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) 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.

A CMIP6 Multi-Model Analysis of the Impact of Climate Change on Severe Meteorological Droughts through Multiple Drought Indices—Case Study of Iran’s Metropolises

“…Per signifies the percentile function, and P m corresponds to the rainfall observed in month m. The DI index offers a straightforward way to assess the deviation of current precipitation conditions from long-term averages. This information is valuable for understanding the relative wetness or dryness of a given period, aiding in various applications, including drought monitoring and water resource management [41].…”