El Nino Exposes Deep Divides in How Indian Farmers Receive Weather Warnings

Severe drought conditions across Indian states during the latest El Nino year exposed critical gaps in how weather warnings reach farmers on the ground. The India Meteorological Department estimated a 92% probability of El Nino developing during the monsoon season, while the United States National Oceanic and Atmospheric Administration put the chance at 96%. Rajasthan experienced an early impact, recording a 21% rainfall deficit with 21 districts deficient and only two in surplus by the first week of September.

KVK Network Divide

Nationally, kharif sowing lagged by 16% on July 10 at 53.12 million hectares compared to 63.27 million a year earlier, while cumulative rainfall stayed about 15% below the long period average through September. Maharashtra declared drought in 265 of its 358 talukas. Agromet Advisory Services, restructured under the Gramin Krishi Mausam Sewa in 2008 and extended to the block level in 2018, now operate through more than 130 Agromet Field Units and District Agromet Units housed at Krishi Vigyan Kendras. However, farmers split into two distinct groups based on their institutional link to these local centers.

Divergent Outcomes

Farmers with active contact with Krishi Vigyan Kendras successfully used early warnings to adjust planting, sowing crops in portions or switching from water-intensive plants like rice and soybeans to pearl millet, bajra, and guar. In contrast, farmers without institutional links relied on guesswork or misleading WhatsApp messages, leading to severe crop loss and financial distress. While connected farmers complained about block-level forecasts lacking microclimate precision and struggling to separate official advisories from private speculation on digital platforms, unconnected farmers suffered from late warnings, technical language barriers, and poor network coverage.

Context

Agriculture in India remains heavily dependent on the seasonal monsoon, making timely and accurate weather forecasts vital for rural livelihoods. Early warning systems rely on complex meteorological data collected by national and space agencies, but translating high-level scientific projections into actionable, localized advice for millions of smallholder farmers has long remained a logistical challenge.