Analysis and comparison of SPI and SPEI indices in meteorological drought assessment ) Case study: West of Iran(

Background and Objectives: Drought is a recurring climatic phenomenon triggered by a moisture deficit due to below-normal precipitation, with extensive economic, social, and environmental consequences, ranking it among the most significant natural hazards. Accurate drought assessment is crucial for water resource planning and management. Among various drought indices, the Standardized Precipitation Index (SPI), relying solely on precipitation data, and the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates both precipitation and temperature (evapotranspiration), are widely used. This research aims to compare the performance and patterns of drought occurrence based on these two indices across different time scales in western Iran, a relatively high-precipitation and crucial region of the country.
Materials and Methods: This study was conducted in western Iran, encompassing the provinces of Ilam, Lorestan, Kurdistan, Kermanshah, and Hamadan. Monthly minimum and maximum temperature and precipitation data from 32 synoptic stations over a 30-year period (1988-2017) were utilized. After data quality control and reconstruction, potential evapotranspiration (PET) was calculated using the Hargreaves-Samani method. The SPI and SPEI were computed for 1-, 6-, and 12-month time scales for the entire 30-year period and two 15-year sub-periods (1988-2002 and 2003-2017). SPI calculation was performed using SPI_SL_6 software, fitting a gamma distribution to the precipitation data. For SPEI calculation, the difference between precipitation and PET (D = P - PET) was used, and a generalized logistic distribution was fitted to the D values. The spatial distribution of the results was mapped using a Geographic Information System (GIS), and the correlation between the two indices was analyzed using SPSS software.
Results: The findings indicated that during the 30-year period, the region experienced widespread drought in seven years (1990, 1995, 1996, 1998, 2007, 2010, 2017). Based on SPI, four years (1994, 2000, 2009, 2015) had widespread wet periods, whereas SPEI identified six years (1992, 1993, 1994, 2009, 2013, 2015). The SPEI index revealed longer and more severe drought periods compared to SPI at most stations, underscoring the significant role of temperature and evapotranspiration. On a monthly scale, during the 2003-2017 period, SPEI identified five months (January, September, October, November, December) with widespread drought, while SPI detected only two months (October and December). Correlation analysis confirmed a significant relationship between the two indices. The highest correlation coefficient at the annual scale was for the 2003-2017 period (0.938), and at the monthly scale, it belonged to February (0.945) and January (0.908) during the 1988-2002 period. The lowest correlations were observed in November and October.
Conclusion: In general, the SPEI index, by concurrently considering precipitation and temperature, demonstrates greater sensitivity to drought, particularly under warming conditions, and identifies longer and more severe dry periods. However, the strong correlation between the two indices at longer time scales (6-month and 12-month) justifies the use of the simpler SPI index in regions lacking reliable temperature data. Given climate change and the increasing temperature trend, employing the SPEI index for drought monitoring and assessment in western Iran and similar regions will yield more realistic results.