Abstract

The novelty of this study lies in integrating long-term Normalized Difference Vegetation Index (NDVI) fusion datasets with El Niño Southern Oscillation (ENSO)-driven climatic variability to generate policy-oriented, weather-based agro-advisory insights for sustainable agricultural management. This study provides a detailed climatological analysis of NDVI trends across India, covering 40 years of data during the Kharif (1983-2022) and Rabi (1982-2022) seasons. To evaluate long-term vegetation and agricultural productivity dynamics, inter-annual variations of NDVI, food grain productivity, and cumulative rainfall were analyzed for both seasons. The Mann-Kendall trend test, coefficient of variation, and decadal relative deviation analyses were applied to assess long-term vegetation variability. Correlations between NDVI anomalies and Oceanic Niño Index (ONI) values during El Niño and La Niña events were conducted to evaluate ENSO impacts, including the effects of 1- and 2-month lags on seasonal NDVI anomalies. In addition, correlations between rainfall during ENSO events and NDVI were assessed to quantify the influence of ENSO-driven rainfall variability on vegetation dynamics. Results reveal that 82.82% of India shows a positive NDVI trend during Kharif and 80.95% during Rabi. Regions like Rajasthan, Gujarat, and interior Karnataka exhibited high variability in Kharif, while southern Madhya Pradesh and eastern Rajasthan showed pronounced deviations in Rabi. ENSO teleconnections critically influenced vegetation, with El Niño inducing strong NDVI-rainfall correlations in the Western Ghats, Rajasthan, and eastern India during Kharif and in Rayalaseema and Tamil Nadu during Rabi. During El Niño events, correlations between NDVI and ONI in the Kharif season were significant for approximately 6.17% and 7.06% of areas at the 95% and 90% confidence levels, respectively. Kharif season NDVI declined in northeastern India, the Western Ghats, and the southern peninsula but increased in the Deccan Plateau and Indo-Gangetic Plains. The findings highlight the importance of irrigation, afforestation, and adaptive agricultural management in sustaining vegetation health and supporting agromet-advisory services under the Gramin Krishi Mausam Sewa (GKMS) initiative of the India Meteorological Department.

Keywords

Agromet-advisory servicesClimatic variabilityEl Niño and La NiñaGKMSNDVI trendsRainfall–vegetation correlation

MeSH Terms

IndiaAgricultureEl Nino-Southern OscillationEnvironmental MonitoringClimate ChangeClimate

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Publication Info

Year
2025
Type
article
Volume
198
Issue
1
Pages
37-37
Citations
0
Access
Closed

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Cite This

Sheshakumar Goroshi (2025). Decoding vegetation resilience: NDVI trends and climate impacts in Indian agriculture. Environmental Monitoring and Assessment , 198 (1) , 37-37. https://doi.org/10.1007/s10661-025-14794-w

Identifiers

DOI
10.1007/s10661-025-14794-w
PMID
41369718

Data Quality

Data completeness: 81%