Regional classification of extreme droughts across Iran

Abstract

In arid and semi-arid regions like Iran, sustainable urban and agricultural development is intimately intertwined with the severity, frequency, and duration of meteorological droughts. Prolonged meteorological droughts can trigger hydrological and socio-economic droughts, posing significant challenges to the region’s sustainability. Therefore, the primary objective of this study is to perform a comprehensive Regional Frequency Analysis (RFA) for extreme meteorological drought events across Iran. To this end, we meticulously calculated the severity, duration, and magnitude of the Standardized Precipitation Index (SPI) over the 3-, 6-, 9-, and 12-month accumulation periods. The data was derived from monthly precipitation records collected at 106 meteorological stations during the period spanning 1993–2016. Subsequently, we employed a rigorous approach, utilizing Ward’s clustering analysis and the test for heterogeneity using L-moment, to effectively classify and categorize the extreme drought characteristics prevalent across the country. The analysis revealed that the generalized Pareto and Pearson type 3 models are the most suitable distribution functions for RFA across almost all the examined clusters. Additionally, the spatiotemporal analysis of the SPI series at various time scales indicated that the extreme events’ characteristics, such as severity, duration, and magnitude, remain surprisingly unaffected by the local climate conditions. The results also showed that even in the typically humid regions located in the north, west, and northwest of Iran, areas that receive considerable annual precipitation, severe droughts can still occur. These droughts primarily stem from temporal events rather than being solely dependent on the local climate conditions. Therefore, the study concludes that the drought events can largely be attributed to mismanagement and inadequate regional water allocation. Moreover, these situations might have been further exacerbated by the occurrence of extreme climatic conditions. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2023.