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Vol. 11, Special Issue 4 (2022)

Assessment of agricultural and meteorological drought indices using remote sensing and GIS technology

Author(s):
Bhukya Srinivas, Mukesh Kumar Tiwari and Namwade Gangadhar
Abstract:
The agricultural productivity of India is greatly dependent on rainfall since it is an agrarian nation. As a result of the lack of rainfall, the national economy is adversely affected. Planning and management of drought require constant monitoring to better understand its intricate nature. Droughts occur in different parts of the world and vary in severity. Long-term vegetation analysis is required for monitoring agricultural drought on a regional scale. The present study attempts to study and monitor the spatial and temporal variation of agriculture and meteorological drought in Gujarat, India. This is, a state prone to drought, especially when monsoons fail or when they change. The long-term Normalized Difference Vegetation Index (NDVI) of NOAA-AVHRR NDVI data was used to assess agricultural drought through the NDVI-based Vegetation Condition Index (VCI), the most popular index to describe vegetation health for the period 1986-to-20015. The variation of VCI during the major crop-growing period of the Kharif season (June to September) was used to determine the spatial-temporal drought conditions of Gujarat. The results indicate that there is a wide variation in drought intensity among the districts within the state. The keen observation of yearly variation of long-term agricultural drought helps find the onset, period, and spatial extent of drought in various districts of the state. The districts that were most often prone to moderate to severe drought conditions during the analysis period were analyzed to develop various strategies to improve agricultural productivity in that region. The VCI values of normal and drought years were compared to the SPI, Rainfall Anomaly Index, and Yield Anomaly Index derived from meteorological data, and a good agreement was found between them. In addition, the correlation coefficient between maximum NDVI and mean seasonal rainfall (r > 0.52) confirms the usefulness of assessing agricultural drought. The persistent drought in the state necessitates that the government takes appropriate preventive measures to prevent drought in the future identifying the high-risk zones based on agricultural drought intensity maps, you can prioritize action plans based on the severity of the drought.
Pages: 1466-1477  |  412 Views  219 Downloads
How to cite this article:
Bhukya Srinivas, Mukesh Kumar Tiwari and Namwade Gangadhar. Assessment of agricultural and meteorological drought indices using remote sensing and GIS technology. The Pharma Innovation Journal. 2022; 11(4S): 1466-1477.

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