Monitoring meteorological drought with SPI and RDI drought indices and Forecasting Class Transitions Using Markov Chains in southern Iran

Document Type : Original Article

Authors

1 Department of Water Science and Engineering, Minab Higher Education Center, University Of Hormozgan

2 Faculty of Agricultural and Natural Resources, University of Torbat Heydarieh

Abstract

The uncertainty found in standard methods of drought monitoring has made it necessary to compare the accuracy of the drought's monitoring methods. This study examined the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) to determine drought severity in 12 meteorological stations in southern Iran from 1975-2015 and predict draught transition from one to another class to another, using the Markov Chain model. According to the coefficient correlation analysis results between the precipitation data collected from the meteorological stations and the drought index, it was found that 3-month SPI and RDI have a high correlation with precipitation data. On the other hand, the analysis of the 3-month SPI and RDI index in all stations showed that the highest probability belonged to normal and near-normal classes, with their mean average probability values being 0.73 and 0.27 for SPI and 0.70 and 0.30 for the RDI, respectively. Moreover, based on RDI and SPI, the most probability rate of the drought occurrence in most of the stations belonged to normal and moderate drought classes, confirming a high correlation between meteorological drought and short-term drought index. According to the results, it is recommended that in the analysis of drought features, their characteristics such as vulnerability, resiliency, and reliability should be examined based on the climate type. Furthermore, to reduce the harmful effects of drought, necessary measures must be taken, especially in managing water resources.

Keywords

References

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Desert Ecosystem Engineering
Volume 10, Issue 7 in English
February 2022
Pages 26-13

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