SPI-based drought assessment and trend identification in seasonally adjusted precipitation series using the STL and SATS approaches

Drought is one of the most significant hydro-climatic hazards impacting water resources, agricultural production and the sustainability of ecosystems, particularly in regions with high climatic variability. In this context, reliable approaches are needed to better evaluate short- and long-term drought conditions in the Upper Euphrates Basin (UEB). In this study, the results obtained from the Standardized Precipitation Index (SPI), Seasonal-Trend Decomposition (STL) Z-score, and Seasonality-Adjusted Time Series (SATS) Z-score approaches were comparatively evaluated. The SPI, STL Z-score, and SATS Z-score approaches were examined for five meteorological stations at 1-, 3-, 6-, and 12-month time scales. The analysis indicated that the STL and SATS Z-score approaches provide seasonality-adjusted perspectives for identifying drought variability at shorter time scales. In contrast, due to its reliance on raw precipitation data, the Standardized Precipitation Index (SPI) was observed to capture such extreme events more sharply within similar short-term periods. A high level of concordance was observed between the proposed methods and the SPI, particularly over a 12-month timescale. The coefficient of determination (R²) values between STL Z-score and SPI were found to be between 0.91 and 0.96 for the 12-month timescale at all stations. For SATS Z-score and SPI, this value was found to be between 0.98 and 0.99. MK and Şen-ITA trend analysis methods were used to analyze the results of the three approaches for all stations. The obtained trend results generally support the consistency observed between the methods. Finally, it is suggested that using the STL, SATS Z-score, and SPI approaches together will offer a comparative perspective for drought assessment in the Upper Euphrates Basin.