An assessment methodology for drought severity and vulnerability using precipitation-based indices for the arid, semi-arid and humid districts of Tamil Nadu, India

Abstract As the short- and long-term impacts of climate change are becoming more visible at smaller regional scales, frequent occurrence (absence) erratic precipitation as well water scarcity issues can be identified reliable indicators for predicting meteorological droughts. A supervised declaration drought based on available data requires an understanding reliability consistency indices appropriate severity classification. An attempt has been made in this study to critically evaluate performance six popular namely, Standardized Precipitation Index (SPI), China Z (CZI), Modified (MCZI), Deciles (DI), Rainfall Anomaly (RAI), Z-Score (ZSI) four districts Tamil Nadu falling under arid (Karur), semi-arid (Cuddalore), dry sub-humid (Kanyakumari) moist (Coimbatore) conditions 120 years records. Results showed that SPI CZI provided similar quantification events (about 18% total months) irrespective their climatic considerations while ZSI RAI resulted overestimation 30–47%). Based classification strategy adopted selected indices, a framework vulnerability assessment is proposed conjunction with estimated classifications.