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This study examines the expected changes in drought patterns in Chhatrapati Sambhajinagar, a semi-arid district in Maharashtra, by using the Statistical Down Scaling Model (SDSM) and the Standardized Precipitation Index (SPI). Due to increasing climate variability, the region faces growing challenges related to water availability and agriculture. The research evaluates drought frequency and intensity under future climate scenarios RCP 4.5 and RCP 8.5 for the period from 2024 to 2100. Using historical climate data from 1980 to 2023, the SDSM was applied to generate detailed projections of temperature and rainfall. These projections show a steady rise in temperature, particularly during summer and post-monsoon seasons, which may lead to higher water loss through evapotranspiration and more stress on agriculture. The results indicate that climate variability will continue to affect the district’s water resources and crop production. The SPI method was effective for identifying drought conditions, while SDSM helped provide district-level future climate estimates. This study highlights the importance of adopting adaptive water management measures such as rainwater harvesting, recharging groundwater, and using climate-resilient agricultural methods to reduce the negative impacts of future droughts. The findings offer useful guidance for local authorities, planners, and farmers of chhatrapati sambhajinagar to make informed decisions for sustainable water and agricultural management in the face of climate change.
"Drought Analysis of Chhatrapati Sambhajinagar District Using SDSM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b413-b424, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506151.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator