Monitoring annual meteorological drought in arid and semi-arid watersheds by SPI12 drought index and spatial autocorrelation pattern analysis: a case study of the Khuzestan province, Southwest Iran

The objective of this research is determining areas that have experienced the most severe annual droughts in Khuzestan, southwest Iran during a 34-year period (1982–2016). For this purpose, the SPI12 index was used to identify the most severe occurred annual droughts. Inverse distance weighting (IDW) interpolation method was used to interpolate the SPI12 index between 60 considered stations and prepare zoning maps. Global and local Moran's I methods were used to determine the pattern of drought (random, scattered, or clustered) and to identify clusters with mild or severe drought. The Gi* local statistics method was used to validate the identified clusters. The Mann–Kendall (MK) trend test and Theil–Sen approach (TSA) were used to determine the trend of droughts in the future and its significance. The results showed that the most severe droughts occurred in December 2008 and January and February 2009. Spatial statistics analysis methods show that there are three main clusters, including the north and southeast regions that were affected by severe drought and the southwest cluster that was affected by milder drought. The results of the Gi* local statistics method also showed these clusters with these conditions. The MK trend test and TSA showed a decreasing trend for SPI12 at most stations at the 95% confidence level, meaning that more severe droughts are expected in the province in the future. The obtained results can be used to inform policy decisions and improve the resilience of the province, especially in the north and southeast, to future drought events.