Enhancing drought monitoring and assessment capability in India through high-resolution (250 m) data

Abstract

Abstract. Drought poses a tremendous challenge to India's socioeconomic development, livelihood, agriculture, and water management. While existing drought monitoring systems have characterized drought impact at different scales, policymaking and management require drought assessment at sub-district or taluka (sub-district) levels. Here, we develop high-resolution (250 m) agriculture drought indices for the Indian region to overcome the shortcomings of the coarse resolution datasets. We used the co-kriging to downscale the Land Surface Temperature (LST) from 1000 m to 250 m. The LST and Enhanced Vegetation Index (EVI) are obtained at 8-day intervals at 250 m spatial resolution. The high-resolution datasets show significant improvement in identifying the severity and coverage of drought. Soil Moisture Agriculture Drought Index (SMADI), which accounts for water stress and vegetation lag response, shows high reliability in drought detection. We evaluated drought extent and severity using the newly developed dataset and found that the high-resolution dataset can be used to separate the irrigation impact on drought alleviation. The high-resolution drought indices from SMADI and the Normalized Vegetation Supply Water Index (NVSWI) effectively represent the drought conditions at district and taluka levels that can be used in drought impacts assessments in India.