Abstract
This research uses the Markov Chain Model to analyze dry and wet spells in Telangana, India’s Adilabad district. The research intends to provide significant insights for agricultural planning in the region, which is critical considering that agriculture is the foundation of Indian economy. The study emphasizes the need to understand and effectively exploit natural resources, particularly rainfall, for the improvement and sustainability of rainfed agriculture. According to the calculation, there is a 70% chance of two consecutive wet weeks throughout the monsoon season (24th SMW to 40th SMW), resulting in about 17 weeks of monsoon rain in the Adilabad area. This enables the successful development of short-duration crops like rice. According to the study, the Markov Chain Model is effective for simulating the long-term frequency behavior of wet or dry spells, providing a comprehensive understanding of rainfall patterns and their impact on agriculture in the Adilabad District
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
