Joint analysis of meteorological drought characteristics based on SPI and CRU senario

Document Type : Research Paper

Authors

1 Department of Water Science and Engineering, Water Resources, Tabriz University, Tabriz, Iran.

2 Department of Hydrology and Water Resources, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

10.22059/jwim.2023.350918.1030

Abstract

There are two limitations in the analysis of drought characteristics, which this study has investigated and resolved. First, the limitation of the length of the statistical period regarding the presentation of meteorological drought characteristics and the other is the frequency analysis. The first case was solved by using CRU climate data and the second case by using copula functions in this research. In this study, while checking the accuracy of the rainfall values extracted from the CRU climate model on a monthly scale, the frequency analysis of drought severity and duration characteristics based on the SPI index in the Zarinehrood basin has been analyzed. The results of the investigations showed that the values of the CRU scenario have a suitable accuracy and error rate with the observational data and have a suitable certainty. By extending the statistical period to 60 years, the SPI index was estimated in the studied area, which indicates the increase in the severity and duration of droughts in recent years. 45% of the studied statistical period had a lack of rainfall and 8% of the studied months were faced with severe drought. By choosing the distribution of generalized extreme values and logistic for drought severity and duration series in the studied stations, Frank's copula was selected for drought severity-duration pair variable. The results of investigation and joint analysis of drought severity -duration pair variables led to the presentation of drought probability curves in the region, which estimate the regional characteristics of drought with different probabilities. The presented approach has better performance due to the increase of time series memory and the use of joint distribution and copula functions and shows the characteristics of drought better.

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References

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Water and Irrigation Management
Volume 13, Issue 1
April 2023
Pages 189-207

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