Evolution of drought characteristics using a new combined joint multivariate index based on the copula function

Narjes Shahbeygi, Bahareh Pirzadeh () and Jamshid Piri ()
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Narjes Shahbeygi: University of Sistan and Baluchestan
Bahareh Pirzadeh: University of Sistan and Baluchestan
Jamshid Piri: University of Zabol

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 9, No 3, 10059-10084

Abstract: Abstract Drought is one type of natural disaster that impacts huge areas over an extended period. Multi-variable indices have been established to evaluate numerous factors at once and obtain more information regarding drought. In this study, a combined Joint Multivariable Index (CJMI) was defined for Iran based on three indices: SPI, PDSI, and SRI, covering the period from 1990 to 2021, aiming to consider all aspects of drought. By examining various marginal distribution functions (such as Log-normal, Logistic, Exponential, Weibull, and Gamma), the most suitable distribution function was determined based on two criteria: AIC and BIC. The best-fit distribution function for most stations was found to be log-normal and exponential, while the gamma distribution function was optimal only for the Mashhad station with AIC = 503.24 and BIC = 513 Subsequently, return periods (AND) and joint risk of the trivariate were evaluated. Return periods and joint risk analysis of the three variables were compared based on three copula functions: Frank, Gumbel, and Clayton, for periods of 50 and 100 years. The obtained values for risk analysis were categorized into three levels, with the highest risk values observed in the northwestern region and stations such as Ardabil, Urmia, Tabriz, and Tehran exceeding 0.70. The overall results of this research indicate that the CJMI index obtained contains more uncertainties than individual indices and better analyzes the primary data approach.

Keywords: Marginal distribution function; Copula function; Return period; Combined joint multivariate index (CJMI) (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07191-6

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