Bivariate Copula–Based Stochastic Modeling for Drought Risk Assessment in Southeastern Iran

Frequent droughts and water scarcity are significant factors undermining the socioeconomic and environmental development of central and southeastern Iran. However, conventional drought risk assessments often rely on univariate approaches, which may fail to capture the compound risk arising from the interplay between drought duration and severity. This limitation hinders the formulation of robust water management and mitigation strategies. This study aims to address this gap by providing a multivariate assessment of drought characteristics in these regions using copula theory. For this purpose, monthly precipitation data from 21 meteorological stations, spanning a 32-year period (1987–2018), were utilized. The Standardized Precipitation-Evapotranspiration Index (SPEI) was calculated and, subsequently, the theory of runs was used to extract drought duration and severity. Ten different copula functions were evaluated, and the results indicated that the Plackett copula performed best in modeling the joint distribution. Finally, using the best-fit Plackett copula, joint return periods for droughts (2, 5, 10, and 25 years) were calculated for all study stations. The findings revealed that areas with the highest drought risk are predominantly located in Yazd province, northern parts of South Khorasan province, eastern Kerman province, and southern Sistan and Baluchestan province. These spatially explicit findings provide critical information for targeted water resource management, infrastructure planning, and the development of effective drought mitigation policies in a highly vulnerable region. Moreover, the proposed framework offers a transferable methodology for comprehensive drought risk assessment in other water-scarce regions globally.