Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions Under Climate Change Condition

Elaheh Motevali Bashi Naeini,Jahangir Abedi Koupai,Fereydoun Radmanesh,Shahrokh Soltaninia,Ali Mohammad Akhoond-Ali

doi:10.1007/s11269-021-02965-6

Abstract

Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two- and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. In this paper, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought in the historical period and the two near and near future periods. Moreover, the results of considering bivariate and trivariate of Copula functions were compared separately with the results of the calculated return periods for each of the drought characteristics; accordingly, the role of each drought characteristics was considered. The most severe historical drought was selected as the benchmark, and the drought-zoning map for the GCM models was drawn. The results showed that severe droughts could be experienced, especially in the upper area of the basin where the primary water resource is located. In addition, the nature of the drought duration plays a decisive role in calculating the return periods of drought events.

Highlights

Drought occurs for long periods of unusual hydrological conditions resulting in a sharp decline in rainfall
The Standardized Precipitation Index (SPI) is proper for measuring meteorological drought since it is based on precipitation data
The results showed that while Temperature Condition Index (TCI) is commonly employed in copula models indicating better probabilities of joint extreme high values of wheat and drought indicators, the Vegetation Condition Index (VCI) and Standardized Precipitation Evapotranspiration Index (SPEI)

Summary

Introduction

Drought occurs for long periods of unusual hydrological conditions resulting in a sharp decline in rainfall. Analyzing drought indices are important for assessing the drought conditions because the incident provides various methods to determine drought severity, arrival (Cahng et al 2016; Hao et al 2016; Tian et al 2018; Mukherjee et al 2018). Some indices are the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI), the modified SPI index, and the Joint Deficit Index (JDI). As climate change could cause extreme hydrological phenomena, investigating its effects is one of the necessities of water resources management (Ahmadalipour et al 2017; Oguntunde et al 2017). Examples include the SPI and the RDI, the Percent of Normal Precipitation Index (PNPI), the Agricultural Rainfall Index (ARI), the Multivariate Standardized Drought Index (MSDI), and JDI Index, having utilized for drought analysis in different parts of the world including Iran Baas 2007, Lee et al 2013, Serinaldi et al 2009; Mirabbasi et al 2013; MirAbbasi et al 2013; Madadgar and Moradkhani 2011; Lee et al 2013; Kirono et al 2011; Srinaldi et al 2009; Hoffman et al 2009; Selavarajo and Bass 2007)

Objectives

Methods

Results