A study on copula-based bivariate and trivariate drought assessment in Godavari River basin and the teleconnection of drought with large-scale climate indices

The single variable-dependent drought cannot adequately define the onset and withdrawal characteristics of the droughts. A Multivariate Standardised Drought Index (MSDI) is developed in the present study, based on precipitation and soil moisture using bivariate copula function. Reconnaissance Trivariate Drought Index (RTDI) is also developed combining precipitation, soil moisture and evapotranspiration. MSDI and RTDI represent meteorological and agricultural droughts by linking the climate status in an effective way. The best fitted copulas obtained for bivariate and trivariate analyses are Frank and Student's t copulas respectively. The two drought indices are developed and tested to study the onset and withdrawal characteristics of drought and their trends. Cross-wavelet analysis (CWA) is performed to identify the substantial effect of large-scale climate anomalies on the derived drought indices. The large-scale climate factors like sea surface temperature (SST), Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Indian Ocean Dipole (IOD) and Indian summer monsoon rainfall (ISMR) are considered in this study. ENSO, IOD and ISMR showed significant influences on the drought variability. The 3-month MSDI is significantly influenced by ISMR while SST showed a significant teleconnection with RTDI-3. The SST showed a strong influence on both 6-month MSDI and 6-month RTDI. This study is robust and reliable for future drought assessment and will provide a great platform to develop warning criteria on onset and termination of droughts.