An assessment methodology for drought severity and vulnerability using precipitation-based indices for the arid, semi-arid and humid districts of Tamil Nadu, India. Issue 1 (9th December 2022) - Natarajan, N.; Vasudevan, M.; Ahash Raja, S.; Mohanpradaap, K.; Sneha, G.; Joshna Shanu, S.
Abstract: As the short- and long-term impacts of climate change are becoming more visible at smaller regional scales, frequent occurrence (absence) of erratic precipitation as well as water scarcity issues can be identified as reliable indicators for predicting meteorological droughts. A supervised declaration of meteorological drought based on available precipitation data requires an understanding of reliability and consistency of drought indices for appropriate severity classification. An attempt has been made in this study to critically evaluate the performance of six popular drought indices namely, Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-Score Index (ZSI) for four districts in Tamil Nadu falling under arid (Karur), semi-arid (Cuddalore), dry sub-humid (Kanyakumari) and moist sub-humid (Coimbatore) conditions based on 120 years of precipitation records. Results showed that the SPI and CZI provided similar quantification of drought events (about 18% of the total months) irrespective of their climatic considerations while ZSI and RAI resulted in overestimation of drought severity (about 30–47%). Based on the classification strategy adopted for the selected indices, a framework for drought vulnerability assessment is proposed in conjunction with the estimated drought severity classifications. HIGHLIGHTS: An attempt is made in this study to critically evaluate the performance of six different drought indices. SPI, CZI, MCZI, DI, RAI and ZSI are calculated for four districts in Tamil Nadu. SPI and CZI provided similar quantification of drought events irrespective of the regional scale climatic considerations. ZSI and RAI resulted in overestimation of drought severity. A framework for the drought vulnerability assessment is provided. Graphical Abstract