Agriculture, V.C. Farm, Mandya, 571405, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India
2Department of Agronomy, College of Sericulture, Chinthamani, 563125, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India
3Department of Agronomy, College of Agriculture, V.C. Farm, Mandya, 571405, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India
4Zonal Agricultural Research Station, V.C. Farm, Mandya, 571405, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India
5AICRP on Small Millets, Zonal Agricultural Research Station, V.C. Farm, Mandya, 571405, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India
* Corresponding Author : sowmyalatha.vinu@gmail.com

Received : 03-02-2022     Accepted : 27-02-2022     Published : 28-02-2022
Volume : 14     Issue : 2       Pages : 11077 - 11081
Int J Agr Sci 14.2 (2022):11077-11081

Keywords : Probability, Dry spell, Wet spell, Markov chain model, Rainfall analysis
Academic Editor : Dr N.N. Jambhulkar, Dr B.P. Bhaskar, Dr Akhilesh Singh
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to Zonal Agricultural Research Station, V.C. Farm, Mandya, 571405, University of Agricultural Sciences, Bengaluru, 560065, Karnataka, India. Authors are also thankful to Department of Agronomy, College of Agriculture, V.C. Farm, Mandya, 571405, Department of Agronomy, College of Sericulture, Chinthamani, 563125, Karnataka, India
Author Contribution : All authors equally contributed

Cite - MLA : SOWMYALATHA, B.S., et al "WEEKLY RAINFALL ANALYSIS USING MARKOV CHAIN MODEL FOR V.C. FARM, MANDYA DISTRICT, KARNATAKA." International Journal of Agriculture Sciences 14.2 (2022):11077-11081.

Cite - APA : SOWMYALATHA, B.S., SHUBHASHREE, K.S., YOGANANDA, S.B., THIMMEGOWDA, P., SAHANA, S.R. (2022). WEEKLY RAINFALL ANALYSIS USING MARKOV CHAIN MODEL FOR V.C. FARM, MANDYA DISTRICT, KARNATAKA. International Journal of Agriculture Sciences, 14 (2), 11077-11081.

Cite - Chicago : SOWMYALATHA, B.S., K.S. SHUBHASHREE, S.B. YOGANANDA, P. THIMMEGOWDA, and S.R. SAHANA. "WEEKLY RAINFALL ANALYSIS USING MARKOV CHAIN MODEL FOR V.C. FARM, MANDYA DISTRICT, KARNATAKA." International Journal of Agriculture Sciences 14, no. 2 (2022):11077-11081.

Copyright : © 2022, B.S. SOWMYALATHA, et al, Published by Bioinfo Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Abstract

For success of agriculture under rainfed situation it is essential to know the onset and withdrawal of monsoon, the pattern of occurrence of dry and wet periods during monsoon season. The present study has been carried out at Zonal Agricultural Research Station which is located at Mandya district in Karnataka state under agro-climatic zone 6 (Southern dry zone) having longitude of 76°49.8' E and latitude of 12°34.3' N with an altitude of 697 meters above the mean sea level. Weekly Rainfall data of 26 years (1991-2018) obtained from Agromet observatory, ZARS, Mandya, University of Agricultural Sciences, Bangalore was studied for spell distribution using Markov Chain Model. For this purpose, a week period was considered as the optimum length of time. The present study has been carried out to find the probabilities of occurrence of wet week (Pw), dry week (Pd), wet week preceded by wet week (Pww), dry week headed by dry week (Pdd), two and three succeeding wet and dry weeks (P2w, P2d, P3w and P3d) at a threshold rainfall limit of 20 mm/week. The results revealed that, the probability of occurrence of wet weeks during the pre-monsoon season starts effectively from 15th May to 15th June in the study area. The chance of occurrence of two or three consecutive wet weeks was high during rainy season, whereas, rest of the period during the year was more prone to have two or three consecutive dry weeks

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