EGU22-11772, updated on 28 Mar 2022
https://doi.org/10.5194/egusphere-egu22-11772
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multivariate Analysis and Assessment of Regional Drought Risks under Climate Change using Copulas

Rajarshi Datta1 and Manne Janga Reddy2
Rajarshi Datta and Manne Janga Reddy
  • 1Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India (rajarshi123.rd@gmail.com)
  • 2Department of Civil Engineering, Interdisciplinary Program (IDP) in Climate Studies, Indian Institute of Technology Bombay, Mumbai, India (mjreddy@civil.iitb.ac.in)

This study intended to understand the effect of climate change on spatiotemporal characteristics of multivariate drought risk over the Vidarbha region of India. The Standardized Precipitation Evapotranspiration Index (SPEI) is employed to characterize droughts in the region. Gridded daily precipitation and temperature data produced by the Indian Meteorological Department (IMD) and Coupled Model Inter-comparison Project Phase 6 (CMIP6) were utilized for estimating the SPEI. The drought events were identified and subsequently characterized by duration, severity, and peak. Different goodness of fit tests was applied to select the best fitting marginal distributions of the individual drought characteristics. Several symmetric and asymmetric Archimedean trivariate copulas and seven bivariate copula families were evaluated for joint distribution modeling. Maximum pseudo-likelihood and genetic algorithms have been applied to estimate the copula parameters accurately. The asymmetric Frank copula was selected to construct the trivariate distribution of the drought characteristics. Frank, Student’s t and Clayton copulas were chosen to build the bivariate distribution of duration-severity, duration-peak, and severity-peak, respectively. The joint distributions were applied for computing the joint return periods of drought events. The drought risk over the region was illustrated using zoning maps for historical along with near and far future periods. The inferences derived from the study will help policymakers to prepare better mitigation strategies under the changing environment.

How to cite: Datta, R. and Reddy, M. J.: Multivariate Analysis and Assessment of Regional Drought Risks under Climate Change using Copulas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11772, https://doi.org/10.5194/egusphere-egu22-11772, 2022.