Multivariate Analysis of Meteorological Droughts in Iran Using Joint Deficit Index (JDI)

Drought is a natural phenomenon, therefor Drought monitoring and forecasting, especially the precise timing of its onset and duration, is of particular importance in water resources management and planning to mitigate drought effects. The purpose of this study is to evaluate, the meteorological droughts in the whole country of Iran using the Joint Deficit Index (JDI) and compared its with SPImod. For this purpose, the monthly precipitation data from 41 meteorological stations in Iran were used in the period of 1971-2017. The results showed that the SPImod index can describe seasonal variations of precipitation which is an advantage for this index. On the other hand, analysis based on the SPImod is sensitive to time scales, as it may present contradictory results in different time scales. To correct these defects the Joint Deficit Index (JDI) can be used. The basis of the JDI index is to create a joint distribution of SPImod indices with time scales of 1 to 12-month using copula functions. The results of the JDI index showed that the number of dry months (JDI <0) in the west, northwest, and some northern provinces were more than other parts of the country. In the next step, the drought characteristics, including severity, duration and the inter-arrival time were extracted from the JDI index time series. The results indicated that the correlation among drought characteristics were more than 0.7. In order to trivariate analysis of drought characteristics, the fitness of nine different copula functions were examined that the Farley- Gamble- Morgenstern copula was specified as the best function for constructing the trivariate distribution.