Assessment of Drought using Meteorological and Remote sensing data

Abstract

The frequency of droughts has increased in recent years due to global warming, and it is a complicated natural hazard that is poorly understood. There are four types of droughts: meteorological, hydrological, agricultural, and socioeconomic. Precipitation deficits leads to meteorological drought. Agricultural drought is a result of several consequences like water deficits in soil, reduction of evapotranspiration and decreased crop yield. Drought occurrence cannot be eliminated; however, their consequences can be diminished if decision makers have access accurate spatio-temporal information about crop status. The objective of the study is to identify the meteorological and agricultural droughts across Anantapur district of Andhra Pradesh by using meteorological and remote sensing data. The SPI (Standardized Precipitation Index) and the SPEI (Standardized Precipitation Evapotranspiration Index) are two multiscalar drought indices that are used to identify Meteorological drought. Agricultural drought is identified by using IDCI (integrated drought condition index). IDCI was used by integrating vegetation conditions, temperature, precipitation, soil moisture and potential evapotranspiration. SPEI, SMCI (Soil Moisture Condition Index) and VCI (Vegetation Condition Index) are three drought indices that make up IDCI. The IDCI is computed in this study using Principal component analysis (PCA). The results shows that 2016 and 2018 are meteorological drought years and 2016,2017 and 2018 are agricultural drought years during 2012-2021in Anantapur district, Andhra Pradesh. The results of the study indicate that drought can be accurately evaluated by merging various data sources and drought indices, allowing for the estimation of risk management plans and the signing of new treaties.