ABSTRACT
This chapter examines drought scenarios using a variety of drought indices. In this chapter, a range of surface and meteorological characteristics were utilized to calculate meteorological, hydrological, and vegetative drought indices. These indices were then mapped using earth imaging products and analyzed through geo-spatial approaches. Agricultural drought, due to its significant impact on rain-fed crop production and subsequent effects on employment and per capita income, has emerged as a critical global concern. The main aim of this work is to determine how well geo-spatial techniques can be used to track the location and time period of agricultural drought. In this study, we specifically used a measure called the Vegetation Condition Index (VCI), which is based on the Normalized Difference Vegetation Index (NDVI). We obtained the NDVI data from the National Oceanic and Atmospheric Administration (NOAA)-Advanced Very High-Resolution Radiometer (AVHRR) to monitor agricultural dryness. Using long-term NDVI images, VCI, Temperature Condition Index (TCI), and Vegetation Health Index (VHI) were estimated for the entire Puruliya district (West Bengal), revealing the existence of drought-related crop stress in 2018. The NDVI, Rainfall Anomaly Index (RAI) based on meteorology were compared with the VCI, TCI, and VHI values of drought (2018) and normal (2017) years, and agreement was observed between them. Five categories, viz., no drought, mild drought, moderate drought, severe drought, and extreme drought, were shown in the conclusion. The district’s monthly meteorological, hydrological, and vegetative droughts over the two years of 2017 (wet year) and 2018 (drought year) were analyzed for spatial and temporal changes, and the impact of the drought on agriculture was determined using data on annual rice production. When a monthly rainfall deficit precedes the start of an agricultural drought, it is possible to issue regional drought warnings and put in place efficient local drought mitigation measures.
