‘IMPACT OF El NINO ON INDIAN AGRICULTURAL PRODUCTION 2026’

Research studies conducted between 1980 and 2015 on El Nino and Indian agriculture have revealed several critical patterns. First and foremost, all drought years since 1980 were El Nino years, establishing a strong correlation between El Nino events and agricultural distress in India. However, research also demonstrated that not all El Niño events caused agricultural disasters, with 1987 serving as a crucial counterexample where a strong El Nino produced minimal agricultural impact despite the climatic conditions, primarily due to improved water management and irrigation infrastructure. Major studies analyzing over 70% of crop districts found that these regions experienced lower production and yields during El Nino years due to warmer and drier conditions. The research identified maize and pearl millet as experiencing the largest yield declines relative to rice, particularly in northwest and southern peninsular India, with production losses ranging from 20 to 35%. Importantly, studies found that transitioning from water intensive crops like maize and rice to drought resistant traditional cereals such as sorghum and finger millet significantly reduces interannual production variability during El Nino events, offering a viable adaptation strategy for climate resilient agriculture. Regional variations were also documented, with coastal Andhra Pradesh showing some resilience due to the Northeast monsoon, while Gujarat and Maharashtra faced severe impacts on cotton, groundnut, and sugarcane. These findings underscore the importance of district level climate resilient agricultural planning and the need for crop diversification strategies that prioritize drought tolerant traditional cereals in El Nino prone regions.Interpretation of Crop Vulnerability Data for 2026 El Nino Using Linear Regression Method Based on the historical crop vulnerability data (1980–2015) and the 2026 El Nino forecast (82% chance of emergence, 33% probability of Super El Nino), This research apply linear regression methodology to predict 2026 crop impacts on Agriculture productions and insure to the Indian farmers to prevent from El Nino by crop diversification for the sustainability and food security of India.  

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