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Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
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Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
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Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India

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Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India
Journal Article

Assessment of wet season agricultural droughts using monthly MODIS and SAR data in the red and lateritic zone of West Bengal, India

2023
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Overview
Recurrent droughts, particularly in the monsoon seasons, often severely affect the agricultural yield. Such short-lived yet acute droughts lead to crop failure, affecting the livelihood of small and marginal farmers of the sub-humid red and laterite zones (RLZs). The present paper analyses the monthly agricultural droughts during the monsoon seasons in the RLZs using MODIS and SAR data. From the analysis of MODIS-derived indices like NDVI, TCI, TVDI, and Z PET for the years 2005 to 2020, three acute drought years of 2005, 2010, and 2015 were identified as severe to extreme drought conditions which led to crop failures. MODIS-derived drought indices were validated by rainfall (SPI) and evapotranspiration (SPEI) based meteorological indices. Results showed that the satellite-derived evapotranspiration index Z PET and soil moisture index TDVI were better correlated with the SPEI, while the NDVI anomaly was better correlated with the SPI. Ground-level drought conditions prevalent during the monsoon months of June to September in 2015 could be further detected by the SAR backscatter of multi-temporal data from 2015 to 2020. This study provides a theoretical basis for the application of MODIS and SAR data in tandem for identifying short-lived but potentially damaging agricultural droughts during monsoon months.