Long-term relationships of MODIS NDVI with rainfall, land surface temperature, surface soil moisture and groundwater storage over monsoon core region of India

• Published in: Arid land research and management Vol. 37; no. 1; pp. 51 - 70
• Main Authors: Naga Rajesh, A., Abinaya, S., Purna Durga, G., Lakshmi Kumar, T. V.
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 02-01-2023; Taylor & Francis Ltd
• Subjects: Climate; Climate change; Climate relationship; Coefficients; Correlation coefficient; Correlation coefficients; El Nino; El Nino phenomena; Groundwater; Groundwater storage; Hydrology; Land surface temperature; Moisture effects; Monsoons; Normalized difference vegetative index; Precipitation; Rainfall; Soil moisture; Soil surfaces; Soil temperature; Southern Oscillation; Statistical analysis; Surface temperature; Temperature; vegetation index; wavelet coherence; India
• ISSN: 1532-4982; 1532-4990
• DOI: 10.1080/15324982.2022.2106323

India's climate is semi-arid, and most of the people in this country depend on agriculture. In this article, we present the long-term relationships of the satellite-derived Normalized Difference Vegetation Index (NDVI) with the rainfall, land surface temperature (LST), surface soil moisture (SSM), and the groundwater storage (GWS) during the Kharif (June-October) season of the monsoon core region (MCR) of India from the year 2000 to 2018. Results show that the NDVI could capture the stages of crop phenology and that it undergoes interannual variability characterized by the El Niño Southern Oscillation. A strong dependence of NDVI on SSM and GWS is evidenced by the statistically significant correlation coefficients of +0.89 and +0.88, respectively. A substantial negative correlation coefficient of −0.91 is observed between NDVI and LST. Wavelet coherence spectrum suggests the in-phase relation of NDVI with rainfall, SSM, GWS, and anti-phase connection with LST, with weaker correlations from 2004 to 2008. The results of this study attain significance since the studies on NDVI and hydrologic variables are much less than those on NDVI and climate variables over the MCR of India.