Copula-Based Non-Stationary Joint Deficit Index for Drought Characterization

major and costly extreme events. The prediction of drought and its characteristics like onset, duration, etc. is important for its planning and mitigation. This emphasizes the need of developing a multi-variate drought index that also incorporates the dynamic behaviour of the drought characteristics. In this study, we aim to develop a multi-variate non-stationary drought index to capture the joint behaviour of the hydrological variables, namely, precipitation and temperature. We computed the modified Standardised Index (mSI) of each variable for various window sizes (1 to 12 months). Here, non-stationarity is incorporated in mSI only if dynamic behaviour is observed in the considered variable, otherwise, stationary mSI is computed. Further, to realise the joint behavior temperature and precipitation, copulas have been used to develop a non-stationary joint deficit index (NJDI). This index provides a probability-based description of the overall drought status and its uncertainty bounds, computed using Bayesian inference. The proposed NJDI is able to reflect the long and short term droughts in a timely manner. NJDI can be used with other variable as well as evidenced by deriving NJDI separately for precipitation and temperature. The proposed NJDI can be a potential method for drought characterization and monitoring in a changing climate.