A copula‐based index for drought analysis in arid and semi‐arid regions of Iran

Abstract

The copula functions are frequently used by researchers for modeling dependence structure among the correlated attributes in many areas. The copulas are widely used for the analysis of drought frequency, drought characteristics, drought coincidence risk, uncertainty, and drought forecasting. In this research, we have compared two indices of drought assessment, including SPI‐12 and copula‐based joint deficit index (JDI). In this regard, the drought characteristics, including the severity, duration, and drought frequency have been studied in 25 synoptic stations of Iran during the 1968–2014. The results showed that, unlike JDI, the SPI‐12 is not able to estimate the drought peak during the critical and extreme condition. Although JDI has identified a severe and extreme drought during the pervasive drought, the SPI‐12 estimated a normal condition. The results show that JDI accurately estimates the drought frequency, but the SPI‐12 provided an unexpected estimation is some stations. In addition, the MannKendal trend test for drought characteristics represents that JDI accurately estimates the expected trend (an increasing trend) whereas the SPI‐12 exhibits no significant trend in most stations. Finally, JDI provides a comprehensive assessment of drought for decision‐makers and natural managers.

Severity, Duration, and Magnitude Regionalization of Standardized Precipitation Index Over Iran During 1993-2016

“…It is concluded that these results are in agreement with Ghadami et al (2020) that identified four homogenous regions of drought severity-duration index at SPI-12 over Iran using 56 stations. Furthermore, based on the results of the Bazrafshan et al (2020), three homogeneous regions of drought in arid and semi-arid areas of Iran can be recognized that confirms the given results of Table 2.…”

“…Recently, Iran has experienced several drought events, that were addressed by many studies. For instance, studies conducted by Amirataee et al (2018), Bazrafshan et al (2020), Ghafori et al (2020), andNickravesh et al (2020) have been carried out either for several regions of Iran or with respect to the low amount of stations, while only the drought severity during a specific time frame is addressed. However, extensive analysis with respect to spatiotemporal characteristics of drought at different time scales has not been conceded across Iran.…”

Identification of Extreme Weather Events Using Meteorological and Hydrological Indicators in the Laborec River Catchment, Slovakia

“…In order to identify extreme events, two indicators were used: standardized precipitation index (SPI) and standardized runoff index (SRI). The SPI was developed by Mc-Kee et al [34] to assess meteorological drought and has been used by many authors [35][36][37]. The SRI was developed on the basis of the SPI concept for the characteristics of hydrological drought [38][39][40][41][42].…”

Spatiotemporal evolution and the driving factors of meteorological drought in the Hun-Taizi River basin, NE China

“…After recognizing the characteristic variables of drought events based on the run theory, it is useful to combine the drought characteristic variables with the copula function to analyze the multivariate probability characteristics of drought events (Mirabbasi et al 2012;Kao & Govindaraju 2019;Wang et al 2020). Copula, as a joint function, provides an effective method for multivariate frequency analysis and can model the structure of dependencies among variables (Fan et al 2017;Bazrafshan et al 2019;Lindenschmidt & Rokaya 2019). The copula function can combine multiple drought characteristic variables, which is widely used in hydrological and meteorological fields (Lee et al 2013;Xu et al 2015;Vyver & Bergh 2018;Dash et al 2019).…”